diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml deleted file mode 100644 index da894d121..000000000 --- a/.github/workflows/tests.yml +++ /dev/null @@ -1,49 +0,0 @@ -name: Tests - -on: - push: - branches: [ master ] - pull_request: - branches: [ master ] - -jobs: - build: - runs-on: ubuntu-latest - strategy: - matrix: - python-version: ["3.9", "3.10", "3.11", "3.12", "3.13", "3.14"] - steps: - - uses: actions/checkout@v3 - - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v4 - with: - python-version: ${{ matrix.python-version }} - allow-prereleases: true - - - name: Install dependencies - run: | - pip install --upgrade pip wheel setuptools - pip install -r requirements_test.txt - pip install flake8 - bash ./tools/build_talib_linux.sh - - - name: Build cython modules in-place - run: | - python setup.py build_ext --inplace - env: - TA_INCLUDE_PATH: "ta-lib-install/include" - TA_LIBRARY_PATH: "ta-lib-install/lib" - - - name: Lint with flake8 - run: | - # stop the build if there are Python syntax errors or undefined names - flake8 talib --count --select=E9,F63,F7,F82 --show-source --statistics - # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide - #flake8 talib --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics - - - name: Test with pytest - run: | - PYTHONPATH=. pytest - env: - LD_LIBRARY_PATH: "ta-lib-install/lib" diff --git a/.github/workflows/wheels.yml b/.github/workflows/wheels.yml deleted file mode 100644 index e023222d2..000000000 --- a/.github/workflows/wheels.yml +++ /dev/null @@ -1,249 +0,0 @@ - -name: Wheels -on: - push: - tags: - - "v*" - workflow_dispatch: - -env: - TALIB_C_VER: 0.6.4 - PIP_NO_VERIFY: 0 - PIP_VERBOSE: 1 - CIBW_BEFORE_BUILD: pip install -U setuptools Cython wheel meson-python ninja && pip install -U numpy - CIBW_TEST_REQUIRES: pytest pandas maturin polars - CIBW_SKIP: "pp*" - -jobs: - build_linux_x86_64: - name: Build Linux x86_64 wheels - strategy: - matrix: - os: ["ubuntu-22.04"] - runs-on: ${{ matrix.os }} - steps: - - name: Checkout repository - uses: actions/checkout@v4 - - name: Build wheels - uses: pypa/cibuildwheel@v2.23.3 - env: - CIBW_BEFORE_ALL: | - bash ./tools/build_talib_linux.sh - CIBW_MANYLINUX_X86_64_IMAGE: manylinux_2_28 - CIBW_MUSLLINUX_X86_64_IMAGE: musllinux_1_2 - CIBW_TEST_SKIP: "cp*-musllinux*" - CIBW_TEST_COMMAND: > - cd .. && - pytest -k "not RSI and not threading" {project}/tests - CIBW_ARCHS_LINUX: x86_64 - CIBW_BUILD_FRONTEND: build - CIBW_ENVIRONMENT_LINUX : > - TA_LIBRARY_PATH="ta-lib-install/lib" - TA_INCLUDE_PATH="ta-lib-install/include" - PIP_NO_BUILD_ISOLATION=false - CIBW_REPAIR_WHEEL_COMMAND_LINUX: | - export LD_LIBRARY_PATH="/project/ta-lib-install/lib:$LD_LIBRARY_PATH" - auditwheel repair -w {dest_dir} {wheel} - - name: Upload wheels - uses: actions/upload-artifact@v4 - with: - path: ./wheelhouse/*.whl - name: "ta_lib-${{ github.ref_name }}-linux_x86_64" - build_linux_arm64: - name: Build Linux arm64 wheels - strategy: - matrix: - os: ["ubuntu-22.04-arm"] - runs-on: ${{ matrix.os }} - steps: - - name: Checkout repository - uses: actions/checkout@v4 - - name: Build wheels - uses: pypa/cibuildwheel@v2.23.3 - env: - CIBW_BEFORE_ALL: | - bash ./tools/build_talib_linux.sh - CIBW_MANYLINUX_AARCH64_IMAGE: manylinux_2_28 - CIBW_MUSLLINUX_AARCH64_IMAGE: musllinux_1_2 - CIBW_TEST_SKIP: "cp*-musllinux*" - CIBW_TEST_COMMAND: > - cd .. && - pytest -k "not RSI and not threading" {project}/tests - CIBW_ARCHS_LINUX: aarch64 - CIBW_BUILD_FRONTEND: build - CIBW_ENVIRONMENT_LINUX : > - TA_LIBRARY_PATH="ta-lib-install/lib" - TA_INCLUDE_PATH="ta-lib-install/include" - PIP_NO_BUILD_ISOLATION=false - CIBW_REPAIR_WHEEL_COMMAND_LINUX: | - export LD_LIBRARY_PATH="/project/ta-lib-install/lib:$LD_LIBRARY_PATH" - auditwheel repair -w {dest_dir} {wheel} - - name: Upload wheels - uses: actions/upload-artifact@v4 - with: - path: ./wheelhouse/*.whl - name: "ta_lib-${{ github.ref_name }}-linux_arm64" - build_windows_amd64: - name: Build Windows amd64 wheels - strategy: - matrix: - os: ["windows-2022"] - runs-on: ${{ matrix.os }} - steps: - - name: Checkout the repository - uses: actions/checkout@v4 - - name: Set up MSVC for x64 - uses: ilammy/msvc-dev-cmd@v1 - with: - arch: amd64 - - name: Build TA-Lib C Library - run: tools/build_talib_windows.cmd - shell: cmd - - name: Build wheels - uses: pypa/cibuildwheel@v2.23.3 - env: - CIBW_TEST_SKIP: "cp*" - CIBW_TEST_COMMAND: > - cd .. && - pytest --rootdir=C: -k "not RSI and not threading" {project}/tests - MSBUILDTREATHIGHERTOOLSVERSIONASCURRENT: 1 - CIBW_ARCHS_WINDOWS: AMD64 - CIBW_ENVIRONMENT_WINDOWS: > - TA_LIBRARY_PATH="ta-lib-$TALIB_C_VER\\_build;$LIB" - TA_INCLUDE_PATH="ta-lib-$TALIB_C_VER\\include;$INCLUDE" - PIP_NO_BUILD_ISOLATION=false - - name: Upload wheel - uses: actions/upload-artifact@v4 - with: - path: ./wheelhouse/*.whl - name: "ta_lib-${{ github.ref_name }}-win_amd64" - build_windows_x86: - name: Build Windows x86 wheels - strategy: - matrix: - os: ["windows-2022"] - runs-on: ${{ matrix.os }} - steps: - - name: Checkout the repository - uses: actions/checkout@v4 - - name: Set up MSVC for x86 - uses: ilammy/msvc-dev-cmd@v1 - with: - arch: amd64_x86 - - name: Build TA-Lib C library - run: tools/build_talib_windows.cmd - shell: cmd - - name: Build wheels - uses: pypa/cibuildwheel@v2.23.3 - env: - CIBW_TEST_SKIP: "cp*" - CIBW_TEST_COMMAND: > - cd .. && - pytest --rootdir=C: -k "not RSI and not threading" {project}/tests - MSBUILDTREATHIGHERTOOLSVERSIONASCURRENT: 1 - CIBW_ARCHS_WINDOWS: x86 - CIBW_ENVIRONMENT_WINDOWS: > - TA_LIBRARY_PATH="ta-lib-$TALIB_C_VER\\_build;$LIB" - TA_INCLUDE_PATH="ta-lib-$TALIB_C_VER\\include;$INCLUDE" - PIP_NO_BUILD_ISOLATION=false - - name: Upload wheel - uses: actions/upload-artifact@v4 - with: - path: ./wheelhouse/*.whl - name: "ta_lib-${{ github.ref_name }}-win32" - build_windows_arm64: - name: Build Windows arm64 wheels - strategy: - matrix: - os: ["windows-11-arm"] - runs-on: ${{ matrix.os }} - steps: - - name: Checkout the repository - uses: actions/checkout@v4 - - name: Set up MSVC for arm - uses: ilammy/msvc-dev-cmd@v1 - with: - arch: arm64 - - name: Build TA-Lib C Library - run: tools/build_talib_windows.cmd - shell: cmd - - name: Build wheels - uses: pypa/cibuildwheel@v2.23.3 - env: - CIBW_TEST_SKIP: "cp*" - CIBW_TEST_COMMAND: > - cd .. && - pytest --rootdir=C: -k "not RSI and not threading" {project}/tests - MSBUILDTREATHIGHERTOOLSVERSIONASCURRENT: 1 - CIBW_ARCHS_WINDOWS: ARM64 - CIBW_ENVIRONMENT_WINDOWS: > - TA_LIBRARY_PATH="ta-lib-$TALIB_C_VER\\_build;$LIB" - TA_INCLUDE_PATH="ta-lib-$TALIB_C_VER\\include;$INCLUDE" - PIP_NO_BUILD_ISOLATION=false - - name: Upload wheel - uses: actions/upload-artifact@v4 - with: - path: ./wheelhouse/*.whl - name: "ta_lib-${{ github.ref_name }}-win_arm64" - build_macos_x86_64: - name: Build MacOS x86_64 wheels - strategy: - matrix: - os: [macos-13] - runs-on: ${{ matrix.os }} - steps: - - name: Checkout repository - uses: actions/checkout@v4 - - name: Build wheels - uses: pypa/cibuildwheel@v2.23.3 - env: - CIBW_BEFORE_ALL: | - bash ./tools/build_talib_macos.sh - CIBW_TEST_COMMAND: > - cd .. && - pytest -k "not RSI and not threading" {project}/tests - CIBW_ARCHS_MACOS: x86_64 - CIBW_ENVIRONMENT_MACOS : > - TA_LIBRARY_PATH="ta-lib-install/lib" - TA_INCLUDE_PATH="ta-lib-install/include" - PIP_NO_BUILD_ISOLATION=false - CIBW_REPAIR_WHEEL_COMMAND_MACOS: | - export MACOSX_DEPLOYMENT_TARGET=13.7 - export DYLD_LIBRARY_PATH="/Users/runner/work/${{ github.event.repository.name }}/${{ github.event.repository.name }}/ta-lib-install/lib:$DYLD_LIBRARY_PATH" - delocate-wheel --require-archs {delocate_archs} -w {dest_dir} -v {wheel} - - name: Upload wheels - uses: actions/upload-artifact@v4 - with: - path: ./wheelhouse/*.whl - name: "ta_lib-${{ github.ref_name }}-macos_x86_64" - build_macos_arm64: - name: Build MacOS arm64 wheels - strategy: - matrix: - os: [macos-14] - runs-on: ${{ matrix.os }} - steps: - - name: Checkout repository - uses: actions/checkout@v4 - - name: Build wheels - uses: pypa/cibuildwheel@v2.23.3 - env: - CIBW_BEFORE_ALL: | - bash ./tools/build_talib_macos.sh - CIBW_TEST_COMMAND: > - cd .. && - pytest -k "not RSI and not threading" {project}/tests - CIBW_ARCHS_MACOS: arm64 - CIBW_ENVIRONMENT_MACOS : > - TA_LIBRARY_PATH="ta-lib-install/lib" - TA_INCLUDE_PATH="ta-lib-install/include" - PIP_NO_BUILD_ISOLATION=false - CIBW_REPAIR_WHEEL_COMMAND_MACOS: | - export MACOSX_DEPLOYMENT_TARGET=14.0 - export DYLD_LIBRARY_PATH="/Users/runner/work/${{ github.event.repository.name }}/${{ github.event.repository.name }}/ta-lib-install/lib:$DYLD_LIBRARY_PATH" - delocate-wheel --require-archs {delocate_archs} -w {dest_dir} -v {wheel} - - name: Upload wheels - uses: actions/upload-artifact@v4 - with: - path: ./wheelhouse/*.whl - name: "ta_lib-${{ github.ref_name }}-macos_arm64" diff --git a/.gitignore b/.gitignore deleted file mode 100644 index 49ddb78e1..000000000 --- a/.gitignore +++ /dev/null @@ -1,11 +0,0 @@ -docs/html -docs/.tadoc.org.html - -*.pyc -build/ -dist/ -*.so -.* -*~ -*.egg-info/ - diff --git a/AUTHORS b/AUTHORS deleted file mode 100644 index fbf4451dc..000000000 --- a/AUTHORS +++ /dev/null @@ -1,2 +0,0 @@ -Project Founder and Lead Developer: John Benediktsson (https://github.com/mrjbq7) -Abstract Interface Author and Maintainer: Brian Cappello (https://github.com/briancappello) diff --git a/CHANGELOG b/CHANGELOG deleted file mode 100644 index 2829f4c23..000000000 --- a/CHANGELOG +++ /dev/null @@ -1,373 +0,0 @@ -0.6.6 -===== - -- [FIX]: Silence project.license warnings when building. - -0.6.5 -===== - -- [FIX]: Support PEP-517 style installation - -- [NEW]: Upgrade to Cython 3.1.2 - -- [NEW]: Build binary wheels for Windows, macOS, and Linux. - -0.6.4 -===== - -- [FIX]: Adding typed for ACCBANDS, AVGDEV, IMI, and stream_* functions - -- [FIX]: Fix for numpy 2.3.0, which removed the npy_1_7_deprecated_api - -0.6.3 -===== - -- [FIX]: Fix issue building against numpy2 - -0.6.2 -===== - -- [NEW]: Adding indicators ACCBANDS, AVGDEV, IMI - -0.6.1 -===== - -- [FIX]: Build properly against TA-Lib 0.6.2 and newer on Windows. - -0.6.0 -===== - -- [FIX]: Make sure this wrapper works with TA-Lib 0.6.1 and newer releases. - -0.5.5 -===== - -- [FIX]: Fix for numpy 2.3.0, which removed the npy_1_7_deprecated_api - -0.5.4 -===== - -- [FIX]: Fix lib name on windows. - -0.5.3 -===== - -- [BUG]: Make this release only support TA-Lib 0.4.0. - -0.5.2 -===== - -- [NEW]: Provide py typed information for C wrapper - -- [FIX]: Make sure this wrapper works with TA-Lib 0.6.1 - -0.5.1 -===== - -- [FIX]: include cython *.pxi files in the source tar.gz - -0.5.0 -===== - -- [NEW]: Upgrade to Numpy 2.0 - -0.4.38 -====== - -- [FIX]: Fix lib name on windows. - -0.4.37 -====== - -- [FIX]: Make sure to pin numpy<2 in the setup.py. - -0.4.36 -====== - -- [BUG]: Make this release only support TA-Lib 0.4.0 - -0.4.35 -====== - -- [FIX]: Make sure this wrapper works with TA-Lib 0.6.1 - -0.4.34 -===== - -- [FIX]: include cython *.pxi files in the source tar.gz - -0.4.33 -====== - -- [NEW]: Upgrade to Cython 3.0.11 - -- [FIX]: Fix import of ``pandas`` and ``polars`` to throw underlying import errors - -0.4.32 -====== - -- [FIX]: Make sure numpy<2 is in the requirements.txt - -0.4.31 -====== - -- [FIX]: Fix build issue with numpy2 released by requiring numpy<2.0.0 for now - -0.4.30 -====== - -- [FIX]: Fix the C library imports to work again on Windows, oops. - -0.4.29 -====== - -- [NEW]: Upgrade to Cython 3.0.10 - -- [FIX]: Make TA_INCLUDE_PATH and TA_LIBRARY_PATH override default search list - -- [FIX]: Silent some compiler warnings about const pointers - -0.4.28 -====== - -- [NEW]: Upgrade to Cython 3.0.0 - -- [FIX]: Use embedsignature to enable code completions? - -0.4.27 -====== - -- [NEW]: Upgrade to Cython 0.29.36 - -- [FIX]: Fix abstract info to keep values doubles when they are (e.g., nbdevup, nvdevdn) - -- [FIX]: Don't throw exceptions when inputs are all NaN - -0.4.26 -====== - -- [NEW]: Upgrade to Cython 0.29.34 - -- [NEW]: Moved to https://github.com/ta-lib/ta-lib-python - -- [FIX]: Fix deprecation warning for polars.DataFrame(columns=[...]) - -0.4.25 -====== - -- [NEW]: Upgrade to Cython 0.29.32 - -- [FIX]: Allow Abstract API to be safely used with multithreading - -0.4.24 -====== - -- [FIX]: runtime_lib_dirs preventing install on Windows - -0.4.23 -====== - -- [NEW]: Upgrade to Cython 0.29.25 - -- [NEW]: Allow TA_INCLUDE_PATH and TA_LIBRARY_PATH to work on Windows. - -- [FIX]: Remove pyproject.toml which was preventing some installs. - -0.4.22 -====== - -- [NEW]: Upgrade to Cython 0.29.24 - -- [NEW]: Support polars.Series in Function API - -- [NEW]: Support polars.Series in Streaming API - -- [NEW]: Support polars.DataFrame in Abstract API - -- [NEW]: Switch tests to pytest from nose (no longer supported). - -0.4.21 -====== - -- [FIX]: Fixed {MIN/MAX/MINMAX}INDEX functions to return correct indices. - -0.4.20 -====== - -- [NEW]: Upgrade to Cython 0.29.23 - -- [FIX]: Fix Homebrew directory on Apple M1 devices - -0.4.19 -====== - -- [NEW]: Upgrade to Cython 0.29.20 - -- [NEW]: from talib import * (imports all func and stream) - -- [FIX]: missing method signatures in PyCharm - -0.4.18 -====== - -- [NEW]: Upgrade to Cython 0.29.17 - -- [NEW]: Support TA_SetCompatibility - -- [NEW]: Reduce size of generated C file and memory requirements to compile it. - -- [FIX]: Fixed caching input price series in Abstract API - -- [NEW]: Support pandas.Series in Streaming API - -0.4.17 -====== - -- [NEW]: Support pandas.Series in Function API - -0.4.16 -====== - -- [FIX]: Fix incorrect C header include on Windows. - -0.4.15 -====== - -- [FIX]: Import TA_FUNC_FLAGS, TA_INPUT_FLAGS, TA_OUTPUT_FLAGS into - talib.abstract to support backwards compatibility for backtrader - -0.4.14 -====== - -- [NEW]: Upgrade to Cython 0.27.3 - -- [NEW]: Add support for set/restore candle settings - -- [DOC]: Note Function API only supports numpy.ndarray (not pandas.Series) - -- [NEW]: Continuous integration using Travis on Python 2.7, 3.4, 3.5, 3.6 - -- [NEW]: Merge common, func, abstract, stream as pxi to _ta_lib.pyx - -- [DOC]: Update documentation to warn about unstable functions - -0.4.10 -====== - -- [NEW]: Upgrade to Cython 0.23.4. - -- [NEW]: Adding an experimental Streaming API (talib.stream). - -- [NEW]: Support for "sunos" - -- [FIX]: Fix issue initializing library for use with candlestick functions. - -- [NEW]: Support for TA_SetUnstablePeriod and TA_GetUnstablePeriod - -0.4.9 -===== - -- [NEW]: Support for python 2.6 and earlier for ordereddict. - -- [FIX]: Add lib64 paths to setup.py. - -- [NEW]: Upgrade to Cython 0.22. - -- [FIX]: Allow running setup.py without numpy or cython - -- [NEW]: Allow TA_LIBRARY_PATH and TA_INCLUDE_PATH environment variables. - -0.4.8 -===== - -- [NEW]: Support pandas.Series and pandas.Dataframe inputs. - -- [FIX]: Simple check to warn if ta-lib library is not installed - -- [FIX]: Fix missing key error when inputs are not default names. - -- [NEW]: Upgrade to Cython 0.20. - -- [FIX]: Check all input array lengths are same. - -- [FIX]: Check all input arrays for NaN elements. - -0.4.7 -===== - -- [NEW]: Upgrade to Cython 0.19.1. - -- [FIX]: Fix "periods" input arrays in abstract interface. - -- [FIX]: Only require necessary input arrays in abstract interface. - -0.4.6 -===== - -- [NEW]: Support for function_flags and output_flags properties in Functions - -0.4.5 -===== - -- [NEW]: Better test coverage of abstract interface. - -- [NEW]: Support for Python 3. - -0.4.4 -===== - -- [FIX]: Make installation on Windows easier. - -0.4.3 -===== - -- [NEW]: Upgrade to Cython 0.18. - -- [FIX]: Improve docstrings for indicators in talib.func. - -- [FIX]: Initialize and shutdown underlying TA-Lib only once each process. - This should give slight speedups when using many indicators (<5%). - -- [DEPRECATED]: The old moving average types that were in talib.func are now - deprecated. See the next bullet item for the replacement, or you can - continue using them with "from talib import deprecated" for the time being. - -- [NEW]: The new moving average types are in talib.MA_Type. It's a class with SMA, - EMA, DEMA, etc attribute variables you should now use. Human-readable lookups - are also possible by using MA_Type as a dict e.g.: - - MA_Type[MA_Type.SMA] # returns "Simple Moving Average" - -- [NEW]: In addition to the existing func interface, we now provide an - enhanced abstract interface too. Functions in "import talib" use the - original interface, or you can use "from talib import abstract" for - the full abstract interface. See the README, tools/example.py and - tests/abstract_test.py for more information. The full (commented) - source code is mostly located in talib/abstract.pyx. The basic usage is very - similar: - - input_arrays = { 'open': np.random.random(100), - 'high': np.random.random(100), - 'low': np.random.random(100), - 'close': np.random.random(100), - 'volume': np.random.random(100) } - ema_20 = abstract.Function('ema', input_arrays, 20).outputs # function names not case-sensitive - slowd, slowk = abstract.Function('STOCH')(input_arrays, 15, 3, 0, 3, 0) - upper, middle, lower = abstract.Function('bbands')(input_arrays, timeperiod=20) - -0.4.2 -===== - -- Move the functions into ``talib.func``, to prepare for ``talib.abstract`` - in a future release. - -0.4.1 -===== - -- Support for MacPorts. -- Fix for FreeBSD. - -0.4.0 -===== - -First version. diff --git a/CITATION.cff b/CITATION.cff deleted file mode 100644 index 3cd0641f2..000000000 --- a/CITATION.cff +++ /dev/null @@ -1,11 +0,0 @@ -cff-version: 1.2.0 -message: "If you use this software, please cite it as below." -title: ta-lib-python -version: 0.6.5 -date-released: 2025-08-07 -url: "https://github.com/ta-lib/ta-lib-python" -type: software -authors: - - given-names: John - family-names: Benediktsson - email: mrjbq7@gmail.com diff --git a/COPYRIGHT b/COPYRIGHT deleted file mode 100644 index 8aa18b0bc..000000000 --- a/COPYRIGHT +++ /dev/null @@ -1,2 +0,0 @@ -Copyright (C) 2012-2013 Silfur Capital, LLC. All Rights Reserved. -The contents of talib/abstract.pyx are Copyright (c) 2013 Brian A Cappello. All Rights Reserved. diff --git a/DEVELOPMENT b/DEVELOPMENT deleted file mode 100644 index 571a48a2c..000000000 --- a/DEVELOPMENT +++ /dev/null @@ -1,48 +0,0 @@ -To get started developing on talib, clone the latest code from git and -install: - -``` -$ git clone git://github.com/ta-lib/ta-lib-python.git -$ cd ta-lib-python -# you can run "git pull" here (no quotes) to update the sources in the future -$ make build -$ [sudo] make install -``` - -Here's the full list of make commands (see the Makefile file): - -make build # builds and places libs in the project directory; required for testing -make clean # cleans the local build files -make install # installs talib system-wide -make generate: # generates a fresh _func.pxi, _stream.pxi file. Requires talib and TA-Lib to both be installed -make perf # run performance profiling -make test # run tests - -The source code is comprised of one python package, located in the talib -directory, which itself has one Cython module (_ta_lib) which consists of -four parts: _common, _func, _abstract and _stream. - -talib/_common.pxi - An internal-use file for functionality shared between func and abstract. - -talib/_func.pxi - This file is generated automatically by tools/generate_func.py and any changes made - to it directly will get overwritten! - -talib/_abstract.pxi - This file contains the code for interfacing with the TA-Lib abstract interface - and wrapping it into a pythonic Function class. - -talib/_ta_lib.pyx - This "Cython header file" defines the C-level functions, variables and types we - need to use in the above pyx files. - -talib/_stream.pxi - This file contains code for interfacing a "streaming" interface to TA-Lib. - -tools/generate_func.py,generate_stream.py - Scripts that generate and print _func.pxi or _stream.pxi to stdout. Gets information - about all functions from the C headers of the installed TA-Lib. - -If you are interested in developing new indicator functions or whatnot on -the underlying TA-Lib, you must install TA-Lib from git. diff --git a/Dockerfile b/Dockerfile deleted file mode 100644 index 68af94a3b..000000000 --- a/Dockerfile +++ /dev/null @@ -1,52 +0,0 @@ -# Dockerfile for TA-Lib. To build: -# -# docker build --rm -t talib . -# -# To run: -# -# docker run --rm -it talib bash -# - -ARG PYTHON_VERSION="3.7" - -FROM python:$PYTHON_VERSION as builder - -ENV TA_PREFIX="/opt/ta-lib-core" -ENV TA_LIBRARY_PATH="$TA_PREFIX/lib" \ - TA_INCLUDE_PATH="$TA_PREFIX/include" - -WORKDIR /src/ta-lib-core -RUN apt-get update && apt-get install -y \ - gfortran \ - libfreetype6-dev \ - libhdf5-dev \ - liblapack-dev \ - libopenblas-dev \ - libpng-dev \ - && rm -rf /var/lib/apt/lists/* \ - && curl -fsSL http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz \ - | tar xvz --strip-components 1 \ - && ./configure --prefix="$TA_PREFIX" \ - && make \ - && make install - -WORKDIR /src/ta-lib-python -COPY . . -RUN python -m pip install -e . \ - && python -c 'import numpy, talib; close = numpy.random.random(100); output = talib.SMA(close); print(output)' \ - && python -m pip wheel --wheel-dir wheels . - -ARG RUN_TESTS="1" -RUN if [ "$RUN_TESTS" -ne "0" ]; then \ - python -m pip install -r requirements_test.txt \ - && pytest . ; \ - else \ - echo "Skipping tests\n" ; \ - fi - -# Build final image. -FROM python:$PYTHON_VERSION-slim -COPY --from=builder /src/ta-lib-python/wheels /opt/ta-lib-python/wheels -COPY --from=builder /opt/ta-lib-core /opt/ta-lib-core -RUN python -m pip install --no-cache-dir /opt/ta-lib-python/wheels/*.whl \ - && python -c 'import numpy, talib; close = numpy.random.random(100); output = talib.SMA(close); print(output)' diff --git a/LICENSE b/LICENSE deleted file mode 100644 index 721ed8541..000000000 --- a/LICENSE +++ /dev/null @@ -1,21 +0,0 @@ -Redistribution and use in source and binary forms, with or without -modification, are permitted provided that the following conditions are met: - -1. Redistributions of source code must retain the above copyright notice, - this list of conditions and the following disclaimer. - -2. Redistributions in binary form must reproduce the above copyright notice, - this list of conditions and the following disclaimer in the documentation - and/or other materials provided with the distribution. - -THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, -INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND -FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE -DEVELOPERS AND CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; -OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, -WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR -OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF -ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - diff --git a/MANIFEST.in b/MANIFEST.in deleted file mode 100644 index 97961f076..000000000 --- a/MANIFEST.in +++ /dev/null @@ -1,7 +0,0 @@ -include LICENSE -include COPYRIGHT -include README.md -include talib/*.c -include talib/*.pyx -include talib/*.pxi -include tests/*.py diff --git a/Makefile b/Makefile deleted file mode 100644 index d86ef416a..000000000 --- a/Makefile +++ /dev/null @@ -1,33 +0,0 @@ -.PHONY: build - -build: - python3 -m pip install --use-pep517 -e . - -install: - python3 -m pip install --use-pep517 . - -talib/_func.pxi: tools/generate_func.py - python3 tools/generate_func.py > talib/_func.pxi - -talib/_stream.pxi: tools/generate_stream.py - python3 tools/generate_stream.py > talib/_stream.pxi - -generate: talib/_func.pxi talib/_stream.pxi - -cython: - cython talib/_ta_lib.pyx - -annotate: - cython -a talib/_ta_lib.pyx - -clean: - rm -rf build talib/_ta_lib.so talib/*.pyc - -perf: - python3 tools/perf_talib.py - -test: build - pytest tests/ - -sdist: - python3 -m build --sdist diff --git a/README.md b/README.md deleted file mode 100644 index 2d435e8fc..000000000 --- a/README.md +++ /dev/null @@ -1,747 +0,0 @@ -# TA-Lib - - -![Tests](https://github.com/ta-lib/ta-lib-python/actions/workflows/tests.yml/badge.svg) -[![Release](https://img.shields.io/github/v/release/ta-lib/ta-lib-python?label=Release)](https://github.com/ta-lib/ta-lib-python/releases) -[![PyPI](https://img.shields.io/pypi/v/TA-Lib?label=PyPI)](https://pypi.org/project/TA-Lib/) -[![Wheels](https://img.shields.io/pypi/wheel/TA-Lib?label=Wheels)](https://pypi.org/project/TA-Lib/#files) -[![Python Versions](https://img.shields.io/pypi/pyversions/TA-Lib?label=Python)](https://pypi.org/project/TA-Lib/) - -This is a Python wrapper for [TA-LIB](http://ta-lib.org) based on Cython -instead of SWIG. From the homepage: - -> TA-Lib is widely used by trading software developers requiring to perform -> technical analysis of financial market data. -> -> * Includes 150+ indicators such as ADX, MACD, RSI, Stochastic, Bollinger -> Bands, etc. -> * Candlestick pattern recognition -> * Open-source API for C/C++, Java, Perl, Python and 100% Managed .NET - -The original Python bindings included with TA-Lib use -[SWIG](http://swig.org) which unfortunately are difficult to install and -aren't as efficient as they could be. Therefore this project uses -[Cython](https://cython.org) and [Numpy](https://numpy.org) to efficiently -and cleanly bind to TA-Lib -- producing results 2-4 times faster than the -SWIG interface. - -In addition, this project also supports the use of the -[Polars](https://www.pola.rs) and [Pandas](https://pandas.pydata.org) -libraries. - -## Versions - -The upstream TA-Lib C library released version 0.6.1 and changed the library -name to ``-lta-lib`` from ``-lta_lib``. After trying to support both via -autodetect and having some issues, we have decided to currently support three -feature branches: - -* ``ta-lib-python`` 0.4.x (supports ``ta-lib`` 0.4.x and ``numpy`` 1) -* ``ta-lib-python`` 0.5.x (supports ``ta-lib`` 0.4.x and ``numpy`` 2) -* ``ta-lib-python`` 0.6.x (supports ``ta-lib`` 0.6.x and ``numpy`` 2) - -## Installation - -You can install from PyPI: - -``` -$ python -m pip install TA-Lib -``` - -Or checkout the sources and run ``setup.py`` yourself: - -``` -$ python setup.py install -``` - -It also appears possible to install via [Conda Forge](https://anaconda.org/conda-forge/ta-lib): - -``` -$ conda install -c conda-forge ta-lib -``` - -### Dependencies - -To use TA-Lib for python, you need to have the [TA-Lib](http://ta-lib.org) -already installed. You should probably follow their [installation -directions](https://ta-lib.org/install/) for your platform, but some -suggestions are included below for reference. - -> Some Conda Forge users have reported success installing the underlying TA-Lib C -> library using [the libta-lib package](https://anaconda.org/conda-forge/libta-lib): -> -> ``$ conda install -c conda-forge libta-lib`` - -##### Mac OS X - -You can simply install using Homebrew: - -``` -$ brew install ta-lib -``` - -If you are using Apple Silicon, such as the M1 processors, and building mixed -architecture Homebrew projects, you might want to make sure it's being built -for your architecture: - -``` -$ arch -arm64 brew install ta-lib -``` - -And perhaps you can set these before installing with ``pip``: - -``` -$ export TA_INCLUDE_PATH="$(brew --prefix ta-lib)/include" -$ export TA_LIBRARY_PATH="$(brew --prefix ta-lib)/lib" -``` - -You might also find this helpful, particularly if you have tried several -different installations without success: - -``` -$ your-arm64-python -m pip install --no-cache-dir ta-lib -``` - -##### Windows - -For 64-bit Windows, the easiest way is to get the *executable installer*: - -1. Download [ta-lib-0.6.4-windows-x86_64.msi](https://github.com/ta-lib/ta-lib/releases/download/v0.6.4/ta-lib-0.6.4-windows-x86_64.msi). -2. Run the Installer or run ``msiexec`` [from the command-line](https://learn.microsoft.com/en-us/windows/win32/msi/standard-installer-command-line-options). - -Alternatively, if you prefer to get the libraries without installing, or -would like to use the 32-bit version: - -* Intel/AMD 64-bit [ta-lib-0.6.4-windows-x86_64.zip](https://github.com/ta-lib/ta-lib/releases/download/v0.6.4/ta-lib-0.6.4-windows-x86_64.zip) -* Intel/AMD 32-bit [ta-lib-0.6.4-windows-x86_32.zip](https://github.com/ta-lib/ta-lib/releases/download/v0.6.4/ta-lib-0.6.4-windows-x86_32.zip) - -##### Linux - -Download -[ta-lib-0.6.4-src.tar.gz](https://github.com/ta-lib/ta-lib/releases/download/v0.6.4/ta-lib-0.6.4-src.tar.gz) -and: - -``` -$ tar -xzf ta-lib-0.6.4-src.tar.gz -$ cd ta-lib-0.6.4/ -$ ./configure --prefix=/usr -$ make -$ sudo make install -``` - -> If you build ``TA-Lib`` using ``make -jX`` it will fail but that's OK! -> Simply rerun ``make -jX`` followed by ``[sudo] make install``. - -Note: if your directory path includes spaces, the installation will probably -fail with ``No such file or directory`` errors. - -### Wheels - -For convenience, and starting with version 0.6.5, we now build binary wheels -for different operating systems, architectures, and Python versions using -GitHub Actions which include the underlying TA-Lib C library and are easy to -install. - -Supported platforms: - -* Linux - * x86_64 - * arm64 -* macOS - * x86_64 - * arm64 -* Windows - * x86_64 - * x86 - * arm64 - -Supported Python versions: - -* 3.9 -* 3.10 -* 3.11 -* 3.12 -* 3.13 - -In the event that your operating system, architecture, or Python version are -not available as a binary wheel, it is fairly easy to install from source -using the instructions above. - -### Troubleshooting - -If you get a warning that looks like this: - -``` -setup.py:79: UserWarning: Cannot find ta-lib library, installation may fail. -warnings.warn('Cannot find ta-lib library, installation may fail.') -``` - -This typically means ``setup.py`` can't find the underlying ``TA-Lib`` -library, a dependency which needs to be installed. - ---- - -If you installed the underlying ``TA-Lib`` library with a custom prefix -(e.g., with ``./configure --prefix=$PREFIX``), then when you go to install -this python wrapper you can specify additional search paths to find the -library and include files for the underlying ``TA-Lib`` library using the -``TA_LIBRARY_PATH`` and ``TA_INCLUDE_PATH`` environment variables: - -```sh -$ export TA_LIBRARY_PATH=$PREFIX/lib -$ export TA_INCLUDE_PATH=$PREFIX/include -$ python setup.py install # or pip install ta-lib -``` - ---- - -Sometimes installation will produce build errors like this: - -``` -talib/_ta_lib.c:601:10: fatal error: ta-lib/ta_defs.h: No such file or directory - 601 | #include "ta-lib/ta_defs.h" - | ^~~~~~~~~~~~~~~~~~ -compilation terminated. -``` - -or: - -``` -common.obj : error LNK2001: unresolved external symbol TA_SetUnstablePeriod -common.obj : error LNK2001: unresolved external symbol TA_Shutdown -common.obj : error LNK2001: unresolved external symbol TA_Initialize -common.obj : error LNK2001: unresolved external symbol TA_GetUnstablePeriod -common.obj : error LNK2001: unresolved external symbol TA_GetVersionString -``` - -This typically means that it can't find the underlying ``TA-Lib`` library, a -dependency which needs to be installed. On Windows, this could be caused by -installing the 32-bit binary distribution of the underlying ``TA-Lib`` library, -but trying to use it with 64-bit Python. - ---- - -Sometimes installation will fail with errors like this: - -``` -talib/common.c:8:22: fatal error: pyconfig.h: No such file or directory - #include "pyconfig.h" - ^ -compilation terminated. -error: command 'x86_64-linux-gnu-gcc' failed with exit status 1 -``` - -This typically means that you need the Python headers, and should run -something like: - -``` -$ sudo apt-get install python3-dev -``` - ---- - -Sometimes building the underlying ``TA-Lib`` library has errors running -``make`` that look like this: - -``` -../libtool: line 1717: cd: .libs/libta_lib.lax/libta_abstract.a: No such file or directory -make[2]: *** [libta_lib.la] Error 1 -make[1]: *** [all-recursive] Error 1 -make: *** [all-recursive] Error 1 -``` - -This might mean that the directory path to the underlying ``TA-Lib`` library -has spaces in the directory names. Try putting it in a path that does not have -any spaces and trying again. - ---- - -Sometimes you might get this error running ``setup.py``: - -``` -/usr/include/limits.h:26:10: fatal error: bits/libc-header-start.h: No such file or directory -#include - ^~~~~~~~~~~~~~~~~~~~~~~~~~ -``` - -This is likely an issue with trying to compile for 32-bit platform but -without the appropriate headers. You might find some success looking at the -first answer to [this question](https://stackoverflow.com/questions/54082459/fatal-error-bits-libc-header-start-h-no-such-file-or-directory-while-compili). - ---- - -If you get an error on macOS like this: - -``` -code signature in <141BC883-189B-322C-AE90-CBF6B5206F67> -'python3.9/site-packages/talib/_ta_lib.cpython-39-darwin.so' not valid for -use in process: Trying to load an unsigned library) -``` - -You might look at [this question](https://stackoverflow.com/questions/69610572/how-can-i-solve-the-below-error-while-importing-nltk-package) -and use ``xcrun codesign`` to fix it. - ---- - -If you wonder why ``STOCHRSI`` gives you different results than you expect, -probably you want ``STOCH`` applied to ``RSI``, which is a little different -than the ``STOCHRSI`` which is ``STOCHF`` applied to ``RSI``: - -```python ->>> import talib ->>> import numpy as np ->>> c = np.random.randn(100) - -# this is the library function ->>> k, d = talib.STOCHRSI(c) - -# this produces the same result, calling STOCHF ->>> rsi = talib.RSI(c) ->>> k, d = talib.STOCHF(rsi, rsi, rsi) - -# you might want this instead, calling STOCH ->>> rsi = talib.RSI(c) ->>> k, d = talib.STOCH(rsi, rsi, rsi) -``` - ---- - -If the build appears to hang, you might be running on a VM with not enough -memory -- try 1 GB or 2 GB. - -It has also been reported that using a swapfile could help, for example: - -``` -$ sudo fallocate -l 1G /swapfile -$ sudo chmod 600 /swapfile -$ sudo mkswap /swapfile -$ sudo swapon /swapfile -``` - ---- - -If you get "permission denied" errors such as this, you might need to give -your user access to the location where the underlying TA-Lib C library is -installed -- or install it to a user-accessible location. - -``` -talib/_ta_lib.c:747:28: fatal error: /usr/include/ta-lib/ta_defs.h: Permission denied - #include "ta-lib/ta-defs.h" - ^ -compilation terminated -error: command 'gcc' failed with exit status 1 -``` - ---- - -If you're having trouble compiling the underlying TA-Lib C library on ARM64, -you might need to configure it with an explicit build type before running -``make`` and ``make install``, for example: - -``` -$ ./configure --build=aarch64-unknown-linux-gnu -``` - -This is caused by old ``config.guess`` file, so another way to solve this is -to copy a newer version of config.guess into the underlying TA-Lib C library -sources: - -``` -$ cp /usr/share/automake-1.16/config.guess /path/to/extracted/ta-lib/config.guess -``` - -And then re-run configure: - -``` -$ ./configure -``` - ---- - -If you're having trouble using [PyInstaller](https://pyinstaller.org) and -get an error that looks like this: - -``` -...site-packages\PyInstaller\loader\pyimod03_importers.py", line 493, in exec_module - exec(bytecode, module.__dict__) - File "talib\__init__.py", line 72, in -ModuleNotFoundError: No module named 'talib.stream' -``` - -Then, perhaps you can use the ``--hidden-import`` argument to fix this: - -``` -$ pyinstaller --hidden-import talib.stream "replaceToYourFileName.py" -``` - ---- - -If you want to use ``numpy<2``, then you should use ``ta-lib<0.5``. - -If you want to use ``numpy>=2``, then you should use ``ta-lib>=0.5``. - ---- - -If you have trouble getting the code autocompletions to work in Visual -Studio Code, a suggestion was made to look for the ``Python`` extension -settings, and an option for ``Language Server``, and change it from -``Default`` (which means ``Pylance if it is installed, Jedi otherwise``, to -manually set ``Jedi`` and the completions should work. It is possible that -you might need to [install it -manually](https://github.com/pappasam/jedi-language-server) for this to -work. - -## Function API - -Similar to TA-Lib, the Function API provides a lightweight wrapper of the -exposed TA-Lib indicators. - -Each function returns an output array and have default values for their -parameters, unless specified as keyword arguments. Typically, these functions -will have an initial "lookback" period (a required number of observations -before an output is generated) set to ``NaN``. - -For convenience, the Function API supports both ``numpy.ndarray`` and -``pandas.Series`` and ``polars.Series`` inputs. - -All of the following examples use the Function API: - -```python -import numpy as np -import talib - -close = np.random.random(100) -``` - -Calculate a simple moving average of the close prices: - -```python -output = talib.SMA(close) -``` - -Calculating bollinger bands, with triple exponential moving average: - -```python -from talib import MA_Type - -upper, middle, lower = talib.BBANDS(close, matype=MA_Type.T3) -``` - -Calculating momentum of the close prices, with a time period of 5: - -```python -output = talib.MOM(close, timeperiod=5) -``` - -##### NaN's - -The underlying TA-Lib C library handles NaN's in a sometimes surprising manner -by typically propagating NaN's to the end of the output, for example: - -```python ->>> c = np.array([1.0, 2.0, 3.0, np.nan, 4.0, 5.0, 6.0]) - ->>> talib.SMA(c, 3) -array([nan, nan, 2., nan, nan, nan, nan]) -``` - -You can compare that to a Pandas rolling mean, where their approach is to -output NaN until enough "lookback" values are observed to generate new outputs: - -```python ->>> c = pandas.Series([1.0, 2.0, 3.0, np.nan, 4.0, 5.0, 6.0]) - ->>> c.rolling(3).mean() -0 NaN -1 NaN -2 2.0 -3 NaN -4 NaN -5 NaN -6 5.0 -dtype: float64 -``` - -## Abstract API - -If you're already familiar with using the function API, you should feel right -at home using the Abstract API. - -Every function takes a collection of named inputs, either a ``dict`` of -``numpy.ndarray`` or ``pandas.Series`` or ``polars.Series``, or a -``pandas.DataFrame`` or ``polars.DataFrame``. If a ``pandas.DataFrame`` or -``polars.DataFrame`` is provided, the output is returned as the same type -with named output columns. - -For example, inputs could be provided for the typical "OHLCV" data: - -```python -import numpy as np - -# note that all ndarrays must be the same length! -inputs = { - 'open': np.random.random(100), - 'high': np.random.random(100), - 'low': np.random.random(100), - 'close': np.random.random(100), - 'volume': np.random.random(100) -} -``` - -Functions can either be imported directly or instantiated by name: - -```python -from talib import abstract - -# directly -SMA = abstract.SMA - -# or by name -SMA = abstract.Function('sma') -``` - -From there, calling functions is basically the same as the function API: - -```python -from talib.abstract import * - -# uses close prices (default) -output = SMA(inputs, timeperiod=25) - -# uses open prices -output = SMA(inputs, timeperiod=25, price='open') - -# uses close prices (default) -upper, middle, lower = BBANDS(inputs, 20, 2.0, 2.0) - -# uses high, low, close (default) -slowk, slowd = STOCH(inputs, 5, 3, 0, 3, 0) # uses high, low, close by default - -# uses high, low, open instead -slowk, slowd = STOCH(inputs, 5, 3, 0, 3, 0, prices=['high', 'low', 'open']) -``` - -## Streaming API - -An experimental Streaming API was added that allows users to compute the latest -value of an indicator. This can be faster than using the Function API, for -example in an application that receives streaming data, and wants to know just -the most recent updated indicator value. - -```python -import talib -from talib import stream - -close = np.random.random(100) - -# the Function API -output = talib.SMA(close) - -# the Streaming API -latest = stream.SMA(close) - -# the latest value is the same as the last output value -assert (output[-1] - latest) < 0.00001 -``` - -## Supported Indicators and Functions - -We can show all the TA functions supported by TA-Lib, either as a ``list`` or -as a ``dict`` sorted by group (e.g. "Overlap Studies", "Momentum Indicators", -etc): - -```python -import talib - -# list of functions -for name in talib.get_functions(): - print(name) - -# dict of functions by group -for group, names in talib.get_function_groups().items(): - print(group) - for name in names: - print(f" {name}") -``` - -### Indicator Groups - -* Overlap Studies -* Momentum Indicators -* Volume Indicators -* Volatility Indicators -* Price Transform -* Cycle Indicators -* Pattern Recognition - -##### Overlap Studies - -``` -BBANDS Bollinger Bands -DEMA Double Exponential Moving Average -EMA Exponential Moving Average -HT_TRENDLINE Hilbert Transform - Instantaneous Trendline -KAMA Kaufman Adaptive Moving Average -MA Moving average -MAMA MESA Adaptive Moving Average -MAVP Moving average with variable period -MIDPOINT MidPoint over period -MIDPRICE Midpoint Price over period -SAR Parabolic SAR -SAREXT Parabolic SAR - Extended -SMA Simple Moving Average -T3 Triple Exponential Moving Average (T3) -TEMA Triple Exponential Moving Average -TRIMA Triangular Moving Average -WMA Weighted Moving Average -``` - -##### Momentum Indicators - -``` -ADX Average Directional Movement Index -ADXR Average Directional Movement Index Rating -APO Absolute Price Oscillator -AROON Aroon -AROONOSC Aroon Oscillator -BOP Balance Of Power -CCI Commodity Channel Index -CMO Chande Momentum Oscillator -DX Directional Movement Index -MACD Moving Average Convergence/Divergence -MACDEXT MACD with controllable MA type -MACDFIX Moving Average Convergence/Divergence Fix 12/26 -MFI Money Flow Index -MINUS_DI Minus Directional Indicator -MINUS_DM Minus Directional Movement -MOM Momentum -PLUS_DI Plus Directional Indicator -PLUS_DM Plus Directional Movement -PPO Percentage Price Oscillator -ROC Rate of change : ((price/prevPrice)-1)*100 -ROCP Rate of change Percentage: (price-prevPrice)/prevPrice -ROCR Rate of change ratio: (price/prevPrice) -ROCR100 Rate of change ratio 100 scale: (price/prevPrice)*100 -RSI Relative Strength Index -STOCH Stochastic -STOCHF Stochastic Fast -STOCHRSI Stochastic Relative Strength Index -TRIX 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA -ULTOSC Ultimate Oscillator -WILLR Williams' %R -``` - -##### Volume Indicators - -``` -AD Chaikin A/D Line -ADOSC Chaikin A/D Oscillator -OBV On Balance Volume -``` - -##### Cycle Indicators - -``` -HT_DCPERIOD Hilbert Transform - Dominant Cycle Period -HT_DCPHASE Hilbert Transform - Dominant Cycle Phase -HT_PHASOR Hilbert Transform - Phasor Components -HT_SINE Hilbert Transform - SineWave -HT_TRENDMODE Hilbert Transform - Trend vs Cycle Mode -``` - -##### Price Transform - -``` -AVGPRICE Average Price -MEDPRICE Median Price -TYPPRICE Typical Price -WCLPRICE Weighted Close Price -``` - -##### Volatility Indicators - -``` -ATR Average True Range -NATR Normalized Average True Range -TRANGE True Range -``` - -##### Pattern Recognition - -``` -CDL2CROWS Two Crows -CDL3BLACKCROWS Three Black Crows -CDL3INSIDE Three Inside Up/Down -CDL3LINESTRIKE Three-Line Strike -CDL3OUTSIDE Three Outside Up/Down -CDL3STARSINSOUTH Three Stars In The South -CDL3WHITESOLDIERS Three Advancing White Soldiers -CDLABANDONEDBABY Abandoned Baby -CDLADVANCEBLOCK Advance Block -CDLBELTHOLD Belt-hold -CDLBREAKAWAY Breakaway -CDLCLOSINGMARUBOZU Closing Marubozu -CDLCONCEALBABYSWALL Concealing Baby Swallow -CDLCOUNTERATTACK Counterattack -CDLDARKCLOUDCOVER Dark Cloud Cover -CDLDOJI Doji -CDLDOJISTAR Doji Star -CDLDRAGONFLYDOJI Dragonfly Doji -CDLENGULFING Engulfing Pattern -CDLEVENINGDOJISTAR Evening Doji Star -CDLEVENINGSTAR Evening Star -CDLGAPSIDESIDEWHITE Up/Down-gap side-by-side white lines -CDLGRAVESTONEDOJI Gravestone Doji -CDLHAMMER Hammer -CDLHANGINGMAN Hanging Man -CDLHARAMI Harami Pattern -CDLHARAMICROSS Harami Cross Pattern -CDLHIGHWAVE High-Wave Candle -CDLHIKKAKE Hikkake Pattern -CDLHIKKAKEMOD Modified Hikkake Pattern -CDLHOMINGPIGEON Homing Pigeon -CDLIDENTICAL3CROWS Identical Three Crows -CDLINNECK In-Neck Pattern -CDLINVERTEDHAMMER Inverted Hammer -CDLKICKING Kicking -CDLKICKINGBYLENGTH Kicking - bull/bear determined by the longer marubozu -CDLLADDERBOTTOM Ladder Bottom -CDLLONGLEGGEDDOJI Long Legged Doji -CDLLONGLINE Long Line Candle -CDLMARUBOZU Marubozu -CDLMATCHINGLOW Matching Low -CDLMATHOLD Mat Hold -CDLMORNINGDOJISTAR Morning Doji Star -CDLMORNINGSTAR Morning Star -CDLONNECK On-Neck Pattern -CDLPIERCING Piercing Pattern -CDLRICKSHAWMAN Rickshaw Man -CDLRISEFALL3METHODS Rising/Falling Three Methods -CDLSEPARATINGLINES Separating Lines -CDLSHOOTINGSTAR Shooting Star -CDLSHORTLINE Short Line Candle -CDLSPINNINGTOP Spinning Top -CDLSTALLEDPATTERN Stalled Pattern -CDLSTICKSANDWICH Stick Sandwich -CDLTAKURI Takuri (Dragonfly Doji with very long lower shadow) -CDLTASUKIGAP Tasuki Gap -CDLTHRUSTING Thrusting Pattern -CDLTRISTAR Tristar Pattern -CDLUNIQUE3RIVER Unique 3 River -CDLUPSIDEGAP2CROWS Upside Gap Two Crows -CDLXSIDEGAP3METHODS Upside/Downside Gap Three Methods -``` - -##### Statistic Functions - -``` -BETA Beta -CORREL Pearson's Correlation Coefficient (r) -LINEARREG Linear Regression -LINEARREG_ANGLE Linear Regression Angle -LINEARREG_INTERCEPT Linear Regression Intercept -LINEARREG_SLOPE Linear Regression Slope -STDDEV Standard Deviation -TSF Time Series Forecast -VAR Variance -``` diff --git a/abstract.html b/abstract.html new file mode 100644 index 000000000..486566127 --- /dev/null +++ b/abstract.html @@ -0,0 +1,129 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Abstract API Quick Start

+

If you're already familiar with using the function API, you should feel right +at home using the abstract API. Every function takes the same input, passed +as a dictionary of Numpy arrays:

+
import numpy as np
+# note that all ndarrays must be the same length!
+inputs = {
+    'open': np.random.random(100),
+    'high': np.random.random(100),
+    'low': np.random.random(100),
+    'close': np.random.random(100),
+    'volume': np.random.random(100)
+}
+
+

Functions can either be imported directly or instantiated by name:

+
from talib import abstract
+sma = abstract.SMA
+sma = abstract.Function('sma')
+
+

From there, calling functions is basically the same as the function API:

+
from talib.abstract import *
+output = SMA(inputs, timeperiod=25) # calculate on close prices by default
+output = SMA(inputs, timeperiod=25, price='open') # calculate on opens
+upper, middle, lower = BBANDS(inputs, 20, 2, 2)
+slowk, slowd = STOCH(inputs, 5, 3, 0, 3, 0) # uses high, low, close by default
+slowk, slowd = STOCH(inputs, 5, 3, 0, 3, 0, prices=['high', 'low', 'open'])
+
+

Advanced Usage

+

For more advanced use cases of TA-Lib, the Abstract API also offers much more +flexibility. You can even subclass abstract.Function and override +set_input_arrays to customize the type of input data Function accepts +(e.g. a pandas DataFrame).

+

Details about every function can be accessed via the info property:

+
print Function('stoch').info
+{
+  'name': 'STOCH',
+  'display_name': 'Stochastic',
+  'group': 'Momentum Indicators',
+  'input_names': OrderedDict([
+    ('prices', ['high', 'low', 'close']),
+  ]),
+  'parameters': OrderedDict([
+    ('fastk_period', 5),
+    ('slowk_period', 3),
+    ('slowk_matype', 0),
+    ('slowd_period', 3),
+    ('slowd_matype', 0),
+  ]),
+  'output_names': ['slowk', 'slowd'],
+}
+
+

Or in human-readable format:

+
help(STOCH)
+str(STOCH)
+
+

Other useful properties of Function:

+
Function('x').function_flags
+Function('x').input_names
+Function('x').input_arrays
+Function('x').parameters
+Function('x').lookback
+Function('x').output_names
+Function('x').output_flags
+Function('x').outputs
+
+

Aside from calling the function directly, Functions maintain state and will +remember their parameters/input_arrays after they've been set. You can set +parameters and recalculate with new input data using run():

+
SMA.parameters = {'timeperiod': 15}
+result1 = SMA.run(input_arrays1)
+result2 = SMA.run(input_arrays2)
+
+# Or set input_arrays and change the parameters:
+SMA.input_arrays = input_arrays1
+ma10 = SMA(timeperiod=10)
+ma20 = SMA(20)
+
+

For more details, take a look at the +code.

+

Documentation Index

+
+
+ + + + + + diff --git a/doc_index.html b/doc_index.html new file mode 100644 index 000000000..9af4f4366 --- /dev/null +++ b/doc_index.html @@ -0,0 +1,68 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Documentation

+ +
+
+ + + + + + diff --git a/docs/abstract.md b/docs/abstract.md deleted file mode 100644 index 96a979967..000000000 --- a/docs/abstract.md +++ /dev/null @@ -1,103 +0,0 @@ -# Abstract API Quick Start - -If you're already familiar with using the function API, you should feel right -at home using the abstract API. Every function takes the same input, passed -as a dictionary of Numpy arrays: - -```python -import numpy as np -# note that all ndarrays must be the same length! -inputs = { - 'open': np.random.random(100), - 'high': np.random.random(100), - 'low': np.random.random(100), - 'close': np.random.random(100), - 'volume': np.random.random(100) -} -``` - -Functions can either be imported directly or instantiated by name: - -```python -from talib import abstract -sma = abstract.SMA -sma = abstract.Function('sma') -``` - -From there, calling functions is basically the same as the function API: - -```python -from talib.abstract import * -output = SMA(inputs, timeperiod=25) # calculate on close prices by default -output = SMA(inputs, timeperiod=25, price='open') # calculate on opens -upper, middle, lower = BBANDS(inputs, 20, 2, 2) -slowk, slowd = STOCH(inputs, 5, 3, 0, 3, 0) # uses high, low, close by default -slowk, slowd = STOCH(inputs, 5, 3, 0, 3, 0, prices=['high', 'low', 'open']) -``` - -## Advanced Usage - -For more advanced use cases of TA-Lib, the Abstract API also offers much more -flexibility. You can even subclass ``abstract.Function`` and override -``set_input_arrays`` to customize the type of input data Function accepts -(e.g. a pandas DataFrame). - -Details about every function can be accessed via the info property: - -```python -print Function('stoch').info -{ - 'name': 'STOCH', - 'display_name': 'Stochastic', - 'group': 'Momentum Indicators', - 'input_names': OrderedDict([ - ('prices', ['high', 'low', 'close']), - ]), - 'parameters': OrderedDict([ - ('fastk_period', 5), - ('slowk_period', 3), - ('slowk_matype', 0), - ('slowd_period', 3), - ('slowd_matype', 0), - ]), - 'output_names': ['slowk', 'slowd'], -} - -``` -Or in human-readable format: -```python -help(STOCH) -str(STOCH) -``` - -Other useful properties of ``Function``: - -```python -Function('x').function_flags -Function('x').input_names -Function('x').input_arrays -Function('x').parameters -Function('x').lookback -Function('x').output_names -Function('x').output_flags -Function('x').outputs -``` - -Aside from calling the function directly, Functions maintain state and will -remember their parameters/input_arrays after they've been set. You can set -parameters and recalculate with new input data using run(): -```python -SMA.parameters = {'timeperiod': 15} -result1 = SMA.run(input_arrays1) -result2 = SMA.run(input_arrays2) - -# Or set input_arrays and change the parameters: -SMA.input_arrays = input_arrays1 -ma10 = SMA(timeperiod=10) -ma20 = SMA(20) -``` - -For more details, take a look at the -[code](https://github.com/ta-lib/ta-lib-python/blob/master/talib/abstract.pyx#L46). - -[Documentation Index](doc_index.md) diff --git a/docs/doc_index.md b/docs/doc_index.md deleted file mode 100644 index ae43f1cf6..000000000 --- a/docs/doc_index.md +++ /dev/null @@ -1,16 +0,0 @@ -# Documentation - -* [Installation and Troubleshooting](install.md) -* [Using the Function API](func.md) -* [Using the Abstract API](abstract.md) -* [All Functions](funcs.md) - * [Overlap Studies](func_groups/overlap_studies.md) - * [Momentum Indicators](func_groups/momentum_indicators.md) - * [Volume Indicators](func_groups/volume_indicators.md) - * [Volatility Indicators](func_groups/volatility_indicators.md) - * [Price Transform](func_groups/price_transform.md) - * [Cycle Indicators](func_groups/cycle_indicators.md) - * [Pattern Recognition](func_groups/pattern_recognition.md) - * [Statistic Functions](func_groups/statistic_functions.md) - * [Math Transform](func_groups/math_transform.md) - * [Math Operators](func_groups/math_operators.md) diff --git a/docs/func.md b/docs/func.md deleted file mode 100644 index 11d4efc09..000000000 --- a/docs/func.md +++ /dev/null @@ -1,54 +0,0 @@ -# Function API Examples - -Similar to TA-Lib, the function interface provides a lightweight wrapper of -the exposed TA-Lib indicators. - -Each function returns an output array and have default values for their -parameters, unless specified as keyword arguments. Typically, these functions -will have an initial "lookback" period (a required number of observations -before an output is generated) set to ``NaN``. - -All of the following examples use the function API: - -```python -import numpy -import talib - -close = numpy.random.random(100) -``` - -Calculate a simple moving average of the close prices: - -```python -output = talib.SMA(close) -``` - -Calculating bollinger bands, with triple exponential moving average: - -```python -from talib import MA_Type - -upper, middle, lower = talib.BBANDS(close, matype=MA_Type.T3) -``` - -Calculating momentum of the close prices, with a time period of 5: - -```python -output = talib.MOM(close, timeperiod=5) -``` - -Documentation for all functions: - -* [Overlap Studies](func_groups/overlap_studies.md) -* [Momentum Indicators](func_groups/momentum_indicators.md) -* [Volume Indicators](func_groups/volume_indicators.md) -* [Volatility Indicators](func_groups/volatility_indicators.md) -* [Pattern Recognition](func_groups/pattern_recognition.md) -* [Cycle Indicators](func_groups/cycle_indicators.md) -* [Statistic Functions](func_groups/statistic_functions.md) -* [Price Transform](func_groups/price_transform.md) -* [Math Transform](func_groups/math_transform.md) -* [Math Operators](func_groups/math_operators.md) - -[Documentation Index](doc_index.md) -[FLOAT_RIGHTNext: Using the Abstract API](abstract.md) diff --git a/docs/func_groups/cycle_indicators.md b/docs/func_groups/cycle_indicators.md deleted file mode 100644 index db5761f26..000000000 --- a/docs/func_groups/cycle_indicators.md +++ /dev/null @@ -1,35 +0,0 @@ -# Cycle Indicator Functions -### HT_DCPERIOD - Hilbert Transform - Dominant Cycle Period -NOTE: The ``HT_DCPERIOD`` function has an unstable period. -```python -real = HT_DCPERIOD(real) -``` - -### HT_DCPHASE - Hilbert Transform - Dominant Cycle Phase -NOTE: The ``HT_DCPHASE`` function has an unstable period. -```python -real = HT_DCPHASE(real) -``` - -### HT_PHASOR - Hilbert Transform - Phasor Components -NOTE: The ``HT_PHASOR`` function has an unstable period. -```python -inphase, quadrature = HT_PHASOR(real) -``` - -### HT_SINE - Hilbert Transform - SineWave -NOTE: The ``HT_SINE`` function has an unstable period. -```python -sine, leadsine = HT_SINE(real) -``` - -### HT_TRENDMODE - Hilbert Transform - Trend vs Cycle Mode -NOTE: The ``HT_TRENDMODE`` function has an unstable period. -```python -integer = HT_TRENDMODE(real) -``` - - -[Documentation Index](../doc_index.md) - -[FLOAT_RIGHTAll Function Groups](../funcs.md) diff --git a/docs/func_groups/math_operators.md b/docs/func_groups/math_operators.md deleted file mode 100644 index 7a48fde22..000000000 --- a/docs/func_groups/math_operators.md +++ /dev/null @@ -1,60 +0,0 @@ -# Math Operator Functions -### ADD - Vector Arithmetic Add -```python -real = ADD(real0, real1) -``` - -### DIV - Vector Arithmetic Div -```python -real = DIV(real0, real1) -``` - -### MAX - Highest value over a specified period -```python -real = MAX(real, timeperiod=30) -``` - -### MAXINDEX - Index of highest value over a specified period -```python -integer = MAXINDEX(real, timeperiod=30) -``` - -### MIN - Lowest value over a specified period -```python -real = MIN(real, timeperiod=30) -``` - -### MININDEX - Index of lowest value over a specified period -```python -integer = MININDEX(real, timeperiod=30) -``` - -### MINMAX - Lowest and highest values over a specified period -```python -min, max = MINMAX(real, timeperiod=30) -``` - -### MINMAXINDEX - Indexes of lowest and highest values over a specified period -```python -minidx, maxidx = MINMAXINDEX(real, timeperiod=30) -``` - -### MULT - Vector Arithmetic Mult -```python -real = MULT(real0, real1) -``` - -### SUB - Vector Arithmetic Subtraction -```python -real = SUB(real0, real1) -``` - -### SUM - Summation -```python -real = SUM(real, timeperiod=30) -``` - - -[Documentation Index](../doc_index.md) - -[FLOAT_RIGHTAll Function Groups](../funcs.md) diff --git a/docs/func_groups/math_transform.md b/docs/func_groups/math_transform.md deleted file mode 100644 index 749f8d034..000000000 --- a/docs/func_groups/math_transform.md +++ /dev/null @@ -1,80 +0,0 @@ -# Math Transform Functions -### ACOS - Vector Trigonometric ACos -```python -real = ACOS(real) -``` - -### ASIN - Vector Trigonometric ASin -```python -real = ASIN(real) -``` - -### ATAN - Vector Trigonometric ATan -```python -real = ATAN(real) -``` - -### CEIL - Vector Ceil -```python -real = CEIL(real) -``` - -### COS - Vector Trigonometric Cos -```python -real = COS(real) -``` - -### COSH - Vector Trigonometric Cosh -```python -real = COSH(real) -``` - -### EXP - Vector Arithmetic Exp -```python -real = EXP(real) -``` - -### FLOOR - Vector Floor -```python -real = FLOOR(real) -``` - -### LN - Vector Log Natural -```python -real = LN(real) -``` - -### LOG10 - Vector Log10 -```python -real = LOG10(real) -``` - -### SIN - Vector Trigonometric Sin -```python -real = SIN(real) -``` - -### SINH - Vector Trigonometric Sinh -```python -real = SINH(real) -``` - -### SQRT - Vector Square Root -```python -real = SQRT(real) -``` - -### TAN - Vector Trigonometric Tan -```python -real = TAN(real) -``` - -### TANH - Vector Trigonometric Tanh -```python -real = TANH(real) -``` - - -[Documentation Index](../doc_index.md) - -[FLOAT_RIGHTAll Function Groups](../funcs.md) diff --git a/docs/func_groups/momentum_indicators.md b/docs/func_groups/momentum_indicators.md deleted file mode 100644 index ea2fa6401..000000000 --- a/docs/func_groups/momentum_indicators.md +++ /dev/null @@ -1,166 +0,0 @@ -# Momentum Indicator Functions -### ADX - Average Directional Movement Index -NOTE: The ``ADX`` function has an unstable period. -```python -real = ADX(high, low, close, timeperiod=14) -``` - -### ADXR - Average Directional Movement Index Rating -NOTE: The ``ADXR`` function has an unstable period. -```python -real = ADXR(high, low, close, timeperiod=14) -``` - -### APO - Absolute Price Oscillator -```python -real = APO(real, fastperiod=12, slowperiod=26, matype=0) -``` - -### AROON - Aroon -```python -aroondown, aroonup = AROON(high, low, timeperiod=14) -``` - -### AROONOSC - Aroon Oscillator -```python -real = AROONOSC(high, low, timeperiod=14) -``` - -### BOP - Balance Of Power -```python -real = BOP(open, high, low, close) -``` - -### CCI - Commodity Channel Index -```python -real = CCI(high, low, close, timeperiod=14) -``` - -### CMO - Chande Momentum Oscillator -NOTE: The ``CMO`` function has an unstable period. -```python -real = CMO(real, timeperiod=14) -``` - -### DX - Directional Movement Index -NOTE: The ``DX`` function has an unstable period. -```python -real = DX(high, low, close, timeperiod=14) -``` - -### MACD - Moving Average Convergence/Divergence -```python -macd, macdsignal, macdhist = MACD(real, fastperiod=12, slowperiod=26, signalperiod=9) -``` - -### MACDEXT - MACD with controllable MA type -```python -macd, macdsignal, macdhist = MACDEXT(real, fastperiod=12, fastmatype=0, slowperiod=26, slowmatype=0, signalperiod=9, signalmatype=0) -``` - -### MACDFIX - Moving Average Convergence/Divergence Fix 12/26 -```python -macd, macdsignal, macdhist = MACDFIX(real, signalperiod=9) -``` - -### MFI - Money Flow Index -NOTE: The ``MFI`` function has an unstable period. -```python -real = MFI(high, low, close, volume, timeperiod=14) -``` - -### MINUS_DI - Minus Directional Indicator -NOTE: The ``MINUS_DI`` function has an unstable period. -```python -real = MINUS_DI(high, low, close, timeperiod=14) -``` - -### MINUS_DM - Minus Directional Movement -NOTE: The ``MINUS_DM`` function has an unstable period. -```python -real = MINUS_DM(high, low, timeperiod=14) -``` - -### MOM - Momentum -```python -real = MOM(real, timeperiod=10) -``` - -### PLUS_DI - Plus Directional Indicator -NOTE: The ``PLUS_DI`` function has an unstable period. -```python -real = PLUS_DI(high, low, close, timeperiod=14) -``` - -### PLUS_DM - Plus Directional Movement -NOTE: The ``PLUS_DM`` function has an unstable period. -```python -real = PLUS_DM(high, low, timeperiod=14) -``` - -### PPO - Percentage Price Oscillator -```python -real = PPO(real, fastperiod=12, slowperiod=26, matype=0) -``` - -### ROC - Rate of change : ((price/prevPrice)-1)*100 -```python -real = ROC(real, timeperiod=10) -``` - -### ROCP - Rate of change Percentage: (price-prevPrice)/prevPrice -```python -real = ROCP(real, timeperiod=10) -``` - -### ROCR - Rate of change ratio: (price/prevPrice) -```python -real = ROCR(real, timeperiod=10) -``` - -### ROCR100 - Rate of change ratio 100 scale: (price/prevPrice)*100 -```python -real = ROCR100(real, timeperiod=10) -``` - -### RSI - Relative Strength Index -NOTE: The ``RSI`` function has an unstable period. -```python -real = RSI(real, timeperiod=14) -``` - -### STOCH - Stochastic -```python -slowk, slowd = STOCH(high, low, close, fastk_period=5, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0) -``` - -### STOCHF - Stochastic Fast -```python -fastk, fastd = STOCHF(high, low, close, fastk_period=5, fastd_period=3, fastd_matype=0) -``` - -### STOCHRSI - Stochastic Relative Strength Index -NOTE: The ``STOCHRSI`` function has an unstable period. -```python -fastk, fastd = STOCHRSI(real, timeperiod=14, fastk_period=5, fastd_period=3, fastd_matype=0) -``` - -### TRIX - 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA -```python -real = TRIX(real, timeperiod=30) -``` - -### ULTOSC - Ultimate Oscillator -```python -real = ULTOSC(high, low, close, timeperiod1=7, timeperiod2=14, timeperiod3=28) -``` - -### WILLR - Williams' %R -```python -real = WILLR(high, low, close, timeperiod=14) -``` - - -[Documentation Index](../doc_index.md) - -[FLOAT_RIGHTAll Function Groups](../funcs.md) diff --git a/docs/func_groups/overlap_studies.md b/docs/func_groups/overlap_studies.md deleted file mode 100644 index 4625ca85b..000000000 --- a/docs/func_groups/overlap_studies.md +++ /dev/null @@ -1,94 +0,0 @@ -# Overlap Studies Functions -### BBANDS - Bollinger Bands -```python -upperband, middleband, lowerband = BBANDS(real, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0) -``` - -### DEMA - Double Exponential Moving Average -```python -real = DEMA(real, timeperiod=30) -``` - -### EMA - Exponential Moving Average -NOTE: The ``EMA`` function has an unstable period. -```python -real = EMA(real, timeperiod=30) -``` - -### HT_TRENDLINE - Hilbert Transform - Instantaneous Trendline -NOTE: The ``HT_TRENDLINE`` function has an unstable period. -```python -real = HT_TRENDLINE(real) -``` - -### KAMA - Kaufman Adaptive Moving Average -NOTE: The ``KAMA`` function has an unstable period. -```python -real = KAMA(real, timeperiod=30) -``` - -### MA - Moving average -```python -real = MA(real, timeperiod=30, matype=0) -``` - -### MAMA - MESA Adaptive Moving Average -NOTE: The ``MAMA`` function has an unstable period. -```python -mama, fama = MAMA(real, fastlimit=0, slowlimit=0) -``` - -### MAVP - Moving average with variable period -```python -real = MAVP(real, periods, minperiod=2, maxperiod=30, matype=0) -``` - -### MIDPOINT - MidPoint over period -```python -real = MIDPOINT(real, timeperiod=14) -``` - -### MIDPRICE - Midpoint Price over period -```python -real = MIDPRICE(high, low, timeperiod=14) -``` - -### SAR - Parabolic SAR -```python -real = SAR(high, low, acceleration=0, maximum=0) -``` - -### SAREXT - Parabolic SAR - Extended -```python -real = SAREXT(high, low, startvalue=0, offsetonreverse=0, accelerationinitlong=0, accelerationlong=0, accelerationmaxlong=0, accelerationinitshort=0, accelerationshort=0, accelerationmaxshort=0) -``` - -### SMA - Simple Moving Average -```python -real = SMA(real, timeperiod=30) -``` - -### T3 - Triple Exponential Moving Average (T3) -NOTE: The ``T3`` function has an unstable period. -```python -real = T3(real, timeperiod=5, vfactor=0) -``` - -### TEMA - Triple Exponential Moving Average -```python -real = TEMA(real, timeperiod=30) -``` - -### TRIMA - Triangular Moving Average -```python -real = TRIMA(real, timeperiod=30) -``` - -### WMA - Weighted Moving Average -```python -real = WMA(real, timeperiod=30) -``` - -[Documentation Index](../doc_index.md) - -[FLOAT_RIGHTAll Function Groups](../funcs.md) diff --git a/docs/func_groups/pattern_recognition.md b/docs/func_groups/pattern_recognition.md deleted file mode 100644 index 39a3efa9d..000000000 --- a/docs/func_groups/pattern_recognition.md +++ /dev/null @@ -1,310 +0,0 @@ -# Pattern Recognition Functions -### CDL2CROWS - Two Crows -```python -integer = CDL2CROWS(open, high, low, close) -``` - -### CDL3BLACKCROWS - Three Black Crows -```python -integer = CDL3BLACKCROWS(open, high, low, close) -``` - -### CDL3INSIDE - Three Inside Up/Down -```python -integer = CDL3INSIDE(open, high, low, close) -``` - -### CDL3LINESTRIKE - Three-Line Strike -```python -integer = CDL3LINESTRIKE(open, high, low, close) -``` - -### CDL3OUTSIDE - Three Outside Up/Down -```python -integer = CDL3OUTSIDE(open, high, low, close) -``` - -### CDL3STARSINSOUTH - Three Stars In The South -```python -integer = CDL3STARSINSOUTH(open, high, low, close) -``` - -### CDL3WHITESOLDIERS - Three Advancing White Soldiers -```python -integer = CDL3WHITESOLDIERS(open, high, low, close) -``` - -### CDLABANDONEDBABY - Abandoned Baby -```python -integer = CDLABANDONEDBABY(open, high, low, close, penetration=0) -``` - -### CDLADVANCEBLOCK - Advance Block -```python -integer = CDLADVANCEBLOCK(open, high, low, close) -``` - -### CDLBELTHOLD - Belt-hold -```python -integer = CDLBELTHOLD(open, high, low, close) -``` - -### CDLBREAKAWAY - Breakaway -```python -integer = CDLBREAKAWAY(open, high, low, close) -``` - -### CDLCLOSINGMARUBOZU - Closing Marubozu -```python -integer = CDLCLOSINGMARUBOZU(open, high, low, close) -``` - -### CDLCONCEALBABYSWALL - Concealing Baby Swallow -```python -integer = CDLCONCEALBABYSWALL(open, high, low, close) -``` - -### CDLCOUNTERATTACK - Counterattack -```python -integer = CDLCOUNTERATTACK(open, high, low, close) -``` - -### CDLDARKCLOUDCOVER - Dark Cloud Cover -```python -integer = CDLDARKCLOUDCOVER(open, high, low, close, penetration=0) -``` - -### CDLDOJI - Doji -```python -integer = CDLDOJI(open, high, low, close) -``` - -### CDLDOJISTAR - Doji Star -```python -integer = CDLDOJISTAR(open, high, low, close) -``` - -### CDLDRAGONFLYDOJI - Dragonfly Doji -```python -integer = CDLDRAGONFLYDOJI(open, high, low, close) -``` - -### CDLENGULFING - Engulfing Pattern -```python -integer = CDLENGULFING(open, high, low, close) -``` - -### CDLEVENINGDOJISTAR - Evening Doji Star -```python -integer = CDLEVENINGDOJISTAR(open, high, low, close, penetration=0) -``` - -### CDLEVENINGSTAR - Evening Star -```python -integer = CDLEVENINGSTAR(open, high, low, close, penetration=0) -``` - -### CDLGAPSIDESIDEWHITE - Up/Down-gap side-by-side white lines -```python -integer = CDLGAPSIDESIDEWHITE(open, high, low, close) -``` - -### CDLGRAVESTONEDOJI - Gravestone Doji -```python -integer = CDLGRAVESTONEDOJI(open, high, low, close) -``` - -### CDLHAMMER - Hammer -```python -integer = CDLHAMMER(open, high, low, close) -``` - -### CDLHANGINGMAN - Hanging Man -```python -integer = CDLHANGINGMAN(open, high, low, close) -``` - -### CDLHARAMI - Harami Pattern -```python -integer = CDLHARAMI(open, high, low, close) -``` - -### CDLHARAMICROSS - Harami Cross Pattern -```python -integer = CDLHARAMICROSS(open, high, low, close) -``` - -### CDLHIGHWAVE - High-Wave Candle -```python -integer = CDLHIGHWAVE(open, high, low, close) -``` - -### CDLHIKKAKE - Hikkake Pattern -```python -integer = CDLHIKKAKE(open, high, low, close) -``` - -### CDLHIKKAKEMOD - Modified Hikkake Pattern -```python -integer = CDLHIKKAKEMOD(open, high, low, close) -``` - -### CDLHOMINGPIGEON - Homing Pigeon -```python -integer = CDLHOMINGPIGEON(open, high, low, close) -``` - -### CDLIDENTICAL3CROWS - Identical Three Crows -```python -integer = CDLIDENTICAL3CROWS(open, high, low, close) -``` - -### CDLINNECK - In-Neck Pattern -```python -integer = CDLINNECK(open, high, low, close) -``` - -### CDLINVERTEDHAMMER - Inverted Hammer -```python -integer = CDLINVERTEDHAMMER(open, high, low, close) -``` - -### CDLKICKING - Kicking -```python -integer = CDLKICKING(open, high, low, close) -``` - -### CDLKICKINGBYLENGTH - Kicking - bull/bear determined by the longer marubozu -```python -integer = CDLKICKINGBYLENGTH(open, high, low, close) -``` - -### CDLLADDERBOTTOM - Ladder Bottom -```python -integer = CDLLADDERBOTTOM(open, high, low, close) -``` - -### CDLLONGLEGGEDDOJI - Long Legged Doji -```python -integer = CDLLONGLEGGEDDOJI(open, high, low, close) -``` - -### CDLLONGLINE - Long Line Candle -```python -integer = CDLLONGLINE(open, high, low, close) -``` - -### CDLMARUBOZU - Marubozu -```python -integer = CDLMARUBOZU(open, high, low, close) -``` - -### CDLMATCHINGLOW - Matching Low -```python -integer = CDLMATCHINGLOW(open, high, low, close) -``` - -### CDLMATHOLD - Mat Hold -```python -integer = CDLMATHOLD(open, high, low, close, penetration=0) -``` - -### CDLMORNINGDOJISTAR - Morning Doji Star -```python -integer = CDLMORNINGDOJISTAR(open, high, low, close, penetration=0) -``` - -### CDLMORNINGSTAR - Morning Star -```python -integer = CDLMORNINGSTAR(open, high, low, close, penetration=0) -``` - -### CDLONNECK - On-Neck Pattern -```python -integer = CDLONNECK(open, high, low, close) -``` - -### CDLPIERCING - Piercing Pattern -```python -integer = CDLPIERCING(open, high, low, close) -``` - -### CDLRICKSHAWMAN - Rickshaw Man -```python -integer = CDLRICKSHAWMAN(open, high, low, close) -``` - -### CDLRISEFALL3METHODS - Rising/Falling Three Methods -```python -integer = CDLRISEFALL3METHODS(open, high, low, close) -``` - -### CDLSEPARATINGLINES - Separating Lines -```python -integer = CDLSEPARATINGLINES(open, high, low, close) -``` - -### CDLSHOOTINGSTAR - Shooting Star -```python -integer = CDLSHOOTINGSTAR(open, high, low, close) -``` - -### CDLSHORTLINE - Short Line Candle -```python -integer = CDLSHORTLINE(open, high, low, close) -``` - -### CDLSPINNINGTOP - Spinning Top -```python -integer = CDLSPINNINGTOP(open, high, low, close) -``` - -### CDLSTALLEDPATTERN - Stalled Pattern -```python -integer = CDLSTALLEDPATTERN(open, high, low, close) -``` - -### CDLSTICKSANDWICH - Stick Sandwich -```python -integer = CDLSTICKSANDWICH(open, high, low, close) -``` - -### CDLTAKURI - Takuri (Dragonfly Doji with very long lower shadow) -```python -integer = CDLTAKURI(open, high, low, close) -``` - -### CDLTASUKIGAP - Tasuki Gap -```python -integer = CDLTASUKIGAP(open, high, low, close) -``` - -### CDLTHRUSTING - Thrusting Pattern -```python -integer = CDLTHRUSTING(open, high, low, close) -``` - -### CDLTRISTAR - Tristar Pattern -```python -integer = CDLTRISTAR(open, high, low, close) -``` - -### CDLUNIQUE3RIVER - Unique 3 River -```python -integer = CDLUNIQUE3RIVER(open, high, low, close) -``` - -### CDLUPSIDEGAP2CROWS - Upside Gap Two Crows -```python -integer = CDLUPSIDEGAP2CROWS(open, high, low, close) -``` - -### CDLXSIDEGAP3METHODS - Upside/Downside Gap Three Methods -```python -integer = CDLXSIDEGAP3METHODS(open, high, low, close) -``` - - -[Documentation Index](../doc_index.md) - -[FLOAT_RIGHTAll Function Groups](../funcs.md) \ No newline at end of file diff --git a/docs/func_groups/price_transform.md b/docs/func_groups/price_transform.md deleted file mode 100644 index 1f79b1962..000000000 --- a/docs/func_groups/price_transform.md +++ /dev/null @@ -1,25 +0,0 @@ -# Price Transform Functions -### AVGPRICE - Average Price -```python -real = AVGPRICE(open, high, low, close) -``` - -### MEDPRICE - Median Price -```python -real = MEDPRICE(high, low) -``` - -### TYPPRICE - Typical Price -```python -real = TYPPRICE(high, low, close) -``` - -### WCLPRICE - Weighted Close Price -```python -real = WCLPRICE(high, low, close) -``` - - -[Documentation Index](../doc_index.md) - -[FLOAT_RIGHTAll Function Groups](../funcs.md) \ No newline at end of file diff --git a/docs/func_groups/statistic_functions.md b/docs/func_groups/statistic_functions.md deleted file mode 100644 index db629952c..000000000 --- a/docs/func_groups/statistic_functions.md +++ /dev/null @@ -1,50 +0,0 @@ -# Statistic Functions -### BETA - Beta -```python -real = BETA(real0, real1, timeperiod=5) -``` - -### CORREL - Pearson's Correlation Coefficient (r) -```python -real = CORREL(real0, real1, timeperiod=30) -``` - -### LINEARREG - Linear Regression -```python -real = LINEARREG(real, timeperiod=14) -``` - -### LINEARREG_ANGLE - Linear Regression Angle -```python -real = LINEARREG_ANGLE(real, timeperiod=14) -``` - -### LINEARREG_INTERCEPT - Linear Regression Intercept -```python -real = LINEARREG_INTERCEPT(real, timeperiod=14) -``` - -### LINEARREG_SLOPE - Linear Regression Slope -```python -real = LINEARREG_SLOPE(real, timeperiod=14) -``` - -### STDDEV - Standard Deviation -```python -real = STDDEV(real, timeperiod=5, nbdev=1) -``` - -### TSF - Time Series Forecast -```python -real = TSF(real, timeperiod=14) -``` - -### VAR - Variance -```python -real = VAR(real, timeperiod=5, nbdev=1) -``` - - -[Documentation Index](../doc_index.md) - -[FLOAT_RIGHTAll Function Groups](../funcs.md) diff --git a/docs/func_groups/volatility_indicators.md b/docs/func_groups/volatility_indicators.md deleted file mode 100644 index d14337b33..000000000 --- a/docs/func_groups/volatility_indicators.md +++ /dev/null @@ -1,22 +0,0 @@ -# Volatility Indicator Functions -### ATR - Average True Range -NOTE: The ``ATR`` function has an unstable period. -```python -real = ATR(high, low, close, timeperiod=14) -``` - -### NATR - Normalized Average True Range -NOTE: The ``NATR`` function has an unstable period. -```python -real = NATR(high, low, close, timeperiod=14) -``` - -### TRANGE - True Range -```python -real = TRANGE(high, low, close) -``` - - -[Documentation Index](../doc_index.md) - -[FLOAT_RIGHTAll Function Groups](../funcs.md) \ No newline at end of file diff --git a/docs/func_groups/volume_indicators.md b/docs/func_groups/volume_indicators.md deleted file mode 100644 index c64fc29c3..000000000 --- a/docs/func_groups/volume_indicators.md +++ /dev/null @@ -1,20 +0,0 @@ -# Volume Indicator Functions -### AD - Chaikin A/D Line -```python -real = AD(high, low, close, volume) -``` - -### ADOSC - Chaikin A/D Oscillator -```python -real = ADOSC(high, low, close, volume, fastperiod=3, slowperiod=10) -``` - -### OBV - On Balance Volume -```python -real = OBV(close, volume) -``` - - -[Documentation Index](../doc_index.md) - -[FLOAT_RIGHTAll Function Groups](../funcs.md) \ No newline at end of file diff --git a/docs/generate_html_pages.py b/docs/generate_html_pages.py deleted file mode 100644 index 4656ee7f5..000000000 --- a/docs/generate_html_pages.py +++ /dev/null @@ -1,260 +0,0 @@ -""" -USAGE: - -To convert markdown docs into html docs: -$ python generate_html_pages.py /path/to/gh-pages/dir - -To generate pygments code highlighting stylesheet: -$ pygmentize -f html -S [STYLE_NAME] -a .highlight > /path/to/gh-pages/stylesheets/dir/pygments_style.css - -To list available style names (at python prompt) ->>> from pygments import styles ->>> sorted(styles.get_all_styles()) -# default, lovelace and xcode are "normal" styles -""" - -from __future__ import print_function - -import os -import sys -import talib - -import mistune - -from pygments import highlight -from pygments.lexers import get_lexer_by_name -from pygments.formatters.html import HtmlFormatter - -from bs4 import BeautifulSoup - -from talib.abstract import Function - - -INPUT_DIR = os.path.dirname(os.path.realpath(__file__)) -FUNCTION_GROUPS_DIR = os.path.join(INPUT_DIR, 'func_groups') -OUTPUT_DIR = os.path.join(INPUT_DIR, 'html') - - -HEADER = '''\ - - - - - - - - - TA-Lib - - - -
-
- View on GitHub -
- -
-
-

TA-Lib

-

Python wrapper for TA-Lib (https://ta-lib.org/).

-
- Download this project as a .zip file - Download this project as a tar.gz file -
-
-
- - -
-
-''' - -FOOTER = '''\ -
-
- - - - - - -''' - - -def slugify(string): - return string.lower().replace(' ', '_') - - -def get_doc_links(): - """Returns a dictionary of function names -> upstream documentation link""" - tadoc_homepage = 'https://www.tadoc.org/' - html_file_path = os.path.join(INPUT_DIR, '.tadoc.org.html') - if os.path.exists(html_file_path): - with open(html_file_path, 'r') as f: - html = f.read() - else: - if sys.version_info < (2, 8): - from urllib2 import urlopen - else: - from urllib.request import urlopen - - html = urlopen(tadoc_homepage).read() - with open(html_file_path, 'wb') as f: - f.write(html) - - # find every link that's for an indicator and convert to absolute urls - soup = BeautifulSoup(html, 'html.parser') - links = [a for a in soup.findAll('a') if 'indicator' in a['href']] - ret = {} - for a in links: - url = ''.join([tadoc_homepage, a['href']]) - func = url[url.rfind('/')+1:url.rfind('.')] - ret[func] = url - return ret - - -def generate_groups_markdown(): - """Generate and save markdown files for function group documentation""" - for group, group_docs in get_groups_markdown().items(): - file_path = os.path.join(FUNCTION_GROUPS_DIR, '%s.md' % group) - with open(file_path, 'w') as f: - f.write(group_docs) - - -def get_groups_markdown(): - """Generate markdown for function groups using the Abstract API - - Returns a dictionary of group_name -> documentation for group functions - """ - def unpluralize(noun): - if noun.endswith('s'): - if len(noun) > 2 and noun[-2] not in ["'", 'e']: - return noun[:-1] - return noun - - doc_links = get_doc_links() - ret = {} - for group, funcs in talib.get_function_groups().items(): - h1 = '# %s' % unpluralize(group) - h1 = h1 + ' Functions' if 'Function' not in h1 else h1 + 's' - group_docs = [h1] - for func in funcs: - # figure out this function's options - f = Function(func) - inputs = f.info['input_names'] - if 'price' in inputs and 'prices' in inputs: - names = [inputs['price']] - names.extend(inputs['prices']) - input_names = ', '.join(names) - elif 'prices' in inputs: - input_names = ', '.join(inputs['prices']) - else: - input_names = ', '.join([x for x in inputs.values() if x]) - - params = ', '.join( - ['%s=%i' % (param, default) - for param, default in f.info['parameters'].items()]) - outputs = ', '.join(f.info['output_names']) - - # print the header - group_docs.append('### %s - %s' % (func, f.info['display_name'])) - - if f.function_flags and 'Function has an unstable period' in f.function_flags: - group_docs.append('NOTE: The ``%s`` function has an unstable period. ' % func) - - # print the code definition block - group_docs.append("```python") - if params: - group_docs.append('%s = %s(%s, %s)' % ( - outputs, func.upper(), input_names, params)) - else: - group_docs.append('%s = %s(%s)' % ( - outputs, func.upper(), input_names)) - group_docs.append("```\n") - - - # print extra info if we can - if func in doc_links: - group_docs.append('Learn more about the %s at [tadoc.org](%s). ' % ( - f.info['display_name'], doc_links[func])) - - group_docs.append('\n[Documentation Index](../doc_index.md)') - group_docs.append('[FLOAT_RIGHTAll Function Groups](../funcs.md)') - - ret[slugify(group)] = '\n'.join(group_docs) + '\n' - return ret - - -def get_markdown_file_paths(): - file_names = [ - 'index.md', - 'doc_index.md', - 'install.md', - 'func.md', - 'funcs.md', - 'abstract.md', - ] - file_names.extend( - ['func_groups/%s' % x for x in os.listdir(FUNCTION_GROUPS_DIR) if x.endswith('.md')] - ) - return [os.path.join(INPUT_DIR, fn) for fn in file_names] - - -def _get_markdown_renderer(): - """Returns a function to convert a Markdown string into pygments-highlighted HTML""" - class PygmentsHighlighter(mistune.HTMLRenderer): - def block_code(self, code, info=None): - if not info: - return '\n
%s
\n' % mistune.escape(code) - lexer = get_lexer_by_name(info, stripall=True) - formatter = HtmlFormatter(classprefix='highlight ') - return highlight(code, lexer, formatter) - return mistune.Markdown(renderer=PygmentsHighlighter()) - - -def run_convert_to_html(output_dir): - """Converts markdown files into their respective html files""" - markdown_to_html = _get_markdown_renderer() - for md_file_path in get_markdown_file_paths(): - with open(md_file_path, 'r') as f: - html = markdown_to_html(f.read()) - html = html.replace('.md">', '.html">') - - head = HEADER - if 'func_groups' in md_file_path: - head = head.replace('"index.html"', '"../index.html"') - head = head.replace('"doc_index.html"', '"../doc_index.html"') - head = head.replace('"stylesheets/', '"../stylesheets/') - - lines = html.split('\n') - for i, line in enumerate(lines): - if 'FLOAT_RIGHT' in line: - line = line.replace('FLOAT_RIGHT', '') - lines[i] = line.replace(' TA-Lib is widely used by trading software developers requiring to perform -> technical analysis of financial market data. - -> * Includes 150+ indicators such as ADX, MACD, RSI, Stochastic, Bollinger -> Bands, etc. -> * Candlestick pattern recognition -> * Open-source API for C/C++, Java, Perl, Python and 100% Managed .NET - -The original Python bindings use [SWIG](https://swig.org) which unfortunately -are difficult to install and aren't as efficient as they could be. Therefore -this project uses Cython and Numpy to efficiently and cleanly bind to TA-Lib --- producing results 2-4 times faster than the SWIG interface. - -#### [Install TA-Lib](install.md) or [Read the Docs](doc_index.md) - -## Examples - -Similar to TA-Lib, the function interface provides a lightweight wrapper of -the exposed TA-Lib indicators. - -Each function returns an output array and have default values for their -parameters, unless specified as keyword arguments. Typically, these functions -will have an initial "lookback" period (a required number of observations -before an output is generated) set to ``NaN``. - -All of the following examples use the function API: - -```python -import numpy -import talib - -close = numpy.random.random(100) -``` - -Calculate a simple moving average of the close prices: - -```python -output = talib.SMA(close) -``` - -Calculating bollinger bands, with triple exponential moving average: - -```python -from talib import MA_Type - -upper, middle, lower = talib.BBANDS(close, matype=MA_Type.T3) -``` - -Calculating momentum of the close prices, with a time period of 5: - -```python -output = talib.MOM(close, timeperiod=5) -``` - -## Abstract API Quick Start - -If you're already familiar with using the function API, you should feel right -at home using the abstract API. Every function takes the same input, passed -as a dictionary of Numpy arrays: - -```python -import numpy as np -# note that all ndarrays must be the same length! -inputs = { - 'open': np.random.random(100), - 'high': np.random.random(100), - 'low': np.random.random(100), - 'close': np.random.random(100), - 'volume': np.random.random(100) -} -``` - -Functions can either be imported directly or instantiated by name: - -```python -from talib import abstract -sma = abstract.SMA -sma = abstract.Function('sma') -``` - -From there, calling functions is basically the same as the function API: - -```python -from talib.abstract import * -output = SMA(input_arrays, timeperiod=25) # calculate on close prices by default -output = SMA(input_arrays, timeperiod=25, price='open') # calculate on opens -upper, middle, lower = BBANDS(input_arrays, 20, 2, 2) -slowk, slowd = STOCH(input_arrays, 5, 3, 0, 3, 0) # uses high, low, close by default -slowk, slowd = STOCH(input_arrays, 5, 3, 0, 3, 0, prices=['high', 'low', 'open']) -``` - -Learn about more advanced usage of TA-Lib [here](abstract.md). - -## Supported Indicators - -We can show all the TA functions supported by TA-Lib, either as a ``list`` or -as a ``dict`` sorted by group (e.g. "Overlap Studies", "Momentum Indicators", -etc): - -```python -import talib - -print talib.get_functions() -print talib.get_function_groups() -``` - -### Function Groups - -* [Overlap Studies](func_groups/overlap_studies.md) -* [Momentum Indicators](func_groups/momentum_indicators.md) -* [Volume Indicators](func_groups/volume_indicators.md) -* [Volatility Indicators](func_groups/volatility_indicators.md) -* [Price Transform](func_groups/price_transform.md) -* [Cycle Indicators](func_groups/cycle_indicators.md) -* [Pattern Recognition](func_groups/pattern_recognition.md) -* [Statistic Functions](func_groups/statistic_functions.md) -* [Math Transform](func_groups/math_transform.md) -* [Math Operators](func_groups/math_operators.md) - -#### [Overlap Studies](func_groups/overlap_studies.md) - -``` -BBANDS Bollinger Bands -DEMA Double Exponential Moving Average -EMA Exponential Moving Average -HT_TRENDLINE Hilbert Transform - Instantaneous Trendline -KAMA Kaufman Adaptive Moving Average -MA Moving average -MAMA MESA Adaptive Moving Average -MAVP Moving average with variable period -MIDPOINT MidPoint over period -MIDPRICE Midpoint Price over period -SAR Parabolic SAR -SAREXT Parabolic SAR - Extended -SMA Simple Moving Average -T3 Triple Exponential Moving Average (T3) -TEMA Triple Exponential Moving Average -TRIMA Triangular Moving Average -WMA Weighted Moving Average -``` - -#### [Momentum Indicators](func_groups/momentum_indicators.md) - -``` -ADX Average Directional Movement Index -ADXR Average Directional Movement Index Rating -APO Absolute Price Oscillator -AROON Aroon -AROONOSC Aroon Oscillator -BOP Balance Of Power -CCI Commodity Channel Index -CMO Chande Momentum Oscillator -DX Directional Movement Index -MACD Moving Average Convergence/Divergence -MACDEXT MACD with controllable MA type -MACDFIX Moving Average Convergence/Divergence Fix 12/26 -MFI Money Flow Index -MINUS_DI Minus Directional Indicator -MINUS_DM Minus Directional Movement -MOM Momentum -PLUS_DI Plus Directional Indicator -PLUS_DM Plus Directional Movement -PPO Percentage Price Oscillator -ROC Rate of change : ((price/prevPrice)-1)*100 -ROCP Rate of change Percentage: (price-prevPrice)/prevPrice -ROCR Rate of change ratio: (price/prevPrice) -ROCR100 Rate of change ratio 100 scale: (price/prevPrice)*100 -RSI Relative Strength Index -STOCH Stochastic -STOCHF Stochastic Fast -STOCHRSI Stochastic Relative Strength Index -TRIX 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA -ULTOSC Ultimate Oscillator -WILLR Williams' %R -``` - -#### [Volume Indicators](func_groups/volume_indicators.md) - -``` -AD Chaikin A/D Line -ADOSC Chaikin A/D Oscillator -OBV On Balance Volume -``` - -#### [Volatility Indicators](func_groups/volatility_indicators.md) - -``` -ATR Average True Range -NATR Normalized Average True Range -TRANGE True Range -``` - -#### [Price Transform](func_groups/price_transform.md) - -``` -AVGPRICE Average Price -MEDPRICE Median Price -TYPPRICE Typical Price -WCLPRICE Weighted Close Price -``` - -#### [Cycle Indicators](func_groups/cycle_indicators.md) - -``` -HT_DCPERIOD Hilbert Transform - Dominant Cycle Period -HT_DCPHASE Hilbert Transform - Dominant Cycle Phase -HT_PHASOR Hilbert Transform - Phasor Components -HT_SINE Hilbert Transform - SineWave -HT_TRENDMODE Hilbert Transform - Trend vs Cycle Mode -``` - -#### [Pattern Recognition](func_groups/pattern_recognition.md) - -``` -CDL2CROWS Two Crows -CDL3BLACKCROWS Three Black Crows -CDL3INSIDE Three Inside Up/Down -CDL3LINESTRIKE Three-Line Strike -CDL3OUTSIDE Three Outside Up/Down -CDL3STARSINSOUTH Three Stars In The South -CDL3WHITESOLDIERS Three Advancing White Soldiers -CDLABANDONEDBABY Abandoned Baby -CDLADVANCEBLOCK Advance Block -CDLBELTHOLD Belt-hold -CDLBREAKAWAY Breakaway -CDLCLOSINGMARUBOZU Closing Marubozu -CDLCONCEALBABYSWALL Concealing Baby Swallow -CDLCOUNTERATTACK Counterattack -CDLDARKCLOUDCOVER Dark Cloud Cover -CDLDOJI Doji -CDLDOJISTAR Doji Star -CDLDRAGONFLYDOJI Dragonfly Doji -CDLENGULFING Engulfing Pattern -CDLEVENINGDOJISTAR Evening Doji Star -CDLEVENINGSTAR Evening Star -CDLGAPSIDESIDEWHITE Up/Down-gap side-by-side white lines -CDLGRAVESTONEDOJI Gravestone Doji -CDLHAMMER Hammer -CDLHANGINGMAN Hanging Man -CDLHARAMI Harami Pattern -CDLHARAMICROSS Harami Cross Pattern -CDLHIGHWAVE High-Wave Candle -CDLHIKKAKE Hikkake Pattern -CDLHIKKAKEMOD Modified Hikkake Pattern -CDLHOMINGPIGEON Homing Pigeon -CDLIDENTICAL3CROWS Identical Three Crows -CDLINNECK In-Neck Pattern -CDLINVERTEDHAMMER Inverted Hammer -CDLKICKING Kicking -CDLKICKINGBYLENGTH Kicking - bull/bear determined by the longer marubozu -CDLLADDERBOTTOM Ladder Bottom -CDLLONGLEGGEDDOJI Long Legged Doji -CDLLONGLINE Long Line Candle -CDLMARUBOZU Marubozu -CDLMATCHINGLOW Matching Low -CDLMATHOLD Mat Hold -CDLMORNINGDOJISTAR Morning Doji Star -CDLMORNINGSTAR Morning Star -CDLONNECK On-Neck Pattern -CDLPIERCING Piercing Pattern -CDLRICKSHAWMAN Rickshaw Man -CDLRISEFALL3METHODS Rising/Falling Three Methods -CDLSEPARATINGLINES Separating Lines -CDLSHOOTINGSTAR Shooting Star -CDLSHORTLINE Short Line Candle -CDLSPINNINGTOP Spinning Top -CDLSTALLEDPATTERN Stalled Pattern -CDLSTICKSANDWICH Stick Sandwich -CDLTAKURI Takuri (Dragonfly Doji with very long lower shadow) -CDLTASUKIGAP Tasuki Gap -CDLTHRUSTING Thrusting Pattern -CDLTRISTAR Tristar Pattern -CDLUNIQUE3RIVER Unique 3 River -CDLUPSIDEGAP2CROWS Upside Gap Two Crows -CDLXSIDEGAP3METHODS Upside/Downside Gap Three Methods -``` - -#### [Statistic Functions](func_groups/statistic_functions.md) - -``` -BETA Beta -CORREL Pearson's Correlation Coefficient (r) -LINEARREG Linear Regression -LINEARREG_ANGLE Linear Regression Angle -LINEARREG_INTERCEPT Linear Regression Intercept -LINEARREG_SLOPE Linear Regression Slope -STDDEV Standard Deviation -TSF Time Series Forecast -VAR Variance -``` diff --git a/docs/install.md b/docs/install.md deleted file mode 100644 index 044e8271a..000000000 --- a/docs/install.md +++ /dev/null @@ -1,52 +0,0 @@ -# Installation - -You can install from PyPI: - -``` -$ pip install TA-Lib -``` - -Or checkout the sources and run ``setup.py`` yourself: - -``` -$ python setup.py install -``` - -### Troubleshooting Install Errors - -``` -func.c:256:28: fatal error: ta-lib/ta_libc.h: No such file or directory -compilation terminated. -``` - -If you get build errors like this, it typically means that it can't find the -underlying ``TA-Lib`` library and needs to be installed: - -# Dependencies -To use TA-Lib for python, you need to have the [TA-Lib](https://ta-lib.org/hdr_dw.html) -already installed: - -#### Mac OS X -``` -$ brew install ta-lib -``` - -#### Windows -Download [ta-lib-0.4.0-msvc.zip](https://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-msvc.zip) -and unzip to ``C:\ta-lib`` - -#### Linux -Download [ta-lib-0.4.0-src.tar.gz](https://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz) and: -``` -$ tar zxvf ta-lib-0.4.0-src.tar.gz -$ cd ta-lib -$ ./configure --prefix=/usr -$ make -$ sudo make install -``` - -> If you build ``TA-Lib`` using ``make -jX`` it will fail but that's OK! -> Simply rerun ``make -jX`` followed by ``[sudo] make install``. - -[Documentation Index](doc_index.md) -[FLOAT_RIGHTNext: Using the Function API](func.md) diff --git a/func.html b/func.html new file mode 100644 index 000000000..6b5ece1be --- /dev/null +++ b/func.html @@ -0,0 +1,88 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Function API Examples

+

Similar to TA-Lib, the function interface provides a lightweight wrapper of +the exposed TA-Lib indicators.

+

Each function returns an output array and have default values for their +parameters, unless specified as keyword arguments. Typically, these functions +will have an initial "lookback" period (a required number of observations +before an output is generated) set to NaN.

+

All of the following examples use the function API:

+
import numpy
+import talib
+
+close = numpy.random.random(100)
+
+

Calculate a simple moving average of the close prices:

+
output = talib.SMA(close)
+
+

Calculating bollinger bands, with triple exponential moving average:

+
from talib import MA_Type
+
+upper, middle, lower = talib.BBANDS(close, matype=MA_Type.T3)
+
+

Calculating momentum of the close prices, with a time period of 5:

+
output = talib.MOM(close, timeperiod=5)
+
+

Documentation for all functions:

+ +

Documentation Index +Next: Using the Abstract API

+
+
+ + + + + + diff --git a/func_groups/cycle_indicators.html b/func_groups/cycle_indicators.html new file mode 100644 index 000000000..30ab1afb5 --- /dev/null +++ b/func_groups/cycle_indicators.html @@ -0,0 +1,72 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Cycle Indicator Functions

+

HT_DCPERIOD - Hilbert Transform - Dominant Cycle Period

+

NOTE: The HT_DCPERIOD function has an unstable period.

+
real = HT_DCPERIOD(real)
+
+

HT_DCPHASE - Hilbert Transform - Dominant Cycle Phase

+

NOTE: The HT_DCPHASE function has an unstable period.

+
real = HT_DCPHASE(real)
+
+

HT_PHASOR - Hilbert Transform - Phasor Components

+

NOTE: The HT_PHASOR function has an unstable period.

+
inphase, quadrature = HT_PHASOR(real)
+
+

HT_SINE - Hilbert Transform - SineWave

+

NOTE: The HT_SINE function has an unstable period.

+
sine, leadsine = HT_SINE(real)
+
+

HT_TRENDMODE - Hilbert Transform - Trend vs Cycle Mode

+

NOTE: The HT_TRENDMODE function has an unstable period.

+
integer = HT_TRENDMODE(real)
+
+

Documentation Index +All Function Groups

+
+
+ + + + + + diff --git a/func_groups/math_operators.html b/func_groups/math_operators.html new file mode 100644 index 000000000..bf80880bd --- /dev/null +++ b/func_groups/math_operators.html @@ -0,0 +1,85 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Math Operator Functions

+

ADD - Vector Arithmetic Add

+
real = ADD(real0, real1)
+
+

DIV - Vector Arithmetic Div

+
real = DIV(real0, real1)
+
+

MAX - Highest value over a specified period

+
real = MAX(real, timeperiod=30)
+
+

MAXINDEX - Index of highest value over a specified period

+
integer = MAXINDEX(real, timeperiod=30)
+
+

MIN - Lowest value over a specified period

+
real = MIN(real, timeperiod=30)
+
+

MININDEX - Index of lowest value over a specified period

+
integer = MININDEX(real, timeperiod=30)
+
+

MINMAX - Lowest and highest values over a specified period

+
min, max = MINMAX(real, timeperiod=30)
+
+

MINMAXINDEX - Indexes of lowest and highest values over a specified period

+
minidx, maxidx = MINMAXINDEX(real, timeperiod=30)
+
+

MULT - Vector Arithmetic Mult

+
real = MULT(real0, real1)
+
+

SUB - Vector Arithmetic Subtraction

+
real = SUB(real0, real1)
+
+

SUM - Summation

+
real = SUM(real, timeperiod=30)
+
+

Documentation Index +All Function Groups

+
+
+ + + + + + diff --git a/func_groups/math_transform.html b/func_groups/math_transform.html new file mode 100644 index 000000000..9183b6b50 --- /dev/null +++ b/func_groups/math_transform.html @@ -0,0 +1,97 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Math Transform Functions

+

ACOS - Vector Trigonometric ACos

+
real = ACOS(real)
+
+

ASIN - Vector Trigonometric ASin

+
real = ASIN(real)
+
+

ATAN - Vector Trigonometric ATan

+
real = ATAN(real)
+
+

CEIL - Vector Ceil

+
real = CEIL(real)
+
+

COS - Vector Trigonometric Cos

+
real = COS(real)
+
+

COSH - Vector Trigonometric Cosh

+
real = COSH(real)
+
+

EXP - Vector Arithmetic Exp

+
real = EXP(real)
+
+

FLOOR - Vector Floor

+
real = FLOOR(real)
+
+

LN - Vector Log Natural

+
real = LN(real)
+
+

LOG10 - Vector Log10

+
real = LOG10(real)
+
+

SIN - Vector Trigonometric Sin

+
real = SIN(real)
+
+

SINH - Vector Trigonometric Sinh

+
real = SINH(real)
+
+

SQRT - Vector Square Root

+
real = SQRT(real)
+
+

TAN - Vector Trigonometric Tan

+
real = TAN(real)
+
+

TANH - Vector Trigonometric Tanh

+
real = TANH(real)
+
+

Documentation Index +All Function Groups

+
+
+ + + + + + diff --git a/func_groups/momentum_indicators.html b/func_groups/momentum_indicators.html new file mode 100644 index 000000000..dbefc848e --- /dev/null +++ b/func_groups/momentum_indicators.html @@ -0,0 +1,153 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Momentum Indicator Functions

+

ADX - Average Directional Movement Index

+

NOTE: The ADX function has an unstable period.

+
real = ADX(high, low, close, timeperiod=14)
+
+

ADXR - Average Directional Movement Index Rating

+

NOTE: The ADXR function has an unstable period.

+
real = ADXR(high, low, close, timeperiod=14)
+
+

APO - Absolute Price Oscillator

+
real = APO(real, fastperiod=12, slowperiod=26, matype=0)
+
+

AROON - Aroon

+
aroondown, aroonup = AROON(high, low, timeperiod=14)
+
+

AROONOSC - Aroon Oscillator

+
real = AROONOSC(high, low, timeperiod=14)
+
+

BOP - Balance Of Power

+
real = BOP(open, high, low, close)
+
+

CCI - Commodity Channel Index

+
real = CCI(high, low, close, timeperiod=14)
+
+

CMO - Chande Momentum Oscillator

+

NOTE: The CMO function has an unstable period.

+
real = CMO(real, timeperiod=14)
+
+

DX - Directional Movement Index

+

NOTE: The DX function has an unstable period.

+
real = DX(high, low, close, timeperiod=14)
+
+

MACD - Moving Average Convergence/Divergence

+
macd, macdsignal, macdhist = MACD(real, fastperiod=12, slowperiod=26, signalperiod=9)
+
+

MACDEXT - MACD with controllable MA type

+
macd, macdsignal, macdhist = MACDEXT(real, fastperiod=12, fastmatype=0, slowperiod=26, slowmatype=0, signalperiod=9, signalmatype=0)
+
+

MACDFIX - Moving Average Convergence/Divergence Fix 12/26

+
macd, macdsignal, macdhist = MACDFIX(real, signalperiod=9)
+
+

MFI - Money Flow Index

+

NOTE: The MFI function has an unstable period.

+
real = MFI(high, low, close, volume, timeperiod=14)
+
+

MINUS_DI - Minus Directional Indicator

+

NOTE: The MINUS_DI function has an unstable period.

+
real = MINUS_DI(high, low, close, timeperiod=14)
+
+

MINUS_DM - Minus Directional Movement

+

NOTE: The MINUS_DM function has an unstable period.

+
real = MINUS_DM(high, low, timeperiod=14)
+
+

MOM - Momentum

+
real = MOM(real, timeperiod=10)
+
+

PLUS_DI - Plus Directional Indicator

+

NOTE: The PLUS_DI function has an unstable period.

+
real = PLUS_DI(high, low, close, timeperiod=14)
+
+

PLUS_DM - Plus Directional Movement

+

NOTE: The PLUS_DM function has an unstable period.

+
real = PLUS_DM(high, low, timeperiod=14)
+
+

PPO - Percentage Price Oscillator

+
real = PPO(real, fastperiod=12, slowperiod=26, matype=0)
+
+

ROC - Rate of change : ((price/prevPrice)-1)*100

+
real = ROC(real, timeperiod=10)
+
+

ROCP - Rate of change Percentage: (price-prevPrice)/prevPrice

+
real = ROCP(real, timeperiod=10)
+
+

ROCR - Rate of change ratio: (price/prevPrice)

+
real = ROCR(real, timeperiod=10)
+
+

ROCR100 - Rate of change ratio 100 scale: (price/prevPrice)*100

+
real = ROCR100(real, timeperiod=10)
+
+

RSI - Relative Strength Index

+

NOTE: The RSI function has an unstable period.

+
real = RSI(real, timeperiod=14)
+
+

STOCH - Stochastic

+
slowk, slowd = STOCH(high, low, close, fastk_period=5, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0)
+
+

STOCHF - Stochastic Fast

+
fastk, fastd = STOCHF(high, low, close, fastk_period=5, fastd_period=3, fastd_matype=0)
+
+

STOCHRSI - Stochastic Relative Strength Index

+

NOTE: The STOCHRSI function has an unstable period.

+
fastk, fastd = STOCHRSI(real, timeperiod=14, fastk_period=5, fastd_period=3, fastd_matype=0)
+
+

TRIX - 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA

+
real = TRIX(real, timeperiod=30)
+
+

ULTOSC - Ultimate Oscillator

+
real = ULTOSC(high, low, close, timeperiod1=7, timeperiod2=14, timeperiod3=28)
+
+

WILLR - Williams' %R

+
real = WILLR(high, low, close, timeperiod=14)
+
+

Documentation Index +All Function Groups

+
+
+ + + + + + diff --git a/func_groups/overlap_studies.html b/func_groups/overlap_studies.html new file mode 100644 index 000000000..a015634b1 --- /dev/null +++ b/func_groups/overlap_studies.html @@ -0,0 +1,108 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Overlap Studies Functions

+

BBANDS - Bollinger Bands

+
upperband, middleband, lowerband = BBANDS(real, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)
+
+

DEMA - Double Exponential Moving Average

+
real = DEMA(real, timeperiod=30)
+
+

EMA - Exponential Moving Average

+

NOTE: The EMA function has an unstable period.

+
real = EMA(real, timeperiod=30)
+
+

HT_TRENDLINE - Hilbert Transform - Instantaneous Trendline

+

NOTE: The HT_TRENDLINE function has an unstable period.

+
real = HT_TRENDLINE(real)
+
+

KAMA - Kaufman Adaptive Moving Average

+

NOTE: The KAMA function has an unstable period.

+
real = KAMA(real, timeperiod=30)
+
+

MA - Moving average

+
real = MA(real, timeperiod=30, matype=0)
+
+

MAMA - MESA Adaptive Moving Average

+

NOTE: The MAMA function has an unstable period.

+
mama, fama = MAMA(real, fastlimit=0, slowlimit=0)
+
+

MAVP - Moving average with variable period

+
real = MAVP(real, periods, minperiod=2, maxperiod=30, matype=0)
+
+

MIDPOINT - MidPoint over period

+
real = MIDPOINT(real, timeperiod=14)
+
+

MIDPRICE - Midpoint Price over period

+
real = MIDPRICE(high, low, timeperiod=14)
+
+

SAR - Parabolic SAR

+
real = SAR(high, low, acceleration=0, maximum=0)
+
+

SAREXT - Parabolic SAR - Extended

+
real = SAREXT(high, low, startvalue=0, offsetonreverse=0, accelerationinitlong=0, accelerationlong=0, accelerationmaxlong=0, accelerationinitshort=0, accelerationshort=0, accelerationmaxshort=0)
+
+

SMA - Simple Moving Average

+
real = SMA(real, timeperiod=30)
+
+

T3 - Triple Exponential Moving Average (T3)

+

NOTE: The T3 function has an unstable period.

+
real = T3(real, timeperiod=5, vfactor=0)
+
+

TEMA - Triple Exponential Moving Average

+
real = TEMA(real, timeperiod=30)
+
+

TRIMA - Triangular Moving Average

+
real = TRIMA(real, timeperiod=30)
+
+

WMA - Weighted Moving Average

+
real = WMA(real, timeperiod=30)
+
+

Documentation Index +All Function Groups

+
+
+ + + + + + diff --git a/func_groups/pattern_recognition.html b/func_groups/pattern_recognition.html new file mode 100644 index 000000000..04411618b --- /dev/null +++ b/func_groups/pattern_recognition.html @@ -0,0 +1,235 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Pattern Recognition Functions

+

CDL2CROWS - Two Crows

+
integer = CDL2CROWS(open, high, low, close)
+
+

CDL3BLACKCROWS - Three Black Crows

+
integer = CDL3BLACKCROWS(open, high, low, close)
+
+

CDL3INSIDE - Three Inside Up/Down

+
integer = CDL3INSIDE(open, high, low, close)
+
+

CDL3LINESTRIKE - Three-Line Strike

+
integer = CDL3LINESTRIKE(open, high, low, close)
+
+

CDL3OUTSIDE - Three Outside Up/Down

+
integer = CDL3OUTSIDE(open, high, low, close)
+
+

CDL3STARSINSOUTH - Three Stars In The South

+
integer = CDL3STARSINSOUTH(open, high, low, close)
+
+

CDL3WHITESOLDIERS - Three Advancing White Soldiers

+
integer = CDL3WHITESOLDIERS(open, high, low, close)
+
+

CDLABANDONEDBABY - Abandoned Baby

+
integer = CDLABANDONEDBABY(open, high, low, close, penetration=0)
+
+

CDLADVANCEBLOCK - Advance Block

+
integer = CDLADVANCEBLOCK(open, high, low, close)
+
+

CDLBELTHOLD - Belt-hold

+
integer = CDLBELTHOLD(open, high, low, close)
+
+

CDLBREAKAWAY - Breakaway

+
integer = CDLBREAKAWAY(open, high, low, close)
+
+

CDLCLOSINGMARUBOZU - Closing Marubozu

+
integer = CDLCLOSINGMARUBOZU(open, high, low, close)
+
+

CDLCONCEALBABYSWALL - Concealing Baby Swallow

+
integer = CDLCONCEALBABYSWALL(open, high, low, close)
+
+

CDLCOUNTERATTACK - Counterattack

+
integer = CDLCOUNTERATTACK(open, high, low, close)
+
+

CDLDARKCLOUDCOVER - Dark Cloud Cover

+
integer = CDLDARKCLOUDCOVER(open, high, low, close, penetration=0)
+
+

CDLDOJI - Doji

+
integer = CDLDOJI(open, high, low, close)
+
+

CDLDOJISTAR - Doji Star

+
integer = CDLDOJISTAR(open, high, low, close)
+
+

CDLDRAGONFLYDOJI - Dragonfly Doji

+
integer = CDLDRAGONFLYDOJI(open, high, low, close)
+
+

CDLENGULFING - Engulfing Pattern

+
integer = CDLENGULFING(open, high, low, close)
+
+

CDLEVENINGDOJISTAR - Evening Doji Star

+
integer = CDLEVENINGDOJISTAR(open, high, low, close, penetration=0)
+
+

CDLEVENINGSTAR - Evening Star

+
integer = CDLEVENINGSTAR(open, high, low, close, penetration=0)
+
+

CDLGAPSIDESIDEWHITE - Up/Down-gap side-by-side white lines

+
integer = CDLGAPSIDESIDEWHITE(open, high, low, close)
+
+

CDLGRAVESTONEDOJI - Gravestone Doji

+
integer = CDLGRAVESTONEDOJI(open, high, low, close)
+
+

CDLHAMMER - Hammer

+
integer = CDLHAMMER(open, high, low, close)
+
+

CDLHANGINGMAN - Hanging Man

+
integer = CDLHANGINGMAN(open, high, low, close)
+
+

CDLHARAMI - Harami Pattern

+
integer = CDLHARAMI(open, high, low, close)
+
+

CDLHARAMICROSS - Harami Cross Pattern

+
integer = CDLHARAMICROSS(open, high, low, close)
+
+

CDLHIGHWAVE - High-Wave Candle

+
integer = CDLHIGHWAVE(open, high, low, close)
+
+

CDLHIKKAKE - Hikkake Pattern

+
integer = CDLHIKKAKE(open, high, low, close)
+
+

CDLHIKKAKEMOD - Modified Hikkake Pattern

+
integer = CDLHIKKAKEMOD(open, high, low, close)
+
+

CDLHOMINGPIGEON - Homing Pigeon

+
integer = CDLHOMINGPIGEON(open, high, low, close)
+
+

CDLIDENTICAL3CROWS - Identical Three Crows

+
integer = CDLIDENTICAL3CROWS(open, high, low, close)
+
+

CDLINNECK - In-Neck Pattern

+
integer = CDLINNECK(open, high, low, close)
+
+

CDLINVERTEDHAMMER - Inverted Hammer

+
integer = CDLINVERTEDHAMMER(open, high, low, close)
+
+

CDLKICKING - Kicking

+
integer = CDLKICKING(open, high, low, close)
+
+

CDLKICKINGBYLENGTH - Kicking - bull/bear determined by the longer marubozu

+
integer = CDLKICKINGBYLENGTH(open, high, low, close)
+
+

CDLLADDERBOTTOM - Ladder Bottom

+
integer = CDLLADDERBOTTOM(open, high, low, close)
+
+

CDLLONGLEGGEDDOJI - Long Legged Doji

+
integer = CDLLONGLEGGEDDOJI(open, high, low, close)
+
+

CDLLONGLINE - Long Line Candle

+
integer = CDLLONGLINE(open, high, low, close)
+
+

CDLMARUBOZU - Marubozu

+
integer = CDLMARUBOZU(open, high, low, close)
+
+

CDLMATCHINGLOW - Matching Low

+
integer = CDLMATCHINGLOW(open, high, low, close)
+
+

CDLMATHOLD - Mat Hold

+
integer = CDLMATHOLD(open, high, low, close, penetration=0)
+
+

CDLMORNINGDOJISTAR - Morning Doji Star

+
integer = CDLMORNINGDOJISTAR(open, high, low, close, penetration=0)
+
+

CDLMORNINGSTAR - Morning Star

+
integer = CDLMORNINGSTAR(open, high, low, close, penetration=0)
+
+

CDLONNECK - On-Neck Pattern

+
integer = CDLONNECK(open, high, low, close)
+
+

CDLPIERCING - Piercing Pattern

+
integer = CDLPIERCING(open, high, low, close)
+
+

CDLRICKSHAWMAN - Rickshaw Man

+
integer = CDLRICKSHAWMAN(open, high, low, close)
+
+

CDLRISEFALL3METHODS - Rising/Falling Three Methods

+
integer = CDLRISEFALL3METHODS(open, high, low, close)
+
+

CDLSEPARATINGLINES - Separating Lines

+
integer = CDLSEPARATINGLINES(open, high, low, close)
+
+

CDLSHOOTINGSTAR - Shooting Star

+
integer = CDLSHOOTINGSTAR(open, high, low, close)
+
+

CDLSHORTLINE - Short Line Candle

+
integer = CDLSHORTLINE(open, high, low, close)
+
+

CDLSPINNINGTOP - Spinning Top

+
integer = CDLSPINNINGTOP(open, high, low, close)
+
+

CDLSTALLEDPATTERN - Stalled Pattern

+
integer = CDLSTALLEDPATTERN(open, high, low, close)
+
+

CDLSTICKSANDWICH - Stick Sandwich

+
integer = CDLSTICKSANDWICH(open, high, low, close)
+
+

CDLTAKURI - Takuri (Dragonfly Doji with very long lower shadow)

+
integer = CDLTAKURI(open, high, low, close)
+
+

CDLTASUKIGAP - Tasuki Gap

+
integer = CDLTASUKIGAP(open, high, low, close)
+
+

CDLTHRUSTING - Thrusting Pattern

+
integer = CDLTHRUSTING(open, high, low, close)
+
+

CDLTRISTAR - Tristar Pattern

+
integer = CDLTRISTAR(open, high, low, close)
+
+

CDLUNIQUE3RIVER - Unique 3 River

+
integer = CDLUNIQUE3RIVER(open, high, low, close)
+
+

CDLUPSIDEGAP2CROWS - Upside Gap Two Crows

+
integer = CDLUPSIDEGAP2CROWS(open, high, low, close)
+
+

CDLXSIDEGAP3METHODS - Upside/Downside Gap Three Methods

+
integer = CDLXSIDEGAP3METHODS(open, high, low, close)
+
+

Documentation Index +All Function Groups

+
+
+ + + + + + diff --git a/func_groups/price_transform.html b/func_groups/price_transform.html new file mode 100644 index 000000000..ec3906278 --- /dev/null +++ b/func_groups/price_transform.html @@ -0,0 +1,64 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Price Transform Functions

+

AVGPRICE - Average Price

+
real = AVGPRICE(open, high, low, close)
+
+

MEDPRICE - Median Price

+
real = MEDPRICE(high, low)
+
+

TYPPRICE - Typical Price

+
real = TYPPRICE(high, low, close)
+
+

WCLPRICE - Weighted Close Price

+
real = WCLPRICE(high, low, close)
+
+

Documentation Index +All Function Groups

+
+
+ + + + + + diff --git a/func_groups/statistic_functions.html b/func_groups/statistic_functions.html new file mode 100644 index 000000000..10b051be3 --- /dev/null +++ b/func_groups/statistic_functions.html @@ -0,0 +1,79 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Statistic Functions

+

BETA - Beta

+
real = BETA(real0, real1, timeperiod=5)
+
+

CORREL - Pearson's Correlation Coefficient (r)

+
real = CORREL(real0, real1, timeperiod=30)
+
+

LINEARREG - Linear Regression

+
real = LINEARREG(real, timeperiod=14)
+
+

LINEARREG_ANGLE - Linear Regression Angle

+
real = LINEARREG_ANGLE(real, timeperiod=14)
+
+

LINEARREG_INTERCEPT - Linear Regression Intercept

+
real = LINEARREG_INTERCEPT(real, timeperiod=14)
+
+

LINEARREG_SLOPE - Linear Regression Slope

+
real = LINEARREG_SLOPE(real, timeperiod=14)
+
+

STDDEV - Standard Deviation

+
real = STDDEV(real, timeperiod=5, nbdev=1)
+
+

TSF - Time Series Forecast

+
real = TSF(real, timeperiod=14)
+
+

VAR - Variance

+
real = VAR(real, timeperiod=5, nbdev=1)
+
+

Documentation Index +All Function Groups

+
+
+ + + + + + diff --git a/func_groups/volatility_indicators.html b/func_groups/volatility_indicators.html new file mode 100644 index 000000000..4926747a4 --- /dev/null +++ b/func_groups/volatility_indicators.html @@ -0,0 +1,63 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Volatility Indicator Functions

+

ATR - Average True Range

+

NOTE: The ATR function has an unstable period.

+
real = ATR(high, low, close, timeperiod=14)
+
+

NATR - Normalized Average True Range

+

NOTE: The NATR function has an unstable period.

+
real = NATR(high, low, close, timeperiod=14)
+
+

TRANGE - True Range

+
real = TRANGE(high, low, close)
+
+

Documentation Index +All Function Groups

+
+
+ + + + + + diff --git a/func_groups/volume_indicators.html b/func_groups/volume_indicators.html new file mode 100644 index 000000000..8d5e8c6cc --- /dev/null +++ b/func_groups/volume_indicators.html @@ -0,0 +1,61 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Volume Indicator Functions

+

AD - Chaikin A/D Line

+
real = AD(high, low, close, volume)
+
+

ADOSC - Chaikin A/D Oscillator

+
real = ADOSC(high, low, close, volume, fastperiod=3, slowperiod=10)
+
+

OBV - On Balance Volume

+
real = OBV(close, volume)
+
+

Documentation Index +All Function Groups

+
+
+ + + + + + diff --git a/docs/funcs.md b/funcs.html similarity index 61% rename from docs/funcs.md rename to funcs.html index 14ab13776..5ce276d78 100644 --- a/docs/funcs.md +++ b/funcs.html @@ -1,20 +1,53 @@ -# All Supported Indicators and Functions - -* [Overlap Studies](func_groups/overlap_studies.md) -* [Momentum Indicators](func_groups/momentum_indicators.md) -* [Volume Indicators](func_groups/volume_indicators.md) -* [Volatility Indicators](func_groups/volatility_indicators.md) -* [Price Transform](func_groups/price_transform.md) -* [Cycle Indicators](func_groups/cycle_indicators.md) -* [Pattern Recognition](func_groups/pattern_recognition.md) -* [Statistic Functions](func_groups/statistic_functions.md) -* [Math Transform](func_groups/math_transform.md) -* [Math Operators](func_groups/math_operators.md) - -#### [Overlap Studies](func_groups/overlap_studies.md) - -``` -BBANDS Bollinger Bands + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

All Supported Indicators and Functions

+ +

Overlap Studies

+ +
BBANDS               Bollinger Bands
 DEMA                 Double Exponential Moving Average
 EMA                  Exponential Moving Average
 HT_TRENDLINE         Hilbert Transform - Instantaneous Trendline
@@ -31,12 +64,10 @@
 TEMA                 Triple Exponential Moving Average
 TRIMA                Triangular Moving Average
 WMA                  Weighted Moving Average
-```
-
-#### [Momentum Indicators](func_groups/momentum_indicators.md)
+
+

Momentum Indicators

-``` -ADX Average Directional Movement Index +
ADX                  Average Directional Movement Index
 ADXR                 Average Directional Movement Index Rating
 APO                  Absolute Price Oscillator
 AROON                Aroon
@@ -66,47 +97,37 @@
 TRIX                 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA
 ULTOSC               Ultimate Oscillator
 WILLR                Williams' %R
-```
+
+

Volume Indicators

-#### [Volume Indicators](func_groups/volume_indicators.md) - -``` -AD Chaikin A/D Line +
AD                   Chaikin A/D Line
 ADOSC                Chaikin A/D Oscillator
 OBV                  On Balance Volume
-```
-
-#### [Cycle Indicators](func_groups/cycle_indicators.md)
+
+

Cycle Indicators

-``` -HT_DCPERIOD Hilbert Transform - Dominant Cycle Period +
HT_DCPERIOD          Hilbert Transform - Dominant Cycle Period
 HT_DCPHASE           Hilbert Transform - Dominant Cycle Phase
 HT_PHASOR            Hilbert Transform - Phasor Components
 HT_SINE              Hilbert Transform - SineWave
 HT_TRENDMODE         Hilbert Transform - Trend vs Cycle Mode
-```
-
-#### [Price Transform](func_groups/price_transform.md)
+
+

Price Transform

-``` -AVGPRICE Average Price +
AVGPRICE             Average Price
 MEDPRICE             Median Price
 TYPPRICE             Typical Price
 WCLPRICE             Weighted Close Price
-```
+
+

Volatility Indicators

-#### [Volatility Indicators](func_groups/volatility_indicators.md) - -``` -ATR Average True Range +
ATR                  Average True Range
 NATR                 Normalized Average True Range
 TRANGE               True Range
-```
-
-#### [Pattern Recognition](func_groups/pattern_recognition.md)
+
+

Pattern Recognition

-``` -CDL2CROWS Two Crows +
CDL2CROWS            Two Crows
 CDL3BLACKCROWS       Three Black Crows
 CDL3INSIDE           Three Inside Up/Down
 CDL3LINESTRIKE       Three-Line Strike
@@ -167,12 +188,10 @@
 CDLUNIQUE3RIVER      Unique 3 River
 CDLUPSIDEGAP2CROWS   Upside Gap Two Crows
 CDLXSIDEGAP3METHODS  Upside/Downside Gap Three Methods
-```
-
-#### [Statistic Functions](func_groups/statistic_functions.md)
+
+

Statistic Functions

-``` -BETA Beta +
BETA                 Beta
 CORREL               Pearson's Correlation Coefficient (r)
 LINEARREG            Linear Regression
 LINEARREG_ANGLE      Linear Regression Angle
@@ -181,12 +200,10 @@
 STDDEV               Standard Deviation
 TSF                  Time Series Forecast
 VAR                  Variance
-```
+
+

Math Transform

-#### [Math Transform](func_groups/math_transform.md) - -``` -ACOS Vector Trigonometric ACos +
ACOS                 Vector Trigonometric ACos
 ASIN                 Vector Trigonometric ASin
 ATAN                 Vector Trigonometric ATan
 CEIL                 Vector Ceil
@@ -201,12 +218,10 @@
 SQRT                 Vector Square Root
 TAN                  Vector Trigonometric Tan
 TANH                 Vector Trigonometric Tanh
-```
-
-#### [Math Operators](func_groups/math_operators.md)
+
+

Math Operators

-``` -ADD Vector Arithmetic Add +
ADD                  Vector Arithmetic Add
 DIV                  Vector Arithmetic Div
 MAX                  Highest value over a specified period
 MAXINDEX             Index of highest value over a specified period
@@ -217,6 +232,20 @@
 MULT                 Vector Arithmetic Mult
 SUB                  Vector Arithmetic Subtraction
 SUM                  Summation
-```
-
-[Documentation Index](doc_index.md)
+
+

Documentation Index

+
+
+ + + + + + diff --git a/images/bg_hr.png b/images/bg_hr.png new file mode 100644 index 000000000..7973bd698 Binary files /dev/null and b/images/bg_hr.png differ diff --git a/images/blacktocat.png b/images/blacktocat.png new file mode 100644 index 000000000..6e264fe57 Binary files /dev/null and b/images/blacktocat.png differ diff --git a/images/icon_download.png b/images/icon_download.png new file mode 100644 index 000000000..a2a287f64 Binary files /dev/null and b/images/icon_download.png differ diff --git a/images/sprite_download.png b/images/sprite_download.png new file mode 100644 index 000000000..f2babd575 Binary files /dev/null and b/images/sprite_download.png differ diff --git a/index.html b/index.html new file mode 100644 index 000000000..8d08a84f3 --- /dev/null +++ b/index.html @@ -0,0 +1,299 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

About

+

This is a Python wrapper for TA-LIB based on Cython +instead of SWIG. From the homepage:

+
+

TA-Lib is widely used by trading software developers requiring to perform +technical analysis of financial market data.

+
+
+
    +
  • Includes 150+ indicators such as ADX, MACD, RSI, Stochastic, Bollinger +Bands, etc.
    • +
  • Candlestick pattern recognition
    • +
  • Open-source API for C/C++, Java, Perl, Python and 100% Managed .NET
    • +
+
+

The original Python bindings use SWIG which unfortunately +are difficult to install and aren't as efficient as they could be. Therefore +this project uses Cython and Numpy to efficiently and cleanly bind to TA-Lib +-- producing results 2-4 times faster than the SWIG interface.

+

Install TA-Lib or Read the Docs

+

Examples

+

Similar to TA-Lib, the function interface provides a lightweight wrapper of +the exposed TA-Lib indicators.

+

Each function returns an output array and have default values for their +parameters, unless specified as keyword arguments. Typically, these functions +will have an initial "lookback" period (a required number of observations +before an output is generated) set to NaN.

+

All of the following examples use the function API:

+
import numpy
+import talib
+
+close = numpy.random.random(100)
+
+

Calculate a simple moving average of the close prices:

+
output = talib.SMA(close)
+
+

Calculating bollinger bands, with triple exponential moving average:

+
from talib import MA_Type
+
+upper, middle, lower = talib.BBANDS(close, matype=MA_Type.T3)
+
+

Calculating momentum of the close prices, with a time period of 5:

+
output = talib.MOM(close, timeperiod=5)
+
+

Abstract API Quick Start

+

If you're already familiar with using the function API, you should feel right +at home using the abstract API. Every function takes the same input, passed +as a dictionary of Numpy arrays:

+
import numpy as np
+# note that all ndarrays must be the same length!
+inputs = {
+    'open': np.random.random(100),
+    'high': np.random.random(100),
+    'low': np.random.random(100),
+    'close': np.random.random(100),
+    'volume': np.random.random(100)
+}
+
+

Functions can either be imported directly or instantiated by name:

+
from talib import abstract
+sma = abstract.SMA
+sma = abstract.Function('sma')
+
+

From there, calling functions is basically the same as the function API:

+
from talib.abstract import *
+output = SMA(input_arrays, timeperiod=25) # calculate on close prices by default
+output = SMA(input_arrays, timeperiod=25, price='open') # calculate on opens
+upper, middle, lower = BBANDS(input_arrays, 20, 2, 2)
+slowk, slowd = STOCH(input_arrays, 5, 3, 0, 3, 0) # uses high, low, close by default
+slowk, slowd = STOCH(input_arrays, 5, 3, 0, 3, 0, prices=['high', 'low', 'open'])
+
+

Learn about more advanced usage of TA-Lib here.

+

Supported Indicators

+

We can show all the TA functions supported by TA-Lib, either as a list or +as a dict sorted by group (e.g. "Overlap Studies", "Momentum Indicators", +etc):

+
import talib
+
+print talib.get_functions()
+print talib.get_function_groups()
+
+

Function Groups

+ +

Overlap Studies

+ +
BBANDS               Bollinger Bands
+DEMA                 Double Exponential Moving Average
+EMA                  Exponential Moving Average
+HT_TRENDLINE         Hilbert Transform - Instantaneous Trendline
+KAMA                 Kaufman Adaptive Moving Average
+MA                   Moving average
+MAMA                 MESA Adaptive Moving Average
+MAVP                 Moving average with variable period
+MIDPOINT             MidPoint over period
+MIDPRICE             Midpoint Price over period
+SAR                  Parabolic SAR
+SAREXT               Parabolic SAR - Extended
+SMA                  Simple Moving Average
+T3                   Triple Exponential Moving Average (T3)
+TEMA                 Triple Exponential Moving Average
+TRIMA                Triangular Moving Average
+WMA                  Weighted Moving Average
+
+

Momentum Indicators

+ +
ADX                  Average Directional Movement Index
+ADXR                 Average Directional Movement Index Rating
+APO                  Absolute Price Oscillator
+AROON                Aroon
+AROONOSC             Aroon Oscillator
+BOP                  Balance Of Power
+CCI                  Commodity Channel Index
+CMO                  Chande Momentum Oscillator
+DX                   Directional Movement Index
+MACD                 Moving Average Convergence/Divergence
+MACDEXT              MACD with controllable MA type
+MACDFIX              Moving Average Convergence/Divergence Fix 12/26
+MFI                  Money Flow Index
+MINUS_DI             Minus Directional Indicator
+MINUS_DM             Minus Directional Movement
+MOM                  Momentum
+PLUS_DI              Plus Directional Indicator
+PLUS_DM              Plus Directional Movement
+PPO                  Percentage Price Oscillator
+ROC                  Rate of change : ((price/prevPrice)-1)*100
+ROCP                 Rate of change Percentage: (price-prevPrice)/prevPrice
+ROCR                 Rate of change ratio: (price/prevPrice)
+ROCR100              Rate of change ratio 100 scale: (price/prevPrice)*100
+RSI                  Relative Strength Index
+STOCH                Stochastic
+STOCHF               Stochastic Fast
+STOCHRSI             Stochastic Relative Strength Index
+TRIX                 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA
+ULTOSC               Ultimate Oscillator
+WILLR                Williams' %R
+
+

Volume Indicators

+ +
AD                   Chaikin A/D Line
+ADOSC                Chaikin A/D Oscillator
+OBV                  On Balance Volume
+
+

Volatility Indicators

+ +
ATR                  Average True Range
+NATR                 Normalized Average True Range
+TRANGE               True Range
+
+

Price Transform

+ +
AVGPRICE             Average Price
+MEDPRICE             Median Price
+TYPPRICE             Typical Price
+WCLPRICE             Weighted Close Price
+
+

Cycle Indicators

+ +
HT_DCPERIOD          Hilbert Transform - Dominant Cycle Period
+HT_DCPHASE           Hilbert Transform - Dominant Cycle Phase
+HT_PHASOR            Hilbert Transform - Phasor Components
+HT_SINE              Hilbert Transform - SineWave
+HT_TRENDMODE         Hilbert Transform - Trend vs Cycle Mode
+
+

Pattern Recognition

+ +
CDL2CROWS            Two Crows
+CDL3BLACKCROWS       Three Black Crows
+CDL3INSIDE           Three Inside Up/Down
+CDL3LINESTRIKE       Three-Line Strike
+CDL3OUTSIDE          Three Outside Up/Down
+CDL3STARSINSOUTH     Three Stars In The South
+CDL3WHITESOLDIERS    Three Advancing White Soldiers
+CDLABANDONEDBABY     Abandoned Baby
+CDLADVANCEBLOCK      Advance Block
+CDLBELTHOLD          Belt-hold
+CDLBREAKAWAY         Breakaway
+CDLCLOSINGMARUBOZU   Closing Marubozu
+CDLCONCEALBABYSWALL  Concealing Baby Swallow
+CDLCOUNTERATTACK     Counterattack
+CDLDARKCLOUDCOVER    Dark Cloud Cover
+CDLDOJI              Doji
+CDLDOJISTAR          Doji Star
+CDLDRAGONFLYDOJI     Dragonfly Doji
+CDLENGULFING         Engulfing Pattern
+CDLEVENINGDOJISTAR   Evening Doji Star
+CDLEVENINGSTAR       Evening Star
+CDLGAPSIDESIDEWHITE  Up/Down-gap side-by-side white lines
+CDLGRAVESTONEDOJI    Gravestone Doji
+CDLHAMMER            Hammer
+CDLHANGINGMAN        Hanging Man
+CDLHARAMI            Harami Pattern
+CDLHARAMICROSS       Harami Cross Pattern
+CDLHIGHWAVE          High-Wave Candle
+CDLHIKKAKE           Hikkake Pattern
+CDLHIKKAKEMOD        Modified Hikkake Pattern
+CDLHOMINGPIGEON      Homing Pigeon
+CDLIDENTICAL3CROWS   Identical Three Crows
+CDLINNECK            In-Neck Pattern
+CDLINVERTEDHAMMER    Inverted Hammer
+CDLKICKING           Kicking
+CDLKICKINGBYLENGTH   Kicking - bull/bear determined by the longer marubozu
+CDLLADDERBOTTOM      Ladder Bottom
+CDLLONGLEGGEDDOJI    Long Legged Doji
+CDLLONGLINE          Long Line Candle
+CDLMARUBOZU          Marubozu
+CDLMATCHINGLOW       Matching Low
+CDLMATHOLD           Mat Hold
+CDLMORNINGDOJISTAR   Morning Doji Star
+CDLMORNINGSTAR       Morning Star
+CDLONNECK            On-Neck Pattern
+CDLPIERCING          Piercing Pattern
+CDLRICKSHAWMAN       Rickshaw Man
+CDLRISEFALL3METHODS  Rising/Falling Three Methods
+CDLSEPARATINGLINES   Separating Lines
+CDLSHOOTINGSTAR      Shooting Star
+CDLSHORTLINE         Short Line Candle
+CDLSPINNINGTOP       Spinning Top
+CDLSTALLEDPATTERN    Stalled Pattern
+CDLSTICKSANDWICH     Stick Sandwich
+CDLTAKURI            Takuri (Dragonfly Doji with very long lower shadow)
+CDLTASUKIGAP         Tasuki Gap
+CDLTHRUSTING         Thrusting Pattern
+CDLTRISTAR           Tristar Pattern
+CDLUNIQUE3RIVER      Unique 3 River
+CDLUPSIDEGAP2CROWS   Upside Gap Two Crows
+CDLXSIDEGAP3METHODS  Upside/Downside Gap Three Methods
+
+

Statistic Functions

+ +
BETA                 Beta
+CORREL               Pearson's Correlation Coefficient (r)
+LINEARREG            Linear Regression
+LINEARREG_ANGLE      Linear Regression Angle
+LINEARREG_INTERCEPT  Linear Regression Intercept
+LINEARREG_SLOPE      Linear Regression Slope
+STDDEV               Standard Deviation
+TSF                  Time Series Forecast
+VAR                  Variance
+
+
+
+ + + + + + diff --git a/install.html b/install.html new file mode 100644 index 000000000..eb80e7560 --- /dev/null +++ b/install.html @@ -0,0 +1,90 @@ + + + + + + + + + TA-Lib + + + +
+
+ View on GitHub +
+ +
+
+

TA-Lib

+

Python wrapper for TA-Lib (https://ta-lib.org/).

+
+ Download this project as a .zip file + Download this project as a tar.gz file +
+
+
+ + +
+
+

Installation

+

You can install from PyPI:

+ +
$ pip install TA-Lib
+
+

Or checkout the sources and run setup.py yourself:

+ +
$ python setup.py install
+
+

Troubleshooting Install Errors

+ +
func.c:256:28: fatal error: ta-lib/ta_libc.h: No such file or directory
+compilation terminated.
+
+

If you get build errors like this, it typically means that it can't find the +underlying TA-Lib library and needs to be installed:

+

Dependencies

+

To use TA-Lib for python, you need to have the TA-Lib +already installed:

+

Mac OS X

+ +
$ brew install ta-lib
+
+

Windows

+

Download ta-lib-0.4.0-msvc.zip +and unzip to C:\ta-lib

+

Linux

+

Download ta-lib-0.4.0-src.tar.gz and:

+ +
$ tar zxvf ta-lib-0.4.0-src.tar.gz
+$ cd ta-lib
+$ ./configure --prefix=/usr
+$ make
+$ sudo make install
+
+
+

If you build TA-Lib using make -jX it will fail but that's OK! +Simply rerun make -jX followed by [sudo] make install.

+
+

Documentation Index +Next: Using the Function API

+
+
+ + + + + + diff --git a/pyproject.toml b/pyproject.toml deleted file mode 100644 index d2335f446..000000000 --- a/pyproject.toml +++ /dev/null @@ -1,45 +0,0 @@ -[build-system] -requires = ["setuptools", "wheel", "Cython", "numpy"] -build-backend = "setuptools.build_meta" - -[project] -name = "TA-Lib" -version = "0.6.6" -description = "Python wrapper for TA-Lib" -readme = "README.md" -license = {file = "LICENSE"} -authors = [ - {name = "John Benediktsson", email = "mrjbq7@gmail.com"} -] -urls = {homepage = "http://github.com/ta-lib/ta-lib-python", download = "https://github.com/ta-lib/ta-lib-python/releases"} -classifiers = [ - "Development Status :: 5 - Production/Stable", - "Operating System :: Unix", - "Operating System :: POSIX", - "Operating System :: MacOS :: MacOS X", - "Operating System :: Microsoft :: Windows", - "Programming Language :: Python", - "Programming Language :: Python :: 3", - "Programming Language :: Python :: 3.9", - "Programming Language :: Python :: 3.10", - "Programming Language :: Python :: 3.11", - "Programming Language :: Python :: 3.12", - "Programming Language :: Python :: 3.13", - "Programming Language :: Python :: 3.14", - "Programming Language :: Cython", - "Topic :: Office/Business :: Financial", - "Topic :: Scientific/Engineering :: Mathematics", - "Intended Audience :: Developers", - "Intended Audience :: Science/Research", - "Intended Audience :: Financial and Insurance Industry", -] -dependencies = [ - "build", - "numpy", - "pip", -] -requires-python = '>=3.9' - -[tool.setuptools] -packages = ["talib"] -package-data = {"talib" = ["_ta_lib.pyi", "py.typed"]} diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 70bf4e3ba..000000000 --- a/requirements.txt +++ /dev/null @@ -1,2 +0,0 @@ -numpy -Cython diff --git a/requirements_dev.txt b/requirements_dev.txt deleted file mode 100644 index 3a6c0a909..000000000 --- a/requirements_dev.txt +++ /dev/null @@ -1,6 +0,0 @@ --r requirements.txt -beautifulsoup4 -mistune -Pygments -build -cython diff --git a/requirements_test.txt b/requirements_test.txt deleted file mode 100644 index 144e7c76c..000000000 --- a/requirements_test.txt +++ /dev/null @@ -1,4 +0,0 @@ --r requirements.txt -pandas -pytest -polars diff --git a/setup.py b/setup.py deleted file mode 100644 index 874983353..000000000 --- a/setup.py +++ /dev/null @@ -1,108 +0,0 @@ -#!/usr/bin/env python - -import sys -import os -import os.path -import warnings - -from setuptools import setup, Extension - -import numpy - -platform_supported = False - -lib_talib_name = 'ta-lib' # the name as of TA-Lib 0.6.1 - -if any(s in sys.platform for s in ['darwin', 'linux', 'bsd', 'sunos']): - platform_supported = True - include_dirs = [ - '/usr/include', - '/usr/local/include', - '/opt/include', - '/opt/local/include', - '/opt/homebrew/include', - '/opt/homebrew/opt/ta-lib/include', - ] - library_dirs = [ - '/usr/lib', - '/usr/local/lib', - '/usr/lib64', - '/usr/local/lib64', - '/opt/lib', - '/opt/local/lib', - '/opt/homebrew/lib', - '/opt/homebrew/opt/ta-lib/lib', - ] - -elif sys.platform == "win32": - platform_supported = True - lib_talib_name = 'ta-lib-static' - include_dirs = [ - r"c:\ta-lib\c\include", - r"c:\Program Files\TA-Lib\include", - r"c:\Program Files (x86)\TA-Lib\include", - ] - library_dirs = [ - r"c:\ta-lib\c\lib", - r"c:\Program Files\TA-Lib\lib", - r"c:\Program Files (x86)\TA-Lib\lib", - ] - -if 'TA_INCLUDE_PATH' in os.environ: - include_dirs = os.environ['TA_INCLUDE_PATH'].split(os.pathsep) - -if 'TA_LIBRARY_PATH' in os.environ: - library_dirs = os.environ['TA_LIBRARY_PATH'].split(os.pathsep) - -if not platform_supported: - raise NotImplementedError(sys.platform) - -for path in library_dirs: - try: - files = os.listdir(path) - if any(lib_talib_name in f for f in files): - break - except OSError: - pass -else: - warnings.warn('Cannot find ta-lib library, installation may fail.') - -# Get the Cython build_ext or fall back to setuptools build_ext -try: - from Cython.Distutils import build_ext - has_cython = True -except ImportError: - from setuptools.command.build_ext import build_ext - has_cython = False - -class NumpyBuildExt(build_ext): - """ - Custom build_ext command that adds numpy's include_dir to extensions. - """ - - def build_extensions(self): - """ - Add numpy's include directory to Extension includes. - """ - numpy_incl = numpy.get_include() - for ext in self.extensions: - ext.include_dirs.append(numpy_incl) - - super().build_extensions() - -cmdclass = {'build_ext': NumpyBuildExt} - -ext_modules = [ - Extension( - 'talib._ta_lib', - ['talib/_ta_lib.pyx' if has_cython else 'talib/_ta_lib.c'], - include_dirs=include_dirs, - library_dirs=library_dirs, - libraries=[lib_talib_name], - runtime_library_dirs=[] if sys.platform == 'win32' else library_dirs) -] - -setup( - ext_modules=ext_modules, - cmdclass=cmdclass, -) diff --git a/stylesheets/pygments_style.css b/stylesheets/pygments_style.css new file mode 100644 index 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wrap talib functions so that they support -# polars.Series input -try: - from polars import Series as _pl_Series -except ImportError as import_error: - try: - if not isinstance(import_error, ModuleNotFoundError) or import_error.name != 'polars': - # Propagate the error when the module exists but failed to be imported. - raise import_error - # `ModuleNotFoundError` was introduced in Python 3.6. - except NameError: - pass - - # polars not available, nothing to wrap - _pl_Series = None - -# If pandas is available, wrap talib functions so that they support -# pandas.Series input -try: - from pandas import Series as _pd_Series -except ImportError as import_error: - try: - if not isinstance(import_error, ModuleNotFoundError) or import_error.name != 'pandas': - # Propagate the error when the module exists but failed to be imported. - raise import_error - # `ModuleNotFoundError` was introduced in Python 3.6. - except NameError: - pass - - # pandas not available, nothing to wrap - _pd_Series = None - -if _pl_Series is not None or _pd_Series is not None: - - def _wrapper(func): - @wraps(func) - def wrapper(*args, **kwds): - - if _pl_Series is not None: - use_pl = any(isinstance(arg, _pl_Series) for arg in args) or \ - any(isinstance(v, _pl_Series) for v in kwds.values()) - else: - use_pl = False - - if _pd_Series is not None: - use_pd = any(isinstance(arg, _pd_Series) for arg in args) or \ - any(isinstance(v, _pd_Series) for v in kwds.values()) - else: - use_pd = False - - if use_pl and use_pd: - raise Exception("Cannot mix polars and pandas") - - # Use float64 values if polars or pandas, else use values as passed - if use_pl: - _args = [arg.to_numpy().astype(float) if isinstance(arg, _pl_Series) else - arg for arg in args] - _kwds = {k: v.to_numpy().astype(float) if isinstance(v, _pl_Series) else - v for k, v in kwds.items()} - - elif use_pd: - index = next(arg.index - for arg in chain(args, kwds.values()) - if isinstance(arg, _pd_Series)) - - _args = [arg.to_numpy().astype(float) if isinstance(arg, _pd_Series) else - arg for arg in args] - _kwds = {k: v.to_numpy().astype(float) if isinstance(v, _pd_Series) else - v for k, v in kwds.items()} - - else: - _args = args - _kwds = kwds - - result = func(*_args, **_kwds) - - # check to see if we got a streaming result - first_result = result[0] if isinstance(result, tuple) else result - is_streaming_fn_result = not hasattr(first_result, '__len__') - if is_streaming_fn_result: - return result - - # Series was passed in, Series gets out - if use_pl: - if isinstance(result, tuple): - return tuple(_pl_Series(arr) for arr in result) - else: - return _pl_Series(result) - - elif use_pd: - if isinstance(result, tuple): - return tuple(_pd_Series(arr, index=index) for arr in result) - else: - return _pd_Series(result, index=index) - - else: - return result - - return wrapper -else: - _wrapper = lambda x: x - - -from ._ta_lib import ( - _ta_initialize, _ta_shutdown, MA_Type, __ta_version__, - _ta_set_unstable_period as set_unstable_period, - _ta_get_unstable_period as get_unstable_period, - _ta_set_compatibility as set_compatibility, - _ta_get_compatibility as get_compatibility, - __TA_FUNCTION_NAMES__ -) - -# import all the func and stream functions -from ._ta_lib import * - -# wrap them for polars or pandas support -func = __import__("_ta_lib", globals(), locals(), __TA_FUNCTION_NAMES__, level=1) -for func_name in __TA_FUNCTION_NAMES__: - wrapped_func = _wrapper(getattr(func, func_name)) - setattr(func, func_name, wrapped_func) - globals()[func_name] = wrapped_func - -stream_func_names = ['stream_%s' % fname for fname in __TA_FUNCTION_NAMES__] -stream = __import__("stream", globals(), locals(), stream_func_names, level=1) -for func_name, stream_func_name in zip(__TA_FUNCTION_NAMES__, stream_func_names): - wrapped_func = _wrapper(getattr(stream, func_name)) - setattr(stream, func_name, wrapped_func) - globals()[stream_func_name] = wrapped_func - -__version__ = '0.6.6' - -# In order to use this python library, talib (i.e. this __file__) will be -# imported at some point, either explicitly or indirectly via talib.func -# or talib.abstract. Here, we handle initializing and shutting down the -# underlying TA-Lib. Initialization happens on import, before any other TA-Lib -# functions are called. Finally, when the python process exits, we shutdown -# the underlying TA-Lib. - -_ta_initialize() -atexit.register(_ta_shutdown) - -__function_groups__ = { - 'Cycle Indicators': [ - 'HT_DCPERIOD', - 'HT_DCPHASE', - 'HT_PHASOR', - 'HT_SINE', - 'HT_TRENDMODE', - ], - 'Math Operators': [ - 'ADD', - 'DIV', - 'MAX', - 'MAXINDEX', - 'MIN', - 'MININDEX', - 'MINMAX', - 'MINMAXINDEX', - 'MULT', - 'SUB', - 'SUM', - ], - 'Math Transform': [ - 'ACOS', - 'ASIN', - 'ATAN', - 'CEIL', - 'COS', - 'COSH', - 'EXP', - 'FLOOR', - 'LN', - 'LOG10', - 'SIN', - 'SINH', - 'SQRT', - 'TAN', - 'TANH', - ], - 'Momentum Indicators': [ - 'ADX', - 'ADXR', - 'APO', - 'AROON', - 'AROONOSC', - 'BOP', - 'CCI', - 'CMO', - 'DX', - 'MACD', - 'MACDEXT', - 'MACDFIX', - 'MFI', - 'MINUS_DI', - 'MINUS_DM', - 'MOM', - 'PLUS_DI', - 'PLUS_DM', - 'PPO', - 'ROC', - 'ROCP', - 'ROCR', - 'ROCR100', - 'RSI', - 'STOCH', - 'STOCHF', - 'STOCHRSI', - 'TRIX', - 'ULTOSC', - 'WILLR', - ], - 'Overlap Studies': [ - 'BBANDS', - 'DEMA', - 'EMA', - 'HT_TRENDLINE', - 'KAMA', - 'MA', - 'MAMA', - 'MAVP', - 'MIDPOINT', - 'MIDPRICE', - 'SAR', - 'SAREXT', - 'SMA', - 'T3', - 'TEMA', - 'TRIMA', - 'WMA', - ], - 'Pattern Recognition': [ - 'CDL2CROWS', - 'CDL3BLACKCROWS', - 'CDL3INSIDE', - 'CDL3LINESTRIKE', - 'CDL3OUTSIDE', - 'CDL3STARSINSOUTH', - 'CDL3WHITESOLDIERS', - 'CDLABANDONEDBABY', - 'CDLADVANCEBLOCK', - 'CDLBELTHOLD', - 'CDLBREAKAWAY', - 'CDLCLOSINGMARUBOZU', - 'CDLCONCEALBABYSWALL', - 'CDLCOUNTERATTACK', - 'CDLDARKCLOUDCOVER', - 'CDLDOJI', - 'CDLDOJISTAR', - 'CDLDRAGONFLYDOJI', - 'CDLENGULFING', - 'CDLEVENINGDOJISTAR', - 'CDLEVENINGSTAR', - 'CDLGAPSIDESIDEWHITE', - 'CDLGRAVESTONEDOJI', - 'CDLHAMMER', - 'CDLHANGINGMAN', - 'CDLHARAMI', - 'CDLHARAMICROSS', - 'CDLHIGHWAVE', - 'CDLHIKKAKE', - 'CDLHIKKAKEMOD', - 'CDLHOMINGPIGEON', - 'CDLIDENTICAL3CROWS', - 'CDLINNECK', - 'CDLINVERTEDHAMMER', - 'CDLKICKING', - 'CDLKICKINGBYLENGTH', - 'CDLLADDERBOTTOM', - 'CDLLONGLEGGEDDOJI', - 'CDLLONGLINE', - 'CDLMARUBOZU', - 'CDLMATCHINGLOW', - 'CDLMATHOLD', - 'CDLMORNINGDOJISTAR', - 'CDLMORNINGSTAR', - 'CDLONNECK', - 'CDLPIERCING', - 'CDLRICKSHAWMAN', - 'CDLRISEFALL3METHODS', - 'CDLSEPARATINGLINES', - 'CDLSHOOTINGSTAR', - 'CDLSHORTLINE', - 'CDLSPINNINGTOP', - 'CDLSTALLEDPATTERN', - 'CDLSTICKSANDWICH', - 'CDLTAKURI', - 'CDLTASUKIGAP', - 'CDLTHRUSTING', - 'CDLTRISTAR', - 'CDLUNIQUE3RIVER', - 'CDLUPSIDEGAP2CROWS', - 'CDLXSIDEGAP3METHODS', - ], - 'Price Transform': [ - 'AVGPRICE', - 'MEDPRICE', - 'TYPPRICE', - 'WCLPRICE', - ], - 'Statistic Functions': [ - 'BETA', - 'CORREL', - 'LINEARREG', - 'LINEARREG_ANGLE', - 'LINEARREG_INTERCEPT', - 'LINEARREG_SLOPE', - 'STDDEV', - 'TSF', - 'VAR', - ], - 'Volatility Indicators': [ - 'ATR', - 'NATR', - 'TRANGE', - ], - 'Volume Indicators': [ - 'AD', - 'ADOSC', - 'OBV' - ], - } - -def get_functions(): - """ - Returns a list of all the functions supported by TALIB - """ - ret = [] - for group in __function_groups__: - ret.extend(__function_groups__[group]) - return ret - -def get_function_groups(): - """ - Returns a dict with keys of function-group names and values of lists - of function names ie {'group_names': ['function_names']} - """ - return __function_groups__.copy() - -__all__ = ['get_functions', 'get_function_groups'] + __TA_FUNCTION_NAMES__ + ["stream_%s" % name for name in __TA_FUNCTION_NAMES__] diff --git a/talib/_abstract.pxi b/talib/_abstract.pxi deleted file mode 100644 index 8fb8089ae..000000000 --- a/talib/_abstract.pxi +++ /dev/null @@ -1,820 +0,0 @@ -''' -This file Copyright (c) 2013 Brian A Cappello -''' -import math -import threading -try: - from collections import OrderedDict -except ImportError: # handle python 2.6 and earlier - from ordereddict import OrderedDict -from cython.operator cimport dereference as deref -import numpy -import sys - -cimport numpy as np -cimport _ta_lib as lib -# NOTE: _ta_check_success, MA_Type is defined in _common.pxi - -np.import_array() # Initialize the NumPy C API - -# lookup for TALIB input parameters which don't define expected price series inputs -__INPUT_PRICE_SERIES_DEFAULTS = {'price': 'close', - 'price0': 'high', - 'price1': 'low', - 'periods': 'periods', # only used by MAVP; not a price series! - } - -__INPUT_ARRAYS_TYPES = [dict] -__ARRAY_TYPES = [np.ndarray] - -# allow use of pandas.DataFrame for input arrays -try: - import pandas - __INPUT_ARRAYS_TYPES.append(pandas.DataFrame) - __ARRAY_TYPES.append(pandas.Series) - __PANDAS_DATAFRAME = pandas.DataFrame - __PANDAS_SERIES = pandas.Series -except ImportError as import_error: - try: - if not isinstance(import_error, ModuleNotFoundError) or import_error.name != 'pandas': - # Propagate the error when the module exists but failed to be imported. - raise import_error - # `ModuleNotFoundError` was introduced in Python 3.6. - except NameError: - pass - - __PANDAS_DATAFRAME = None - __PANDAS_SERIES = None - -# allow use of polars.DataFrame for input arrays -try: - import polars - __INPUT_ARRAYS_TYPES.append(polars.DataFrame) - __ARRAY_TYPES.append(polars.Series) - __POLARS_DATAFRAME = polars.DataFrame - __POLARS_SERIES = polars.Series -except ImportError as import_error: - try: - if not isinstance(import_error, ModuleNotFoundError) or import_error.name != 'polars': - # Propagate the error when the module exists but failed to be imported. - raise import_error - # `ModuleNotFoundError` was introduced in Python 3.6. - except NameError: - pass - - __POLARS_DATAFRAME = None - __POLARS_SERIES = None - -__INPUT_ARRAYS_TYPES = tuple(__INPUT_ARRAYS_TYPES) -__ARRAY_TYPES = tuple(__ARRAY_TYPES) - - -if sys.version >= '3': - - def str2bytes(s): - return bytes(s, 'ascii') - - def bytes2str(b): - return b.decode('ascii') - -else: - - def str2bytes(s): - return s - - def bytes2str(b): - return b - -class Function(object): - """ - This is a pythonic wrapper around TALIB's abstract interface. It is - intended to simplify using individual TALIB functions by providing a - unified interface for setting/controlling input data, setting function - parameters and retrieving results. Input data consists of a ``dict`` of - ``numpy`` arrays (or a ``pandas.DataFrame`` or ``polars.DataFrame``), one - array for each of open, high, low, close and volume. This can be set with - the set_input_arrays() method. Which keyed array(s) are used as inputs when - calling the function is controlled using the input_names property. - - This class gets initialized with a TALIB function name and optionally an - input_arrays object. It provides the following primary functions for - setting inputs and retrieving results: - - ---- input_array/TA-function-parameter set-only functions ----- - - set_input_arrays(input_arrays) - - set_function_args([input_arrays,] [param_args_andor_kwargs]) - - Documentation for param_args_andor_kwargs can be seen by printing the - Function instance or programmatically via the info, input_names and - parameters properties. - - ----- result-returning functions ----- - - the outputs property wraps a method which ensures results are always valid - - run([input_arrays]) # calls set_input_arrays and returns self.outputs - - FunctionInstance([input_arrays,] [param_args_andor_kwargs]) # calls set_function_args and returns self.outputs - """ - - def __init__(self, function_name, func_object, *args, **kwargs): - # make sure the function_name is valid and define all of our variables - self.__name = function_name.upper() - self.__namestr = self.__name - self.__name = str2bytes(self.__name) - - # thread-local storage - self.__localdata = threading.local() - - # finish initializing: query the TALIB abstract interface and set arguments - self.set_function_args(*args, **kwargs) - self.func_object = func_object - - @property - def __local(self): - local = self.__localdata - if not hasattr(local, 'info'): - local.info = None - local.input_arrays = {} - - # dictionaries of function args. keys are input/opt_input/output parameter names - local.input_names = OrderedDict() - local.opt_inputs = OrderedDict() - local.outputs = OrderedDict() - local.outputs_valid = False - - # function info - local.info = _ta_getFuncInfo(self.__name) - - # inputs (price series names) - for i in xrange(local.info.pop('num_inputs')): - info = _ta_getInputParameterInfo(self.__name, i) - input_name = info['name'] - if info['price_series'] is None: - info['price_series'] = __INPUT_PRICE_SERIES_DEFAULTS[input_name] - local.input_names[input_name] = info - local.info['input_names'] = self.input_names - - # optional inputs (function parameters) - for i in xrange(local.info.pop('num_opt_inputs')): - info = _ta_getOptInputParameterInfo(self.__name, i) - param_name = info['name'] - local.opt_inputs[param_name] = info - local.info['parameters'] = self.parameters - - # outputs - local.info['output_flags'] = OrderedDict() - for i in xrange(local.info.pop('num_outputs')): - info = _ta_getOutputParameterInfo(self.__name, i) - output_name = info['name'] - local.info['output_flags'][output_name] = info['flags'] - local.outputs[output_name] = None - local.info['output_names'] = self.output_names - return local - - @property - def info(self): - """ - Returns a copy of the function's info dict. - """ - return self.__local.info.copy() - - @property - def function_flags(self): - """ - Returns any function flags defined for this indicator function. - """ - return self.__local.info['function_flags'] - - @property - def output_flags(self): - """ - Returns the flags for each output for this indicator function. - """ - return self.__local.info['output_flags'].copy() - - def get_input_names(self): - """ - Returns the dict of input price series names that specifies which - of the ndarrays in input_arrays will be used to calculate the function. - """ - local = self.__local - ret = OrderedDict() - for input_name in local.input_names: - ret[input_name] = local.input_names[input_name]['price_series'] - return ret - - def set_input_names(self, input_names): - """ - Sets the input price series names to use. - """ - local = self.__local - for input_name, price_series in input_names.items(): - local.input_names[input_name]['price_series'] = price_series - local.info['input_names'][input_name] = price_series - local.outputs_valid = False - - input_names = property(get_input_names, set_input_names) - - def get_input_arrays(self): - """ - Returns a copy of the dict of input arrays in use. - """ - local = self.__local - if __POLARS_DATAFRAME is not None \ - and isinstance(local.input_arrays, __POLARS_DATAFRAME): - return local.input_arrays.clone() - else: - return local.input_arrays.copy() - - def set_input_arrays(self, input_arrays): - """ - Sets the dict of input_arrays to use. Returns True/False for - subclasses: - - If input_arrays is a dict with the keys open, high, low, close and - volume, it is assigned as the input_array to use and this function - returns True, returning False otherwise. If you implement your own - data type and wish to subclass Function, you should wrap this function - with an if-statement: - - class CustomFunction(Function): - def __init__(self, function_name): - Function.__init__(self, function_name) - - def set_input_arrays(self, input_data): - if Function.set_input_arrays(self, input_data): - return True - elif isinstance(input_data, some_module.CustomDataType): - input_arrays = Function.get_input_arrays(self) - # convert input_data to input_arrays and then call the super - Function.set_input_arrays(self, input_arrays) - return True - return False - """ - local = self.__local - if isinstance(input_arrays, __INPUT_ARRAYS_TYPES): - missing_keys = [] - for key in self.__input_price_series_names(): - if __POLARS_DATAFRAME is not None \ - and isinstance(input_arrays, __POLARS_DATAFRAME): - missing = key not in input_arrays.columns - else: - missing = key not in input_arrays - if missing: - missing_keys.append(key) - if len(missing_keys) == 0: - local.input_arrays = input_arrays - local.outputs_valid = False - return True - else: - raise Exception('input_arrays parameter missing required data '\ - 'key%s: %s' % ('s' if len(missing_keys) > 1 \ - else '', - ', '.join(missing_keys))) - return False - - input_arrays = property(get_input_arrays, set_input_arrays) - - def get_parameters(self): - """ - Returns the function's optional parameters and their default values. - """ - local = self.__local - ret = OrderedDict() - for opt_input in local.opt_inputs: - ret[opt_input] = self.__get_opt_input_value(opt_input) - return ret - - def set_parameters(self, parameters=None, **kwargs): - """ - Sets the function parameter values. - """ - local = self.__local - parameters = parameters or {} - parameters.update(kwargs) - for param, value in parameters.items(): - if self.__check_opt_input_value(param, value): - local.opt_inputs[param]['value'] = value - local.outputs_valid = False - local.info['parameters'] = self.parameters - - parameters = property(get_parameters, set_parameters) - - def set_function_args(self, *args, **kwargs): - """ - optional args:[input_arrays,] [parameter_args,] [input_price_series_kwargs,] [parameter_kwargs] - """ - local = self.__local - update_info = False - - for key in kwargs: - if key in local.opt_inputs: - value = kwargs[key] - if self.__check_opt_input_value(key, value): - local.opt_inputs[key]['value'] = kwargs[key] - update_info = True - elif key in local.input_names: - local.input_names[key]['price_series'] = kwargs[key] - local.info['input_names'][key] = kwargs[key] - - if args: - skip_first = 0 - if self.set_input_arrays(args[0]): - skip_first = 1 - if len(args) > skip_first: - for i, param_name in enumerate(local.opt_inputs): - i += skip_first - if i < len(args): - value = args[i] - if self.__check_opt_input_value(param_name, value): - local.opt_inputs[param_name]['value'] = value - update_info = True - - if args or kwargs: - if update_info: - local.info['parameters'] = self.parameters - local.outputs_valid = False - - @property - def lookback(self): - """ - Returns the lookback window size for the function with the parameter - values that are currently set. - """ - local = self.__local - cdef lib.TA_ParamHolder *holder - holder = __ta_paramHolderAlloc(self.__name) - for i, opt_input in enumerate(local.opt_inputs): - value = self.__get_opt_input_value(opt_input) - type_ = local.opt_inputs[opt_input]['type'] - if type_ == lib.TA_OptInput_RealRange or type_ == lib.TA_OptInput_RealList: - __ta_setOptInputParamReal(holder, i, value) - elif type_ == lib.TA_OptInput_IntegerRange or type_ == lib.TA_OptInput_IntegerList: - __ta_setOptInputParamInteger(holder, i, value) - - lookback = __ta_getLookback(holder) - __ta_paramHolderFree(holder) - return lookback - - @property - def output_names(self): - """ - Returns a list of the output names returned by this function. - """ - ret = self.__local.outputs.keys() - if not isinstance(ret, list): - ret = list(ret) - return ret - - @property - def outputs(self): - """ - Returns the TA function values for the currently set input_arrays and - parameters. Returned values are a ndarray if there is only one output - or a list of ndarrays for more than one output. - """ - local = self.__local - if not local.outputs_valid: - self.__call_function() - ret = local.outputs.values() - if not isinstance(ret, list): - ret = list(ret) - if __PANDAS_DATAFRAME is not None and \ - isinstance(local.input_arrays, __PANDAS_DATAFRAME): - index = local.input_arrays.index - if len(ret) == 1: - return __PANDAS_SERIES(ret[0], index=index) - else: - return __PANDAS_DATAFRAME(numpy.column_stack(ret), - index=index, - columns=self.output_names) - elif __POLARS_DATAFRAME is not None and \ - isinstance(local.input_arrays, __POLARS_DATAFRAME): - if len(ret) == 1: - return __POLARS_SERIES(ret[0]) - else: - return __POLARS_DATAFRAME(numpy.column_stack(ret), - schema=self.output_names) - else: - return ret[0] if len(ret) == 1 else ret - - def run(self, input_arrays=None): - """ - run([input_arrays=None]) - - This is a shortcut to the outputs property that also allows setting - the input_arrays dict. - """ - if input_arrays: - self.set_input_arrays(input_arrays) - self.__call_function() - return self.outputs - - def __call__(self, *args, **kwargs): - """ - func_instance([input_arrays,] [parameter_args,] [input_price_series_kwargs,] [parameter_kwargs]) - - This is a shortcut to the outputs property that also allows setting - the input_arrays dict and function parameters. - """ - local = self.__local - # do not cache ta-func parameters passed to __call__ - opt_input_values = [(param_name, local.opt_inputs[param_name]['value']) - for param_name in local.opt_inputs.keys()] - price_series_name_values = [(n, local.input_names[n]['price_series']) - for n in local.input_names] - - # allow calling with same signature as talib.func module functions - args = list(args) - input_arrays = {} - input_price_series_names = self.__input_price_series_names() - if args and not isinstance(args[0], __INPUT_ARRAYS_TYPES): - for i, arg in enumerate(args): - if not isinstance(arg, __ARRAY_TYPES): - break - - try: - input_arrays[input_price_series_names[i]] = arg - except IndexError: - msg = 'Too many price arguments: expected %d (%s)' % ( - len(input_price_series_names), - ', '.join(input_price_series_names)) - raise TypeError(msg) - - if __PANDAS_DATAFRAME is not None \ - and isinstance(local.input_arrays, __PANDAS_DATAFRAME): - no_existing_input_arrays = local.input_arrays.empty - elif __POLARS_DATAFRAME is not None \ - and isinstance(local.input_arrays, __POLARS_DATAFRAME): - no_existing_input_arrays = local.input_arrays.is_empty() - else: - no_existing_input_arrays = not bool(local.input_arrays) - - if len(input_arrays) == len(input_price_series_names): - self.set_input_arrays(input_arrays) - args = args[len(input_arrays):] - elif len(input_arrays) or (no_existing_input_arrays and ( - not len(args) or not isinstance(args[0], __INPUT_ARRAYS_TYPES))): - msg = 'Not enough price arguments: expected %d (%s)' % ( - len(input_price_series_names), - ', '.join(input_price_series_names)) - raise TypeError(msg) - - self.set_function_args(*args, **kwargs) - self.__call_function() - - # restore opt_input values to as they were before this call - for param_name, value in opt_input_values: - local.opt_inputs[param_name]['value'] = value - local.info['parameters'] = self.parameters - - # restore input names values to as they were before this call - for input_name, value in price_series_name_values: - local.input_names[input_name]['price_series'] = value - local.info['input_names'][input_name] = value - - return self.outputs - - # figure out which price series names we're using for inputs - def __input_price_series_names(self): - local = self.__local - input_price_series_names = [] - for input_name in local.input_names: - price_series = local.input_names[input_name]['price_series'] - if isinstance(price_series, list): # TALIB-supplied input names - for name in price_series: - input_price_series_names.append(name) - else: # name came from __INPUT_PRICE_SERIES_DEFAULTS - input_price_series_names.append(price_series) - return input_price_series_names - - def __call_function(self): - local = self.__local - input_price_series_names = self.__input_price_series_names() - - # populate the ordered args we'll call the function with - args = [] - for price_series in input_price_series_names: - series = local.input_arrays[price_series] - if __PANDAS_SERIES is not None and \ - isinstance(series, __PANDAS_SERIES): - series = series.values.astype(float) - elif __POLARS_SERIES is not None and \ - isinstance(series, __POLARS_SERIES): - series = series.to_numpy().astype(float) - args.append(series) - for opt_input in local.opt_inputs: - value = self.__get_opt_input_value(opt_input) - args.append(value) - - # Use the func module to actually call the function. - results = self.func_object(*args) - if isinstance(results, np.ndarray): - keys = local.outputs.keys() - if not isinstance(keys, list): - keys = list(keys) - local.outputs[keys[0]] = results - else: - for i, output in enumerate(local.outputs): - local.outputs[output] = results[i] - local.outputs_valid = True - - def __check_opt_input_value(self, input_name, value): - type_ = self.__local.opt_inputs[input_name]['type'] - if type_ in {lib.TA_OptInput_IntegerList, lib.TA_OptInput_IntegerRange}: - type_ = int - elif type_ in {lib.TA_OptInput_RealList, lib.TA_OptInput_RealRange}: - type_ = float - - if isinstance(value, type_): - return True - elif value is not None: - raise TypeError( - 'Invalid parameter value for %s (expected %s, got %s)' % ( - input_name, type_.__name__, type(value).__name__)) - return False - - def __get_opt_input_value(self, input_name): - """ - Returns the user-set value if there is one, otherwise the default. - """ - local = self.__local - value = local.opt_inputs[input_name]['value'] - if value is None: - value = local.opt_inputs[input_name]['default_value'] - return value - - def __repr__(self): - return '%s' % self.info - - def __unicode__(self): - return unicode(self.__str__()) - - def __str__(self): - return _get_defaults_and_docs(self.info)[1] # docstring includes defaults - - -###################### INTERNAL python-level functions ####################### -# These map 1-1 with native C TALIB abstract interface calls. Their names -# are the same except for having the leading 4 characters lowercased (and -# the Alloc/Free function pairs which have been combined into single get -# functions) -# -# These are TA function information-discovery calls. The Function class -# encapsulates these functions into an easy-to-use, pythonic interface. It's -# therefore recommended over using these functions directly. - -def _ta_getGroupTable(): - """ - Returns the list of available TALIB function group names. *slow* - """ - cdef lib.TA_StringTable *table - _ta_check_success('TA_GroupTableAlloc', lib.TA_GroupTableAlloc(&table)) - groups = [] - for i in xrange(table.size): - groups.append(deref(&table.string[i])) - _ta_check_success('TA_GroupTableFree', lib.TA_GroupTableFree(table)) - return groups - -def _ta_getFuncTable(char *group): - """ - Returns a list of the functions for the specified group name. *slow* - """ - cdef lib.TA_StringTable *table - _ta_check_success('TA_FuncTableAlloc', lib.TA_FuncTableAlloc(group, &table)) - functions = [] - for i in xrange(table.size): - functions.append(deref(&table.string[i])) - _ta_check_success('TA_FuncTableFree', lib.TA_FuncTableFree(table)) - return functions - -def __get_flags(int flag, dict flags_lookup_dict): - """ - TA-LIB provides hints for multiple flags as a bitwise-ORed int. - This function returns the flags from flag found in the provided - flags_lookup_dict. - """ - value_range = flags_lookup_dict.keys() - if not isinstance(value_range, list): - value_range = list(value_range) - min_int = int(math.log(min(value_range), 2)) - max_int = int(math.log(max(value_range), 2)) - - # if the flag we got is out-of-range, it just means no extra info provided - if flag < 1 or flag > 2**max_int: - return None - - # In this loop, i is essentially the bit-position, which represents an - # input from flags_lookup_dict. We loop through as many flags_lookup_dict - # bit-positions as we need to check, bitwise-ANDing each with flag for a hit. - ret = [] - for i in xrange(min_int, max_int+1): - if 2**i & flag: - ret.append(flags_lookup_dict[2**i]) - return ret - -TA_FUNC_FLAGS = { - 16777216: 'Output scale same as input', - 67108864: 'Output is over volume', - 134217728: 'Function has an unstable period', - 268435456: 'Output is a candlestick' -} - -# when flag is 0, the function (should) work on any reasonable input ndarray -TA_INPUT_FLAGS = { - 1: 'open', - 2: 'high', - 4: 'low', - 8: 'close', - 16: 'volume', - 32: 'openInterest', - 64: 'timeStamp' -} - -TA_OUTPUT_FLAGS = { - 1: 'Line', - 2: 'Dotted Line', - 4: 'Dashed Line', - 8: 'Dot', - 16: 'Histogram', - 32: 'Pattern (Bool)', - 64: 'Bull/Bear Pattern (Bearish < 0, Neutral = 0, Bullish > 0)', - 128: 'Strength Pattern ([-200..-100] = Bearish, [-100..0] = Getting Bearish, 0 = Neutral, [0..100] = Getting Bullish, [100-200] = Bullish)', - 256: 'Output can be positive', - 512: 'Output can be negative', - 1024: 'Output can be zero', - 2048: 'Values represent an upper limit', - 4096: 'Values represent a lower limit' -} - -def _ta_getFuncInfo(char *function_name): - """ - Returns the info dict for the function. It has the following keys: name, - group, help, flags, num_inputs, num_opt_inputs and num_outputs. - """ - cdef const lib.TA_FuncInfo *info - retCode = lib.TA_GetFuncInfo(__ta_getFuncHandle(function_name), &info) - _ta_check_success('TA_GetFuncInfo', retCode) - - return { - 'name': bytes2str(info.name), - 'group': bytes2str(info.group), - 'display_name': bytes2str(info.hint), - 'function_flags': __get_flags(info.flags, TA_FUNC_FLAGS), - 'num_inputs': int(info.nbInput), - 'num_opt_inputs': int(info.nbOptInput), - 'num_outputs': int(info.nbOutput) - } - -def _ta_getInputParameterInfo(char *function_name, int idx): - """ - Returns the function's input info dict for the given index. It has two - keys: name and flags. - """ - cdef const lib.TA_InputParameterInfo *info - retCode = lib.TA_GetInputParameterInfo(__ta_getFuncHandle(function_name), idx, &info) - _ta_check_success('TA_GetInputParameterInfo', retCode) - - name = bytes2str(info.paramName) - name = name[len('in'):].lower() - if 'real' in name: - name = name.replace('real', 'price') - elif 'price' in name: - name = 'prices' - - return { - 'name': name, - 'price_series': __get_flags(info.flags, TA_INPUT_FLAGS) - } - -def _ta_getOptInputParameterInfo(char *function_name, int idx): - """ - Returns the function's opt_input info dict for the given index. It has the - following keys: name, display_name, type, help, default_value and value. - """ - cdef const lib.TA_OptInputParameterInfo *info - retCode = lib.TA_GetOptInputParameterInfo(__ta_getFuncHandle(function_name), idx, &info) - _ta_check_success('TA_GetOptInputParameterInfo', retCode) - - name = bytes2str(info.paramName) - name = name[len('optIn'):].lower() - default_value = info.defaultValue - if default_value % 1 == 0 and info.type > 1: - default_value = int(default_value) - - return { - 'name': name, - 'display_name': bytes2str(info.displayName), - 'type': info.type, - 'help': bytes2str(info.hint), - 'default_value': default_value, - 'value': None - } - -def _ta_getOutputParameterInfo(char *function_name, int idx): - """ - Returns the function's output info dict for the given index. It has two - keys: name and flags. - """ - cdef const lib.TA_OutputParameterInfo *info - retCode = lib.TA_GetOutputParameterInfo(__ta_getFuncHandle(function_name), idx, &info) - _ta_check_success('TA_GetOutputParameterInfo', retCode) - - name = bytes2str(info.paramName) - name = name[len('out'):].lower() - # chop off leading 'real' if a descriptive name follows - if 'real' in name and name not in ['real', 'real0', 'real1']: - name = name[len('real'):] - - return { - 'name': name, - 'flags': __get_flags(info.flags, TA_OUTPUT_FLAGS) - } - -def _get_defaults_and_docs(func_info): - """ - Returns a tuple with two outputs: defaults, a dict of parameter defaults, - and documentation, a formatted docstring for the function. - .. Note: func_info should come from Function.info, *not* _ta_getFuncInfo. - """ - defaults = {} - func_line = [func_info['name'], '('] - func_args = ['[input_arrays]'] - docs = [] - docs.append('%(display_name)s (%(group)s)\n' % func_info) - - input_names = func_info['input_names'] - docs.append('Inputs:') - for input_name in input_names: - value = input_names[input_name] - if not isinstance(value, list): - value = '(any ndarray)' - docs.append(' %s: %s' % (input_name, value)) - - params = func_info['parameters'] - if params: - docs.append('Parameters:') - for param in params: - docs.append(' %s: %s' % (param, params[param])) - func_args.append('[%s=%s]' % (param, params[param])) - defaults[param] = params[param] - if param == 'matype': - docs[-1] = ' '.join([docs[-1], '(%s)' % MA_Type[params[param]]]) - - outputs = func_info['output_names'] - docs.append('Outputs:') - for output in outputs: - if output == 'integer': - output = 'integer (values are -100, 0 or 100)' - docs.append(' %s' % output) - - func_line.append(', '.join(func_args)) - func_line.append(')\n') - docs.insert(0, ''.join(func_line)) - documentation = '\n'.join(docs) - return defaults, documentation - - -############### PRIVATE C-level-only functions ########################### -# These map 1-1 with native C TALIB abstract interface calls. Their names are the -# same except for having the leading 4 characters lowercased. - -# These functions are for: -# - Getting TALIB handle and paramholder pointers -# - Setting TALIB paramholder optInput values and calling the lookback function - -cdef const lib.TA_FuncHandle* __ta_getFuncHandle(char *function_name): - """ - Returns a pointer to a function handle for the given function name - """ - cdef const lib.TA_FuncHandle *handle - _ta_check_success('TA_GetFuncHandle', lib.TA_GetFuncHandle(function_name, &handle)) - return handle - -cdef lib.TA_ParamHolder* __ta_paramHolderAlloc(char *function_name): - """ - Returns a pointer to a parameter holder for the given function name - """ - cdef lib.TA_ParamHolder *holder - retCode = lib.TA_ParamHolderAlloc(__ta_getFuncHandle(function_name), &holder) - _ta_check_success('TA_ParamHolderAlloc', retCode) - return holder - -cdef int __ta_paramHolderFree(lib.TA_ParamHolder *params): - """ - Frees the memory allocated by __ta_paramHolderAlloc (call when done with the parameter holder) - WARNING: Not properly calling this function will cause memory leaks! - """ - _ta_check_success('TA_ParamHolderFree', lib.TA_ParamHolderFree(params)) - -cdef int __ta_setOptInputParamInteger(lib.TA_ParamHolder *holder, int idx, int value): - retCode = lib.TA_SetOptInputParamInteger(holder, idx, value) - _ta_check_success('TA_SetOptInputParamInteger', retCode) - -cdef int __ta_setOptInputParamReal(lib.TA_ParamHolder *holder, int idx, double value): - retCode = lib.TA_SetOptInputParamReal(holder, idx, value) - _ta_check_success('TA_SetOptInputParamReal', retCode) - -cdef int __ta_getLookback(lib.TA_ParamHolder *holder): - cdef int lookback - retCode = lib.TA_GetLookback(holder, &lookback) - _ta_check_success('TA_GetLookback', retCode) - return lookback diff --git a/talib/_common.pxi b/talib/_common.pxi deleted file mode 100644 index b7d01d252..000000000 --- a/talib/_common.pxi +++ /dev/null @@ -1,132 +0,0 @@ -cimport _ta_lib as lib -from _ta_lib cimport TA_RetCode, TA_FuncUnstId - -__ta_version__ = lib.TA_GetVersionString() - -cpdef _ta_check_success(str function_name, TA_RetCode ret_code): - if ret_code == 0: - return True - elif ret_code == 1: - description = 'Library Not Initialized (TA_LIB_NOT_INITIALIZE)' - elif ret_code == 2: - description = 'Bad Parameter (TA_BAD_PARAM)' - elif ret_code == 3: - description = 'Allocation Error (TA_ALLOC_ERR)' - elif ret_code == 4: - description = 'Group Not Found (TA_GROUP_NOT_FOUND)' - elif ret_code == 5: - description = 'Function Not Found (TA_FUNC_NOT_FOUND)' - elif ret_code == 6: - description = 'Invalid Handle (TA_INVALID_HANDLE)' - elif ret_code == 7: - description = 'Invalid Parameter Holder (TA_INVALID_PARAM_HOLDER)' - elif ret_code == 8: - description = 'Invalid Parameter Holder Type (TA_INVALID_PARAM_HOLDER_TYPE)' - elif ret_code == 9: - description = 'Invalid Parameter Function (TA_INVALID_PARAM_FUNCTION)' - elif ret_code == 10: - description = 'Input Not All Initialized (TA_INPUT_NOT_ALL_INITIALIZE)' - elif ret_code == 11: - description = 'Output Not All Initialized (TA_OUTPUT_NOT_ALL_INITIALIZE)' - elif ret_code == 12: - description = 'Out-of-Range Start Index (TA_OUT_OF_RANGE_START_INDEX)' - elif ret_code == 13: - description = 'Out-of-Range End Index (TA_OUT_OF_RANGE_END_INDEX)' - elif ret_code == 14: - description = 'Invalid List Type (TA_INVALID_LIST_TYPE)' - elif ret_code == 15: - description = 'Bad Object (TA_BAD_OBJECT)' - elif ret_code == 16: - description = 'Not Supported (TA_NOT_SUPPORTED)' - elif ret_code == 5000: - description = 'Internal Error (TA_INTERNAL_ERROR)' - elif ret_code == 65535: - description = 'Unknown Error (TA_UNKNOWN_ERR)' - else: - description = 'Unknown Error' - raise Exception('%s function failed with error code %s: %s' % ( - function_name, ret_code, description)) - -def _ta_initialize(): - cdef TA_RetCode ret_code - ret_code = lib.TA_Initialize() - _ta_check_success('TA_Initialize', ret_code) - -def _ta_shutdown(): - cdef TA_RetCode ret_code - ret_code = lib.TA_Shutdown() - _ta_check_success('TA_Shutdown', ret_code) - -class MA_Type(object): - SMA, EMA, WMA, DEMA, TEMA, TRIMA, KAMA, MAMA, T3 = range(9) - - def __init__(self): - self._lookup = { - MA_Type.SMA: 'Simple Moving Average', - MA_Type.EMA: 'Exponential Moving Average', - MA_Type.WMA: 'Weighted Moving Average', - MA_Type.DEMA: 'Double Exponential Moving Average', - MA_Type.TEMA: 'Triple Exponential Moving Average', - MA_Type.TRIMA: 'Triangular Moving Average', - MA_Type.KAMA: 'Kaufman Adaptive Moving Average', - MA_Type.MAMA: 'MESA Adaptive Moving Average', - MA_Type.T3: 'Triple Generalized Double Exponential Moving Average', - } - - def __getitem__(self, type_): - return self._lookup[type_] - -MA_Type = MA_Type() - -_ta_func_unst_ids = {'NONE': -1} -for i, name in enumerate([ - 'ADX', 'ADXR', 'ATR', 'CMO', 'DX', 'EMA', 'HT_DCPERIOD', - 'HT_DCPHASE', 'HT_PHASOR', 'HT_SINE', 'HT_TRENDLINE', - 'HT_TRENDMODE', 'KAMA', 'MAMA', 'MFI', 'MINUS_DI', 'MINUS_DM', - 'NATR', 'PLUS_DI', 'PLUS_DM', 'RSI', 'STOCHRSI', 'T3', 'ALL' - ]): - _ta_func_unst_ids[name] = i - -def _ta_set_unstable_period(name, period): - cdef TA_RetCode ret_code - cdef TA_FuncUnstId id = _ta_func_unst_ids[name] - ret_code = lib.TA_SetUnstablePeriod(id, period) - _ta_check_success('TA_SetUnstablePeriod', ret_code) - -def _ta_get_unstable_period(name): - cdef unsigned int period - cdef TA_FuncUnstId id = _ta_func_unst_ids[name] - period = lib.TA_GetUnstablePeriod(id) - return period - -def _ta_set_compatibility(value): - cdef TA_RetCode ret_code - ret_code = lib.TA_SetCompatibility(value) - _ta_check_success('TA_SetCompatibility', ret_code) - -def _ta_get_compatibility(): - cdef int value - value = lib.TA_GetCompatibility() - return value - -class CandleSettingType(object): - BodyLong, BodyVeryLong, BodyShort, BodyDoji, ShadowLong, ShadowVeryLong, \ - ShadowShort, ShadowVeryShort, Near, Far, Equal, AllCandleSettings = \ - range(12) - -CandleSettingType = CandleSettingType() - -class RangeType(object): - RealBody, HighLow, Shadows = range(3) - -RangeType = RangeType() - -def _ta_set_candle_settings(settingtype, rangetype, avgperiod, factor): - cdef TA_RetCode ret_code - ret_code = lib.TA_SetCandleSettings(settingtype, rangetype, avgperiod, factor) - _ta_check_success('TA_SetCandleSettings', ret_code) - -def _ta_restore_candle_default_settings(settingtype): - cdef TA_RetCode ret_code - ret_code = lib.TA_RestoreCandleDefaultSettings(settingtype) - _ta_check_success('TA_RestoreCandleDefaultSettings', ret_code) diff --git a/talib/_func.pxi b/talib/_func.pxi deleted file mode 100644 index c4555a42c..000000000 --- a/talib/_func.pxi +++ /dev/null @@ -1,5324 +0,0 @@ -cimport numpy as np -from numpy import nan -from cython import boundscheck, wraparound - -# _ta_check_success: defined in _common.pxi - -cdef double NaN = nan - -cdef extern from "numpy/arrayobject.h": - int PyArray_TYPE(np.ndarray) - np.ndarray PyArray_EMPTY(int, np.npy_intp*, int, int) - int PyArray_FLAGS(np.ndarray) - np.ndarray PyArray_GETCONTIGUOUS(np.ndarray) - -np.import_array() # Initialize the NumPy C API - -cimport _ta_lib as lib -from _ta_lib cimport TA_RetCode - -cdef np.ndarray check_array(np.ndarray real): - if PyArray_TYPE(real) != np.NPY_DOUBLE: - raise Exception("input array type is not double") - if real.ndim != 1: - raise Exception("input array has wrong dimensions") - if not (PyArray_FLAGS(real) & np.NPY_ARRAY_C_CONTIGUOUS): - real = PyArray_GETCONTIGUOUS(real) - return real - -cdef np.npy_intp check_length2(np.ndarray a1, np.ndarray a2) except -1: - cdef: - np.npy_intp length - length = a1.shape[0] - if length != a2.shape[0]: - raise Exception("input array lengths are different") - return length - -cdef np.npy_intp check_length3(np.ndarray a1, np.ndarray a2, np.ndarray a3) except -1: - cdef: - np.npy_intp length - length = a1.shape[0] - if length != a2.shape[0]: - raise Exception("input array lengths are different") - if length != a3.shape[0]: - raise Exception("input array lengths are different") - return length - -cdef np.npy_intp check_length4(np.ndarray a1, np.ndarray a2, np.ndarray a3, np.ndarray a4) except -1: - cdef: - np.npy_intp length - length = a1.shape[0] - if length != a2.shape[0]: - raise Exception("input array lengths are different") - if length != a3.shape[0]: - raise Exception("input array lengths are different") - if length != a4.shape[0]: - raise Exception("input array lengths are different") - return length - -cdef np.npy_int check_begidx1(np.npy_intp length, double* a1): - cdef: - double val - for i from 0 <= i < length: - val = a1[i] - if val != val: - continue - return i - else: - return length - 1 - -cdef np.npy_int check_begidx2(np.npy_intp length, double* a1, double* a2): - cdef: - double val - for i from 0 <= i < length: - val = a1[i] - if val != val: - continue - val = a2[i] - if val != val: - continue - return i - else: - return length - 1 - -cdef np.npy_int check_begidx3(np.npy_intp length, double* a1, double* a2, double* a3): - cdef: - double val - for i from 0 <= i < length: - val = a1[i] - if val != val: - continue - val = a2[i] - if val != val: - continue - val = a3[i] - if val != val: - continue - return i - else: - return length - 1 - -cdef np.npy_int check_begidx4(np.npy_intp length, double* a1, double* a2, double* a3, double* a4): - cdef: - double val - for i from 0 <= i < length: - val = a1[i] - if val != val: - continue - val = a2[i] - if val != val: - continue - val = a3[i] - if val != val: - continue - val = a4[i] - if val != val: - continue - return i - else: - return length - 1 - -cdef np.ndarray make_double_array(np.npy_intp length, int lookback): - cdef: - np.ndarray outreal - double* outreal_data - outreal = PyArray_EMPTY(1, &length, np.NPY_DOUBLE, np.NPY_ARRAY_DEFAULT) - outreal_data = outreal.data - for i from 0 <= i < min(lookback, length): - outreal_data[i] = NaN - return outreal - -cdef np.ndarray make_int_array(np.npy_intp length, int lookback): - cdef: - np.ndarray outinteger - int* outinteger_data - outinteger = PyArray_EMPTY(1, &length, np.NPY_INT32, np.NPY_ARRAY_DEFAULT) - outinteger_data = outinteger.data - for i from 0 <= i < min(lookback, length): - outinteger_data[i] = 0 - return outinteger - - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ACCBANDS( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ ACCBANDS(high, low, close[, timeperiod=?]) - - Acceleration Bands (Overlap Studies) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 20 - Outputs: - upperband - middleband - lowerband - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outrealupperband - np.ndarray outrealmiddleband - np.ndarray outreallowerband - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ACCBANDS_Lookback( timeperiod ) - outrealupperband = make_double_array(length, lookback) - outrealmiddleband = make_double_array(length, lookback) - outreallowerband = make_double_array(length, lookback) - retCode = lib.TA_ACCBANDS( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outrealupperband.data)+lookback , (outrealmiddleband.data)+lookback , (outreallowerband.data)+lookback ) - _ta_check_success("TA_ACCBANDS", retCode) - return outrealupperband , outrealmiddleband , outreallowerband - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ACOS( np.ndarray real not None ): - """ ACOS(real) - - Vector Trigonometric ACos (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ACOS_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_ACOS( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_ACOS", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def AD( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , np.ndarray volume not None ): - """ AD(high, low, close, volume) - - Chaikin A/D Line (Volume Indicators) - - Inputs: - prices: ['high', 'low', 'close', 'volume'] - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - volume = check_array(volume) - length = check_length4(high, low, close, volume) - begidx = check_begidx4(length, (high.data), (low.data), (close.data), (volume.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_AD_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_AD( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , (volume.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_AD", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ADD( np.ndarray real0 not None , np.ndarray real1 not None ): - """ ADD(real0, real1) - - Vector Arithmetic Add (Math Operators) - - Inputs: - real0: (any ndarray) - real1: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real0 = check_array(real0) - real1 = check_array(real1) - length = check_length2(real0, real1) - begidx = check_begidx2(length, (real0.data), (real1.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ADD_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_ADD( 0 , endidx , (real0.data)+begidx , (real1.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_ADD", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ADOSC( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , np.ndarray volume not None , int fastperiod=-2**31 , int slowperiod=-2**31 ): - """ ADOSC(high, low, close, volume[, fastperiod=?, slowperiod=?]) - - Chaikin A/D Oscillator (Volume Indicators) - - Inputs: - prices: ['high', 'low', 'close', 'volume'] - Parameters: - fastperiod: 3 - slowperiod: 10 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - volume = check_array(volume) - length = check_length4(high, low, close, volume) - begidx = check_begidx4(length, (high.data), (low.data), (close.data), (volume.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ADOSC_Lookback( fastperiod , slowperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_ADOSC( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , (volume.data)+begidx , fastperiod , slowperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_ADOSC", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ADX( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ ADX(high, low, close[, timeperiod=?]) - - Average Directional Movement Index (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ADX_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_ADX( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_ADX", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ADXR( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ ADXR(high, low, close[, timeperiod=?]) - - Average Directional Movement Index Rating (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ADXR_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_ADXR( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_ADXR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def APO( np.ndarray real not None , int fastperiod=-2**31 , int slowperiod=-2**31 , int matype=0 ): - """ APO(real[, fastperiod=?, slowperiod=?, matype=?]) - - Absolute Price Oscillator (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - fastperiod: 12 - slowperiod: 26 - matype: 0 (Simple Moving Average) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_APO_Lookback( fastperiod , slowperiod , matype ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_APO( 0 , endidx , (real.data)+begidx , fastperiod , slowperiod , matype , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_APO", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def AROON( np.ndarray high not None , np.ndarray low not None , int timeperiod=-2**31 ): - """ AROON(high, low[, timeperiod=?]) - - Aroon (Momentum Indicators) - - Inputs: - prices: ['high', 'low'] - Parameters: - timeperiod: 14 - Outputs: - aroondown - aroonup - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outaroondown - np.ndarray outaroonup - high = check_array(high) - low = check_array(low) - length = check_length2(high, low) - begidx = check_begidx2(length, (high.data), (low.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_AROON_Lookback( timeperiod ) - outaroondown = make_double_array(length, lookback) - outaroonup = make_double_array(length, lookback) - retCode = lib.TA_AROON( 0 , endidx , (high.data)+begidx , (low.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outaroondown.data)+lookback , (outaroonup.data)+lookback ) - _ta_check_success("TA_AROON", retCode) - return outaroondown , outaroonup - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def AROONOSC( np.ndarray high not None , np.ndarray low not None , int timeperiod=-2**31 ): - """ AROONOSC(high, low[, timeperiod=?]) - - Aroon Oscillator (Momentum Indicators) - - Inputs: - prices: ['high', 'low'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - length = check_length2(high, low) - begidx = check_begidx2(length, (high.data), (low.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_AROONOSC_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_AROONOSC( 0 , endidx , (high.data)+begidx , (low.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_AROONOSC", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ASIN( np.ndarray real not None ): - """ ASIN(real) - - Vector Trigonometric ASin (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ASIN_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_ASIN( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_ASIN", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ATAN( np.ndarray real not None ): - """ ATAN(real) - - Vector Trigonometric ATan (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ATAN_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_ATAN( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_ATAN", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ATR( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ ATR(high, low, close[, timeperiod=?]) - - Average True Range (Volatility Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ATR_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_ATR( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_ATR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def AVGPRICE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ AVGPRICE(open, high, low, close) - - Average Price (Price Transform) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_AVGPRICE_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_AVGPRICE( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_AVGPRICE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def AVGDEV( np.ndarray real not None , int timeperiod=-2**31 ): - """ AVGDEV(real[, timeperiod=?]) - - Average Deviation (Price Transform) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_AVGDEV_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_AVGDEV( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_AVGDEV", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def BBANDS( np.ndarray real not None , int timeperiod=-2**31 , double nbdevup=-4e37 , double nbdevdn=-4e37 , int matype=0 ): - """ BBANDS(real[, timeperiod=?, nbdevup=?, nbdevdn=?, matype=?]) - - Bollinger Bands (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 5 - nbdevup: 2.0 - nbdevdn: 2.0 - matype: 0 (Simple Moving Average) - Outputs: - upperband - middleband - lowerband - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outrealupperband - np.ndarray outrealmiddleband - np.ndarray outreallowerband - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_BBANDS_Lookback( timeperiod , nbdevup , nbdevdn , matype ) - outrealupperband = make_double_array(length, lookback) - outrealmiddleband = make_double_array(length, lookback) - outreallowerband = make_double_array(length, lookback) - retCode = lib.TA_BBANDS( 0 , endidx , (real.data)+begidx , timeperiod , nbdevup , nbdevdn , matype , &outbegidx , &outnbelement , (outrealupperband.data)+lookback , (outrealmiddleband.data)+lookback , (outreallowerband.data)+lookback ) - _ta_check_success("TA_BBANDS", retCode) - return outrealupperband , outrealmiddleband , outreallowerband - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def BETA( np.ndarray real0 not None , np.ndarray real1 not None , int timeperiod=-2**31 ): - """ BETA(real0, real1[, timeperiod=?]) - - Beta (Statistic Functions) - - Inputs: - real0: (any ndarray) - real1: (any ndarray) - Parameters: - timeperiod: 5 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real0 = check_array(real0) - real1 = check_array(real1) - length = check_length2(real0, real1) - begidx = check_begidx2(length, (real0.data), (real1.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_BETA_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_BETA( 0 , endidx , (real0.data)+begidx , (real1.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_BETA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def BOP( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ BOP(open, high, low, close) - - Balance Of Power (Momentum Indicators) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_BOP_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_BOP( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_BOP", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CCI( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ CCI(high, low, close[, timeperiod=?]) - - Commodity Channel Index (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CCI_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_CCI( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_CCI", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDL2CROWS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL2CROWS(open, high, low, close) - - Two Crows (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDL2CROWS_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDL2CROWS( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDL2CROWS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDL3BLACKCROWS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL3BLACKCROWS(open, high, low, close) - - Three Black Crows (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDL3BLACKCROWS_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDL3BLACKCROWS( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDL3BLACKCROWS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDL3INSIDE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL3INSIDE(open, high, low, close) - - Three Inside Up/Down (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDL3INSIDE_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDL3INSIDE( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDL3INSIDE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDL3LINESTRIKE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL3LINESTRIKE(open, high, low, close) - - Three-Line Strike (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDL3LINESTRIKE_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDL3LINESTRIKE( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDL3LINESTRIKE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDL3OUTSIDE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL3OUTSIDE(open, high, low, close) - - Three Outside Up/Down (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDL3OUTSIDE_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDL3OUTSIDE( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDL3OUTSIDE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDL3STARSINSOUTH( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL3STARSINSOUTH(open, high, low, close) - - Three Stars In The South (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDL3STARSINSOUTH_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDL3STARSINSOUTH( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDL3STARSINSOUTH", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDL3WHITESOLDIERS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL3WHITESOLDIERS(open, high, low, close) - - Three Advancing White Soldiers (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDL3WHITESOLDIERS_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDL3WHITESOLDIERS( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDL3WHITESOLDIERS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLABANDONEDBABY( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.3 ): - """ CDLABANDONEDBABY(open, high, low, close[, penetration=?]) - - Abandoned Baby (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.3 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLABANDONEDBABY_Lookback( penetration ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLABANDONEDBABY( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , penetration , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLABANDONEDBABY", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLADVANCEBLOCK( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLADVANCEBLOCK(open, high, low, close) - - Advance Block (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLADVANCEBLOCK_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLADVANCEBLOCK( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLADVANCEBLOCK", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLBELTHOLD( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLBELTHOLD(open, high, low, close) - - Belt-hold (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLBELTHOLD_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLBELTHOLD( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLBELTHOLD", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLBREAKAWAY( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLBREAKAWAY(open, high, low, close) - - Breakaway (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLBREAKAWAY_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLBREAKAWAY( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLBREAKAWAY", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLCLOSINGMARUBOZU( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLCLOSINGMARUBOZU(open, high, low, close) - - Closing Marubozu (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLCLOSINGMARUBOZU_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLCLOSINGMARUBOZU( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLCLOSINGMARUBOZU", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLCONCEALBABYSWALL( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLCONCEALBABYSWALL(open, high, low, close) - - Concealing Baby Swallow (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLCONCEALBABYSWALL_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLCONCEALBABYSWALL( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLCONCEALBABYSWALL", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLCOUNTERATTACK( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLCOUNTERATTACK(open, high, low, close) - - Counterattack (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLCOUNTERATTACK_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLCOUNTERATTACK( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLCOUNTERATTACK", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLDARKCLOUDCOVER( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.5 ): - """ CDLDARKCLOUDCOVER(open, high, low, close[, penetration=?]) - - Dark Cloud Cover (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.5 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLDARKCLOUDCOVER_Lookback( penetration ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLDARKCLOUDCOVER( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , penetration , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLDARKCLOUDCOVER", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLDOJI( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLDOJI(open, high, low, close) - - Doji (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLDOJI_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLDOJI( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLDOJI", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLDOJISTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLDOJISTAR(open, high, low, close) - - Doji Star (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLDOJISTAR_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLDOJISTAR( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLDOJISTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLDRAGONFLYDOJI( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLDRAGONFLYDOJI(open, high, low, close) - - Dragonfly Doji (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLDRAGONFLYDOJI_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLDRAGONFLYDOJI( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLDRAGONFLYDOJI", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLENGULFING( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLENGULFING(open, high, low, close) - - Engulfing Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLENGULFING_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLENGULFING( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLENGULFING", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLEVENINGDOJISTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.3 ): - """ CDLEVENINGDOJISTAR(open, high, low, close[, penetration=?]) - - Evening Doji Star (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.3 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLEVENINGDOJISTAR_Lookback( penetration ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLEVENINGDOJISTAR( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , penetration , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLEVENINGDOJISTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLEVENINGSTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.3 ): - """ CDLEVENINGSTAR(open, high, low, close[, penetration=?]) - - Evening Star (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.3 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLEVENINGSTAR_Lookback( penetration ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLEVENINGSTAR( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , penetration , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLEVENINGSTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLGAPSIDESIDEWHITE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLGAPSIDESIDEWHITE(open, high, low, close) - - Up/Down-gap side-by-side white lines (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLGAPSIDESIDEWHITE_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLGAPSIDESIDEWHITE( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLGAPSIDESIDEWHITE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLGRAVESTONEDOJI( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLGRAVESTONEDOJI(open, high, low, close) - - Gravestone Doji (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLGRAVESTONEDOJI_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLGRAVESTONEDOJI( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLGRAVESTONEDOJI", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLHAMMER( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHAMMER(open, high, low, close) - - Hammer (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLHAMMER_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLHAMMER( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLHAMMER", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLHANGINGMAN( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHANGINGMAN(open, high, low, close) - - Hanging Man (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLHANGINGMAN_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLHANGINGMAN( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLHANGINGMAN", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLHARAMI( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHARAMI(open, high, low, close) - - Harami Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLHARAMI_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLHARAMI( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLHARAMI", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLHARAMICROSS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHARAMICROSS(open, high, low, close) - - Harami Cross Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLHARAMICROSS_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLHARAMICROSS( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLHARAMICROSS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLHIGHWAVE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHIGHWAVE(open, high, low, close) - - High-Wave Candle (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLHIGHWAVE_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLHIGHWAVE( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLHIGHWAVE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLHIKKAKE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHIKKAKE(open, high, low, close) - - Hikkake Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLHIKKAKE_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLHIKKAKE( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLHIKKAKE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLHIKKAKEMOD( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHIKKAKEMOD(open, high, low, close) - - Modified Hikkake Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLHIKKAKEMOD_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLHIKKAKEMOD( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLHIKKAKEMOD", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLHOMINGPIGEON( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHOMINGPIGEON(open, high, low, close) - - Homing Pigeon (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLHOMINGPIGEON_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLHOMINGPIGEON( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLHOMINGPIGEON", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLIDENTICAL3CROWS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLIDENTICAL3CROWS(open, high, low, close) - - Identical Three Crows (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLIDENTICAL3CROWS_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLIDENTICAL3CROWS( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLIDENTICAL3CROWS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLINNECK( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLINNECK(open, high, low, close) - - In-Neck Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLINNECK_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLINNECK( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLINNECK", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLINVERTEDHAMMER( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLINVERTEDHAMMER(open, high, low, close) - - Inverted Hammer (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLINVERTEDHAMMER_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLINVERTEDHAMMER( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLINVERTEDHAMMER", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLKICKING( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLKICKING(open, high, low, close) - - Kicking (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLKICKING_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLKICKING( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLKICKING", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLKICKINGBYLENGTH( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLKICKINGBYLENGTH(open, high, low, close) - - Kicking - bull/bear determined by the longer marubozu (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLKICKINGBYLENGTH_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLKICKINGBYLENGTH( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLKICKINGBYLENGTH", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLLADDERBOTTOM( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLLADDERBOTTOM(open, high, low, close) - - Ladder Bottom (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLLADDERBOTTOM_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLLADDERBOTTOM( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLLADDERBOTTOM", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLLONGLEGGEDDOJI( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLLONGLEGGEDDOJI(open, high, low, close) - - Long Legged Doji (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLLONGLEGGEDDOJI_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLLONGLEGGEDDOJI( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLLONGLEGGEDDOJI", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLLONGLINE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLLONGLINE(open, high, low, close) - - Long Line Candle (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLLONGLINE_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLLONGLINE( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLLONGLINE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLMARUBOZU( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLMARUBOZU(open, high, low, close) - - Marubozu (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLMARUBOZU_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLMARUBOZU( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLMARUBOZU", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLMATCHINGLOW( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLMATCHINGLOW(open, high, low, close) - - Matching Low (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLMATCHINGLOW_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLMATCHINGLOW( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLMATCHINGLOW", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLMATHOLD( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.5 ): - """ CDLMATHOLD(open, high, low, close[, penetration=?]) - - Mat Hold (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.5 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLMATHOLD_Lookback( penetration ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLMATHOLD( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , penetration , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLMATHOLD", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLMORNINGDOJISTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.3 ): - """ CDLMORNINGDOJISTAR(open, high, low, close[, penetration=?]) - - Morning Doji Star (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.3 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLMORNINGDOJISTAR_Lookback( penetration ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLMORNINGDOJISTAR( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , penetration , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLMORNINGDOJISTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLMORNINGSTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.3 ): - """ CDLMORNINGSTAR(open, high, low, close[, penetration=?]) - - Morning Star (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.3 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLMORNINGSTAR_Lookback( penetration ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLMORNINGSTAR( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , penetration , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLMORNINGSTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLONNECK( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLONNECK(open, high, low, close) - - On-Neck Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLONNECK_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLONNECK( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLONNECK", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLPIERCING( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLPIERCING(open, high, low, close) - - Piercing Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLPIERCING_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLPIERCING( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLPIERCING", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLRICKSHAWMAN( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLRICKSHAWMAN(open, high, low, close) - - Rickshaw Man (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLRICKSHAWMAN_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLRICKSHAWMAN( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLRICKSHAWMAN", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLRISEFALL3METHODS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLRISEFALL3METHODS(open, high, low, close) - - Rising/Falling Three Methods (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLRISEFALL3METHODS_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLRISEFALL3METHODS( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLRISEFALL3METHODS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLSEPARATINGLINES( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLSEPARATINGLINES(open, high, low, close) - - Separating Lines (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLSEPARATINGLINES_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLSEPARATINGLINES( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLSEPARATINGLINES", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLSHOOTINGSTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLSHOOTINGSTAR(open, high, low, close) - - Shooting Star (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLSHOOTINGSTAR_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLSHOOTINGSTAR( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLSHOOTINGSTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLSHORTLINE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLSHORTLINE(open, high, low, close) - - Short Line Candle (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLSHORTLINE_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLSHORTLINE( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLSHORTLINE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLSPINNINGTOP( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLSPINNINGTOP(open, high, low, close) - - Spinning Top (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLSPINNINGTOP_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLSPINNINGTOP( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLSPINNINGTOP", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLSTALLEDPATTERN( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLSTALLEDPATTERN(open, high, low, close) - - Stalled Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLSTALLEDPATTERN_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLSTALLEDPATTERN( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLSTALLEDPATTERN", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLSTICKSANDWICH( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLSTICKSANDWICH(open, high, low, close) - - Stick Sandwich (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLSTICKSANDWICH_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLSTICKSANDWICH( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLSTICKSANDWICH", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLTAKURI( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLTAKURI(open, high, low, close) - - Takuri (Dragonfly Doji with very long lower shadow) (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLTAKURI_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLTAKURI( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLTAKURI", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLTASUKIGAP( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLTASUKIGAP(open, high, low, close) - - Tasuki Gap (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLTASUKIGAP_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLTASUKIGAP( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLTASUKIGAP", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLTHRUSTING( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLTHRUSTING(open, high, low, close) - - Thrusting Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLTHRUSTING_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLTHRUSTING( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLTHRUSTING", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLTRISTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLTRISTAR(open, high, low, close) - - Tristar Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLTRISTAR_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLTRISTAR( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLTRISTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLUNIQUE3RIVER( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLUNIQUE3RIVER(open, high, low, close) - - Unique 3 River (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLUNIQUE3RIVER_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLUNIQUE3RIVER( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLUNIQUE3RIVER", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLUPSIDEGAP2CROWS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLUPSIDEGAP2CROWS(open, high, low, close) - - Upside Gap Two Crows (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLUPSIDEGAP2CROWS_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLUPSIDEGAP2CROWS( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLUPSIDEGAP2CROWS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CDLXSIDEGAP3METHODS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLXSIDEGAP3METHODS(open, high, low, close) - - Upside/Downside Gap Three Methods (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - open = check_array(open) - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length4(open, high, low, close) - begidx = check_begidx4(length, (open.data), (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CDLXSIDEGAP3METHODS_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_CDLXSIDEGAP3METHODS( 0 , endidx , (open.data)+begidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_CDLXSIDEGAP3METHODS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CEIL( np.ndarray real not None ): - """ CEIL(real) - - Vector Ceil (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CEIL_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_CEIL( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_CEIL", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CMO( np.ndarray real not None , int timeperiod=-2**31 ): - """ CMO(real[, timeperiod=?]) - - Chande Momentum Oscillator (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CMO_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_CMO( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_CMO", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def CORREL( np.ndarray real0 not None , np.ndarray real1 not None , int timeperiod=-2**31 ): - """ CORREL(real0, real1[, timeperiod=?]) - - Pearson's Correlation Coefficient (r) (Statistic Functions) - - Inputs: - real0: (any ndarray) - real1: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real0 = check_array(real0) - real1 = check_array(real1) - length = check_length2(real0, real1) - begidx = check_begidx2(length, (real0.data), (real1.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_CORREL_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_CORREL( 0 , endidx , (real0.data)+begidx , (real1.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_CORREL", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def COS( np.ndarray real not None ): - """ COS(real) - - Vector Trigonometric Cos (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_COS_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_COS( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_COS", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def COSH( np.ndarray real not None ): - """ COSH(real) - - Vector Trigonometric Cosh (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_COSH_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_COSH( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_COSH", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def DEMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ DEMA(real[, timeperiod=?]) - - Double Exponential Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_DEMA_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_DEMA( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_DEMA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def DIV( np.ndarray real0 not None , np.ndarray real1 not None ): - """ DIV(real0, real1) - - Vector Arithmetic Div (Math Operators) - - Inputs: - real0: (any ndarray) - real1: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real0 = check_array(real0) - real1 = check_array(real1) - length = check_length2(real0, real1) - begidx = check_begidx2(length, (real0.data), (real1.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_DIV_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_DIV( 0 , endidx , (real0.data)+begidx , (real1.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_DIV", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def DX( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ DX(high, low, close[, timeperiod=?]) - - Directional Movement Index (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_DX_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_DX( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_DX", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def EMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ EMA(real[, timeperiod=?]) - - Exponential Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_EMA_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_EMA( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_EMA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def EXP( np.ndarray real not None ): - """ EXP(real) - - Vector Arithmetic Exp (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_EXP_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_EXP( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_EXP", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def FLOOR( np.ndarray real not None ): - """ FLOOR(real) - - Vector Floor (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_FLOOR_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_FLOOR( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_FLOOR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def HT_DCPERIOD( np.ndarray real not None ): - """ HT_DCPERIOD(real) - - Hilbert Transform - Dominant Cycle Period (Cycle Indicators) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_HT_DCPERIOD_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_HT_DCPERIOD( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_HT_DCPERIOD", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def HT_DCPHASE( np.ndarray real not None ): - """ HT_DCPHASE(real) - - Hilbert Transform - Dominant Cycle Phase (Cycle Indicators) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_HT_DCPHASE_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_HT_DCPHASE( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_HT_DCPHASE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def HT_PHASOR( np.ndarray real not None ): - """ HT_PHASOR(real) - - Hilbert Transform - Phasor Components (Cycle Indicators) - - Inputs: - real: (any ndarray) - Outputs: - inphase - quadrature - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinphase - np.ndarray outquadrature - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_HT_PHASOR_Lookback( ) - outinphase = make_double_array(length, lookback) - outquadrature = make_double_array(length, lookback) - retCode = lib.TA_HT_PHASOR( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outinphase.data)+lookback , (outquadrature.data)+lookback ) - _ta_check_success("TA_HT_PHASOR", retCode) - return outinphase , outquadrature - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def HT_SINE( np.ndarray real not None ): - """ HT_SINE(real) - - Hilbert Transform - SineWave (Cycle Indicators) - - Inputs: - real: (any ndarray) - Outputs: - sine - leadsine - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outsine - np.ndarray outleadsine - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_HT_SINE_Lookback( ) - outsine = make_double_array(length, lookback) - outleadsine = make_double_array(length, lookback) - retCode = lib.TA_HT_SINE( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outsine.data)+lookback , (outleadsine.data)+lookback ) - _ta_check_success("TA_HT_SINE", retCode) - return outsine , outleadsine - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def HT_TRENDLINE( np.ndarray real not None ): - """ HT_TRENDLINE(real) - - Hilbert Transform - Instantaneous Trendline (Overlap Studies) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_HT_TRENDLINE_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_HT_TRENDLINE( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_HT_TRENDLINE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def HT_TRENDMODE( np.ndarray real not None ): - """ HT_TRENDMODE(real) - - Hilbert Transform - Trend vs Cycle Mode (Cycle Indicators) - - Inputs: - real: (any ndarray) - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_HT_TRENDMODE_Lookback( ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_HT_TRENDMODE( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_HT_TRENDMODE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def IMI( np.ndarray open not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ IMI(open, close[, timeperiod=?]) - - Intraday Momentum Index (Momentum Indicators) - - Inputs: - prices: ['open', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - open = check_array(open) - close = check_array(close) - length = check_length2(open, close) - begidx = check_begidx2(length, (open.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_IMI_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_IMI( 0 , endidx , (open.data)+begidx , (close.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_IMI", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def KAMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ KAMA(real[, timeperiod=?]) - - Kaufman Adaptive Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_KAMA_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_KAMA( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_KAMA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def LINEARREG( np.ndarray real not None , int timeperiod=-2**31 ): - """ LINEARREG(real[, timeperiod=?]) - - Linear Regression (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_LINEARREG_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_LINEARREG( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_LINEARREG", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def LINEARREG_ANGLE( np.ndarray real not None , int timeperiod=-2**31 ): - """ LINEARREG_ANGLE(real[, timeperiod=?]) - - Linear Regression Angle (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_LINEARREG_ANGLE_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_LINEARREG_ANGLE( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_LINEARREG_ANGLE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def LINEARREG_INTERCEPT( np.ndarray real not None , int timeperiod=-2**31 ): - """ LINEARREG_INTERCEPT(real[, timeperiod=?]) - - Linear Regression Intercept (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_LINEARREG_INTERCEPT_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_LINEARREG_INTERCEPT( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_LINEARREG_INTERCEPT", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def LINEARREG_SLOPE( np.ndarray real not None , int timeperiod=-2**31 ): - """ LINEARREG_SLOPE(real[, timeperiod=?]) - - Linear Regression Slope (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_LINEARREG_SLOPE_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_LINEARREG_SLOPE( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_LINEARREG_SLOPE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def LN( np.ndarray real not None ): - """ LN(real) - - Vector Log Natural (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_LN_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_LN( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_LN", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def LOG10( np.ndarray real not None ): - """ LOG10(real) - - Vector Log10 (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_LOG10_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_LOG10( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_LOG10", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MA( np.ndarray real not None , int timeperiod=-2**31 , int matype=0 ): - """ MA(real[, timeperiod=?, matype=?]) - - Moving average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - matype: 0 (Simple Moving Average) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MA_Lookback( timeperiod , matype ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_MA( 0 , endidx , (real.data)+begidx , timeperiod , matype , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_MA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MACD( np.ndarray real not None , int fastperiod=-2**31 , int slowperiod=-2**31 , int signalperiod=-2**31 ): - """ MACD(real[, fastperiod=?, slowperiod=?, signalperiod=?]) - - Moving Average Convergence/Divergence (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - fastperiod: 12 - slowperiod: 26 - signalperiod: 9 - Outputs: - macd - macdsignal - macdhist - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outmacd - np.ndarray outmacdsignal - np.ndarray outmacdhist - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MACD_Lookback( fastperiod , slowperiod , signalperiod ) - outmacd = make_double_array(length, lookback) - outmacdsignal = make_double_array(length, lookback) - outmacdhist = make_double_array(length, lookback) - retCode = lib.TA_MACD( 0 , endidx , (real.data)+begidx , fastperiod , slowperiod , signalperiod , &outbegidx , &outnbelement , (outmacd.data)+lookback , (outmacdsignal.data)+lookback , (outmacdhist.data)+lookback ) - _ta_check_success("TA_MACD", retCode) - return outmacd , outmacdsignal , outmacdhist - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MACDEXT( np.ndarray real not None , int fastperiod=-2**31 , int fastmatype=0 , int slowperiod=-2**31 , int slowmatype=0 , int signalperiod=-2**31 , int signalmatype=0 ): - """ MACDEXT(real[, fastperiod=?, fastmatype=?, slowperiod=?, slowmatype=?, signalperiod=?, signalmatype=?]) - - MACD with controllable MA type (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - fastperiod: 12 - fastmatype: 0 - slowperiod: 26 - slowmatype: 0 - signalperiod: 9 - signalmatype: 0 - Outputs: - macd - macdsignal - macdhist - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outmacd - np.ndarray outmacdsignal - np.ndarray outmacdhist - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MACDEXT_Lookback( fastperiod , fastmatype , slowperiod , slowmatype , signalperiod , signalmatype ) - outmacd = make_double_array(length, lookback) - outmacdsignal = make_double_array(length, lookback) - outmacdhist = make_double_array(length, lookback) - retCode = lib.TA_MACDEXT( 0 , endidx , (real.data)+begidx , fastperiod , fastmatype , slowperiod , slowmatype , signalperiod , signalmatype , &outbegidx , &outnbelement , (outmacd.data)+lookback , (outmacdsignal.data)+lookback , (outmacdhist.data)+lookback ) - _ta_check_success("TA_MACDEXT", retCode) - return outmacd , outmacdsignal , outmacdhist - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MACDFIX( np.ndarray real not None , int signalperiod=-2**31 ): - """ MACDFIX(real[, signalperiod=?]) - - Moving Average Convergence/Divergence Fix 12/26 (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - signalperiod: 9 - Outputs: - macd - macdsignal - macdhist - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outmacd - np.ndarray outmacdsignal - np.ndarray outmacdhist - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MACDFIX_Lookback( signalperiod ) - outmacd = make_double_array(length, lookback) - outmacdsignal = make_double_array(length, lookback) - outmacdhist = make_double_array(length, lookback) - retCode = lib.TA_MACDFIX( 0 , endidx , (real.data)+begidx , signalperiod , &outbegidx , &outnbelement , (outmacd.data)+lookback , (outmacdsignal.data)+lookback , (outmacdhist.data)+lookback ) - _ta_check_success("TA_MACDFIX", retCode) - return outmacd , outmacdsignal , outmacdhist - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MAMA( np.ndarray real not None , double fastlimit=-4e37 , double slowlimit=-4e37 ): - """ MAMA(real[, fastlimit=?, slowlimit=?]) - - MESA Adaptive Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - fastlimit: 0.5 - slowlimit: 0.05 - Outputs: - mama - fama - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outmama - np.ndarray outfama - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MAMA_Lookback( fastlimit , slowlimit ) - outmama = make_double_array(length, lookback) - outfama = make_double_array(length, lookback) - retCode = lib.TA_MAMA( 0 , endidx , (real.data)+begidx , fastlimit , slowlimit , &outbegidx , &outnbelement , (outmama.data)+lookback , (outfama.data)+lookback ) - _ta_check_success("TA_MAMA", retCode) - return outmama , outfama - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MAVP( np.ndarray real not None , np.ndarray periods not None , int minperiod=-2**31 , int maxperiod=-2**31 , int matype=0 ): - """ MAVP(real, periods[, minperiod=?, maxperiod=?, matype=?]) - - Moving average with variable period (Overlap Studies) - - Inputs: - real: (any ndarray) - periods: (any ndarray) - Parameters: - minperiod: 2 - maxperiod: 30 - matype: 0 (Simple Moving Average) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - periods = check_array(periods) - length = check_length2(real, periods) - begidx = check_begidx2(length, (real.data), (periods.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MAVP_Lookback( minperiod , maxperiod , matype ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_MAVP( 0 , endidx , (real.data)+begidx , (periods.data)+begidx , minperiod , maxperiod , matype , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_MAVP", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MAX( np.ndarray real not None , int timeperiod=-2**31 ): - """ MAX(real[, timeperiod=?]) - - Highest value over a specified period (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MAX_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_MAX( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_MAX", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MAXINDEX( np.ndarray real not None , int timeperiod=-2**31 ): - """ MAXINDEX(real[, timeperiod=?]) - - Index of highest value over a specified period (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MAXINDEX_Lookback( timeperiod ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_MAXINDEX( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_MAXINDEX", retCode) - outinteger_data = outinteger.data - for i from lookback <= i < length: - outinteger_data[i] += begidx - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MEDPRICE( np.ndarray high not None , np.ndarray low not None ): - """ MEDPRICE(high, low) - - Median Price (Price Transform) - - Inputs: - prices: ['high', 'low'] - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - length = check_length2(high, low) - begidx = check_begidx2(length, (high.data), (low.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MEDPRICE_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_MEDPRICE( 0 , endidx , (high.data)+begidx , (low.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_MEDPRICE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MFI( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , np.ndarray volume not None , int timeperiod=-2**31 ): - """ MFI(high, low, close, volume[, timeperiod=?]) - - Money Flow Index (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close', 'volume'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - volume = check_array(volume) - length = check_length4(high, low, close, volume) - begidx = check_begidx4(length, (high.data), (low.data), (close.data), (volume.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MFI_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_MFI( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , (volume.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_MFI", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MIDPOINT( np.ndarray real not None , int timeperiod=-2**31 ): - """ MIDPOINT(real[, timeperiod=?]) - - MidPoint over period (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MIDPOINT_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_MIDPOINT( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_MIDPOINT", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MIDPRICE( np.ndarray high not None , np.ndarray low not None , int timeperiod=-2**31 ): - """ MIDPRICE(high, low[, timeperiod=?]) - - Midpoint Price over period (Overlap Studies) - - Inputs: - prices: ['high', 'low'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - length = check_length2(high, low) - begidx = check_begidx2(length, (high.data), (low.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MIDPRICE_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_MIDPRICE( 0 , endidx , (high.data)+begidx , (low.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_MIDPRICE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MIN( np.ndarray real not None , int timeperiod=-2**31 ): - """ MIN(real[, timeperiod=?]) - - Lowest value over a specified period (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MIN_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_MIN( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_MIN", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MININDEX( np.ndarray real not None , int timeperiod=-2**31 ): - """ MININDEX(real[, timeperiod=?]) - - Index of lowest value over a specified period (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outinteger - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MININDEX_Lookback( timeperiod ) - outinteger = make_int_array(length, lookback) - retCode = lib.TA_MININDEX( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outinteger.data)+lookback ) - _ta_check_success("TA_MININDEX", retCode) - outinteger_data = outinteger.data - for i from lookback <= i < length: - outinteger_data[i] += begidx - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MINMAX( np.ndarray real not None , int timeperiod=-2**31 ): - """ MINMAX(real[, timeperiod=?]) - - Lowest and highest values over a specified period (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - min - max - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outmin - np.ndarray outmax - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MINMAX_Lookback( timeperiod ) - outmin = make_double_array(length, lookback) - outmax = make_double_array(length, lookback) - retCode = lib.TA_MINMAX( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outmin.data)+lookback , (outmax.data)+lookback ) - _ta_check_success("TA_MINMAX", retCode) - return outmin , outmax - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MINMAXINDEX( np.ndarray real not None , int timeperiod=-2**31 ): - """ MINMAXINDEX(real[, timeperiod=?]) - - Indexes of lowest and highest values over a specified period (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - minidx - maxidx - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outminidx - np.ndarray outmaxidx - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MINMAXINDEX_Lookback( timeperiod ) - outminidx = make_int_array(length, lookback) - outmaxidx = make_int_array(length, lookback) - retCode = lib.TA_MINMAXINDEX( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outminidx.data)+lookback , (outmaxidx.data)+lookback ) - _ta_check_success("TA_MINMAXINDEX", retCode) - outminidx_data = outminidx.data - for i from lookback <= i < length: - outminidx_data[i] += begidx - outmaxidx_data = outmaxidx.data - for i from lookback <= i < length: - outmaxidx_data[i] += begidx - return outminidx , outmaxidx - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MINUS_DI( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ MINUS_DI(high, low, close[, timeperiod=?]) - - Minus Directional Indicator (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MINUS_DI_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_MINUS_DI( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_MINUS_DI", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MINUS_DM( np.ndarray high not None , np.ndarray low not None , int timeperiod=-2**31 ): - """ MINUS_DM(high, low[, timeperiod=?]) - - Minus Directional Movement (Momentum Indicators) - - Inputs: - prices: ['high', 'low'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - length = check_length2(high, low) - begidx = check_begidx2(length, (high.data), (low.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MINUS_DM_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_MINUS_DM( 0 , endidx , (high.data)+begidx , (low.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_MINUS_DM", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MOM( np.ndarray real not None , int timeperiod=-2**31 ): - """ MOM(real[, timeperiod=?]) - - Momentum (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 10 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MOM_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_MOM( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_MOM", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def MULT( np.ndarray real0 not None , np.ndarray real1 not None ): - """ MULT(real0, real1) - - Vector Arithmetic Mult (Math Operators) - - Inputs: - real0: (any ndarray) - real1: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real0 = check_array(real0) - real1 = check_array(real1) - length = check_length2(real0, real1) - begidx = check_begidx2(length, (real0.data), (real1.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_MULT_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_MULT( 0 , endidx , (real0.data)+begidx , (real1.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_MULT", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def NATR( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ NATR(high, low, close[, timeperiod=?]) - - Normalized Average True Range (Volatility Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_NATR_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_NATR( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_NATR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def OBV( np.ndarray real not None , np.ndarray volume not None ): - """ OBV(real, volume) - - On Balance Volume (Volume Indicators) - - Inputs: - real: (any ndarray) - prices: ['volume'] - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - volume = check_array(volume) - length = check_length2(real, volume) - begidx = check_begidx2(length, (real.data), (volume.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_OBV_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_OBV( 0 , endidx , (real.data)+begidx , (volume.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_OBV", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def PLUS_DI( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ PLUS_DI(high, low, close[, timeperiod=?]) - - Plus Directional Indicator (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_PLUS_DI_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_PLUS_DI( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_PLUS_DI", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def PLUS_DM( np.ndarray high not None , np.ndarray low not None , int timeperiod=-2**31 ): - """ PLUS_DM(high, low[, timeperiod=?]) - - Plus Directional Movement (Momentum Indicators) - - Inputs: - prices: ['high', 'low'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - length = check_length2(high, low) - begidx = check_begidx2(length, (high.data), (low.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_PLUS_DM_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_PLUS_DM( 0 , endidx , (high.data)+begidx , (low.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_PLUS_DM", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def PPO( np.ndarray real not None , int fastperiod=-2**31 , int slowperiod=-2**31 , int matype=0 ): - """ PPO(real[, fastperiod=?, slowperiod=?, matype=?]) - - Percentage Price Oscillator (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - fastperiod: 12 - slowperiod: 26 - matype: 0 (Simple Moving Average) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_PPO_Lookback( fastperiod , slowperiod , matype ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_PPO( 0 , endidx , (real.data)+begidx , fastperiod , slowperiod , matype , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_PPO", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ROC( np.ndarray real not None , int timeperiod=-2**31 ): - """ ROC(real[, timeperiod=?]) - - Rate of change : ((real/prevPrice)-1)*100 (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 10 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ROC_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_ROC( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_ROC", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ROCP( np.ndarray real not None , int timeperiod=-2**31 ): - """ ROCP(real[, timeperiod=?]) - - Rate of change Percentage: (real-prevPrice)/prevPrice (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 10 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ROCP_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_ROCP( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_ROCP", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ROCR( np.ndarray real not None , int timeperiod=-2**31 ): - """ ROCR(real[, timeperiod=?]) - - Rate of change ratio: (real/prevPrice) (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 10 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ROCR_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_ROCR( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_ROCR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ROCR100( np.ndarray real not None , int timeperiod=-2**31 ): - """ ROCR100(real[, timeperiod=?]) - - Rate of change ratio 100 scale: (real/prevPrice)*100 (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 10 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ROCR100_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_ROCR100( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_ROCR100", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def RSI( np.ndarray real not None , int timeperiod=-2**31 ): - """ RSI(real[, timeperiod=?]) - - Relative Strength Index (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_RSI_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_RSI( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_RSI", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def SAR( np.ndarray high not None , np.ndarray low not None , double acceleration=0.02 , double maximum=0.2 ): - """ SAR(high, low[, acceleration=?, maximum=?]) - - Parabolic SAR (Overlap Studies) - - Inputs: - prices: ['high', 'low'] - Parameters: - acceleration: 0.02 - maximum: 0.2 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - length = check_length2(high, low) - begidx = check_begidx2(length, (high.data), (low.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_SAR_Lookback( acceleration , maximum ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_SAR( 0 , endidx , (high.data)+begidx , (low.data)+begidx , acceleration , maximum , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_SAR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def SAREXT( np.ndarray high not None , np.ndarray low not None , double startvalue=-4e37 , double offsetonreverse=-4e37 , double accelerationinitlong=-4e37 , double accelerationlong=-4e37 , double accelerationmaxlong=-4e37 , double accelerationinitshort=-4e37 , double accelerationshort=-4e37 , double accelerationmaxshort=-4e37 ): - """ SAREXT(high, low[, startvalue=?, offsetonreverse=?, accelerationinitlong=?, accelerationlong=?, accelerationmaxlong=?, accelerationinitshort=?, accelerationshort=?, accelerationmaxshort=?]) - - Parabolic SAR - Extended (Overlap Studies) - - Inputs: - prices: ['high', 'low'] - Parameters: - startvalue: 0.0 - offsetonreverse: 0.0 - accelerationinitlong: 0.02 - accelerationlong: 0.02 - accelerationmaxlong: 0.2 - accelerationinitshort: 0.02 - accelerationshort: 0.02 - accelerationmaxshort: 0.2 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - length = check_length2(high, low) - begidx = check_begidx2(length, (high.data), (low.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_SAREXT_Lookback( startvalue , offsetonreverse , accelerationinitlong , accelerationlong , accelerationmaxlong , accelerationinitshort , accelerationshort , accelerationmaxshort ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_SAREXT( 0 , endidx , (high.data)+begidx , (low.data)+begidx , startvalue , offsetonreverse , accelerationinitlong , accelerationlong , accelerationmaxlong , accelerationinitshort , accelerationshort , accelerationmaxshort , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_SAREXT", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def SIN( np.ndarray real not None ): - """ SIN(real) - - Vector Trigonometric Sin (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_SIN_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_SIN( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_SIN", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def SINH( np.ndarray real not None ): - """ SINH(real) - - Vector Trigonometric Sinh (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_SINH_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_SINH( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_SINH", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def SMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ SMA(real[, timeperiod=?]) - - Simple Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_SMA_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_SMA( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_SMA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def SQRT( np.ndarray real not None ): - """ SQRT(real) - - Vector Square Root (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_SQRT_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_SQRT( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_SQRT", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def STDDEV( np.ndarray real not None , int timeperiod=-2**31 , double nbdev=-4e37 ): - """ STDDEV(real[, timeperiod=?, nbdev=?]) - - Standard Deviation (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 5 - nbdev: 1.0 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_STDDEV_Lookback( timeperiod , nbdev ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_STDDEV( 0 , endidx , (real.data)+begidx , timeperiod , nbdev , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_STDDEV", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def STOCH( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int fastk_period=-2**31 , int slowk_period=-2**31 , int slowk_matype=0 , int slowd_period=-2**31 , int slowd_matype=0 ): - """ STOCH(high, low, close[, fastk_period=?, slowk_period=?, slowk_matype=?, slowd_period=?, slowd_matype=?]) - - Stochastic (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - fastk_period: 5 - slowk_period: 3 - slowk_matype: 0 - slowd_period: 3 - slowd_matype: 0 - Outputs: - slowk - slowd - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outslowk - np.ndarray outslowd - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_STOCH_Lookback( fastk_period , slowk_period , slowk_matype , slowd_period , slowd_matype ) - outslowk = make_double_array(length, lookback) - outslowd = make_double_array(length, lookback) - retCode = lib.TA_STOCH( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , fastk_period , slowk_period , slowk_matype , slowd_period , slowd_matype , &outbegidx , &outnbelement , (outslowk.data)+lookback , (outslowd.data)+lookback ) - _ta_check_success("TA_STOCH", retCode) - return outslowk , outslowd - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def STOCHF( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int fastk_period=-2**31 , int fastd_period=-2**31 , int fastd_matype=0 ): - """ STOCHF(high, low, close[, fastk_period=?, fastd_period=?, fastd_matype=?]) - - Stochastic Fast (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - fastk_period: 5 - fastd_period: 3 - fastd_matype: 0 - Outputs: - fastk - fastd - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outfastk - np.ndarray outfastd - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_STOCHF_Lookback( fastk_period , fastd_period , fastd_matype ) - outfastk = make_double_array(length, lookback) - outfastd = make_double_array(length, lookback) - retCode = lib.TA_STOCHF( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , fastk_period , fastd_period , fastd_matype , &outbegidx , &outnbelement , (outfastk.data)+lookback , (outfastd.data)+lookback ) - _ta_check_success("TA_STOCHF", retCode) - return outfastk , outfastd - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def STOCHRSI( np.ndarray real not None , int timeperiod=-2**31 , int fastk_period=-2**31 , int fastd_period=-2**31 , int fastd_matype=0 ): - """ STOCHRSI(real[, timeperiod=?, fastk_period=?, fastd_period=?, fastd_matype=?]) - - Stochastic Relative Strength Index (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - fastk_period: 5 - fastd_period: 3 - fastd_matype: 0 - Outputs: - fastk - fastd - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outfastk - np.ndarray outfastd - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_STOCHRSI_Lookback( timeperiod , fastk_period , fastd_period , fastd_matype ) - outfastk = make_double_array(length, lookback) - outfastd = make_double_array(length, lookback) - retCode = lib.TA_STOCHRSI( 0 , endidx , (real.data)+begidx , timeperiod , fastk_period , fastd_period , fastd_matype , &outbegidx , &outnbelement , (outfastk.data)+lookback , (outfastd.data)+lookback ) - _ta_check_success("TA_STOCHRSI", retCode) - return outfastk , outfastd - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def SUB( np.ndarray real0 not None , np.ndarray real1 not None ): - """ SUB(real0, real1) - - Vector Arithmetic Subtraction (Math Operators) - - Inputs: - real0: (any ndarray) - real1: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real0 = check_array(real0) - real1 = check_array(real1) - length = check_length2(real0, real1) - begidx = check_begidx2(length, (real0.data), (real1.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_SUB_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_SUB( 0 , endidx , (real0.data)+begidx , (real1.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_SUB", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def SUM( np.ndarray real not None , int timeperiod=-2**31 ): - """ SUM(real[, timeperiod=?]) - - Summation (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_SUM_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_SUM( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_SUM", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def T3( np.ndarray real not None , int timeperiod=-2**31 , double vfactor=-4e37 ): - """ T3(real[, timeperiod=?, vfactor=?]) - - Triple Exponential Moving Average (T3) (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 5 - vfactor: 0.7 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_T3_Lookback( timeperiod , vfactor ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_T3( 0 , endidx , (real.data)+begidx , timeperiod , vfactor , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_T3", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def TAN( np.ndarray real not None ): - """ TAN(real) - - Vector Trigonometric Tan (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_TAN_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_TAN( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_TAN", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def TANH( np.ndarray real not None ): - """ TANH(real) - - Vector Trigonometric Tanh (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_TANH_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_TANH( 0 , endidx , (real.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_TANH", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def TEMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ TEMA(real[, timeperiod=?]) - - Triple Exponential Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_TEMA_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_TEMA( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_TEMA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def TRANGE( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ TRANGE(high, low, close) - - True Range (Volatility Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_TRANGE_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_TRANGE( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_TRANGE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def TRIMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ TRIMA(real[, timeperiod=?]) - - Triangular Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_TRIMA_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_TRIMA( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_TRIMA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def TRIX( np.ndarray real not None , int timeperiod=-2**31 ): - """ TRIX(real[, timeperiod=?]) - - 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_TRIX_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_TRIX( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_TRIX", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def TSF( np.ndarray real not None , int timeperiod=-2**31 ): - """ TSF(real[, timeperiod=?]) - - Time Series Forecast (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_TSF_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_TSF( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_TSF", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def TYPPRICE( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ TYPPRICE(high, low, close) - - Typical Price (Price Transform) - - Inputs: - prices: ['high', 'low', 'close'] - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_TYPPRICE_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_TYPPRICE( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_TYPPRICE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def ULTOSC( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod1=-2**31 , int timeperiod2=-2**31 , int timeperiod3=-2**31 ): - """ ULTOSC(high, low, close[, timeperiod1=?, timeperiod2=?, timeperiod3=?]) - - Ultimate Oscillator (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod1: 7 - timeperiod2: 14 - timeperiod3: 28 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_ULTOSC_Lookback( timeperiod1 , timeperiod2 , timeperiod3 ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_ULTOSC( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , timeperiod1 , timeperiod2 , timeperiod3 , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_ULTOSC", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def VAR( np.ndarray real not None , int timeperiod=-2**31 , double nbdev=-4e37 ): - """ VAR(real[, timeperiod=?, nbdev=?]) - - Variance (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 5 - nbdev: 1.0 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_VAR_Lookback( timeperiod , nbdev ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_VAR( 0 , endidx , (real.data)+begidx , timeperiod , nbdev , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_VAR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def WCLPRICE( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ WCLPRICE(high, low, close) - - Weighted Close Price (Price Transform) - - Inputs: - prices: ['high', 'low', 'close'] - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_WCLPRICE_Lookback( ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_WCLPRICE( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_WCLPRICE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def WILLR( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ WILLR(high, low, close[, timeperiod=?]) - - Williams' %R (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - high = check_array(high) - low = check_array(low) - close = check_array(close) - length = check_length3(high, low, close) - begidx = check_begidx3(length, (high.data), (low.data), (close.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_WILLR_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_WILLR( 0 , endidx , (high.data)+begidx , (low.data)+begidx , (close.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_WILLR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def WMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ WMA(real[, timeperiod=?]) - - Weighted Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - int begidx, endidx, lookback - TA_RetCode retCode - int outbegidx - int outnbelement - np.ndarray outreal - real = check_array(real) - length = real.shape[0] - begidx = check_begidx1(length, (real.data)) - endidx = length - begidx - 1 - lookback = begidx + lib.TA_WMA_Lookback( timeperiod ) - outreal = make_double_array(length, lookback) - retCode = lib.TA_WMA( 0 , endidx , (real.data)+begidx , timeperiod , &outbegidx , &outnbelement , (outreal.data)+lookback ) - _ta_check_success("TA_WMA", retCode) - return outreal - -__TA_FUNCTION_NAMES__ = ["ACCBANDS","ACOS","AD","ADD","ADOSC","ADX","ADXR","APO","AROON","AROONOSC","ASIN","ATAN","ATR","AVGPRICE","AVGDEV","BBANDS","BETA","BOP","CCI","CDL2CROWS","CDL3BLACKCROWS","CDL3INSIDE","CDL3LINESTRIKE","CDL3OUTSIDE","CDL3STARSINSOUTH","CDL3WHITESOLDIERS","CDLABANDONEDBABY","CDLADVANCEBLOCK","CDLBELTHOLD","CDLBREAKAWAY","CDLCLOSINGMARUBOZU","CDLCONCEALBABYSWALL","CDLCOUNTERATTACK","CDLDARKCLOUDCOVER","CDLDOJI","CDLDOJISTAR","CDLDRAGONFLYDOJI","CDLENGULFING","CDLEVENINGDOJISTAR","CDLEVENINGSTAR","CDLGAPSIDESIDEWHITE","CDLGRAVESTONEDOJI","CDLHAMMER","CDLHANGINGMAN","CDLHARAMI","CDLHARAMICROSS","CDLHIGHWAVE","CDLHIKKAKE","CDLHIKKAKEMOD","CDLHOMINGPIGEON","CDLIDENTICAL3CROWS","CDLINNECK","CDLINVERTEDHAMMER","CDLKICKING","CDLKICKINGBYLENGTH","CDLLADDERBOTTOM","CDLLONGLEGGEDDOJI","CDLLONGLINE","CDLMARUBOZU","CDLMATCHINGLOW","CDLMATHOLD","CDLMORNINGDOJISTAR","CDLMORNINGSTAR","CDLONNECK","CDLPIERCING","CDLRICKSHAWMAN","CDLRISEFALL3METHODS","CDLSEPARATINGLINES","CDLSHOOTINGSTAR","CDLSHORTLINE","CDLSPINNINGTOP","CDLSTALLEDPATTERN","CDLSTICKSANDWICH","CDLTAKURI","CDLTASUKIGAP","CDLTHRUSTING","CDLTRISTAR","CDLUNIQUE3RIVER","CDLUPSIDEGAP2CROWS","CDLXSIDEGAP3METHODS","CEIL","CMO","CORREL","COS","COSH","DEMA","DIV","DX","EMA","EXP","FLOOR","HT_DCPERIOD","HT_DCPHASE","HT_PHASOR","HT_SINE","HT_TRENDLINE","HT_TRENDMODE","IMI","KAMA","LINEARREG","LINEARREG_ANGLE","LINEARREG_INTERCEPT","LINEARREG_SLOPE","LN","LOG10","MA","MACD","MACDEXT","MACDFIX","MAMA","MAVP","MAX","MAXINDEX","MEDPRICE","MFI","MIDPOINT","MIDPRICE","MIN","MININDEX","MINMAX","MINMAXINDEX","MINUS_DI","MINUS_DM","MOM","MULT","NATR","OBV","PLUS_DI","PLUS_DM","PPO","ROC","ROCP","ROCR","ROCR100","RSI","SAR","SAREXT","SIN","SINH","SMA","SQRT","STDDEV","STOCH","STOCHF","STOCHRSI","SUB","SUM","T3","TAN","TANH","TEMA","TRANGE","TRIMA","TRIX","TSF","TYPPRICE","ULTOSC","VAR","WCLPRICE","WILLR","WMA"] diff --git a/talib/_stream.pxi b/talib/_stream.pxi deleted file mode 100644 index b1575b2cc..000000000 --- a/talib/_stream.pxi +++ /dev/null @@ -1,5350 +0,0 @@ -cimport numpy as np -from cython import boundscheck, wraparound -cimport _ta_lib as lib -from _ta_lib cimport TA_RetCode -# NOTE: _ta_check_success, NaN are defined in common.pxi - -np.import_array() # Initialize the NumPy C API - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ACCBANDS( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ ACCBANDS(high, low, close[, timeperiod=?]) - - Acceleration Bands (Overlap Studies) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 20 - Outputs: - upperband - middleband - lowerband - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outrealupperband - double outrealmiddleband - double outreallowerband - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outrealupperband = NaN - outrealmiddleband = NaN - outreallowerband = NaN - retCode = lib.TA_ACCBANDS( (length) - 1 , (length) - 1 , high_data , low_data , close_data , timeperiod , &outbegidx , &outnbelement , &outrealupperband , &outrealmiddleband , &outreallowerband ) - _ta_check_success("TA_ACCBANDS", retCode) - return outrealupperband , outrealmiddleband , outreallowerband - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ACOS( np.ndarray real not None ): - """ ACOS(real) - - Vector Trigonometric ACos (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_ACOS( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_ACOS", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_AD( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , np.ndarray volume not None ): - """ AD(high, low, close, volume) - - Chaikin A/D Line (Volume Indicators) - - Inputs: - prices: ['high', 'low', 'close', 'volume'] - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - double* volume_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - volume = check_array(volume) - volume_data = volume.data - length = check_length4(high, low, close, volume) - outreal = NaN - retCode = lib.TA_AD( (length) - 1 , (length) - 1 , high_data , low_data , close_data , volume_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_AD", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ADD( np.ndarray real0 not None , np.ndarray real1 not None ): - """ ADD(real0, real1) - - Vector Arithmetic Add (Math Operators) - - Inputs: - real0: (any ndarray) - real1: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real0_data - double* real1_data - int outbegidx - int outnbelement - double outreal - real0 = check_array(real0) - real0_data = real0.data - real1 = check_array(real1) - real1_data = real1.data - length = check_length2(real0, real1) - outreal = NaN - retCode = lib.TA_ADD( (length) - 1 , (length) - 1 , real0_data , real1_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_ADD", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ADOSC( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , np.ndarray volume not None , int fastperiod=-2**31 , int slowperiod=-2**31 ): - """ ADOSC(high, low, close, volume[, fastperiod=?, slowperiod=?]) - - Chaikin A/D Oscillator (Volume Indicators) - - Inputs: - prices: ['high', 'low', 'close', 'volume'] - Parameters: - fastperiod: 3 - slowperiod: 10 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - double* volume_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - volume = check_array(volume) - volume_data = volume.data - length = check_length4(high, low, close, volume) - outreal = NaN - retCode = lib.TA_ADOSC( (length) - 1 , (length) - 1 , high_data , low_data , close_data , volume_data , fastperiod , slowperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_ADOSC", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ADX( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ ADX(high, low, close[, timeperiod=?]) - - Average Directional Movement Index (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outreal = NaN - retCode = lib.TA_ADX( (length) - 1 , (length) - 1 , high_data , low_data , close_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_ADX", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ADXR( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ ADXR(high, low, close[, timeperiod=?]) - - Average Directional Movement Index Rating (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outreal = NaN - retCode = lib.TA_ADXR( (length) - 1 , (length) - 1 , high_data , low_data , close_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_ADXR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_APO( np.ndarray real not None , int fastperiod=-2**31 , int slowperiod=-2**31 , int matype=0 ): - """ APO(real[, fastperiod=?, slowperiod=?, matype=?]) - - Absolute Price Oscillator (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - fastperiod: 12 - slowperiod: 26 - matype: 0 (Simple Moving Average) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_APO( (length) - 1 , (length) - 1 , real_data , fastperiod , slowperiod , matype , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_APO", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_AROON( np.ndarray high not None , np.ndarray low not None , int timeperiod=-2**31 ): - """ AROON(high, low[, timeperiod=?]) - - Aroon (Momentum Indicators) - - Inputs: - prices: ['high', 'low'] - Parameters: - timeperiod: 14 - Outputs: - aroondown - aroonup - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - int outbegidx - int outnbelement - double outaroondown - double outaroonup - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - length = check_length2(high, low) - outaroondown = NaN - outaroonup = NaN - retCode = lib.TA_AROON( (length) - 1 , (length) - 1 , high_data , low_data , timeperiod , &outbegidx , &outnbelement , &outaroondown , &outaroonup ) - _ta_check_success("TA_AROON", retCode) - return outaroondown , outaroonup - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_AROONOSC( np.ndarray high not None , np.ndarray low not None , int timeperiod=-2**31 ): - """ AROONOSC(high, low[, timeperiod=?]) - - Aroon Oscillator (Momentum Indicators) - - Inputs: - prices: ['high', 'low'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - length = check_length2(high, low) - outreal = NaN - retCode = lib.TA_AROONOSC( (length) - 1 , (length) - 1 , high_data , low_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_AROONOSC", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ASIN( np.ndarray real not None ): - """ ASIN(real) - - Vector Trigonometric ASin (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_ASIN( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_ASIN", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ATAN( np.ndarray real not None ): - """ ATAN(real) - - Vector Trigonometric ATan (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_ATAN( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_ATAN", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ATR( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ ATR(high, low, close[, timeperiod=?]) - - Average True Range (Volatility Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outreal = NaN - retCode = lib.TA_ATR( (length) - 1 , (length) - 1 , high_data , low_data , close_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_ATR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_AVGPRICE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ AVGPRICE(open, high, low, close) - - Average Price (Price Transform) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outreal = NaN - retCode = lib.TA_AVGPRICE( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_AVGPRICE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_AVGDEV( np.ndarray real not None , int timeperiod=-2**31 ): - """ AVGDEV(real[, timeperiod=?]) - - Average Deviation (Price Transform) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_AVGDEV( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_AVGDEV", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_BBANDS( np.ndarray real not None , int timeperiod=-2**31 , double nbdevup=-4e37 , double nbdevdn=-4e37 , int matype=0 ): - """ BBANDS(real[, timeperiod=?, nbdevup=?, nbdevdn=?, matype=?]) - - Bollinger Bands (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 5 - nbdevup: 2.0 - nbdevdn: 2.0 - matype: 0 (Simple Moving Average) - Outputs: - upperband - middleband - lowerband - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outrealupperband - double outrealmiddleband - double outreallowerband - real = check_array(real) - real_data = real.data - length = real.shape[0] - outrealupperband = NaN - outrealmiddleband = NaN - outreallowerband = NaN - retCode = lib.TA_BBANDS( (length) - 1 , (length) - 1 , real_data , timeperiod , nbdevup , nbdevdn , matype , &outbegidx , &outnbelement , &outrealupperband , &outrealmiddleband , &outreallowerband ) - _ta_check_success("TA_BBANDS", retCode) - return outrealupperband , outrealmiddleband , outreallowerband - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_BETA( np.ndarray real0 not None , np.ndarray real1 not None , int timeperiod=-2**31 ): - """ BETA(real0, real1[, timeperiod=?]) - - Beta (Statistic Functions) - - Inputs: - real0: (any ndarray) - real1: (any ndarray) - Parameters: - timeperiod: 5 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real0_data - double* real1_data - int outbegidx - int outnbelement - double outreal - real0 = check_array(real0) - real0_data = real0.data - real1 = check_array(real1) - real1_data = real1.data - length = check_length2(real0, real1) - outreal = NaN - retCode = lib.TA_BETA( (length) - 1 , (length) - 1 , real0_data , real1_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_BETA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_BOP( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ BOP(open, high, low, close) - - Balance Of Power (Momentum Indicators) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outreal = NaN - retCode = lib.TA_BOP( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_BOP", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CCI( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ CCI(high, low, close[, timeperiod=?]) - - Commodity Channel Index (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outreal = NaN - retCode = lib.TA_CCI( (length) - 1 , (length) - 1 , high_data , low_data , close_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_CCI", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDL2CROWS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL2CROWS(open, high, low, close) - - Two Crows (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDL2CROWS( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDL2CROWS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDL3BLACKCROWS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL3BLACKCROWS(open, high, low, close) - - Three Black Crows (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDL3BLACKCROWS( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDL3BLACKCROWS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDL3INSIDE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL3INSIDE(open, high, low, close) - - Three Inside Up/Down (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDL3INSIDE( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDL3INSIDE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDL3LINESTRIKE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL3LINESTRIKE(open, high, low, close) - - Three-Line Strike (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDL3LINESTRIKE( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDL3LINESTRIKE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDL3OUTSIDE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL3OUTSIDE(open, high, low, close) - - Three Outside Up/Down (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDL3OUTSIDE( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDL3OUTSIDE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDL3STARSINSOUTH( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL3STARSINSOUTH(open, high, low, close) - - Three Stars In The South (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDL3STARSINSOUTH( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDL3STARSINSOUTH", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDL3WHITESOLDIERS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDL3WHITESOLDIERS(open, high, low, close) - - Three Advancing White Soldiers (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDL3WHITESOLDIERS( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDL3WHITESOLDIERS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLABANDONEDBABY( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.3 ): - """ CDLABANDONEDBABY(open, high, low, close[, penetration=?]) - - Abandoned Baby (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.3 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLABANDONEDBABY( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , penetration , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLABANDONEDBABY", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLADVANCEBLOCK( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLADVANCEBLOCK(open, high, low, close) - - Advance Block (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLADVANCEBLOCK( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLADVANCEBLOCK", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLBELTHOLD( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLBELTHOLD(open, high, low, close) - - Belt-hold (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLBELTHOLD( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLBELTHOLD", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLBREAKAWAY( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLBREAKAWAY(open, high, low, close) - - Breakaway (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLBREAKAWAY( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLBREAKAWAY", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLCLOSINGMARUBOZU( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLCLOSINGMARUBOZU(open, high, low, close) - - Closing Marubozu (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLCLOSINGMARUBOZU( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLCLOSINGMARUBOZU", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLCONCEALBABYSWALL( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLCONCEALBABYSWALL(open, high, low, close) - - Concealing Baby Swallow (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLCONCEALBABYSWALL( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLCONCEALBABYSWALL", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLCOUNTERATTACK( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLCOUNTERATTACK(open, high, low, close) - - Counterattack (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLCOUNTERATTACK( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLCOUNTERATTACK", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLDARKCLOUDCOVER( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.5 ): - """ CDLDARKCLOUDCOVER(open, high, low, close[, penetration=?]) - - Dark Cloud Cover (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.5 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLDARKCLOUDCOVER( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , penetration , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLDARKCLOUDCOVER", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLDOJI( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLDOJI(open, high, low, close) - - Doji (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLDOJI( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLDOJI", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLDOJISTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLDOJISTAR(open, high, low, close) - - Doji Star (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLDOJISTAR( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLDOJISTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLDRAGONFLYDOJI( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLDRAGONFLYDOJI(open, high, low, close) - - Dragonfly Doji (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLDRAGONFLYDOJI( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLDRAGONFLYDOJI", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLENGULFING( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLENGULFING(open, high, low, close) - - Engulfing Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLENGULFING( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLENGULFING", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLEVENINGDOJISTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.3 ): - """ CDLEVENINGDOJISTAR(open, high, low, close[, penetration=?]) - - Evening Doji Star (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.3 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLEVENINGDOJISTAR( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , penetration , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLEVENINGDOJISTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLEVENINGSTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.3 ): - """ CDLEVENINGSTAR(open, high, low, close[, penetration=?]) - - Evening Star (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.3 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLEVENINGSTAR( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , penetration , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLEVENINGSTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLGAPSIDESIDEWHITE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLGAPSIDESIDEWHITE(open, high, low, close) - - Up/Down-gap side-by-side white lines (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLGAPSIDESIDEWHITE( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLGAPSIDESIDEWHITE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLGRAVESTONEDOJI( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLGRAVESTONEDOJI(open, high, low, close) - - Gravestone Doji (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLGRAVESTONEDOJI( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLGRAVESTONEDOJI", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLHAMMER( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHAMMER(open, high, low, close) - - Hammer (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLHAMMER( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLHAMMER", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLHANGINGMAN( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHANGINGMAN(open, high, low, close) - - Hanging Man (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLHANGINGMAN( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLHANGINGMAN", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLHARAMI( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHARAMI(open, high, low, close) - - Harami Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLHARAMI( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLHARAMI", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLHARAMICROSS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHARAMICROSS(open, high, low, close) - - Harami Cross Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLHARAMICROSS( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLHARAMICROSS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLHIGHWAVE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHIGHWAVE(open, high, low, close) - - High-Wave Candle (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLHIGHWAVE( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLHIGHWAVE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLHIKKAKE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHIKKAKE(open, high, low, close) - - Hikkake Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLHIKKAKE( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLHIKKAKE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLHIKKAKEMOD( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHIKKAKEMOD(open, high, low, close) - - Modified Hikkake Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLHIKKAKEMOD( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLHIKKAKEMOD", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLHOMINGPIGEON( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLHOMINGPIGEON(open, high, low, close) - - Homing Pigeon (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLHOMINGPIGEON( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLHOMINGPIGEON", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLIDENTICAL3CROWS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLIDENTICAL3CROWS(open, high, low, close) - - Identical Three Crows (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLIDENTICAL3CROWS( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLIDENTICAL3CROWS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLINNECK( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLINNECK(open, high, low, close) - - In-Neck Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLINNECK( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLINNECK", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLINVERTEDHAMMER( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLINVERTEDHAMMER(open, high, low, close) - - Inverted Hammer (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLINVERTEDHAMMER( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLINVERTEDHAMMER", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLKICKING( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLKICKING(open, high, low, close) - - Kicking (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLKICKING( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLKICKING", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLKICKINGBYLENGTH( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLKICKINGBYLENGTH(open, high, low, close) - - Kicking - bull/bear determined by the longer marubozu (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLKICKINGBYLENGTH( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLKICKINGBYLENGTH", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLLADDERBOTTOM( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLLADDERBOTTOM(open, high, low, close) - - Ladder Bottom (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLLADDERBOTTOM( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLLADDERBOTTOM", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLLONGLEGGEDDOJI( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLLONGLEGGEDDOJI(open, high, low, close) - - Long Legged Doji (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLLONGLEGGEDDOJI( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLLONGLEGGEDDOJI", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLLONGLINE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLLONGLINE(open, high, low, close) - - Long Line Candle (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLLONGLINE( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLLONGLINE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLMARUBOZU( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLMARUBOZU(open, high, low, close) - - Marubozu (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLMARUBOZU( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLMARUBOZU", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLMATCHINGLOW( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLMATCHINGLOW(open, high, low, close) - - Matching Low (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLMATCHINGLOW( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLMATCHINGLOW", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLMATHOLD( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.5 ): - """ CDLMATHOLD(open, high, low, close[, penetration=?]) - - Mat Hold (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.5 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLMATHOLD( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , penetration , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLMATHOLD", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLMORNINGDOJISTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.3 ): - """ CDLMORNINGDOJISTAR(open, high, low, close[, penetration=?]) - - Morning Doji Star (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.3 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLMORNINGDOJISTAR( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , penetration , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLMORNINGDOJISTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLMORNINGSTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , double penetration=0.3 ): - """ CDLMORNINGSTAR(open, high, low, close[, penetration=?]) - - Morning Star (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Parameters: - penetration: 0.3 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLMORNINGSTAR( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , penetration , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLMORNINGSTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLONNECK( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLONNECK(open, high, low, close) - - On-Neck Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLONNECK( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLONNECK", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLPIERCING( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLPIERCING(open, high, low, close) - - Piercing Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLPIERCING( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLPIERCING", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLRICKSHAWMAN( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLRICKSHAWMAN(open, high, low, close) - - Rickshaw Man (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLRICKSHAWMAN( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLRICKSHAWMAN", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLRISEFALL3METHODS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLRISEFALL3METHODS(open, high, low, close) - - Rising/Falling Three Methods (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLRISEFALL3METHODS( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLRISEFALL3METHODS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLSEPARATINGLINES( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLSEPARATINGLINES(open, high, low, close) - - Separating Lines (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLSEPARATINGLINES( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLSEPARATINGLINES", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLSHOOTINGSTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLSHOOTINGSTAR(open, high, low, close) - - Shooting Star (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLSHOOTINGSTAR( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLSHOOTINGSTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLSHORTLINE( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLSHORTLINE(open, high, low, close) - - Short Line Candle (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLSHORTLINE( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLSHORTLINE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLSPINNINGTOP( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLSPINNINGTOP(open, high, low, close) - - Spinning Top (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLSPINNINGTOP( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLSPINNINGTOP", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLSTALLEDPATTERN( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLSTALLEDPATTERN(open, high, low, close) - - Stalled Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLSTALLEDPATTERN( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLSTALLEDPATTERN", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLSTICKSANDWICH( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLSTICKSANDWICH(open, high, low, close) - - Stick Sandwich (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLSTICKSANDWICH( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLSTICKSANDWICH", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLTAKURI( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLTAKURI(open, high, low, close) - - Takuri (Dragonfly Doji with very long lower shadow) (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLTAKURI( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLTAKURI", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLTASUKIGAP( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLTASUKIGAP(open, high, low, close) - - Tasuki Gap (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLTASUKIGAP( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLTASUKIGAP", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLTHRUSTING( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLTHRUSTING(open, high, low, close) - - Thrusting Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLTHRUSTING( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLTHRUSTING", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLTRISTAR( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLTRISTAR(open, high, low, close) - - Tristar Pattern (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLTRISTAR( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLTRISTAR", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLUNIQUE3RIVER( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLUNIQUE3RIVER(open, high, low, close) - - Unique 3 River (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLUNIQUE3RIVER( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLUNIQUE3RIVER", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLUPSIDEGAP2CROWS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLUPSIDEGAP2CROWS(open, high, low, close) - - Upside Gap Two Crows (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLUPSIDEGAP2CROWS( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLUPSIDEGAP2CROWS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CDLXSIDEGAP3METHODS( np.ndarray open not None , np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ CDLXSIDEGAP3METHODS(open, high, low, close) - - Upside/Downside Gap Three Methods (Pattern Recognition) - - Inputs: - prices: ['open', 'high', 'low', 'close'] - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - int outinteger - open = check_array(open) - open_data = open.data - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length4(open, high, low, close) - outinteger = 0 - retCode = lib.TA_CDLXSIDEGAP3METHODS( (length) - 1 , (length) - 1 , open_data , high_data , low_data , close_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_CDLXSIDEGAP3METHODS", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CEIL( np.ndarray real not None ): - """ CEIL(real) - - Vector Ceil (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_CEIL( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_CEIL", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CMO( np.ndarray real not None , int timeperiod=-2**31 ): - """ CMO(real[, timeperiod=?]) - - Chande Momentum Oscillator (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_CMO( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_CMO", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_CORREL( np.ndarray real0 not None , np.ndarray real1 not None , int timeperiod=-2**31 ): - """ CORREL(real0, real1[, timeperiod=?]) - - Pearson's Correlation Coefficient (r) (Statistic Functions) - - Inputs: - real0: (any ndarray) - real1: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real0_data - double* real1_data - int outbegidx - int outnbelement - double outreal - real0 = check_array(real0) - real0_data = real0.data - real1 = check_array(real1) - real1_data = real1.data - length = check_length2(real0, real1) - outreal = NaN - retCode = lib.TA_CORREL( (length) - 1 , (length) - 1 , real0_data , real1_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_CORREL", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_COS( np.ndarray real not None ): - """ COS(real) - - Vector Trigonometric Cos (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_COS( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_COS", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_COSH( np.ndarray real not None ): - """ COSH(real) - - Vector Trigonometric Cosh (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_COSH( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_COSH", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_DEMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ DEMA(real[, timeperiod=?]) - - Double Exponential Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_DEMA( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_DEMA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_DIV( np.ndarray real0 not None , np.ndarray real1 not None ): - """ DIV(real0, real1) - - Vector Arithmetic Div (Math Operators) - - Inputs: - real0: (any ndarray) - real1: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real0_data - double* real1_data - int outbegidx - int outnbelement - double outreal - real0 = check_array(real0) - real0_data = real0.data - real1 = check_array(real1) - real1_data = real1.data - length = check_length2(real0, real1) - outreal = NaN - retCode = lib.TA_DIV( (length) - 1 , (length) - 1 , real0_data , real1_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_DIV", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_DX( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ DX(high, low, close[, timeperiod=?]) - - Directional Movement Index (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outreal = NaN - retCode = lib.TA_DX( (length) - 1 , (length) - 1 , high_data , low_data , close_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_DX", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_EMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ EMA(real[, timeperiod=?]) - - Exponential Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_EMA( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_EMA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_EXP( np.ndarray real not None ): - """ EXP(real) - - Vector Arithmetic Exp (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_EXP( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_EXP", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_FLOOR( np.ndarray real not None ): - """ FLOOR(real) - - Vector Floor (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_FLOOR( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_FLOOR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_HT_DCPERIOD( np.ndarray real not None ): - """ HT_DCPERIOD(real) - - Hilbert Transform - Dominant Cycle Period (Cycle Indicators) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_HT_DCPERIOD( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_HT_DCPERIOD", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_HT_DCPHASE( np.ndarray real not None ): - """ HT_DCPHASE(real) - - Hilbert Transform - Dominant Cycle Phase (Cycle Indicators) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_HT_DCPHASE( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_HT_DCPHASE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_HT_PHASOR( np.ndarray real not None ): - """ HT_PHASOR(real) - - Hilbert Transform - Phasor Components (Cycle Indicators) - - Inputs: - real: (any ndarray) - Outputs: - inphase - quadrature - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outinphase - double outquadrature - real = check_array(real) - real_data = real.data - length = real.shape[0] - outinphase = NaN - outquadrature = NaN - retCode = lib.TA_HT_PHASOR( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outinphase , &outquadrature ) - _ta_check_success("TA_HT_PHASOR", retCode) - return outinphase , outquadrature - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_HT_SINE( np.ndarray real not None ): - """ HT_SINE(real) - - Hilbert Transform - SineWave (Cycle Indicators) - - Inputs: - real: (any ndarray) - Outputs: - sine - leadsine - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outsine - double outleadsine - real = check_array(real) - real_data = real.data - length = real.shape[0] - outsine = NaN - outleadsine = NaN - retCode = lib.TA_HT_SINE( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outsine , &outleadsine ) - _ta_check_success("TA_HT_SINE", retCode) - return outsine , outleadsine - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_HT_TRENDLINE( np.ndarray real not None ): - """ HT_TRENDLINE(real) - - Hilbert Transform - Instantaneous Trendline (Overlap Studies) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_HT_TRENDLINE( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_HT_TRENDLINE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_HT_TRENDMODE( np.ndarray real not None ): - """ HT_TRENDMODE(real) - - Hilbert Transform - Trend vs Cycle Mode (Cycle Indicators) - - Inputs: - real: (any ndarray) - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - int outinteger - real = check_array(real) - real_data = real.data - length = real.shape[0] - outinteger = 0 - retCode = lib.TA_HT_TRENDMODE( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_HT_TRENDMODE", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_IMI( np.ndarray open not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ IMI(open, close[, timeperiod=?]) - - Intraday Momentum Index (Momentum Indicators) - - Inputs: - prices: ['open', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* open_data - double* close_data - int outbegidx - int outnbelement - double outreal - open = check_array(open) - open_data = open.data - close = check_array(close) - close_data = close.data - length = check_length2(open, close) - outreal = NaN - retCode = lib.TA_IMI( (length) - 1 , (length) - 1 , open_data , close_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_IMI", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_KAMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ KAMA(real[, timeperiod=?]) - - Kaufman Adaptive Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_KAMA( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_KAMA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_LINEARREG( np.ndarray real not None , int timeperiod=-2**31 ): - """ LINEARREG(real[, timeperiod=?]) - - Linear Regression (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_LINEARREG( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_LINEARREG", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_LINEARREG_ANGLE( np.ndarray real not None , int timeperiod=-2**31 ): - """ LINEARREG_ANGLE(real[, timeperiod=?]) - - Linear Regression Angle (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_LINEARREG_ANGLE( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_LINEARREG_ANGLE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_LINEARREG_INTERCEPT( np.ndarray real not None , int timeperiod=-2**31 ): - """ LINEARREG_INTERCEPT(real[, timeperiod=?]) - - Linear Regression Intercept (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_LINEARREG_INTERCEPT( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_LINEARREG_INTERCEPT", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_LINEARREG_SLOPE( np.ndarray real not None , int timeperiod=-2**31 ): - """ LINEARREG_SLOPE(real[, timeperiod=?]) - - Linear Regression Slope (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_LINEARREG_SLOPE( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_LINEARREG_SLOPE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_LN( np.ndarray real not None ): - """ LN(real) - - Vector Log Natural (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_LN( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_LN", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_LOG10( np.ndarray real not None ): - """ LOG10(real) - - Vector Log10 (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_LOG10( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_LOG10", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MA( np.ndarray real not None , int timeperiod=-2**31 , int matype=0 ): - """ MA(real[, timeperiod=?, matype=?]) - - Moving average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - matype: 0 (Simple Moving Average) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_MA( (length) - 1 , (length) - 1 , real_data , timeperiod , matype , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_MA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MACD( np.ndarray real not None , int fastperiod=-2**31 , int slowperiod=-2**31 , int signalperiod=-2**31 ): - """ MACD(real[, fastperiod=?, slowperiod=?, signalperiod=?]) - - Moving Average Convergence/Divergence (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - fastperiod: 12 - slowperiod: 26 - signalperiod: 9 - Outputs: - macd - macdsignal - macdhist - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outmacd - double outmacdsignal - double outmacdhist - real = check_array(real) - real_data = real.data - length = real.shape[0] - outmacd = NaN - outmacdsignal = NaN - outmacdhist = NaN - retCode = lib.TA_MACD( (length) - 1 , (length) - 1 , real_data , fastperiod , slowperiod , signalperiod , &outbegidx , &outnbelement , &outmacd , &outmacdsignal , &outmacdhist ) - _ta_check_success("TA_MACD", retCode) - return outmacd , outmacdsignal , outmacdhist - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MACDEXT( np.ndarray real not None , int fastperiod=-2**31 , int fastmatype=0 , int slowperiod=-2**31 , int slowmatype=0 , int signalperiod=-2**31 , int signalmatype=0 ): - """ MACDEXT(real[, fastperiod=?, fastmatype=?, slowperiod=?, slowmatype=?, signalperiod=?, signalmatype=?]) - - MACD with controllable MA type (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - fastperiod: 12 - fastmatype: 0 - slowperiod: 26 - slowmatype: 0 - signalperiod: 9 - signalmatype: 0 - Outputs: - macd - macdsignal - macdhist - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outmacd - double outmacdsignal - double outmacdhist - real = check_array(real) - real_data = real.data - length = real.shape[0] - outmacd = NaN - outmacdsignal = NaN - outmacdhist = NaN - retCode = lib.TA_MACDEXT( (length) - 1 , (length) - 1 , real_data , fastperiod , fastmatype , slowperiod , slowmatype , signalperiod , signalmatype , &outbegidx , &outnbelement , &outmacd , &outmacdsignal , &outmacdhist ) - _ta_check_success("TA_MACDEXT", retCode) - return outmacd , outmacdsignal , outmacdhist - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MACDFIX( np.ndarray real not None , int signalperiod=-2**31 ): - """ MACDFIX(real[, signalperiod=?]) - - Moving Average Convergence/Divergence Fix 12/26 (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - signalperiod: 9 - Outputs: - macd - macdsignal - macdhist - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outmacd - double outmacdsignal - double outmacdhist - real = check_array(real) - real_data = real.data - length = real.shape[0] - outmacd = NaN - outmacdsignal = NaN - outmacdhist = NaN - retCode = lib.TA_MACDFIX( (length) - 1 , (length) - 1 , real_data , signalperiod , &outbegidx , &outnbelement , &outmacd , &outmacdsignal , &outmacdhist ) - _ta_check_success("TA_MACDFIX", retCode) - return outmacd , outmacdsignal , outmacdhist - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MAMA( np.ndarray real not None , double fastlimit=-4e37 , double slowlimit=-4e37 ): - """ MAMA(real[, fastlimit=?, slowlimit=?]) - - MESA Adaptive Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - fastlimit: 0.5 - slowlimit: 0.05 - Outputs: - mama - fama - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outmama - double outfama - real = check_array(real) - real_data = real.data - length = real.shape[0] - outmama = NaN - outfama = NaN - retCode = lib.TA_MAMA( (length) - 1 , (length) - 1 , real_data , fastlimit , slowlimit , &outbegidx , &outnbelement , &outmama , &outfama ) - _ta_check_success("TA_MAMA", retCode) - return outmama , outfama - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MAVP( np.ndarray real not None , np.ndarray periods not None , int minperiod=-2**31 , int maxperiod=-2**31 , int matype=0 ): - """ MAVP(real, periods[, minperiod=?, maxperiod=?, matype=?]) - - Moving average with variable period (Overlap Studies) - - Inputs: - real: (any ndarray) - periods: (any ndarray) - Parameters: - minperiod: 2 - maxperiod: 30 - matype: 0 (Simple Moving Average) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - double* periods_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - periods = check_array(periods) - periods_data = periods.data - length = check_length2(real, periods) - outreal = NaN - retCode = lib.TA_MAVP( (length) - 1 , (length) - 1 , real_data , periods_data , minperiod , maxperiod , matype , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_MAVP", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MAX( np.ndarray real not None , int timeperiod=-2**31 ): - """ MAX(real[, timeperiod=?]) - - Highest value over a specified period (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_MAX( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_MAX", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MAXINDEX( np.ndarray real not None , int timeperiod=-2**31 ): - """ MAXINDEX(real[, timeperiod=?]) - - Index of highest value over a specified period (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - int outinteger - real = check_array(real) - real_data = real.data - length = real.shape[0] - outinteger = 0 - retCode = lib.TA_MAXINDEX( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_MAXINDEX", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MEDPRICE( np.ndarray high not None , np.ndarray low not None ): - """ MEDPRICE(high, low) - - Median Price (Price Transform) - - Inputs: - prices: ['high', 'low'] - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - length = check_length2(high, low) - outreal = NaN - retCode = lib.TA_MEDPRICE( (length) - 1 , (length) - 1 , high_data , low_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_MEDPRICE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MFI( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , np.ndarray volume not None , int timeperiod=-2**31 ): - """ MFI(high, low, close, volume[, timeperiod=?]) - - Money Flow Index (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close', 'volume'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - double* volume_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - volume = check_array(volume) - volume_data = volume.data - length = check_length4(high, low, close, volume) - outreal = NaN - retCode = lib.TA_MFI( (length) - 1 , (length) - 1 , high_data , low_data , close_data , volume_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_MFI", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MIDPOINT( np.ndarray real not None , int timeperiod=-2**31 ): - """ MIDPOINT(real[, timeperiod=?]) - - MidPoint over period (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_MIDPOINT( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_MIDPOINT", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MIDPRICE( np.ndarray high not None , np.ndarray low not None , int timeperiod=-2**31 ): - """ MIDPRICE(high, low[, timeperiod=?]) - - Midpoint Price over period (Overlap Studies) - - Inputs: - prices: ['high', 'low'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - length = check_length2(high, low) - outreal = NaN - retCode = lib.TA_MIDPRICE( (length) - 1 , (length) - 1 , high_data , low_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_MIDPRICE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MIN( np.ndarray real not None , int timeperiod=-2**31 ): - """ MIN(real[, timeperiod=?]) - - Lowest value over a specified period (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_MIN( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_MIN", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MININDEX( np.ndarray real not None , int timeperiod=-2**31 ): - """ MININDEX(real[, timeperiod=?]) - - Index of lowest value over a specified period (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - integer (values are -100, 0 or 100) - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - int outinteger - real = check_array(real) - real_data = real.data - length = real.shape[0] - outinteger = 0 - retCode = lib.TA_MININDEX( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outinteger ) - _ta_check_success("TA_MININDEX", retCode) - return outinteger - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MINMAX( np.ndarray real not None , int timeperiod=-2**31 ): - """ MINMAX(real[, timeperiod=?]) - - Lowest and highest values over a specified period (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - min - max - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outmin - double outmax - real = check_array(real) - real_data = real.data - length = real.shape[0] - outmin = NaN - outmax = NaN - retCode = lib.TA_MINMAX( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outmin , &outmax ) - _ta_check_success("TA_MINMAX", retCode) - return outmin , outmax - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MINMAXINDEX( np.ndarray real not None , int timeperiod=-2**31 ): - """ MINMAXINDEX(real[, timeperiod=?]) - - Indexes of lowest and highest values over a specified period (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - minidx - maxidx - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - int outminidx - int outmaxidx - real = check_array(real) - real_data = real.data - length = real.shape[0] - outminidx = 0 - outmaxidx = 0 - retCode = lib.TA_MINMAXINDEX( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outminidx , &outmaxidx ) - _ta_check_success("TA_MINMAXINDEX", retCode) - return outminidx , outmaxidx - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MINUS_DI( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ MINUS_DI(high, low, close[, timeperiod=?]) - - Minus Directional Indicator (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outreal = NaN - retCode = lib.TA_MINUS_DI( (length) - 1 , (length) - 1 , high_data , low_data , close_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_MINUS_DI", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MINUS_DM( np.ndarray high not None , np.ndarray low not None , int timeperiod=-2**31 ): - """ MINUS_DM(high, low[, timeperiod=?]) - - Minus Directional Movement (Momentum Indicators) - - Inputs: - prices: ['high', 'low'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - length = check_length2(high, low) - outreal = NaN - retCode = lib.TA_MINUS_DM( (length) - 1 , (length) - 1 , high_data , low_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_MINUS_DM", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MOM( np.ndarray real not None , int timeperiod=-2**31 ): - """ MOM(real[, timeperiod=?]) - - Momentum (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 10 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_MOM( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_MOM", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_MULT( np.ndarray real0 not None , np.ndarray real1 not None ): - """ MULT(real0, real1) - - Vector Arithmetic Mult (Math Operators) - - Inputs: - real0: (any ndarray) - real1: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real0_data - double* real1_data - int outbegidx - int outnbelement - double outreal - real0 = check_array(real0) - real0_data = real0.data - real1 = check_array(real1) - real1_data = real1.data - length = check_length2(real0, real1) - outreal = NaN - retCode = lib.TA_MULT( (length) - 1 , (length) - 1 , real0_data , real1_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_MULT", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_NATR( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ NATR(high, low, close[, timeperiod=?]) - - Normalized Average True Range (Volatility Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outreal = NaN - retCode = lib.TA_NATR( (length) - 1 , (length) - 1 , high_data , low_data , close_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_NATR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_OBV( np.ndarray real not None , np.ndarray volume not None ): - """ OBV(real, volume) - - On Balance Volume (Volume Indicators) - - Inputs: - real: (any ndarray) - prices: ['volume'] - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - double* volume_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - volume = check_array(volume) - volume_data = volume.data - length = check_length2(real, volume) - outreal = NaN - retCode = lib.TA_OBV( (length) - 1 , (length) - 1 , real_data , volume_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_OBV", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_PLUS_DI( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ PLUS_DI(high, low, close[, timeperiod=?]) - - Plus Directional Indicator (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outreal = NaN - retCode = lib.TA_PLUS_DI( (length) - 1 , (length) - 1 , high_data , low_data , close_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_PLUS_DI", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_PLUS_DM( np.ndarray high not None , np.ndarray low not None , int timeperiod=-2**31 ): - """ PLUS_DM(high, low[, timeperiod=?]) - - Plus Directional Movement (Momentum Indicators) - - Inputs: - prices: ['high', 'low'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - length = check_length2(high, low) - outreal = NaN - retCode = lib.TA_PLUS_DM( (length) - 1 , (length) - 1 , high_data , low_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_PLUS_DM", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_PPO( np.ndarray real not None , int fastperiod=-2**31 , int slowperiod=-2**31 , int matype=0 ): - """ PPO(real[, fastperiod=?, slowperiod=?, matype=?]) - - Percentage Price Oscillator (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - fastperiod: 12 - slowperiod: 26 - matype: 0 (Simple Moving Average) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_PPO( (length) - 1 , (length) - 1 , real_data , fastperiod , slowperiod , matype , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_PPO", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ROC( np.ndarray real not None , int timeperiod=-2**31 ): - """ ROC(real[, timeperiod=?]) - - Rate of change : ((real/prevPrice)-1)*100 (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 10 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_ROC( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_ROC", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ROCP( np.ndarray real not None , int timeperiod=-2**31 ): - """ ROCP(real[, timeperiod=?]) - - Rate of change Percentage: (real-prevPrice)/prevPrice (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 10 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_ROCP( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_ROCP", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ROCR( np.ndarray real not None , int timeperiod=-2**31 ): - """ ROCR(real[, timeperiod=?]) - - Rate of change ratio: (real/prevPrice) (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 10 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_ROCR( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_ROCR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ROCR100( np.ndarray real not None , int timeperiod=-2**31 ): - """ ROCR100(real[, timeperiod=?]) - - Rate of change ratio 100 scale: (real/prevPrice)*100 (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 10 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_ROCR100( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_ROCR100", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_RSI( np.ndarray real not None , int timeperiod=-2**31 ): - """ RSI(real[, timeperiod=?]) - - Relative Strength Index (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_RSI( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_RSI", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_SAR( np.ndarray high not None , np.ndarray low not None , double acceleration=0.02 , double maximum=0.2 ): - """ SAR(high, low[, acceleration=?, maximum=?]) - - Parabolic SAR (Overlap Studies) - - Inputs: - prices: ['high', 'low'] - Parameters: - acceleration: 0.02 - maximum: 0.2 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - length = check_length2(high, low) - outreal = NaN - retCode = lib.TA_SAR( (length) - 1 , (length) - 1 , high_data , low_data , acceleration , maximum , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_SAR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_SAREXT( np.ndarray high not None , np.ndarray low not None , double startvalue=-4e37 , double offsetonreverse=-4e37 , double accelerationinitlong=-4e37 , double accelerationlong=-4e37 , double accelerationmaxlong=-4e37 , double accelerationinitshort=-4e37 , double accelerationshort=-4e37 , double accelerationmaxshort=-4e37 ): - """ SAREXT(high, low[, startvalue=?, offsetonreverse=?, accelerationinitlong=?, accelerationlong=?, accelerationmaxlong=?, accelerationinitshort=?, accelerationshort=?, accelerationmaxshort=?]) - - Parabolic SAR - Extended (Overlap Studies) - - Inputs: - prices: ['high', 'low'] - Parameters: - startvalue: 0.0 - offsetonreverse: 0.0 - accelerationinitlong: 0.02 - accelerationlong: 0.02 - accelerationmaxlong: 0.2 - accelerationinitshort: 0.02 - accelerationshort: 0.02 - accelerationmaxshort: 0.2 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - length = check_length2(high, low) - outreal = NaN - retCode = lib.TA_SAREXT( (length) - 1 , (length) - 1 , high_data , low_data , startvalue , offsetonreverse , accelerationinitlong , accelerationlong , accelerationmaxlong , accelerationinitshort , accelerationshort , accelerationmaxshort , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_SAREXT", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_SIN( np.ndarray real not None ): - """ SIN(real) - - Vector Trigonometric Sin (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_SIN( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_SIN", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_SINH( np.ndarray real not None ): - """ SINH(real) - - Vector Trigonometric Sinh (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_SINH( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_SINH", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_SMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ SMA(real[, timeperiod=?]) - - Simple Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_SMA( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_SMA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_SQRT( np.ndarray real not None ): - """ SQRT(real) - - Vector Square Root (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_SQRT( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_SQRT", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_STDDEV( np.ndarray real not None , int timeperiod=-2**31 , double nbdev=-4e37 ): - """ STDDEV(real[, timeperiod=?, nbdev=?]) - - Standard Deviation (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 5 - nbdev: 1.0 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_STDDEV( (length) - 1 , (length) - 1 , real_data , timeperiod , nbdev , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_STDDEV", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_STOCH( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int fastk_period=-2**31 , int slowk_period=-2**31 , int slowk_matype=0 , int slowd_period=-2**31 , int slowd_matype=0 ): - """ STOCH(high, low, close[, fastk_period=?, slowk_period=?, slowk_matype=?, slowd_period=?, slowd_matype=?]) - - Stochastic (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - fastk_period: 5 - slowk_period: 3 - slowk_matype: 0 - slowd_period: 3 - slowd_matype: 0 - Outputs: - slowk - slowd - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outslowk - double outslowd - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outslowk = NaN - outslowd = NaN - retCode = lib.TA_STOCH( (length) - 1 , (length) - 1 , high_data , low_data , close_data , fastk_period , slowk_period , slowk_matype , slowd_period , slowd_matype , &outbegidx , &outnbelement , &outslowk , &outslowd ) - _ta_check_success("TA_STOCH", retCode) - return outslowk , outslowd - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_STOCHF( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int fastk_period=-2**31 , int fastd_period=-2**31 , int fastd_matype=0 ): - """ STOCHF(high, low, close[, fastk_period=?, fastd_period=?, fastd_matype=?]) - - Stochastic Fast (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - fastk_period: 5 - fastd_period: 3 - fastd_matype: 0 - Outputs: - fastk - fastd - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outfastk - double outfastd - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outfastk = NaN - outfastd = NaN - retCode = lib.TA_STOCHF( (length) - 1 , (length) - 1 , high_data , low_data , close_data , fastk_period , fastd_period , fastd_matype , &outbegidx , &outnbelement , &outfastk , &outfastd ) - _ta_check_success("TA_STOCHF", retCode) - return outfastk , outfastd - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_STOCHRSI( np.ndarray real not None , int timeperiod=-2**31 , int fastk_period=-2**31 , int fastd_period=-2**31 , int fastd_matype=0 ): - """ STOCHRSI(real[, timeperiod=?, fastk_period=?, fastd_period=?, fastd_matype=?]) - - Stochastic Relative Strength Index (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - fastk_period: 5 - fastd_period: 3 - fastd_matype: 0 - Outputs: - fastk - fastd - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outfastk - double outfastd - real = check_array(real) - real_data = real.data - length = real.shape[0] - outfastk = NaN - outfastd = NaN - retCode = lib.TA_STOCHRSI( (length) - 1 , (length) - 1 , real_data , timeperiod , fastk_period , fastd_period , fastd_matype , &outbegidx , &outnbelement , &outfastk , &outfastd ) - _ta_check_success("TA_STOCHRSI", retCode) - return outfastk , outfastd - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_SUB( np.ndarray real0 not None , np.ndarray real1 not None ): - """ SUB(real0, real1) - - Vector Arithmetic Subtraction (Math Operators) - - Inputs: - real0: (any ndarray) - real1: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real0_data - double* real1_data - int outbegidx - int outnbelement - double outreal - real0 = check_array(real0) - real0_data = real0.data - real1 = check_array(real1) - real1_data = real1.data - length = check_length2(real0, real1) - outreal = NaN - retCode = lib.TA_SUB( (length) - 1 , (length) - 1 , real0_data , real1_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_SUB", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_SUM( np.ndarray real not None , int timeperiod=-2**31 ): - """ SUM(real[, timeperiod=?]) - - Summation (Math Operators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_SUM( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_SUM", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_T3( np.ndarray real not None , int timeperiod=-2**31 , double vfactor=-4e37 ): - """ T3(real[, timeperiod=?, vfactor=?]) - - Triple Exponential Moving Average (T3) (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 5 - vfactor: 0.7 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_T3( (length) - 1 , (length) - 1 , real_data , timeperiod , vfactor , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_T3", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_TAN( np.ndarray real not None ): - """ TAN(real) - - Vector Trigonometric Tan (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_TAN( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_TAN", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_TANH( np.ndarray real not None ): - """ TANH(real) - - Vector Trigonometric Tanh (Math Transform) - - Inputs: - real: (any ndarray) - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_TANH( (length) - 1 , (length) - 1 , real_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_TANH", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_TEMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ TEMA(real[, timeperiod=?]) - - Triple Exponential Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_TEMA( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_TEMA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_TRANGE( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ TRANGE(high, low, close) - - True Range (Volatility Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outreal = NaN - retCode = lib.TA_TRANGE( (length) - 1 , (length) - 1 , high_data , low_data , close_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_TRANGE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_TRIMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ TRIMA(real[, timeperiod=?]) - - Triangular Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_TRIMA( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_TRIMA", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_TRIX( np.ndarray real not None , int timeperiod=-2**31 ): - """ TRIX(real[, timeperiod=?]) - - 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA (Momentum Indicators) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_TRIX( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_TRIX", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_TSF( np.ndarray real not None , int timeperiod=-2**31 ): - """ TSF(real[, timeperiod=?]) - - Time Series Forecast (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_TSF( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_TSF", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_TYPPRICE( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ TYPPRICE(high, low, close) - - Typical Price (Price Transform) - - Inputs: - prices: ['high', 'low', 'close'] - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outreal = NaN - retCode = lib.TA_TYPPRICE( (length) - 1 , (length) - 1 , high_data , low_data , close_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_TYPPRICE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_ULTOSC( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod1=-2**31 , int timeperiod2=-2**31 , int timeperiod3=-2**31 ): - """ ULTOSC(high, low, close[, timeperiod1=?, timeperiod2=?, timeperiod3=?]) - - Ultimate Oscillator (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod1: 7 - timeperiod2: 14 - timeperiod3: 28 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outreal = NaN - retCode = lib.TA_ULTOSC( (length) - 1 , (length) - 1 , high_data , low_data , close_data , timeperiod1 , timeperiod2 , timeperiod3 , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_ULTOSC", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_VAR( np.ndarray real not None , int timeperiod=-2**31 , double nbdev=-4e37 ): - """ VAR(real[, timeperiod=?, nbdev=?]) - - Variance (Statistic Functions) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 5 - nbdev: 1.0 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_VAR( (length) - 1 , (length) - 1 , real_data , timeperiod , nbdev , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_VAR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_WCLPRICE( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None ): - """ WCLPRICE(high, low, close) - - Weighted Close Price (Price Transform) - - Inputs: - prices: ['high', 'low', 'close'] - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outreal = NaN - retCode = lib.TA_WCLPRICE( (length) - 1 , (length) - 1 , high_data , low_data , close_data , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_WCLPRICE", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_WILLR( np.ndarray high not None , np.ndarray low not None , np.ndarray close not None , int timeperiod=-2**31 ): - """ WILLR(high, low, close[, timeperiod=?]) - - Williams' %R (Momentum Indicators) - - Inputs: - prices: ['high', 'low', 'close'] - Parameters: - timeperiod: 14 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* high_data - double* low_data - double* close_data - int outbegidx - int outnbelement - double outreal - high = check_array(high) - high_data = high.data - low = check_array(low) - low_data = low.data - close = check_array(close) - close_data = close.data - length = check_length3(high, low, close) - outreal = NaN - retCode = lib.TA_WILLR( (length) - 1 , (length) - 1 , high_data , low_data , close_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_WILLR", retCode) - return outreal - -@wraparound(False) # turn off relative indexing from end of lists -@boundscheck(False) # turn off bounds-checking for entire function -def stream_WMA( np.ndarray real not None , int timeperiod=-2**31 ): - """ WMA(real[, timeperiod=?]) - - Weighted Moving Average (Overlap Studies) - - Inputs: - real: (any ndarray) - Parameters: - timeperiod: 30 - Outputs: - real - """ - cdef: - np.npy_intp length - TA_RetCode retCode - double* real_data - int outbegidx - int outnbelement - double outreal - real = check_array(real) - real_data = real.data - length = real.shape[0] - outreal = NaN - retCode = lib.TA_WMA( (length) - 1 , (length) - 1 , real_data , timeperiod , &outbegidx , &outnbelement , &outreal ) - _ta_check_success("TA_WMA", retCode) - return outreal - diff --git a/talib/_ta_lib.c b/talib/_ta_lib.c deleted file mode 100644 index aa82dd14f..000000000 --- a/talib/_ta_lib.c +++ /dev/null @@ -1,99180 +0,0 @@ -/* Generated by Cython 3.1.2 */ - -#ifndef PY_SSIZE_T_CLEAN -#define PY_SSIZE_T_CLEAN -#endif /* PY_SSIZE_T_CLEAN */ -/* InitLimitedAPI */ -#if defined(Py_LIMITED_API) && !defined(CYTHON_LIMITED_API) - #define CYTHON_LIMITED_API 1 -#endif - -#include "Python.h" -#ifndef Py_PYTHON_H - #error Python headers needed to compile C extensions, please install development version of Python. -#elif PY_VERSION_HEX < 0x03080000 - #error Cython requires Python 3.8+. -#else -#define __PYX_ABI_VERSION "3_1_2" -#define CYTHON_HEX_VERSION 0x030102F0 -#define CYTHON_FUTURE_DIVISION 0 -/* CModulePreamble */ -#include -#ifndef offsetof - #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) -#endif -#if !defined(_WIN32) && !defined(WIN32) && !defined(MS_WINDOWS) - #ifndef __stdcall - #define __stdcall - #endif - #ifndef __cdecl - #define __cdecl - #endif - #ifndef __fastcall - #define __fastcall - #endif -#endif -#ifndef DL_IMPORT - #define DL_IMPORT(t) t -#endif -#ifndef DL_EXPORT - #define DL_EXPORT(t) t -#endif -#define __PYX_COMMA , -#ifndef HAVE_LONG_LONG - #define HAVE_LONG_LONG -#endif -#ifndef PY_LONG_LONG - #define PY_LONG_LONG LONG_LONG -#endif -#ifndef Py_HUGE_VAL - #define Py_HUGE_VAL HUGE_VAL -#endif -#define __PYX_LIMITED_VERSION_HEX PY_VERSION_HEX -#if defined(GRAALVM_PYTHON) - /* For very preliminary testing purposes. Most variables are set the same as PyPy. - The existence of this section does not imply that anything works or is even tested */ - #define CYTHON_COMPILING_IN_PYPY 0 - #define CYTHON_COMPILING_IN_CPYTHON 0 - #define CYTHON_COMPILING_IN_LIMITED_API 0 - #define CYTHON_COMPILING_IN_GRAAL 1 - #define CYTHON_COMPILING_IN_CPYTHON_FREETHREADING 0 - #undef CYTHON_USE_TYPE_SLOTS - #define CYTHON_USE_TYPE_SLOTS 0 - #undef CYTHON_USE_TYPE_SPECS - #define CYTHON_USE_TYPE_SPECS 0 - #undef CYTHON_USE_PYTYPE_LOOKUP - #define CYTHON_USE_PYTYPE_LOOKUP 0 - #undef CYTHON_USE_PYLIST_INTERNALS - #define CYTHON_USE_PYLIST_INTERNALS 0 - #undef CYTHON_USE_UNICODE_INTERNALS - #define CYTHON_USE_UNICODE_INTERNALS 0 - #undef CYTHON_USE_UNICODE_WRITER - #define CYTHON_USE_UNICODE_WRITER 0 - #undef CYTHON_USE_PYLONG_INTERNALS - #define CYTHON_USE_PYLONG_INTERNALS 0 - #undef CYTHON_AVOID_BORROWED_REFS - #define CYTHON_AVOID_BORROWED_REFS 1 - #undef CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS - #define CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS 1 - #undef CYTHON_ASSUME_SAFE_MACROS - #define CYTHON_ASSUME_SAFE_MACROS 0 - #undef CYTHON_ASSUME_SAFE_SIZE - #define CYTHON_ASSUME_SAFE_SIZE 0 - #undef CYTHON_UNPACK_METHODS - #define CYTHON_UNPACK_METHODS 0 - #undef CYTHON_FAST_THREAD_STATE - #define CYTHON_FAST_THREAD_STATE 0 - #undef CYTHON_FAST_GIL - #define CYTHON_FAST_GIL 0 - #undef CYTHON_METH_FASTCALL - #define CYTHON_METH_FASTCALL 0 - #undef CYTHON_FAST_PYCALL - #define CYTHON_FAST_PYCALL 0 - #ifndef CYTHON_PEP487_INIT_SUBCLASS - #define CYTHON_PEP487_INIT_SUBCLASS 1 - #endif - #undef CYTHON_PEP489_MULTI_PHASE_INIT - #define CYTHON_PEP489_MULTI_PHASE_INIT 1 - #undef CYTHON_USE_MODULE_STATE - #define CYTHON_USE_MODULE_STATE 0 - #undef CYTHON_USE_SYS_MONITORING - #define CYTHON_USE_SYS_MONITORING 0 - #undef CYTHON_USE_TP_FINALIZE - #define CYTHON_USE_TP_FINALIZE 0 - #undef CYTHON_USE_AM_SEND - #define CYTHON_USE_AM_SEND 0 - #undef CYTHON_USE_DICT_VERSIONS - #define CYTHON_USE_DICT_VERSIONS 0 - #undef CYTHON_USE_EXC_INFO_STACK - #define CYTHON_USE_EXC_INFO_STACK 1 - #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC - #define CYTHON_UPDATE_DESCRIPTOR_DOC 0 - #endif - #undef CYTHON_USE_FREELISTS - #define CYTHON_USE_FREELISTS 0 -#elif defined(PYPY_VERSION) - #define CYTHON_COMPILING_IN_PYPY 1 - #define CYTHON_COMPILING_IN_CPYTHON 0 - #define CYTHON_COMPILING_IN_LIMITED_API 0 - #define CYTHON_COMPILING_IN_GRAAL 0 - #define CYTHON_COMPILING_IN_CPYTHON_FREETHREADING 0 - #undef CYTHON_USE_TYPE_SLOTS - #define CYTHON_USE_TYPE_SLOTS 1 - #ifndef CYTHON_USE_TYPE_SPECS - #define CYTHON_USE_TYPE_SPECS 0 - #endif - #undef CYTHON_USE_PYTYPE_LOOKUP - #define CYTHON_USE_PYTYPE_LOOKUP 0 - #undef CYTHON_USE_PYLIST_INTERNALS - #define CYTHON_USE_PYLIST_INTERNALS 0 - #undef CYTHON_USE_UNICODE_INTERNALS - #define CYTHON_USE_UNICODE_INTERNALS 0 - #undef CYTHON_USE_UNICODE_WRITER - #define CYTHON_USE_UNICODE_WRITER 0 - #undef CYTHON_USE_PYLONG_INTERNALS - #define CYTHON_USE_PYLONG_INTERNALS 0 - #undef CYTHON_AVOID_BORROWED_REFS - #define CYTHON_AVOID_BORROWED_REFS 1 - #undef CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS - #define CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS 1 - #undef CYTHON_ASSUME_SAFE_MACROS - #define CYTHON_ASSUME_SAFE_MACROS 0 - #ifndef CYTHON_ASSUME_SAFE_SIZE - #define CYTHON_ASSUME_SAFE_SIZE 1 - #endif - #undef CYTHON_UNPACK_METHODS - #define CYTHON_UNPACK_METHODS 0 - #undef CYTHON_FAST_THREAD_STATE - #define CYTHON_FAST_THREAD_STATE 0 - #undef CYTHON_FAST_GIL - #define CYTHON_FAST_GIL 0 - #undef CYTHON_METH_FASTCALL - #define CYTHON_METH_FASTCALL 0 - #undef CYTHON_FAST_PYCALL - #define CYTHON_FAST_PYCALL 0 - #ifndef CYTHON_PEP487_INIT_SUBCLASS - #define CYTHON_PEP487_INIT_SUBCLASS 1 - #endif - #if PY_VERSION_HEX < 0x03090000 - #undef CYTHON_PEP489_MULTI_PHASE_INIT - #define CYTHON_PEP489_MULTI_PHASE_INIT 0 - #elif !defined(CYTHON_PEP489_MULTI_PHASE_INIT) - #define CYTHON_PEP489_MULTI_PHASE_INIT 1 - #endif - #undef CYTHON_USE_MODULE_STATE - #define CYTHON_USE_MODULE_STATE 0 - #undef CYTHON_USE_SYS_MONITORING - #define CYTHON_USE_SYS_MONITORING 0 - #ifndef CYTHON_USE_TP_FINALIZE - #define CYTHON_USE_TP_FINALIZE (PYPY_VERSION_NUM >= 0x07030C00) - #endif - #undef CYTHON_USE_AM_SEND - #define CYTHON_USE_AM_SEND 0 - #undef CYTHON_USE_DICT_VERSIONS - #define CYTHON_USE_DICT_VERSIONS 0 - #undef CYTHON_USE_EXC_INFO_STACK - #define CYTHON_USE_EXC_INFO_STACK 0 - #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC - #define CYTHON_UPDATE_DESCRIPTOR_DOC (PYPY_VERSION_NUM >= 0x07031100) - #endif - #undef CYTHON_USE_FREELISTS - #define CYTHON_USE_FREELISTS 0 -#elif defined(CYTHON_LIMITED_API) - #ifdef Py_LIMITED_API - #undef __PYX_LIMITED_VERSION_HEX - #define __PYX_LIMITED_VERSION_HEX Py_LIMITED_API - #endif - #define CYTHON_COMPILING_IN_PYPY 0 - #define CYTHON_COMPILING_IN_CPYTHON 0 - #define CYTHON_COMPILING_IN_LIMITED_API 1 - #define CYTHON_COMPILING_IN_GRAAL 0 - #define CYTHON_COMPILING_IN_CPYTHON_FREETHREADING 0 - #undef CYTHON_CLINE_IN_TRACEBACK - #define CYTHON_CLINE_IN_TRACEBACK 0 - #undef CYTHON_USE_TYPE_SLOTS - #define CYTHON_USE_TYPE_SLOTS 0 - #undef CYTHON_USE_TYPE_SPECS - #define CYTHON_USE_TYPE_SPECS 1 - #undef CYTHON_USE_PYTYPE_LOOKUP - #define CYTHON_USE_PYTYPE_LOOKUP 0 - #undef CYTHON_USE_PYLIST_INTERNALS - #define CYTHON_USE_PYLIST_INTERNALS 0 - #undef CYTHON_USE_UNICODE_INTERNALS - #define CYTHON_USE_UNICODE_INTERNALS 0 - #ifndef CYTHON_USE_UNICODE_WRITER - #define CYTHON_USE_UNICODE_WRITER 0 - #endif - #undef CYTHON_USE_PYLONG_INTERNALS - #define CYTHON_USE_PYLONG_INTERNALS 0 - #ifndef CYTHON_AVOID_BORROWED_REFS - #define CYTHON_AVOID_BORROWED_REFS 0 - #endif - #ifndef CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS - #define CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS 0 - #endif - #undef CYTHON_ASSUME_SAFE_MACROS - #define CYTHON_ASSUME_SAFE_MACROS 0 - #undef CYTHON_ASSUME_SAFE_SIZE - #define CYTHON_ASSUME_SAFE_SIZE 0 - #undef CYTHON_UNPACK_METHODS - #define CYTHON_UNPACK_METHODS 0 - #undef CYTHON_FAST_THREAD_STATE - #define CYTHON_FAST_THREAD_STATE 0 - #undef CYTHON_FAST_GIL - #define CYTHON_FAST_GIL 0 - #undef CYTHON_METH_FASTCALL - #define CYTHON_METH_FASTCALL (__PYX_LIMITED_VERSION_HEX >= 0x030C0000) - #undef CYTHON_FAST_PYCALL - #define CYTHON_FAST_PYCALL 0 - #ifndef CYTHON_PEP487_INIT_SUBCLASS - #define CYTHON_PEP487_INIT_SUBCLASS 1 - #endif - #ifndef CYTHON_PEP489_MULTI_PHASE_INIT - #define CYTHON_PEP489_MULTI_PHASE_INIT 1 - #endif - #ifndef CYTHON_USE_MODULE_STATE - #define CYTHON_USE_MODULE_STATE 0 - #endif - #undef CYTHON_USE_SYS_MONITORING - #define CYTHON_USE_SYS_MONITORING 0 - #ifndef CYTHON_USE_TP_FINALIZE - #define CYTHON_USE_TP_FINALIZE 0 - #endif - #ifndef CYTHON_USE_AM_SEND - #define CYTHON_USE_AM_SEND (__PYX_LIMITED_VERSION_HEX >= 0x030A0000) - #endif - #undef CYTHON_USE_DICT_VERSIONS - #define CYTHON_USE_DICT_VERSIONS 0 - #undef CYTHON_USE_EXC_INFO_STACK - #define CYTHON_USE_EXC_INFO_STACK 0 - #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC - #define CYTHON_UPDATE_DESCRIPTOR_DOC 0 - #endif - #undef CYTHON_USE_FREELISTS - #define CYTHON_USE_FREELISTS 0 -#else - #define CYTHON_COMPILING_IN_PYPY 0 - #define CYTHON_COMPILING_IN_CPYTHON 1 - #define CYTHON_COMPILING_IN_LIMITED_API 0 - #define CYTHON_COMPILING_IN_GRAAL 0 - #ifdef Py_GIL_DISABLED - #define CYTHON_COMPILING_IN_CPYTHON_FREETHREADING 1 - #else - #define CYTHON_COMPILING_IN_CPYTHON_FREETHREADING 0 - #endif - #if PY_VERSION_HEX < 0x030A0000 - #undef CYTHON_USE_TYPE_SLOTS - #define CYTHON_USE_TYPE_SLOTS 1 - #elif !defined(CYTHON_USE_TYPE_SLOTS) - #define CYTHON_USE_TYPE_SLOTS 1 - #endif - #ifndef CYTHON_USE_TYPE_SPECS - #define CYTHON_USE_TYPE_SPECS 0 - #endif - #ifndef CYTHON_USE_PYTYPE_LOOKUP - #define CYTHON_USE_PYTYPE_LOOKUP 1 - #endif - #ifndef CYTHON_USE_PYLONG_INTERNALS - #define CYTHON_USE_PYLONG_INTERNALS 1 - #endif - #if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING - #undef CYTHON_USE_PYLIST_INTERNALS - #define CYTHON_USE_PYLIST_INTERNALS 0 - #elif !defined(CYTHON_USE_PYLIST_INTERNALS) - #define CYTHON_USE_PYLIST_INTERNALS 1 - #endif - #ifndef CYTHON_USE_UNICODE_INTERNALS - #define CYTHON_USE_UNICODE_INTERNALS 1 - #endif - #if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING || PY_VERSION_HEX >= 0x030B00A2 - #undef CYTHON_USE_UNICODE_WRITER - #define CYTHON_USE_UNICODE_WRITER 0 - #elif !defined(CYTHON_USE_UNICODE_WRITER) - #define CYTHON_USE_UNICODE_WRITER 1 - #endif - #ifndef CYTHON_AVOID_BORROWED_REFS - #define CYTHON_AVOID_BORROWED_REFS 0 - #endif - #if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING - #undef CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS - #define CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS 1 - #elif !defined(CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS) - #define CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS 0 - #endif - #ifndef CYTHON_ASSUME_SAFE_MACROS - #define CYTHON_ASSUME_SAFE_MACROS 1 - #endif - #ifndef CYTHON_ASSUME_SAFE_SIZE - #define CYTHON_ASSUME_SAFE_SIZE 1 - #endif - #ifndef CYTHON_UNPACK_METHODS - #define CYTHON_UNPACK_METHODS 1 - #endif - #ifndef CYTHON_FAST_THREAD_STATE - #define CYTHON_FAST_THREAD_STATE 1 - #endif - #if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING - #undef CYTHON_FAST_GIL - #define CYTHON_FAST_GIL 0 - #elif !defined(CYTHON_FAST_GIL) - #define CYTHON_FAST_GIL (PY_VERSION_HEX < 0x030C00A6) - #endif - #ifndef CYTHON_METH_FASTCALL - #define CYTHON_METH_FASTCALL 1 - #endif - #ifndef CYTHON_FAST_PYCALL - #define CYTHON_FAST_PYCALL 1 - #endif - #ifndef CYTHON_PEP487_INIT_SUBCLASS - #define CYTHON_PEP487_INIT_SUBCLASS 1 - #endif - #ifndef CYTHON_PEP489_MULTI_PHASE_INIT - #define CYTHON_PEP489_MULTI_PHASE_INIT 1 - #endif - #ifndef CYTHON_USE_MODULE_STATE - #define CYTHON_USE_MODULE_STATE 0 - #endif - #ifndef CYTHON_USE_SYS_MONITORING - #define CYTHON_USE_SYS_MONITORING (PY_VERSION_HEX >= 0x030d00B1) - #endif - #ifndef CYTHON_USE_TP_FINALIZE - #define CYTHON_USE_TP_FINALIZE 1 - #endif - #ifndef CYTHON_USE_AM_SEND - #define CYTHON_USE_AM_SEND 1 - #endif - #if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING - #undef CYTHON_USE_DICT_VERSIONS - #define CYTHON_USE_DICT_VERSIONS 0 - #elif !defined(CYTHON_USE_DICT_VERSIONS) - #define CYTHON_USE_DICT_VERSIONS (PY_VERSION_HEX < 0x030C00A5 && !CYTHON_USE_MODULE_STATE) - #endif - #ifndef CYTHON_USE_EXC_INFO_STACK - #define CYTHON_USE_EXC_INFO_STACK 1 - #endif - #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC - #define CYTHON_UPDATE_DESCRIPTOR_DOC 1 - 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(sdigit) 0 : ((Py_SIZE(x) < 0) ? -(sdigit)__Pyx_PyLong_Digits(x)[0] : (sdigit)__Pyx_PyLong_Digits(x)[0])) - typedef sdigit __Pyx_compact_pylong; - typedef digit __Pyx_compact_upylong; - #endif - #if PY_VERSION_HEX >= 0x030C00A5 - #define __Pyx_PyLong_Digits(x) (((PyLongObject*)x)->long_value.ob_digit) - #else - #define __Pyx_PyLong_Digits(x) (((PyLongObject*)x)->ob_digit) - #endif -#endif -#if __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 - #define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL) -#elif __PYX_DEFAULT_STRING_ENCODING_IS_ASCII - #define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeASCII(c_str, size, NULL) -#else - #define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL) -#endif - - -/* Test for GCC > 2.95 */ -#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) - #define likely(x) __builtin_expect(!!(x), 1) - #define unlikely(x) __builtin_expect(!!(x), 0) -#else /* !__GNUC__ or GCC < 2.95 */ - #define likely(x) (x) - #define unlikely(x) (x) -#endif /* __GNUC__ */ -/* PretendToInitialize */ -#ifdef __cplusplus -#if __cplusplus > 201103L -#include -#endif -template -static void __Pyx_pretend_to_initialize(T* ptr) { -#if __cplusplus > 201103L - if ((std::is_trivially_default_constructible::value)) -#endif - *ptr = T(); - (void)ptr; -} -#else -static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; } -#endif - - -#if !CYTHON_USE_MODULE_STATE -static PyObject *__pyx_m = NULL; -#endif -static int __pyx_lineno; -static int __pyx_clineno = 0; -static const char * const __pyx_cfilenm = __FILE__; -static const char *__pyx_filename; - -/* Header.proto */ -#if !defined(CYTHON_CCOMPLEX) - #if defined(__cplusplus) - #define CYTHON_CCOMPLEX 1 - #elif (defined(_Complex_I) && !defined(_MSC_VER)) || ((defined (__STDC_VERSION__) && __STDC_VERSION__ >= 201112L) && !defined(__STDC_NO_COMPLEX__) && !defined(_MSC_VER)) - #define CYTHON_CCOMPLEX 1 - #else - #define CYTHON_CCOMPLEX 0 - #endif -#endif -#if CYTHON_CCOMPLEX - #ifdef __cplusplus - #include - #else - #include - #endif -#endif -#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__) - #undef _Complex_I - #define _Complex_I 1.0fj -#endif - -/* #### Code section: filename_table ### */ - -static const char* const __pyx_f[] = { - "talib/_ta_lib.pyx", - "talib/_common.pxi", - "talib/_abstract.pxi", - ".venv/lib/python3.12/site-packages/numpy/__init__.cython-30.pxd", - "talib/_func.pxi", - "talib/_stream.pxi", - ".venv/lib/python3.12/site-packages/Cython/Includes/cpython/type.pxd", -}; -/* #### Code section: utility_code_proto_before_types ### */ -/* Atomics.proto */ -#include -#ifndef CYTHON_ATOMICS - #define CYTHON_ATOMICS 1 -#endif -#define __PYX_CYTHON_ATOMICS_ENABLED() CYTHON_ATOMICS -#define __PYX_GET_CYTHON_COMPILING_IN_CPYTHON_FREETHREADING() CYTHON_COMPILING_IN_CPYTHON_FREETHREADING -#define __pyx_atomic_int_type int -#define __pyx_nonatomic_int_type int -#if CYTHON_ATOMICS && (defined(__STDC_VERSION__) &&\ - (__STDC_VERSION__ >= 201112L) &&\ - !defined(__STDC_NO_ATOMICS__)) - #include -#elif CYTHON_ATOMICS && (defined(__cplusplus) && (\ - (__cplusplus >= 201103L) ||\ - (defined(_MSC_VER) && _MSC_VER >= 1700))) - #include -#endif -#if CYTHON_ATOMICS && (defined(__STDC_VERSION__) &&\ - (__STDC_VERSION__ >= 201112L) &&\ - !defined(__STDC_NO_ATOMICS__) &&\ - ATOMIC_INT_LOCK_FREE == 2) - #undef __pyx_atomic_int_type - #define __pyx_atomic_int_type atomic_int - #define __pyx_atomic_ptr_type atomic_uintptr_t - #define __pyx_nonatomic_ptr_type uintptr_t - #define __pyx_atomic_incr_relaxed(value) atomic_fetch_add_explicit(value, 1, memory_order_relaxed) - #define __pyx_atomic_incr_acq_rel(value) atomic_fetch_add_explicit(value, 1, memory_order_acq_rel) - #define __pyx_atomic_decr_acq_rel(value) atomic_fetch_sub_explicit(value, 1, memory_order_acq_rel) - #define __pyx_atomic_sub(value, arg) atomic_fetch_sub(value, arg) - #define __pyx_atomic_int_cmp_exchange(value, expected, desired) atomic_compare_exchange_strong(value, expected, desired) - #define __pyx_atomic_load(value) atomic_load(value) - #define __pyx_atomic_store(value, new_value) atomic_store(value, new_value) - #define __pyx_atomic_pointer_load_relaxed(value) atomic_load_explicit(value, memory_order_relaxed) - #define __pyx_atomic_pointer_load_acquire(value) atomic_load_explicit(value, memory_order_acquire) - #define __pyx_atomic_pointer_exchange(value, new_value) atomic_exchange(value, (__pyx_nonatomic_ptr_type)new_value) - #if defined(__PYX_DEBUG_ATOMICS) && defined(_MSC_VER) - #pragma message ("Using standard C atomics") - #elif defined(__PYX_DEBUG_ATOMICS) - #warning "Using standard C atomics" - #endif -#elif CYTHON_ATOMICS && (defined(__cplusplus) && (\ - (__cplusplus >= 201103L) ||\ -\ - (defined(_MSC_VER) && _MSC_VER >= 1700)) &&\ - ATOMIC_INT_LOCK_FREE == 2) - #undef __pyx_atomic_int_type - #define __pyx_atomic_int_type std::atomic_int - #define __pyx_atomic_ptr_type std::atomic_uintptr_t - #define __pyx_nonatomic_ptr_type uintptr_t - #define __pyx_atomic_incr_relaxed(value) std::atomic_fetch_add_explicit(value, 1, std::memory_order_relaxed) - #define __pyx_atomic_incr_acq_rel(value) std::atomic_fetch_add_explicit(value, 1, std::memory_order_acq_rel) - #define __pyx_atomic_decr_acq_rel(value) std::atomic_fetch_sub_explicit(value, 1, std::memory_order_acq_rel) - #define __pyx_atomic_sub(value, arg) std::atomic_fetch_sub(value, arg) - #define __pyx_atomic_int_cmp_exchange(value, expected, desired) std::atomic_compare_exchange_strong(value, expected, desired) - #define __pyx_atomic_load(value) std::atomic_load(value) - #define __pyx_atomic_store(value, new_value) std::atomic_store(value, new_value) - #define __pyx_atomic_pointer_load_relaxed(value) std::atomic_load_explicit(value, std::memory_order_relaxed) - #define __pyx_atomic_pointer_load_acquire(value) std::atomic_load_explicit(value, std::memory_order_acquire) - #define __pyx_atomic_pointer_exchange(value, new_value) std::atomic_exchange(value, (__pyx_nonatomic_ptr_type)new_value) - #if defined(__PYX_DEBUG_ATOMICS) && defined(_MSC_VER) - #pragma message ("Using standard C++ atomics") - #elif defined(__PYX_DEBUG_ATOMICS) - #warning "Using standard C++ atomics" - #endif -#elif CYTHON_ATOMICS && (__GNUC__ >= 5 || (__GNUC__ == 4 &&\ - (__GNUC_MINOR__ > 1 ||\ - (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL__ >= 2)))) - #define __pyx_atomic_ptr_type void* - #define __pyx_atomic_incr_relaxed(value) __sync_fetch_and_add(value, 1) - #define __pyx_atomic_incr_acq_rel(value) __sync_fetch_and_add(value, 1) - #define __pyx_atomic_decr_acq_rel(value) __sync_fetch_and_sub(value, 1) - #define __pyx_atomic_sub(value, arg) __sync_fetch_and_sub(value, arg) - static CYTHON_INLINE int __pyx_atomic_int_cmp_exchange(__pyx_atomic_int_type* value, __pyx_nonatomic_int_type* expected, __pyx_nonatomic_int_type desired) { - __pyx_nonatomic_int_type old = __sync_val_compare_and_swap(value, *expected, desired); - int result = old == *expected; - *expected = old; - return result; - } - #define __pyx_atomic_load(value) __sync_fetch_and_add(value, 0) - #define __pyx_atomic_store(value, new_value) __sync_lock_test_and_set(value, new_value) - #define __pyx_atomic_pointer_load_relaxed(value) __sync_fetch_and_add(value, 0) - #define __pyx_atomic_pointer_load_acquire(value) __sync_fetch_and_add(value, 0) - #define __pyx_atomic_pointer_exchange(value, new_value) __sync_lock_test_and_set(value, (__pyx_atomic_ptr_type)new_value) - #ifdef __PYX_DEBUG_ATOMICS - #warning "Using GNU atomics" - #endif -#elif CYTHON_ATOMICS && defined(_MSC_VER) - #include - #undef __pyx_atomic_int_type - #define __pyx_atomic_int_type long - #define __pyx_atomic_ptr_type void* - #undef __pyx_nonatomic_int_type - #define __pyx_nonatomic_int_type long - #pragma intrinsic (_InterlockedExchangeAdd, _InterlockedExchange, _InterlockedCompareExchange, _InterlockedCompareExchangePointer, _InterlockedExchangePointer) - #define __pyx_atomic_incr_relaxed(value) _InterlockedExchangeAdd(value, 1) - #define __pyx_atomic_incr_acq_rel(value) _InterlockedExchangeAdd(value, 1) - #define __pyx_atomic_decr_acq_rel(value) _InterlockedExchangeAdd(value, -1) - #define __pyx_atomic_sub(value, arg) _InterlockedExchangeAdd(value, -arg) - static CYTHON_INLINE int __pyx_atomic_int_cmp_exchange(__pyx_atomic_int_type* value, __pyx_nonatomic_int_type* expected, __pyx_nonatomic_int_type desired) { - __pyx_nonatomic_int_type old = _InterlockedCompareExchange(value, desired, *expected); - int result = old == *expected; - *expected = old; - return result; - } - #define __pyx_atomic_load(value) _InterlockedExchangeAdd(value, 0) - #define __pyx_atomic_store(value, new_value) _InterlockedExchange(value, new_value) - #define __pyx_atomic_pointer_load_relaxed(value) *(void * volatile *)value - #define __pyx_atomic_pointer_load_acquire(value) _InterlockedCompareExchangePointer(value, 0, 0) - #define __pyx_atomic_pointer_exchange(value, new_value) _InterlockedExchangePointer(value, (__pyx_atomic_ptr_type)new_value) - #ifdef __PYX_DEBUG_ATOMICS - #pragma message ("Using MSVC atomics") - #endif -#else - #undef CYTHON_ATOMICS - #define CYTHON_ATOMICS 0 - #ifdef __PYX_DEBUG_ATOMICS - #warning "Not using atomics" - #endif -#endif -#if CYTHON_ATOMICS - #define __pyx_add_acquisition_count(memview)\ - __pyx_atomic_incr_relaxed(__pyx_get_slice_count_pointer(memview)) - #define __pyx_sub_acquisition_count(memview)\ - __pyx_atomic_decr_acq_rel(__pyx_get_slice_count_pointer(memview)) -#else - #define __pyx_add_acquisition_count(memview)\ - __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) - #define __pyx_sub_acquisition_count(memview)\ - __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) -#endif - -/* CriticalSections.proto */ -#if !CYTHON_COMPILING_IN_CPYTHON_FREETHREADING -#define __Pyx_PyCriticalSection void* -#define __Pyx_PyCriticalSection2 void* -#define __Pyx_PyCriticalSection_Begin1(cs, arg) (void)cs -#define __Pyx_PyCriticalSection_Begin2(cs, arg1, arg2) (void)cs -#define __Pyx_PyCriticalSection_End1(cs) -#define __Pyx_PyCriticalSection_End2(cs) -#else -#define __Pyx_PyCriticalSection PyCriticalSection -#define __Pyx_PyCriticalSection2 PyCriticalSection2 -#define __Pyx_PyCriticalSection_Begin1 PyCriticalSection_Begin -#define __Pyx_PyCriticalSection_Begin2 PyCriticalSection2_Begin -#define __Pyx_PyCriticalSection_End1 PyCriticalSection_End -#define __Pyx_PyCriticalSection_End2 PyCriticalSection2_End -#endif -#if PY_VERSION_HEX < 0x030d0000 || CYTHON_COMPILING_IN_LIMITED_API -#define __Pyx_BEGIN_CRITICAL_SECTION(o) { -#define __Pyx_END_CRITICAL_SECTION() } -#else -#define __Pyx_BEGIN_CRITICAL_SECTION Py_BEGIN_CRITICAL_SECTION -#define __Pyx_END_CRITICAL_SECTION Py_END_CRITICAL_SECTION -#endif - -/* IncludeStructmemberH.proto */ -#include - -/* #### Code section: numeric_typedefs ### */ - -typedef npy_int8 __pyx_t_5numpy_int8_t; 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-#else -#define __Pyx_GetModuleGlobalName(var, name) (var) = __Pyx__GetModuleGlobalName(name) -#define __Pyx_GetModuleGlobalNameUncached(var, name) (var) = __Pyx__GetModuleGlobalName(name) -static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name); -#endif - -/* PyObjectDelAttr.proto */ -#if CYTHON_COMPILING_IN_LIMITED_API && __PYX_LIMITED_VERSION_HEX < 0x030d0000 -#define __Pyx_PyObject_DelAttr(o, n) PyObject_SetAttr(o, n, NULL) -#else -#define __Pyx_PyObject_DelAttr(o, n) PyObject_DelAttr(o, n) -#endif - -/* PyObjectSetAttrStr.proto */ -#if CYTHON_USE_TYPE_SLOTS -#define __Pyx_PyObject_DelAttrStr(o,n) __Pyx_PyObject_SetAttrStr(o, n, NULL) -static CYTHON_INLINE int __Pyx_PyObject_SetAttrStr(PyObject* obj, PyObject* attr_name, PyObject* value); -#else -#define __Pyx_PyObject_DelAttrStr(o,n) __Pyx_PyObject_DelAttr(o,n) -#define __Pyx_PyObject_SetAttrStr(o,n,v) PyObject_SetAttr(o,n,v) -#endif - -/* GetItemInt.proto */ -#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck, has_gil)\ - (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ - __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\ - (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ - __Pyx_GetItemInt_Generic(o, to_py_func(i)))) -#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck, has_gil)\ - (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ - __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ - (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, - int wraparound, int boundscheck); -#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck, has_gil)\ - (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ - __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ - (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, - int wraparound, int boundscheck); -static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, - int is_list, int wraparound, int boundscheck); - -/* PyObjectCallOneArg.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); - -/* ObjectGetItem.proto */ -#if CYTHON_USE_TYPE_SLOTS -static CYTHON_INLINE PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject *key); -#else -#define __Pyx_PyObject_GetItem(obj, key) PyObject_GetItem(obj, key) -#endif - -/* PyObjectFastCallMethod.proto */ -#if CYTHON_VECTORCALL && PY_VERSION_HEX >= 0x03090000 -#define __Pyx_PyObject_FastCallMethod(name, args, nargsf) PyObject_VectorcallMethod(name, args, nargsf, NULL) -#else -static PyObject *__Pyx_PyObject_FastCallMethod(PyObject *name, PyObject *const *args, size_t nargsf); -#endif - -/* HasAttr.proto */ -#if __PYX_LIMITED_VERSION_HEX >= 0x030d0000 -#define __Pyx_HasAttr(o, n) PyObject_HasAttrWithError(o, n) -#else -static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *); -#endif - -/* DictGetItem.proto */ -#if !CYTHON_COMPILING_IN_PYPY -static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key); -#define __Pyx_PyObject_Dict_GetItem(obj, name)\ - (likely(PyDict_CheckExact(obj)) ?\ - __Pyx_PyDict_GetItem(obj, name) : PyObject_GetItem(obj, name)) -#else -#define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) -#define __Pyx_PyObject_Dict_GetItem(obj, name) PyObject_GetItem(obj, name) -#endif - -/* RaiseTooManyValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); - -/* RaiseNeedMoreValuesToUnpack.proto */ -static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); - -/* IterFinish.proto */ -static CYTHON_INLINE int __Pyx_IterFinish(void); - -/* UnpackItemEndCheck.proto */ -static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected); - -/* PySequenceContains.proto */ -static CYTHON_INLINE int __Pyx_PySequence_ContainsTF(PyObject* item, PyObject* seq, int eq) { - int result = PySequence_Contains(seq, item); - return unlikely(result < 0) ? result : (result == (eq == Py_EQ)); -} - -/* ListAppend.proto */ -#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS -static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { - PyListObject* L = (PyListObject*) list; - Py_ssize_t len = Py_SIZE(list); - if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { - Py_INCREF(x); - #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030d0000 - L->ob_item[len] = x; - #else - PyList_SET_ITEM(list, len, x); - #endif - __Pyx_SET_SIZE(list, len + 1); - return 0; - } - return PyList_Append(list, x); -} -#else -#define __Pyx_PyList_Append(L,x) PyList_Append(L,x) -#endif - -/* PyObjectCallNoArg.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func); - -/* PyObjectGetMethod.proto */ -static int __Pyx_PyObject_GetMethod(PyObject *obj, PyObject *name, PyObject **method); - -/* PyObjectCallMethod0.proto */ -static PyObject* __Pyx_PyObject_CallMethod0(PyObject* obj, PyObject* method_name); - -/* RaiseNoneIterError.proto */ -static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); - -/* UnpackTupleError.proto */ -static void __Pyx_UnpackTupleError(PyObject *, Py_ssize_t index); - -/* UnpackTuple2.proto */ -static CYTHON_INLINE int __Pyx_unpack_tuple2( - PyObject* tuple, PyObject** value1, PyObject** value2, int is_tuple, int has_known_size, int decref_tuple); -static CYTHON_INLINE int __Pyx_unpack_tuple2_exact( - PyObject* tuple, PyObject** value1, PyObject** value2, int decref_tuple); -static int __Pyx_unpack_tuple2_generic( - PyObject* tuple, PyObject** value1, PyObject** value2, int has_known_size, int decref_tuple); - -/* dict_iter.proto */ -static CYTHON_INLINE PyObject* __Pyx_dict_iterator(PyObject* dict, int is_dict, PyObject* method_name, - Py_ssize_t* p_orig_length, int* p_is_dict); -static CYTHON_INLINE int __Pyx_dict_iter_next(PyObject* dict_or_iter, Py_ssize_t orig_length, Py_ssize_t* ppos, - PyObject** pkey, PyObject** pvalue, PyObject** pitem, int is_dict); - -/* PyLongBinop.proto */ -#if !CYTHON_COMPILING_IN_PYPY -static CYTHON_INLINE PyObject* __Pyx_PyLong_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); -#else -#define __Pyx_PyLong_AddObjC(op1, op2, intval, inplace, zerodivision_check)\ - (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) -#endif - -/* PyObjectVectorCallKwBuilder.proto */ -CYTHON_UNUSED static int __Pyx_VectorcallBuilder_AddArg_Check(PyObject *key, PyObject *value, PyObject *builder, PyObject **args, int n); -#if CYTHON_VECTORCALL -#if PY_VERSION_HEX >= 0x03090000 -#define __Pyx_Object_Vectorcall_CallFromBuilder PyObject_Vectorcall -#else -#define __Pyx_Object_Vectorcall_CallFromBuilder _PyObject_Vectorcall -#endif -#define __Pyx_MakeVectorcallBuilderKwds(n) PyTuple_New(n) -static int __Pyx_VectorcallBuilder_AddArg(PyObject *key, PyObject *value, PyObject *builder, PyObject **args, int n); -static int __Pyx_VectorcallBuilder_AddArgStr(const char *key, PyObject *value, PyObject *builder, PyObject **args, int n); -#else -#define __Pyx_Object_Vectorcall_CallFromBuilder __Pyx_PyObject_FastCallDict -#define __Pyx_MakeVectorcallBuilderKwds(n) __Pyx_PyDict_NewPresized(n) -#define __Pyx_VectorcallBuilder_AddArg(key, value, builder, args, n) PyDict_SetItem(builder, key, value) -#define __Pyx_VectorcallBuilder_AddArgStr(key, value, builder, args, n) PyDict_SetItemString(builder, key, value) -#endif - -/* ListCompAppend.proto */ -#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS -static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { - PyListObject* L = (PyListObject*) list; - Py_ssize_t len = Py_SIZE(list); - if (likely(L->allocated > len)) { - Py_INCREF(x); - #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030d0000 - L->ob_item[len] = x; - #else - PyList_SET_ITEM(list, len, x); - #endif - __Pyx_SET_SIZE(list, len + 1); - return 0; - } - return PyList_Append(list, x); -} -#else -#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) -#endif - -/* BuildPyUnicode.proto */ -static PyObject* __Pyx_PyUnicode_BuildFromAscii(Py_ssize_t ulength, const char* chars, int clength, - int prepend_sign, char padding_char); - -/* COrdinalToPyUnicode.proto */ -static CYTHON_INLINE int __Pyx_CheckUnicodeValue(int value); -static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromOrdinal_Padded(int value, Py_ssize_t width, char padding_char); - -/* GCCDiagnostics.proto */ -#if !defined(__INTEL_COMPILER) && defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6)) -#define __Pyx_HAS_GCC_DIAGNOSTIC -#endif - -/* IncludeStdlibH.proto */ -#include - -/* CIntToPyUnicode.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyUnicode_From_Py_ssize_t(Py_ssize_t value, Py_ssize_t width, char padding_char, char format_char); - -/* SliceTupleAndList.proto */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyList_GetSlice(PyObject* src, Py_ssize_t start, Py_ssize_t stop); -static CYTHON_INLINE PyObject* __Pyx_PyTuple_GetSlice(PyObject* src, Py_ssize_t start, Py_ssize_t stop); -#else -#define __Pyx_PyList_GetSlice(seq, start, stop) PySequence_GetSlice(seq, start, stop) -#define __Pyx_PyTuple_GetSlice(seq, start, stop) PySequence_GetSlice(seq, start, stop) -#endif - -/* PyObject_Unicode.proto */ -#define __Pyx_PyObject_Unicode(obj)\ - (likely(PyUnicode_CheckExact(obj)) ? __Pyx_NewRef(obj) : PyObject_Str(obj)) - -/* py_dict_keys.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyDict_Keys(PyObject* d); - -/* CallUnboundCMethod0.proto */ -CYTHON_UNUSED -static PyObject* __Pyx__CallUnboundCMethod0(__Pyx_CachedCFunction* cfunc, PyObject* self); -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_CallUnboundCMethod0(__Pyx_CachedCFunction* cfunc, PyObject* self); -#else -#define __Pyx_CallUnboundCMethod0(cfunc, self) __Pyx__CallUnboundCMethod0(cfunc, self) -#endif - -/* RaiseUnexpectedTypeError.proto */ -static int __Pyx_RaiseUnexpectedTypeError(const char *expected, PyObject *obj); - -/* SliceObject.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_GetSlice( - PyObject* obj, Py_ssize_t cstart, Py_ssize_t cstop, - PyObject** py_start, PyObject** py_stop, PyObject** py_slice, - int has_cstart, int has_cstop, int wraparound); - -/* ModFloat[double].proto */ -static CYTHON_INLINE double __Pyx_mod_double(double, double, int b_is_constant); - -/* SetItemInt.proto */ -#define __Pyx_SetItemInt(o, i, v, type, is_signed, to_py_func, is_list, wraparound, boundscheck, has_gil)\ - (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ - __Pyx_SetItemInt_Fast(o, (Py_ssize_t)i, v, is_list, wraparound, boundscheck) :\ - (is_list ? (PyErr_SetString(PyExc_IndexError, "list assignment index out of range"), -1) :\ - __Pyx_SetItemInt_Generic(o, to_py_func(i), v))) -static int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v); -static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v, - int is_list, int wraparound, int boundscheck); - -/* TypeImport.proto */ -#ifndef __PYX_HAVE_RT_ImportType_proto_3_1_2 -#define __PYX_HAVE_RT_ImportType_proto_3_1_2 -#if defined (__STDC_VERSION__) && __STDC_VERSION__ >= 201112L -#include -#endif -#if (defined (__STDC_VERSION__) && __STDC_VERSION__ >= 201112L) || __cplusplus >= 201103L -#define __PYX_GET_STRUCT_ALIGNMENT_3_1_2(s) alignof(s) -#else -#define __PYX_GET_STRUCT_ALIGNMENT_3_1_2(s) sizeof(void*) -#endif -enum __Pyx_ImportType_CheckSize_3_1_2 { - __Pyx_ImportType_CheckSize_Error_3_1_2 = 0, - __Pyx_ImportType_CheckSize_Warn_3_1_2 = 1, - __Pyx_ImportType_CheckSize_Ignore_3_1_2 = 2 -}; -static PyTypeObject *__Pyx_ImportType_3_1_2(PyObject* module, const char *module_name, const char *class_name, size_t size, size_t alignment, enum __Pyx_ImportType_CheckSize_3_1_2 check_size); -#endif - -/* LimitedApiGetTypeDict.proto */ -#if CYTHON_COMPILING_IN_LIMITED_API -static PyObject *__Pyx_GetTypeDict(PyTypeObject *tp); -#endif - -/* SetItemOnTypeDict.proto */ -static int __Pyx__SetItemOnTypeDict(PyTypeObject *tp, PyObject *k, PyObject *v); -#define __Pyx_SetItemOnTypeDict(tp, k, v) __Pyx__SetItemOnTypeDict((PyTypeObject*)tp, k, v) - -/* FixUpExtensionType.proto */ -static CYTHON_INLINE int __Pyx_fix_up_extension_type_from_spec(PyType_Spec *spec, PyTypeObject *type); - -/* FetchSharedCythonModule.proto */ -static PyObject *__Pyx_FetchSharedCythonABIModule(void); - -/* dict_setdefault.proto */ -static CYTHON_INLINE PyObject *__Pyx_PyDict_SetDefault(PyObject *d, PyObject *key, PyObject *default_value, int is_safe_type); - -/* FetchCommonType.proto */ -static PyTypeObject* __Pyx_FetchCommonTypeFromSpec(PyTypeObject *metaclass, PyObject *module, PyType_Spec *spec, PyObject *bases); - -/* CommonTypesMetaclass.proto */ -static int __pyx_CommonTypesMetaclass_init(PyObject *module); -#define __Pyx_CommonTypesMetaclass_USED - -/* CallTypeTraverse.proto */ -#if !CYTHON_USE_TYPE_SPECS || (!CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX < 0x03090000) -#define __Pyx_call_type_traverse(o, always_call, visit, arg) 0 -#else -static int __Pyx_call_type_traverse(PyObject *o, int always_call, visitproc visit, void *arg); -#endif - -/* PyMethodNew.proto */ -static PyObject *__Pyx_PyMethod_New(PyObject *func, PyObject *self, PyObject *typ); - -/* PyVectorcallFastCallDict.proto */ -#if CYTHON_METH_FASTCALL && (CYTHON_VECTORCALL || CYTHON_BACKPORT_VECTORCALL) -static CYTHON_INLINE PyObject *__Pyx_PyVectorcall_FastCallDict(PyObject *func, __pyx_vectorcallfunc vc, PyObject *const *args, size_t nargs, PyObject *kw); -#endif - -/* CythonFunctionShared.proto */ -#define __Pyx_CyFunction_USED -#define __Pyx_CYFUNCTION_STATICMETHOD 0x01 -#define __Pyx_CYFUNCTION_CLASSMETHOD 0x02 -#define __Pyx_CYFUNCTION_CCLASS 0x04 -#define __Pyx_CYFUNCTION_COROUTINE 0x08 -#define __Pyx_CyFunction_GetClosure(f)\ - (((__pyx_CyFunctionObject *) (f))->func_closure) -#if PY_VERSION_HEX < 0x030900B1 || CYTHON_COMPILING_IN_LIMITED_API - #define __Pyx_CyFunction_GetClassObj(f)\ - (((__pyx_CyFunctionObject *) (f))->func_classobj) -#else - #define __Pyx_CyFunction_GetClassObj(f)\ - ((PyObject*) ((PyCMethodObject *) (f))->mm_class) -#endif -#define __Pyx_CyFunction_SetClassObj(f, classobj)\ - __Pyx__CyFunction_SetClassObj((__pyx_CyFunctionObject *) (f), (classobj)) -#define __Pyx_CyFunction_Defaults(type, f)\ - ((type *)(((__pyx_CyFunctionObject *) (f))->defaults)) -#define __Pyx_CyFunction_SetDefaultsGetter(f, g)\ - ((__pyx_CyFunctionObject *) (f))->defaults_getter = (g) -typedef struct { -#if CYTHON_COMPILING_IN_LIMITED_API - PyObject_HEAD - PyObject *func; -#elif PY_VERSION_HEX < 0x030900B1 - PyCFunctionObject func; -#else - PyCMethodObject func; -#endif -#if CYTHON_BACKPORT_VECTORCALL ||\ - (CYTHON_COMPILING_IN_LIMITED_API && CYTHON_METH_FASTCALL) - __pyx_vectorcallfunc func_vectorcall; -#endif -#if CYTHON_COMPILING_IN_LIMITED_API - PyObject *func_weakreflist; -#endif - PyObject *func_dict; - PyObject *func_name; - PyObject *func_qualname; - PyObject *func_doc; - PyObject *func_globals; - PyObject *func_code; - PyObject *func_closure; -#if PY_VERSION_HEX < 0x030900B1 || CYTHON_COMPILING_IN_LIMITED_API - PyObject *func_classobj; -#endif - PyObject *defaults; - int flags; - PyObject *defaults_tuple; - PyObject *defaults_kwdict; - PyObject *(*defaults_getter)(PyObject *); - PyObject *func_annotations; - PyObject *func_is_coroutine; -} __pyx_CyFunctionObject; -#undef __Pyx_CyOrPyCFunction_Check -#define __Pyx_CyFunction_Check(obj) __Pyx_TypeCheck(obj, __pyx_mstate_global->__pyx_CyFunctionType) -#define __Pyx_CyOrPyCFunction_Check(obj) __Pyx_TypeCheck2(obj, __pyx_mstate_global->__pyx_CyFunctionType, &PyCFunction_Type) -#define __Pyx_CyFunction_CheckExact(obj) __Pyx_IS_TYPE(obj, __pyx_mstate_global->__pyx_CyFunctionType) -static CYTHON_INLINE int __Pyx__IsSameCyOrCFunction(PyObject *func, void (*cfunc)(void)); -#undef __Pyx_IsSameCFunction -#define __Pyx_IsSameCFunction(func, cfunc) __Pyx__IsSameCyOrCFunction(func, cfunc) -static PyObject *__Pyx_CyFunction_Init(__pyx_CyFunctionObject* op, PyMethodDef *ml, - int flags, PyObject* qualname, - PyObject *closure, - PyObject *module, PyObject *globals, - PyObject* code); -static CYTHON_INLINE void __Pyx__CyFunction_SetClassObj(__pyx_CyFunctionObject* f, PyObject* classobj); -static CYTHON_INLINE PyObject *__Pyx_CyFunction_InitDefaults(PyObject *func, - PyTypeObject *defaults_type); -static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsTuple(PyObject *m, - PyObject *tuple); -static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsKwDict(PyObject *m, - PyObject *dict); -static CYTHON_INLINE void __Pyx_CyFunction_SetAnnotationsDict(PyObject *m, - PyObject *dict); -static int __pyx_CyFunction_init(PyObject *module); -#if CYTHON_METH_FASTCALL -static PyObject * __Pyx_CyFunction_Vectorcall_NOARGS(PyObject *func, PyObject *const *args, size_t nargsf, PyObject *kwnames); -static PyObject * __Pyx_CyFunction_Vectorcall_O(PyObject *func, PyObject *const *args, size_t nargsf, PyObject *kwnames); -static PyObject * __Pyx_CyFunction_Vectorcall_FASTCALL_KEYWORDS(PyObject *func, PyObject *const *args, size_t nargsf, PyObject *kwnames); -static PyObject * __Pyx_CyFunction_Vectorcall_FASTCALL_KEYWORDS_METHOD(PyObject *func, PyObject *const *args, size_t nargsf, PyObject *kwnames); -#if CYTHON_BACKPORT_VECTORCALL || CYTHON_COMPILING_IN_LIMITED_API -#define __Pyx_CyFunction_func_vectorcall(f) (((__pyx_CyFunctionObject*)f)->func_vectorcall) -#else -#define __Pyx_CyFunction_func_vectorcall(f) (((PyCFunctionObject*)f)->vectorcall) -#endif -#endif - -/* CythonFunction.proto */ -static PyObject *__Pyx_CyFunction_New(PyMethodDef *ml, - int flags, PyObject* qualname, - PyObject *closure, - PyObject *module, PyObject *globals, - PyObject* code); - -/* Py3UpdateBases.proto */ -static PyObject* __Pyx_PEP560_update_bases(PyObject *bases); - -/* CalculateMetaclass.proto */ -static PyObject *__Pyx_CalculateMetaclass(PyTypeObject *metaclass, PyObject *bases); - -/* SetNameInClass.proto */ -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030d0000 -#define __Pyx_SetNameInClass(ns, name, value)\ - (likely(PyDict_CheckExact(ns)) ? _PyDict_SetItem_KnownHash(ns, name, value, ((PyASCIIObject *) name)->hash) : PyObject_SetItem(ns, name, value)) -#elif CYTHON_COMPILING_IN_CPYTHON -#define __Pyx_SetNameInClass(ns, name, value)\ - (likely(PyDict_CheckExact(ns)) ? PyDict_SetItem(ns, name, value) : PyObject_SetItem(ns, name, value)) -#else -#define __Pyx_SetNameInClass(ns, name, value) PyObject_SetItem(ns, name, value) -#endif - -/* PyObjectCall2Args.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2); - -/* PyObjectLookupSpecial.proto */ -#if CYTHON_USE_PYTYPE_LOOKUP && CYTHON_USE_TYPE_SLOTS -#define __Pyx_PyObject_LookupSpecialNoError(obj, attr_name) __Pyx__PyObject_LookupSpecial(obj, attr_name, 0) -#define __Pyx_PyObject_LookupSpecial(obj, attr_name) __Pyx__PyObject_LookupSpecial(obj, attr_name, 1) -static CYTHON_INLINE PyObject* __Pyx__PyObject_LookupSpecial(PyObject* obj, PyObject* attr_name, int with_error); -#else -#define __Pyx_PyObject_LookupSpecialNoError(o,n) __Pyx_PyObject_GetAttrStrNoError(o,n) -#define __Pyx_PyObject_LookupSpecial(o,n) __Pyx_PyObject_GetAttrStr(o,n) -#endif - -/* Py3ClassCreate.proto */ -static PyObject *__Pyx_Py3MetaclassPrepare(PyObject *metaclass, PyObject *bases, PyObject *name, PyObject *qualname, - PyObject *mkw, PyObject *modname, PyObject *doc); -static PyObject *__Pyx_Py3ClassCreate(PyObject *metaclass, PyObject *name, PyObject *bases, PyObject *dict, - PyObject *mkw, int calculate_metaclass, int allow_py2_metaclass); - -/* ListPack.proto */ -static PyObject *__Pyx_PyList_Pack(Py_ssize_t n, ...); - -/* Import.proto */ -static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); - -/* ImportFrom.proto */ -static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name); - -/* ImportDottedModule.proto */ -static PyObject *__Pyx_ImportDottedModule(PyObject *name, PyObject *parts_tuple); -static PyObject *__Pyx_ImportDottedModule_WalkParts(PyObject *module, PyObject *name, PyObject *parts_tuple); - -/* ImportDottedModuleRelFirst.proto */ -static PyObject *__Pyx_ImportDottedModuleRelFirst(PyObject *name, PyObject *parts_tuple); - -/* PyObjectCallMethod1.proto */ -static PyObject* __Pyx_PyObject_CallMethod1(PyObject* obj, PyObject* method_name, PyObject* arg); - -/* append.proto */ -static CYTHON_INLINE int __Pyx_PyObject_Append(PyObject* L, PyObject* x); - -/* CLineInTraceback.proto */ -#if CYTHON_CLINE_IN_TRACEBACK && CYTHON_CLINE_IN_TRACEBACK_RUNTIME -static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); -#else -#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) -#endif - -/* CodeObjectCache.proto */ -#if CYTHON_COMPILING_IN_LIMITED_API -typedef PyObject __Pyx_CachedCodeObjectType; -#else -typedef PyCodeObject __Pyx_CachedCodeObjectType; -#endif -typedef struct { - __Pyx_CachedCodeObjectType* code_object; - int code_line; -} __Pyx_CodeObjectCacheEntry; -struct __Pyx_CodeObjectCache { - int count; - int max_count; - __Pyx_CodeObjectCacheEntry* entries; - #if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING - __pyx_atomic_int_type accessor_count; - #endif -}; -static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); -static __Pyx_CachedCodeObjectType *__pyx_find_code_object(int code_line); -static void __pyx_insert_code_object(int code_line, __Pyx_CachedCodeObjectType* code_object); - -/* AddTraceback.proto */ -static void __Pyx_AddTraceback(const char *funcname, int c_line, - int py_line, const char *filename); - -/* RealImag.proto */ -#if CYTHON_CCOMPLEX - #ifdef __cplusplus - #define __Pyx_CREAL(z) ((z).real()) - #define __Pyx_CIMAG(z) ((z).imag()) - #else - #define __Pyx_CREAL(z) (__real__(z)) - #define __Pyx_CIMAG(z) (__imag__(z)) - #endif -#else - #define __Pyx_CREAL(z) ((z).real) - #define __Pyx_CIMAG(z) ((z).imag) -#endif -#if defined(__cplusplus) && CYTHON_CCOMPLEX\ - && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) - #define __Pyx_SET_CREAL(z,x) ((z).real(x)) - #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) -#else - #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) - #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) -#endif - -/* Arithmetic.proto */ -#if CYTHON_CCOMPLEX && (1) && (!0 || __cplusplus) - #define __Pyx_c_eq_float(a, b) ((a)==(b)) - #define __Pyx_c_sum_float(a, b) ((a)+(b)) - #define __Pyx_c_diff_float(a, b) ((a)-(b)) - #define __Pyx_c_prod_float(a, b) ((a)*(b)) - #define __Pyx_c_quot_float(a, b) ((a)/(b)) - #define __Pyx_c_neg_float(a) (-(a)) - #ifdef __cplusplus - #define __Pyx_c_is_zero_float(z) ((z)==(float)0) - #define __Pyx_c_conj_float(z) (::std::conj(z)) - #if 1 - #define __Pyx_c_abs_float(z) (::std::abs(z)) - #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) - #endif - #else - #define __Pyx_c_is_zero_float(z) ((z)==0) - #define __Pyx_c_conj_float(z) (conjf(z)) - #if 1 - #define __Pyx_c_abs_float(z) (cabsf(z)) - #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) - #endif - #endif -#else - static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); - static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); - #if 1 - static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); - #endif -#endif - -/* Arithmetic.proto */ -#if CYTHON_CCOMPLEX && (1) && (!0 || __cplusplus) - #define __Pyx_c_eq_double(a, b) ((a)==(b)) - #define __Pyx_c_sum_double(a, b) ((a)+(b)) - #define __Pyx_c_diff_double(a, b) ((a)-(b)) - #define __Pyx_c_prod_double(a, b) ((a)*(b)) - #define __Pyx_c_quot_double(a, b) ((a)/(b)) - #define __Pyx_c_neg_double(a) (-(a)) - #ifdef __cplusplus - #define __Pyx_c_is_zero_double(z) ((z)==(double)0) - #define __Pyx_c_conj_double(z) (::std::conj(z)) - #if 1 - #define __Pyx_c_abs_double(z) (::std::abs(z)) - #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) - #endif - #else - #define __Pyx_c_is_zero_double(z) ((z)==0) - #define __Pyx_c_conj_double(z) (conj(z)) - #if 1 - #define __Pyx_c_abs_double(z) (cabs(z)) - #define __Pyx_c_pow_double(a, b) (cpow(a, b)) - #endif - #endif -#else - static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); - static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); - #if 1 - static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); - #endif -#endif - -/* Arithmetic.proto */ -#if CYTHON_CCOMPLEX && (1) && (!0 || __cplusplus) - #define __Pyx_c_eq_long__double(a, b) ((a)==(b)) - #define __Pyx_c_sum_long__double(a, b) ((a)+(b)) - #define __Pyx_c_diff_long__double(a, b) ((a)-(b)) - #define __Pyx_c_prod_long__double(a, b) ((a)*(b)) - #define __Pyx_c_quot_long__double(a, b) ((a)/(b)) - #define __Pyx_c_neg_long__double(a) (-(a)) - #ifdef __cplusplus - #define __Pyx_c_is_zero_long__double(z) ((z)==(long double)0) - #define __Pyx_c_conj_long__double(z) (::std::conj(z)) - #if 1 - #define __Pyx_c_abs_long__double(z) (::std::abs(z)) - #define __Pyx_c_pow_long__double(a, b) (::std::pow(a, b)) - #endif - #else - #define __Pyx_c_is_zero_long__double(z) ((z)==0) - #define __Pyx_c_conj_long__double(z) (conjl(z)) - #if 1 - #define __Pyx_c_abs_long__double(z) (cabsl(z)) - #define __Pyx_c_pow_long__double(a, b) (cpowl(a, b)) - #endif - #endif -#else - static CYTHON_INLINE int __Pyx_c_eq_long__double(__pyx_t_long_double_complex, __pyx_t_long_double_complex); - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_sum_long__double(__pyx_t_long_double_complex, __pyx_t_long_double_complex); - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_diff_long__double(__pyx_t_long_double_complex, __pyx_t_long_double_complex); - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_prod_long__double(__pyx_t_long_double_complex, __pyx_t_long_double_complex); - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_quot_long__double(__pyx_t_long_double_complex, __pyx_t_long_double_complex); - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_neg_long__double(__pyx_t_long_double_complex); - static CYTHON_INLINE int __Pyx_c_is_zero_long__double(__pyx_t_long_double_complex); - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_conj_long__double(__pyx_t_long_double_complex); - #if 1 - static CYTHON_INLINE long double __Pyx_c_abs_long__double(__pyx_t_long_double_complex); - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_pow_long__double(__pyx_t_long_double_complex, __pyx_t_long_double_complex); - #endif -#endif - -/* CIntFromPy.proto */ -static CYTHON_INLINE TA_RetCode __Pyx_PyLong_As_TA_RetCode(PyObject *); - -/* CIntFromPy.proto */ -static CYTHON_INLINE int __Pyx_PyLong_As_int(PyObject *); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_int(int value); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_TA_RetCode(TA_RetCode value); - -/* CIntFromPy.proto */ -static CYTHON_INLINE TA_FuncUnstId __Pyx_PyLong_As_TA_FuncUnstId(PyObject *); - -/* CIntFromPy.proto */ -static CYTHON_INLINE unsigned int __Pyx_PyLong_As_unsigned_int(PyObject *); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_unsigned_int(unsigned int value); - -/* CIntFromPy.proto */ -static CYTHON_INLINE TA_Compatibility __Pyx_PyLong_As_TA_Compatibility(PyObject *); - -/* CIntFromPy.proto */ -static CYTHON_INLINE TA_CandleSettingType __Pyx_PyLong_As_TA_CandleSettingType(PyObject *); - -/* CIntFromPy.proto */ -static CYTHON_INLINE TA_RangeType __Pyx_PyLong_As_TA_RangeType(PyObject *); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_long(long value); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_TA_OptInputParameterType(TA_OptInputParameterType value); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_TA_FuncFlags(TA_FuncFlags value); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_TA_InputFlags(TA_InputFlags value); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_TA_OutputFlags(TA_OutputFlags value); - -/* FormatTypeName.proto */ -#if CYTHON_COMPILING_IN_LIMITED_API -typedef PyObject *__Pyx_TypeName; -#define __Pyx_FMT_TYPENAME "%U" -#define __Pyx_DECREF_TypeName(obj) Py_XDECREF(obj) -#if __PYX_LIMITED_VERSION_HEX >= 0x030d0000 -#define __Pyx_PyType_GetFullyQualifiedName PyType_GetFullyQualifiedName -#else -static __Pyx_TypeName __Pyx_PyType_GetFullyQualifiedName(PyTypeObject* tp); -#endif -#else // !LIMITED_API -typedef const char *__Pyx_TypeName; -#define __Pyx_FMT_TYPENAME "%.200s" -#define __Pyx_PyType_GetFullyQualifiedName(tp) ((tp)->tp_name) -#define __Pyx_DECREF_TypeName(obj) -#endif - -/* CIntFromPy.proto */ -static CYTHON_INLINE long __Pyx_PyLong_As_long(PyObject *); - -/* FastTypeChecks.proto */ -#if CYTHON_COMPILING_IN_CPYTHON -#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) -#define __Pyx_TypeCheck2(obj, type1, type2) __Pyx_IsAnySubtype2(Py_TYPE(obj), (PyTypeObject *)type1, (PyTypeObject *)type2) -static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); -static CYTHON_INLINE int __Pyx_IsAnySubtype2(PyTypeObject *cls, PyTypeObject *a, PyTypeObject *b); -static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); -static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); -#else -#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) -#define __Pyx_TypeCheck2(obj, type1, type2) (PyObject_TypeCheck(obj, (PyTypeObject *)type1) || PyObject_TypeCheck(obj, (PyTypeObject *)type2)) -#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) -static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2) { - return PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2); -} -#endif -#define __Pyx_PyErr_ExceptionMatches2(err1, err2) __Pyx_PyErr_GivenExceptionMatches2(__Pyx_PyErr_CurrentExceptionType(), err1, err2) -#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) -#ifdef PyExceptionInstance_Check - #define __Pyx_PyBaseException_Check(obj) PyExceptionInstance_Check(obj) -#else - #define __Pyx_PyBaseException_Check(obj) __Pyx_TypeCheck(obj, PyExc_BaseException) -#endif - -/* GetRuntimeVersion.proto */ -static unsigned long __Pyx_get_runtime_version(void); - -/* CheckBinaryVersion.proto */ -static int __Pyx_check_binary_version(unsigned long ct_version, unsigned long rt_version, int allow_newer); - -/* MultiPhaseInitModuleState.proto */ -#if CYTHON_PEP489_MULTI_PHASE_INIT && CYTHON_USE_MODULE_STATE -static PyObject *__Pyx_State_FindModule(void*); -static int __Pyx_State_AddModule(PyObject* module, void*); -static int __Pyx_State_RemoveModule(void*); -#elif CYTHON_USE_MODULE_STATE -#define __Pyx_State_FindModule PyState_FindModule -#define __Pyx_State_AddModule PyState_AddModule -#define __Pyx_State_RemoveModule PyState_RemoveModule -#endif - -/* #### Code section: module_declarations ### */ -/* CythonABIVersion.proto */ -#if CYTHON_COMPILING_IN_LIMITED_API - #if CYTHON_METH_FASTCALL - #define __PYX_FASTCALL_ABI_SUFFIX "_fastcall" - #else - #define __PYX_FASTCALL_ABI_SUFFIX - #endif - #define __PYX_LIMITED_ABI_SUFFIX "limited" __PYX_FASTCALL_ABI_SUFFIX __PYX_AM_SEND_ABI_SUFFIX -#else - #define __PYX_LIMITED_ABI_SUFFIX -#endif -#if __PYX_HAS_PY_AM_SEND == 1 - #define __PYX_AM_SEND_ABI_SUFFIX -#elif __PYX_HAS_PY_AM_SEND == 2 - #define __PYX_AM_SEND_ABI_SUFFIX "amsendbackport" -#else - #define __PYX_AM_SEND_ABI_SUFFIX "noamsend" -#endif -#ifndef __PYX_MONITORING_ABI_SUFFIX - #define __PYX_MONITORING_ABI_SUFFIX -#endif -#if CYTHON_USE_TP_FINALIZE - #define __PYX_TP_FINALIZE_ABI_SUFFIX -#else - #define __PYX_TP_FINALIZE_ABI_SUFFIX "nofinalize" -#endif -#if CYTHON_USE_FREELISTS || !defined(__Pyx_AsyncGen_USED) - #define __PYX_FREELISTS_ABI_SUFFIX -#else - #define __PYX_FREELISTS_ABI_SUFFIX "nofreelists" -#endif -#define CYTHON_ABI __PYX_ABI_VERSION __PYX_LIMITED_ABI_SUFFIX __PYX_MONITORING_ABI_SUFFIX __PYX_TP_FINALIZE_ABI_SUFFIX __PYX_FREELISTS_ABI_SUFFIX __PYX_AM_SEND_ABI_SUFFIX -#define __PYX_ABI_MODULE_NAME "_cython_" CYTHON_ABI -#define __PYX_TYPE_MODULE_PREFIX __PYX_ABI_MODULE_NAME "." - -static CYTHON_INLINE npy_intp __pyx_f_5numpy_5dtype_8itemsize_itemsize(PyArray_Descr *__pyx_v_self); /* proto*/ -static CYTHON_INLINE npy_intp __pyx_f_5numpy_5dtype_9alignment_alignment(PyArray_Descr *__pyx_v_self); /* proto*/ -static CYTHON_INLINE PyObject *__pyx_f_5numpy_5dtype_6fields_fields(PyArray_Descr *__pyx_v_self); /* proto*/ -static CYTHON_INLINE PyObject *__pyx_f_5numpy_5dtype_5names_names(PyArray_Descr *__pyx_v_self); /* proto*/ -static CYTHON_INLINE PyArray_ArrayDescr *__pyx_f_5numpy_5dtype_8subarray_subarray(PyArray_Descr *__pyx_v_self); /* proto*/ -static CYTHON_INLINE npy_uint64 __pyx_f_5numpy_5dtype_5flags_flags(PyArray_Descr *__pyx_v_self); /* proto*/ -static CYTHON_INLINE int __pyx_f_5numpy_9broadcast_7numiter_numiter(PyArrayMultiIterObject *__pyx_v_self); /* proto*/ -static CYTHON_INLINE npy_intp __pyx_f_5numpy_9broadcast_4size_size(PyArrayMultiIterObject *__pyx_v_self); /* proto*/ -static CYTHON_INLINE npy_intp __pyx_f_5numpy_9broadcast_5index_index(PyArrayMultiIterObject *__pyx_v_self); /* proto*/ -static CYTHON_INLINE int __pyx_f_5numpy_9broadcast_2nd_nd(PyArrayMultiIterObject *__pyx_v_self); /* proto*/ -static CYTHON_INLINE npy_intp *__pyx_f_5numpy_9broadcast_10dimensions_dimensions(PyArrayMultiIterObject *__pyx_v_self); /* proto*/ -static CYTHON_INLINE void **__pyx_f_5numpy_9broadcast_5iters_iters(PyArrayMultiIterObject *__pyx_v_self); /* proto*/ -static CYTHON_INLINE PyObject *__pyx_f_5numpy_7ndarray_4base_base(PyArrayObject *__pyx_v_self); /* proto*/ -static CYTHON_INLINE PyArray_Descr *__pyx_f_5numpy_7ndarray_5descr_descr(PyArrayObject *__pyx_v_self); /* proto*/ -static CYTHON_INLINE int __pyx_f_5numpy_7ndarray_4ndim_ndim(PyArrayObject *__pyx_v_self); /* proto*/ -static CYTHON_INLINE npy_intp *__pyx_f_5numpy_7ndarray_5shape_shape(PyArrayObject *__pyx_v_self); /* proto*/ -static CYTHON_INLINE npy_intp *__pyx_f_5numpy_7ndarray_7strides_strides(PyArrayObject *__pyx_v_self); /* proto*/ -static CYTHON_INLINE npy_intp __pyx_f_5numpy_7ndarray_4size_size(PyArrayObject *__pyx_v_self); /* proto*/ -static CYTHON_INLINE char *__pyx_f_5numpy_7ndarray_4data_data(PyArrayObject *__pyx_v_self); /* proto*/ - -/* Module declarations from "libc.string" */ - -/* Module declarations from "libc.stdio" */ - -/* Module declarations from "__builtin__" */ - -/* Module declarations from "cpython.type" */ - -/* Module declarations from "cpython" */ - -/* Module declarations from "cpython.object" */ - -/* Module declarations from "cpython.ref" */ - -/* Module declarations from "numpy" */ - -/* Module declarations from "numpy" */ -static CYTHON_INLINE int __pyx_f_5numpy_import_array(void); /*proto*/ - -/* Module declarations from "talib._ta_lib" */ -static double __pyx_v_5talib_7_ta_lib_NaN; -static PyObject *__pyx_f_5talib_7_ta_lib__ta_check_success(PyObject *, TA_RetCode, int __pyx_skip_dispatch); /*proto*/ -static PyArrayObject *__pyx_f_5talib_7_ta_lib_check_array(PyArrayObject *); /*proto*/ -static npy_intp __pyx_f_5talib_7_ta_lib_check_length2(PyArrayObject *, PyArrayObject *); /*proto*/ -static npy_intp __pyx_f_5talib_7_ta_lib_check_length3(PyArrayObject *, PyArrayObject *, PyArrayObject *); /*proto*/ -static npy_intp __pyx_f_5talib_7_ta_lib_check_length4(PyArrayObject *, PyArrayObject *, PyArrayObject *, PyArrayObject *); /*proto*/ -static npy_int __pyx_f_5talib_7_ta_lib_check_begidx1(npy_intp, double *); /*proto*/ -static npy_int __pyx_f_5talib_7_ta_lib_check_begidx2(npy_intp, double *, double *); /*proto*/ -static npy_int __pyx_f_5talib_7_ta_lib_check_begidx3(npy_intp, double *, double *, double *); /*proto*/ -static npy_int __pyx_f_5talib_7_ta_lib_check_begidx4(npy_intp, double *, double *, double *, double *); /*proto*/ -static PyArrayObject *__pyx_f_5talib_7_ta_lib_make_double_array(npy_intp, int); /*proto*/ -static PyArrayObject *__pyx_f_5talib_7_ta_lib_make_int_array(npy_intp, int); /*proto*/ -static TA_FuncHandle const *__pyx_f_5talib_7_ta_lib___ta_getFuncHandle(char *); /*proto*/ -static TA_ParamHolder *__pyx_f_5talib_7_ta_lib___ta_paramHolderAlloc(char *); /*proto*/ -static int __pyx_f_5talib_7_ta_lib___ta_paramHolderFree(TA_ParamHolder *); /*proto*/ -static int __pyx_f_5talib_7_ta_lib___ta_setOptInputParamInteger(TA_ParamHolder *, int, int); /*proto*/ -static int __pyx_f_5talib_7_ta_lib___ta_setOptInputParamReal(TA_ParamHolder *, int, double); /*proto*/ -static int __pyx_f_5talib_7_ta_lib___ta_getLookback(TA_ParamHolder *); /*proto*/ -/* #### Code section: typeinfo ### */ -/* #### Code section: before_global_var ### */ -#define __Pyx_MODULE_NAME "talib._ta_lib" -extern int __pyx_module_is_main_talib___ta_lib; -int __pyx_module_is_main_talib___ta_lib = 0; - -/* Implementation of "talib._ta_lib" */ -/* #### Code section: global_var ### */ -static PyObject *__pyx_builtin_object; -static PyObject *__pyx_builtin_range; -static PyObject *__pyx_builtin_enumerate; -static PyObject *__pyx_builtin_ImportError; -static PyObject *__pyx_builtin_ModuleNotFoundError; -static PyObject *__pyx_builtin_NameError; -static PyObject *__pyx_builtin_property; -static PyObject *__pyx_builtin_xrange; -static PyObject *__pyx_builtin_IndexError; -static PyObject *__pyx_builtin_TypeError; -static PyObject *__pyx_builtin_min; -static PyObject *__pyx_builtin_max; -/* #### Code section: string_decls ### */ -static const char __pyx_k_[] = ": "; -static const char __pyx_k_3[] = "3"; -static const char __pyx_k_b[] = "b"; -static const char __pyx_k_d[] = "d"; -static const char __pyx_k_i[] = "i"; -static const char __pyx_k_n[] = "n"; -static const char __pyx_k_s[] = "s"; -static const char __pyx_k_AD[] = "AD"; -static const char __pyx_k_DX[] = "DX"; -static const char __pyx_k_LN[] = "LN"; -static const char __pyx_k_MA[] = "MA"; -static const char __pyx_k_T3[] = "T3"; -static const char __pyx_k__2[] = ""; -static const char __pyx_k__3[] = ", "; -static const char __pyx_k__4[] = " ("; -static const char __pyx_k__5[] = ")"; -static const char __pyx_k__6[] = "("; -static const char __pyx_k__7[] = " "; -static const char __pyx_k__8[] = "["; -static const char __pyx_k__9[] = "="; -static const char __pyx_k_id[] = "id"; -static const char __pyx_k_in[] = "in"; -static const char __pyx_k_1_1[] = "\200\001\340\004\017\320\017#\2401\330\004\013\2101"; -static const char __pyx_k_ADD[] = "ADD"; -static const char __pyx_k_ADX[] = "ADX"; -static const char __pyx_k_ALL[] = "ALL"; -static const char __pyx_k_APO[] = "APO"; -static const char __pyx_k_ATR[] = "ATR"; -static const char __pyx_k_A_q[] = "\200A\330\010\017\210q"; -static const char __pyx_k_BOP[] = "BOP"; -static const char __pyx_k_CCI[] = "CCI"; -static const char __pyx_k_CMO[] = "CMO"; -static const char __pyx_k_COS[] = "COS"; -static const char __pyx_k_DIV[] = "DIV"; -static const char __pyx_k_Dot[] = "Dot"; -static const char __pyx_k_EMA[] = "EMA"; -static const char __pyx_k_EXP[] = "EXP"; -static const char __pyx_k_Far[] = "Far"; -static const char __pyx_k_IMI[] = "IMI"; -static const char __pyx_k_MAX[] = "MAX"; -static const char __pyx_k_MFI[] = "MFI"; -static const char __pyx_k_MIN[] = "MIN"; -static const char __pyx_k_MOM[] = "MOM"; -static const char __pyx_k_OBV[] = "OBV"; -static const char __pyx_k_PPO[] = "PPO"; -static const char __pyx_k_Q_q[] = "\200\001\340\004\022\220.\240\001\330\004\025\220Q\320\026'\240q"; -static const char __pyx_k_ROC[] = "ROC"; -static const char __pyx_k_RSI[] = "RSI"; -static const char __pyx_k_SAR[] = "SAR"; -static const char __pyx_k_SIN[] = "SIN"; -static const char __pyx_k_SMA[] = "SMA"; -static const char __pyx_k_SUB[] = "SUB"; -static const char __pyx_k_SUM[] = "SUM"; -static const char __pyx_k_TAN[] = "TAN"; -static const char __pyx_k_TSF[] = "TSF"; -static const char __pyx_k_VAR[] = "VAR"; -static const char __pyx_k_WMA[] = "WMA"; -static const char __pyx_k__10[] = "]"; -static const char __pyx_k__11[] = " "; -static const char __pyx_k__12[] = ")\n"; -static const char __pyx_k__13[] = "\n"; -static const char __pyx_k__14[] = "."; -static const char __pyx_k__15[] = "?"; -static const char __pyx_k_all[] = "__all__"; -static const char __pyx_k_arg[] = "arg"; -static const char __pyx_k_doc[] = "__doc__"; -static const char __pyx_k_got[] = ", got "; -static const char __pyx_k_idx[] = "idx"; -static const char __pyx_k_key[] = "key"; -static const char __pyx_k_log[] = "log"; -static const char __pyx_k_low[] = "low"; -static const char __pyx_k_max[] = "max"; -static const char __pyx_k_min[] = "min"; -static const char __pyx_k_msg[] = "msg"; -static const char __pyx_k_nan[] = "nan"; -static const char __pyx_k_out[] = "out"; -static const char __pyx_k_pop[] = "pop"; -static const char __pyx_k_ret[] = "ret"; -static const char __pyx_k_run[] = "run"; -static const char __pyx_k_s_2[] = "%s"; -static const char __pyx_k_s_3[] = "(%s)"; -static const char __pyx_k_s_4[] = " %s"; -static const char __pyx_k_str[] = "__str__"; -static const char __pyx_k_sys[] = "sys"; -static const char __pyx_k_ACOS[] = "ACOS"; -static const char __pyx_k_ADXR[] = "ADXR"; -static const char __pyx_k_ASIN[] = "ASIN"; -static const char __pyx_k_ATAN[] = "ATAN"; -static const char __pyx_k_A_Qd[] = "\200A\330\010\017\320\017%\240Q\240d\250&\260\001\260\021"; -static const char __pyx_k_BETA[] = "BETA"; -static const char __pyx_k_CEIL[] = "CEIL"; -static const char __pyx_k_COSH[] = "COSH"; -static const char __pyx_k_DEMA[] = "DEMA"; -static const char __pyx_k_KAMA[] = "KAMA"; -static const char __pyx_k_Line[] = "Line"; -static const char __pyx_k_MACD[] = "MACD"; -static const char __pyx_k_MAMA[] = "MAMA"; -static const char __pyx_k_MAVP[] = "MAVP"; -static const char __pyx_k_MULT[] = "MULT"; -static const char __pyx_k_NATR[] = "NATR"; -static const char __pyx_k_NONE[] = "NONE"; -static const char __pyx_k_Near[] = "Near"; -static const char __pyx_k_None[] = "None"; -static const char __pyx_k_ROCP[] = "ROCP"; -static const char __pyx_k_ROCR[] = "ROCR"; -static const char __pyx_k_SINH[] = "SINH"; -static const char __pyx_k_SQRT[] = "SQRT"; -static const char __pyx_k_TANH[] = "TANH"; -static const char __pyx_k_TEMA[] = "TEMA"; -static const char __pyx_k_TRIX[] = "TRIX"; -static const char __pyx_k_args[] = "args"; -static const char __pyx_k_call[] = "__call__"; -static const char __pyx_k_copy[] = "copy"; -static const char __pyx_k_docs[] = "docs"; -static const char __pyx_k_flag[] = "flag"; -static const char __pyx_k_func[] = "__func__"; -static const char __pyx_k_help[] = "help"; -static const char __pyx_k_high[] = "high"; -static const char __pyx_k_info[] = "info"; -static const char __pyx_k_init[] = "__init__"; -static const char __pyx_k_keys[] = "keys"; -static const char __pyx_k_main[] = "__main__"; -static const char __pyx_k_math[] = "math"; -static const char __pyx_k_name[] = "name"; -static const char __pyx_k_open[] = "open"; -static const char __pyx_k_real[] = "real"; -static const char __pyx_k_repr[] = "__repr__"; -static const char __pyx_k_self[] = "self"; -static const char __pyx_k_spec[] = "__spec__"; -static const char __pyx_k_test[] = "__test__"; -static const char __pyx_k_type[] = "type_"; -static const char __pyx_k_ADOSC[] = "ADOSC"; -static const char __pyx_k_AROON[] = "AROON"; -static const char __pyx_k_A_q_q[] = "\200A\330\010\017\210q\220\007\220q\230\001"; -static const char __pyx_k_A_t85[] = "\200A\360\n\000\t\020\210t\2208\2305\240\001\240\021"; -static const char __pyx_k_A_uAS[] = "\200A\330\010\017\210u\220A\220S\230\001"; -static const char __pyx_k_A_uBd[] = "\200A\330\010\017\210u\220B\220d\230!"; -static const char __pyx_k_Equal[] = "Equal"; -static const char __pyx_k_FLOOR[] = "FLOOR"; -static const char __pyx_k_LOG10[] = "LOG10"; -static const char __pyx_k_STOCH[] = "STOCH"; -static const char __pyx_k_TA_AD[] = "TA_AD"; -static const char __pyx_k_TA_DX[] = "TA_DX"; -static const char __pyx_k_TA_LN[] = "TA_LN"; -static const char __pyx_k_TA_MA[] = "TA_MA"; -static const char __pyx_k_TA_T3[] = "TA_T3"; -static const char __pyx_k_TRIMA[] = "TRIMA"; -static const char __pyx_k_WILLR[] = "WILLR"; -static const char __pyx_k_a_QoQ[] = "\200\001\340\004\022\220,\230a\330\004\025\220Q\220o\240Q"; -static const char __pyx_k_ascii[] = "ascii"; -static const char __pyx_k_clone[] = "clone"; -static const char __pyx_k_close[] = "close"; -static const char __pyx_k_empty[] = "empty"; -static const char __pyx_k_flags[] = "flags"; -static const char __pyx_k_group[] = "group"; -static const char __pyx_k_index[] = "index"; -static const char __pyx_k_items[] = "items"; -static const char __pyx_k_local[] = "local"; -static const char __pyx_k_lower[] = "lower"; -static const char __pyx_k_nbdev[] = "nbdev"; -static const char __pyx_k_numpy[] = "numpy"; -static const char __pyx_k_optIn[] = "optIn"; -static const char __pyx_k_param[] = "param"; -static const char __pyx_k_price[] = "price"; -static const char __pyx_k_range[] = "range"; -static const char __pyx_k_real0[] = "real0"; -static const char __pyx_k_real1[] = "real1"; -static const char __pyx_k_table[] = "table"; -static const char __pyx_k_upper[] = "upper"; -static const char __pyx_k_value[] = "value"; -static const char __pyx_k_AVGDEV[] = "AVGDEV"; -static const char __pyx_k_A_t81A[] = "\200A\330\010\017\210t\2208\2301\230A"; -static const char __pyx_k_BBANDS[] = "BBANDS"; -static const char __pyx_k_CORREL[] = "CORREL"; -static const char __pyx_k_Inputs[] = "Inputs:"; -static const char __pyx_k_MINMAX[] = "MINMAX"; -static const char __pyx_k_SAREXT[] = "SAREXT"; -static const char __pyx_k_STDDEV[] = "STDDEV"; -static const char __pyx_k_STOCHF[] = "STOCHF"; -static const char __pyx_k_Series[] = "Series"; -static const char __pyx_k_TA_ADD[] = "TA_ADD"; -static const char __pyx_k_TA_ADX[] = "TA_ADX"; -static const char __pyx_k_TA_APO[] = "TA_APO"; -static const char __pyx_k_TA_ATR[] = "TA_ATR"; -static const char __pyx_k_TA_BOP[] = "TA_BOP"; -static const char __pyx_k_TA_CCI[] = "TA_CCI"; -static const char __pyx_k_TA_CMO[] = "TA_CMO"; -static const char __pyx_k_TA_COS[] = "TA_COS"; -static const char __pyx_k_TA_DIV[] = "TA_DIV"; -static const char __pyx_k_TA_EMA[] = "TA_EMA"; -static const char __pyx_k_TA_EXP[] = "TA_EXP"; -static const char __pyx_k_TA_IMI[] = "TA_IMI"; -static const char __pyx_k_TA_MAX[] = "TA_MAX"; -static const char __pyx_k_TA_MFI[] = "TA_MFI"; -static const char __pyx_k_TA_MIN[] = "TA_MIN"; -static const char __pyx_k_TA_MOM[] = "TA_MOM"; -static const char __pyx_k_TA_OBV[] = "TA_OBV"; -static const char __pyx_k_TA_PPO[] = "TA_PPO"; -static const char __pyx_k_TA_ROC[] = "TA_ROC"; -static const char __pyx_k_TA_RSI[] = "TA_RSI"; -static const char __pyx_k_TA_SAR[] = "TA_SAR"; -static const char __pyx_k_TA_SIN[] = "TA_SIN"; -static const char __pyx_k_TA_SMA[] = "TA_SMA"; -static const char __pyx_k_TA_SUB[] = "TA_SUB"; -static const char __pyx_k_TA_SUM[] = "TA_SUM"; -static const char __pyx_k_TA_TAN[] = "TA_TAN"; -static const char __pyx_k_TA_TSF[] = "TA_TSF"; -static const char __pyx_k_TA_VAR[] = "TA_VAR"; -static const char __pyx_k_TA_WMA[] = "TA_WMA"; -static const char __pyx_k_TRANGE[] = "TRANGE"; -static const char __pyx_k_ULTOSC[] = "ULTOSC"; -static const char __pyx_k_append[] = "append"; -static const char __pyx_k_aq_Q_Q[] = "\200\001\340\004\022\320\022&\240a\240q\330\004\025\220Q\320\026-\250Q"; -static const char __pyx_k_astype[] = "astype"; -static const char __pyx_k_begidx[] = "begidx"; -static const char __pyx_k_decode[] = "decode"; -static const char __pyx_k_endidx[] = "endidx"; -static const char __pyx_k_factor[] = "factor"; -static const char __pyx_k_groups[] = "groups"; -static const char __pyx_k_holder[] = "holder"; -static const char __pyx_k_kwargs[] = "kwargs"; -static const char __pyx_k_length[] = "length"; -static const char __pyx_k_lookup[] = "_lookup"; -static const char __pyx_k_matype[] = "matype"; -static const char __pyx_k_module[] = "__module__"; -static const char __pyx_k_name_2[] = "__name__"; -static const char __pyx_k_object[] = "object"; -static const char __pyx_k_outmax[] = "outmax"; -static const char __pyx_k_outmin[] = "outmin"; -static const char __pyx_k_output[] = "output"; -static const char __pyx_k_pandas[] = "pandas"; -static const char __pyx_k_params[] = "params"; -static const char __pyx_k_period[] = "period"; -static const char __pyx_k_polars[] = "polars"; -static const char __pyx_k_price0[] = "price0"; -static const char __pyx_k_price1[] = "price1"; -static const char __pyx_k_prices[] = "prices"; -static const char __pyx_k_schema[] = "schema"; -static const char __pyx_k_series[] = "series"; -static const char __pyx_k_type_2[] = "type"; -static const char __pyx_k_update[] = "update"; -static const char __pyx_k_values[] = "values"; -static const char __pyx_k_volume[] = "volume"; -static const char __pyx_k_2_1_Q_9[] = "\200\001\340\004\022\320\0222\260!\2601\330\004\025\220Q\320\0269\270\021"; -static const char __pyx_k_A_t85_Q[] = "\200A\360\n\000\t\020\210t\2208\2305\240\005\240Q"; -static const char __pyx_k_A_wat81[] = "\200A\330\010\017\210w\220a\220t\2308\2401"; -static const char __pyx_k_CDLDOJI[] = "CDLDOJI"; -static const char __pyx_k_HT_SINE[] = "HT_SINE"; -static const char __pyx_k_HighLow[] = "HighLow"; -static const char __pyx_k_MACDEXT[] = "MACDEXT"; -static const char __pyx_k_MACDFIX[] = "MACDFIX"; -static const char __pyx_k_MA_Type[] = "MA_Type"; -static const char __pyx_k_Outputs[] = "Outputs:"; -static const char __pyx_k_PLUS_DI[] = "PLUS_DI"; -static const char __pyx_k_PLUS_DM[] = "PLUS_DM"; -static const char __pyx_k_Qa_Qa_1[] = "\200\001\340\004\034\320\034-\250Q\250a\330\004\020\320\020%\240Q\240a\330\004\013\2101"; -static const char __pyx_k_ROCR100[] = "ROCR100"; -static const char __pyx_k_Shadows[] = "Shadows"; -static const char __pyx_k_TA_ACOS[] = "TA_ACOS"; -static const char __pyx_k_TA_ADXR[] = "TA_ADXR"; -static const char __pyx_k_TA_ASIN[] = "TA_ASIN"; -static const char __pyx_k_TA_ATAN[] = "TA_ATAN"; -static const char __pyx_k_TA_BETA[] = "TA_BETA"; -static const char __pyx_k_TA_CEIL[] = "TA_CEIL"; -static const char __pyx_k_TA_COSH[] = "TA_COSH"; -static const char __pyx_k_TA_DEMA[] = "TA_DEMA"; -static const char __pyx_k_TA_KAMA[] = "TA_KAMA"; -static const char __pyx_k_TA_MACD[] = "TA_MACD"; -static const char __pyx_k_TA_MAMA[] = "TA_MAMA"; -static const char __pyx_k_TA_MAVP[] = "TA_MAVP"; -static const char __pyx_k_TA_MULT[] = "TA_MULT"; -static const char __pyx_k_TA_NATR[] = "TA_NATR"; -static const char __pyx_k_TA_ROCP[] = "TA_ROCP"; -static const char __pyx_k_TA_ROCR[] = "TA_ROCR"; -static const char __pyx_k_TA_SINH[] = "TA_SINH"; -static const char __pyx_k_TA_SQRT[] = "TA_SQRT"; -static const char __pyx_k_TA_TANH[] = "TA_TANH"; -static const char __pyx_k_TA_TEMA[] = "TA_TEMA"; -static const char __pyx_k_TA_TRIX[] = "TA_TRIX"; -static const char __pyx_k_columns[] = "columns"; -static const char __pyx_k_getitem[] = "__getitem__"; -static const char __pyx_k_integer[] = "integer"; -static const char __pyx_k_local_2[] = "__local"; -static const char __pyx_k_max_int[] = "max_int"; -static const char __pyx_k_maximum[] = "maximum"; -static const char __pyx_k_min_int[] = "min_int"; -static const char __pyx_k_missing[] = "missing"; -static const char __pyx_k_nbdevdn[] = "nbdevdn"; -static const char __pyx_k_nbdevup[] = "nbdevup"; -static const char __pyx_k_outfama[] = "outfama"; -static const char __pyx_k_outmacd[] = "outmacd"; -static const char __pyx_k_outmama[] = "outmama"; -static const char __pyx_k_outputs[] = "outputs"; -static const char __pyx_k_outreal[] = "outreal"; -static const char __pyx_k_outsine[] = "outsine"; -static const char __pyx_k_periods[] = "periods"; -static const char __pyx_k_prepare[] = "__prepare__"; -static const char __pyx_k_q_1_Q_a[] = "\200\001\340\004\022\320\022'\240q\250\r\260[\300\013\3101\330\004\025\220Q\320\026.\250a"; -static const char __pyx_k_replace[] = "replace"; -static const char __pyx_k_results[] = "results"; -static const char __pyx_k_retCode[] = "retCode"; -static const char __pyx_k_unicode[] = "__unicode__"; -static const char __pyx_k_version[] = "version"; -static const char __pyx_k_vfactor[] = "vfactor"; -static const char __pyx_k_ACCBANDS[] = "ACCBANDS"; -static const char __pyx_k_AROONOSC[] = "AROONOSC"; -static const char __pyx_k_AVGPRICE[] = "AVGPRICE"; -static const char __pyx_k_BodyDoji[] = "BodyDoji"; -static const char __pyx_k_BodyLong[] = "BodyLong"; -static const char __pyx_k_Function[] = "Function"; -static const char __pyx_k_MAXINDEX[] = "MAXINDEX"; -static const char __pyx_k_MEDPRICE[] = "MEDPRICE"; -static const char __pyx_k_MIDPOINT[] = "MIDPOINT"; -static const char __pyx_k_MIDPRICE[] = "MIDPRICE"; -static const char __pyx_k_MININDEX[] = "MININDEX"; -static const char __pyx_k_MINUS_DI[] = "MINUS_DI"; -static const char __pyx_k_MINUS_DM[] = "MINUS_DM"; -static const char __pyx_k_N_1_A_t1[] = "\200N\220!\360\016\000\t\014\2101\330\014\020\320\020!\240\021\240!\330\010\014\320\014\034\230A\330\010\017\210t\2201"; -static const char __pyx_k_RealBody[] = "RealBody"; -static const char __pyx_k_STOCHRSI[] = "STOCHRSI"; -static const char __pyx_k_TA_ADOSC[] = "TA_ADOSC"; -static const char __pyx_k_TA_AROON[] = "TA_AROON"; -static const char __pyx_k_TA_FLOOR[] = "TA_FLOOR"; -static const char __pyx_k_TA_LOG10[] = "TA_LOG10"; -static const char __pyx_k_TA_STOCH[] = "TA_STOCH"; -static const char __pyx_k_TA_TRIMA[] = "TA_TRIMA"; -static const char __pyx_k_TA_WILLR[] = "TA_WILLR"; -static const char __pyx_k_TYPPRICE[] = "TYPPRICE"; -static const char __pyx_k_WCLPRICE[] = "WCLPRICE"; -static const char __pyx_k_add_note[] = "add_note"; -static const char __pyx_k_defaults[] = "defaults"; -static const char __pyx_k_expected[] = " (expected "; -static const char __pyx_k_is_empty[] = "is_empty"; -static const char __pyx_k_lookback[] = "lookback"; -static const char __pyx_k_low_data[] = "low_data"; -static const char __pyx_k_outfastd[] = "outfastd"; -static const char __pyx_k_outfastk[] = "outfastk"; -static const char __pyx_k_outslowd[] = "outslowd"; -static const char __pyx_k_outslowk[] = "outslowk"; -static const char __pyx_k_property[] = "property"; -static const char __pyx_k_qualname[] = "__qualname__"; -static const char __pyx_k_ret_code[] = "ret_code"; -static const char __pyx_k_set_name[] = "__set_name__"; -static const char __pyx_k_to_numpy[] = "to_numpy"; -static const char __pyx_k_A_t85_Q_2[] = "\200A\360\n\000\t\020\210t\2208\2305\240\001\240\037\260\005\260Q"; -static const char __pyx_k_BodyShort[] = "BodyShort"; -static const char __pyx_k_CDL2CROWS[] = "CDL2CROWS"; -static const char __pyx_k_CDLHAMMER[] = "CDLHAMMER"; -static const char __pyx_k_CDLHARAMI[] = "CDLHARAMI"; -static const char __pyx_k_CDLINNECK[] = "CDLINNECK"; -static const char __pyx_k_CDLONNECK[] = "CDLONNECK"; -static const char __pyx_k_CDLTAKURI[] = "CDLTAKURI"; -static const char __pyx_k_DataFrame[] = "DataFrame"; -static const char __pyx_k_HT_PHASOR[] = "HT_PHASOR"; -static const char __pyx_k_Histogram[] = "Histogram"; -static const char __pyx_k_LINEARREG[] = "LINEARREG"; -static const char __pyx_k_NameError[] = "NameError"; -static const char __pyx_k_RangeType[] = "RangeType"; -static const char __pyx_k_TA_AVGDEV[] = "TA_AVGDEV"; -static const char __pyx_k_TA_BBANDS[] = "TA_BBANDS"; -static const char __pyx_k_TA_CORREL[] = "TA_CORREL"; -static const char __pyx_k_TA_MINMAX[] = "TA_MINMAX"; -static const char __pyx_k_TA_SAREXT[] = "TA_SAREXT"; -static const char __pyx_k_TA_STDDEV[] = "TA_STDDEV"; -static const char __pyx_k_TA_STOCHF[] = "TA_STOCHF"; -static const char __pyx_k_TA_TRANGE[] = "TA_TRANGE"; -static const char __pyx_k_TA_ULTOSC[] = "TA_ULTOSC"; -static const char __pyx_k_TypeError[] = "TypeError"; -static const char __pyx_k_avgperiod[] = "avgperiod"; -static const char __pyx_k_bytes2str[] = "bytes2str"; -static const char __pyx_k_enumerate[] = "enumerate"; -static const char __pyx_k_fastlimit[] = "fastlimit"; -static const char __pyx_k_func_args[] = "func_args"; -static const char __pyx_k_func_info[] = "func_info"; -static const char __pyx_k_func_line[] = "func_line"; -static const char __pyx_k_functions[] = "functions"; -static const char __pyx_k_get_flags[] = "__get_flags"; -static const char __pyx_k_high_data[] = "high_data"; -static const char __pyx_k_maxperiod[] = "maxperiod"; -static const char __pyx_k_metaclass[] = "__metaclass__"; -static const char __pyx_k_minperiod[] = "minperiod"; -static const char __pyx_k_open_data[] = "open_data"; -static const char __pyx_k_opt_input[] = "opt_input"; -static const char __pyx_k_outbegidx[] = "outbegidx"; -static const char __pyx_k_outmaxidx[] = "outmaxidx"; -static const char __pyx_k_outminidx[] = "outminidx"; -static const char __pyx_k_rangetype[] = "rangetype"; -static const char __pyx_k_real_data[] = "real_data"; -static const char __pyx_k_slowlimit[] = "slowlimit"; -static const char __pyx_k_str2bytes[] = "str2bytes"; -static const char __pyx_k_stream_AD[] = "stream_AD"; -static const char __pyx_k_stream_DX[] = "stream_DX"; -static const char __pyx_k_stream_LN[] = "stream_LN"; -static const char __pyx_k_stream_MA[] = "stream_MA"; -static const char __pyx_k_stream_T3[] = "stream_T3"; -static const char __pyx_k_stream__s[] = "stream_%s"; -static const char __pyx_k_threading[] = "threading"; -static const char __pyx_k_timeStamp[] = "timeStamp"; -static const char __pyx_k_CDL3INSIDE[] = "CDL3INSIDE"; -static const char __pyx_k_CDLHIKKAKE[] = "CDLHIKKAKE"; -static const char __pyx_k_CDLKICKING[] = "CDLKICKING"; -static const char __pyx_k_CDLMATHOLD[] = "CDLMATHOLD"; -static const char __pyx_k_CDLTRISTAR[] = "CDLTRISTAR"; -static const char __pyx_k_HT_DCPHASE[] = "HT_DCPHASE"; -static const char __pyx_k_IndexError[] = "IndexError"; -static const char __pyx_k_Parameters[] = "Parameters:"; -static const char __pyx_k_Qa_q_A_Q_a[] = "\200\001\340\004\034\320\034-\250Q\250a\330\004\022\320\022'\240q\250\004\250A\330\004\025\220Q\320\026.\250a"; -static const char __pyx_k_ShadowLong[] = "ShadowLong"; -static const char __pyx_k_TA_CDLDOJI[] = "TA_CDLDOJI"; -static const char __pyx_k_TA_HT_SINE[] = "TA_HT_SINE"; -static const char __pyx_k_TA_MACDEXT[] = "TA_MACDEXT"; -static const char __pyx_k_TA_MACDFIX[] = "TA_MACDFIX"; -static const char __pyx_k_TA_PLUS_DI[] = "TA_PLUS_DI"; -static const char __pyx_k_TA_PLUS_DM[] = "TA_PLUS_DM"; -static const char __pyx_k_TA_ROCR100[] = "TA_ROCR100"; -static const char __pyx_k_close_data[] = "close_data"; -static const char __pyx_k_fastmatype[] = "fastmatype"; -static const char __pyx_k_fastperiod[] = "fastperiod"; -static const char __pyx_k_input_name[] = "input_name"; -static const char __pyx_k_num_inputs[] = "num_inputs"; -static const char __pyx_k_opt_inputs[] = "opt_inputs"; -static const char __pyx_k_outaroonup[] = "outaroonup"; -static const char __pyx_k_outinphase[] = "outinphase"; -static const char __pyx_k_outinteger[] = "outinteger"; -static const char __pyx_k_param_name[] = "param_name"; -static const char __pyx_k_parameters[] = "parameters"; -static const char __pyx_k_real0_data[] = "real0_data"; -static const char __pyx_k_real1_data[] = "real1_data"; -static const char __pyx_k_skip_first[] = "skip_first"; -static const char __pyx_k_slowmatype[] = "slowmatype"; -static const char __pyx_k_slowperiod[] = "slowperiod"; -static const char __pyx_k_startvalue[] = "startvalue"; -static const char __pyx_k_stream_ADD[] = "stream_ADD"; -static const char __pyx_k_stream_ADX[] = "stream_ADX"; -static const char __pyx_k_stream_APO[] = "stream_APO"; -static const char __pyx_k_stream_ATR[] = "stream_ATR"; -static const char __pyx_k_stream_BOP[] = "stream_BOP"; -static const char __pyx_k_stream_CCI[] = "stream_CCI"; -static const char __pyx_k_stream_CMO[] = "stream_CMO"; -static const char __pyx_k_stream_COS[] = "stream_COS"; -static const char __pyx_k_stream_DIV[] = "stream_DIV"; -static const char __pyx_k_stream_EMA[] = "stream_EMA"; -static const char __pyx_k_stream_EXP[] = "stream_EXP"; -static const char __pyx_k_stream_IMI[] = "stream_IMI"; -static const char __pyx_k_stream_MAX[] = "stream_MAX"; -static const char __pyx_k_stream_MFI[] = "stream_MFI"; -static const char __pyx_k_stream_MIN[] = "stream_MIN"; -static const char __pyx_k_stream_MOM[] = "stream_MOM"; -static const char __pyx_k_stream_OBV[] = "stream_OBV"; -static const char __pyx_k_stream_PPO[] = "stream_PPO"; -static const char __pyx_k_stream_ROC[] = "stream_ROC"; -static const char __pyx_k_stream_RSI[] = "stream_RSI"; -static const char __pyx_k_stream_SAR[] = "stream_SAR"; -static const char __pyx_k_stream_SIN[] = "stream_SIN"; -static const char __pyx_k_stream_SMA[] = "stream_SMA"; -static const char __pyx_k_stream_SUB[] = "stream_SUB"; -static const char __pyx_k_stream_SUM[] = "stream_SUM"; -static const char __pyx_k_stream_TAN[] = "stream_TAN"; -static const char __pyx_k_stream_TSF[] = "stream_TSF"; -static const char __pyx_k_stream_VAR[] = "stream_VAR"; -static const char __pyx_k_stream_WMA[] = "stream_WMA"; -static const char __pyx_k_ta_version[] = "__ta_version__"; -static const char __pyx_k_timeperiod[] = "timeperiod"; -static const char __pyx_k_ARRAY_TYPES[] = "__ARRAY_TYPES"; -static const char __pyx_k_CDL3OUTSIDE[] = "CDL3OUTSIDE"; -static const char __pyx_k_CDLBELTHOLD[] = "CDLBELTHOLD"; -static const char __pyx_k_CDLDOJISTAR[] = "CDLDOJISTAR"; -static const char __pyx_k_CDLHIGHWAVE[] = "CDLHIGHWAVE"; -static const char __pyx_k_CDLLONGLINE[] = "CDLLONGLINE"; -static const char __pyx_k_CDLMARUBOZU[] = "CDLMARUBOZU"; -static const char __pyx_k_CDLPIERCING[] = "CDLPIERCING"; -static const char __pyx_k_Dashed_Line[] = "Dashed Line"; -static const char __pyx_k_Dotted_Line[] = "Dotted Line"; -static const char __pyx_k_HT_DCPERIOD[] = "HT_DCPERIOD"; -static const char __pyx_k_ImportError[] = "ImportError"; -static const char __pyx_k_MINMAXINDEX[] = "MINMAXINDEX"; -static const char __pyx_k_OrderedDict[] = "OrderedDict"; -static const char __pyx_k_ShadowShort[] = "ShadowShort"; -static const char __pyx_k_TA_ACCBANDS[] = "TA_ACCBANDS"; -static const char __pyx_k_TA_AROONOSC[] = "TA_AROONOSC"; -static const char __pyx_k_TA_AVGPRICE[] = "TA_AVGPRICE"; -static const char __pyx_k_TA_MAXINDEX[] = "TA_MAXINDEX"; -static const char __pyx_k_TA_MEDPRICE[] = "TA_MEDPRICE"; -static const char __pyx_k_TA_MIDPOINT[] = "TA_MIDPOINT"; -static const char __pyx_k_TA_MIDPRICE[] = "TA_MIDPRICE"; -static const char __pyx_k_TA_MININDEX[] = "TA_MININDEX"; -static const char __pyx_k_TA_MINUS_DI[] = "TA_MINUS_DI"; -static const char __pyx_k_TA_MINUS_DM[] = "TA_MINUS_DM"; -static const char __pyx_k_TA_STOCHRSI[] = "TA_STOCHRSI"; -static const char __pyx_k_TA_Shutdown[] = "TA_Shutdown"; -static const char __pyx_k_TA_TYPPRICE[] = "TA_TYPPRICE"; -static const char __pyx_k_TA_WCLPRICE[] = "TA_WCLPRICE"; -static const char __pyx_k_any_ndarray[] = "(any ndarray)"; -static const char __pyx_k_collections[] = "collections"; -static const char __pyx_k_func_object[] = "func_object"; -static const char __pyx_k_input_names[] = "input_names"; -static const char __pyx_k_mro_entries[] = "__mro_entries__"; -static const char __pyx_k_num_outputs[] = "num_outputs"; -static const char __pyx_k_ordereddict[] = "ordereddict"; -static const char __pyx_k_outleadsine[] = "outleadsine"; -static const char __pyx_k_outmacdhist[] = "outmacdhist"; -static const char __pyx_k_output_name[] = "output_name"; -static const char __pyx_k_penetration[] = "penetration"; -static const char __pyx_k_settingtype[] = "settingtype"; -static const char __pyx_k_stream_ACOS[] = "stream_ACOS"; -static const char __pyx_k_stream_ADXR[] = "stream_ADXR"; -static const char __pyx_k_stream_ASIN[] = "stream_ASIN"; -static const char __pyx_k_stream_ATAN[] = "stream_ATAN"; -static const char __pyx_k_stream_BETA[] = "stream_BETA"; -static const char __pyx_k_stream_CEIL[] = "stream_CEIL"; -static const char __pyx_k_stream_COSH[] = "stream_COSH"; -static const char __pyx_k_stream_DEMA[] = "stream_DEMA"; -static const char __pyx_k_stream_KAMA[] = "stream_KAMA"; -static const char __pyx_k_stream_MACD[] = "stream_MACD"; -static const char __pyx_k_stream_MAMA[] = "stream_MAMA"; -static const char __pyx_k_stream_MAVP[] = "stream_MAVP"; -static const char __pyx_k_stream_MULT[] = "stream_MULT"; -static const char __pyx_k_stream_NATR[] = "stream_NATR"; -static const char __pyx_k_stream_ROCP[] = "stream_ROCP"; -static const char __pyx_k_stream_ROCR[] = "stream_ROCR"; -static const char __pyx_k_stream_SINH[] = "stream_SINH"; -static const char __pyx_k_stream_SQRT[] = "stream_SQRT"; -static const char __pyx_k_stream_TANH[] = "stream_TANH"; -static const char __pyx_k_stream_TEMA[] = "stream_TEMA"; -static const char __pyx_k_stream_TRIX[] = "stream_TRIX"; -static const char __pyx_k_ta_shutdown[] = "_ta_shutdown"; -static const char __pyx_k_timeperiod1[] = "timeperiod1"; -static const char __pyx_k_timeperiod2[] = "timeperiod2"; -static const char __pyx_k_timeperiod3[] = "timeperiod3"; -static const char __pyx_k_update_info[] = "update_info"; -static const char __pyx_k_value_range[] = "value_range"; -static const char __pyx_k_volume_data[] = "volume_data"; -static const char __pyx_k_BodyVeryLong[] = "BodyVeryLong"; -static const char __pyx_k_CDLBREAKAWAY[] = "CDLBREAKAWAY"; -static const char __pyx_k_CDLENGULFING[] = "CDLENGULFING"; -static const char __pyx_k_CDLSHORTLINE[] = "CDLSHORTLINE"; -static const char __pyx_k_CDLTASUKIGAP[] = "CDLTASUKIGAP"; -static const char __pyx_k_CDLTHRUSTING[] = "CDLTHRUSTING"; -static const char __pyx_k_Function_run[] = "Function.run"; -static const char __pyx_k_HT_TRENDLINE[] = "HT_TRENDLINE"; -static const char __pyx_k_HT_TRENDMODE[] = "HT_TRENDMODE"; -static const char __pyx_k_Pattern_Bool[] = "Pattern (Bool)"; -static const char __pyx_k_TA_CDL2CROWS[] = "TA_CDL2CROWS"; -static const char __pyx_k_TA_CDLHAMMER[] = "TA_CDLHAMMER"; -static const char __pyx_k_TA_CDLHARAMI[] = "TA_CDLHARAMI"; -static const char __pyx_k_TA_CDLINNECK[] = "TA_CDLINNECK"; -static const char __pyx_k_TA_CDLONNECK[] = "TA_CDLONNECK"; -static const char __pyx_k_TA_CDLTAKURI[] = "TA_CDLTAKURI"; -static const char __pyx_k_TA_HT_PHASOR[] = "TA_HT_PHASOR"; -static const char __pyx_k_TA_LINEARREG[] = "TA_LINEARREG"; -static const char __pyx_k_acceleration[] = "acceleration"; -static const char __pyx_k_column_stack[] = "column_stack"; -static const char __pyx_k_display_name[] = "display_name"; -static const char __pyx_k_fastd_matype[] = "fastd_matype"; -static const char __pyx_k_fastd_period[] = "fastd_period"; -static const char __pyx_k_fastk_period[] = "fastk_period"; -static const char __pyx_k_import_error[] = "import_error"; -static const char __pyx_k_initializing[] = "_initializing"; -static const char __pyx_k_input_arrays[] = "input_arrays"; -static const char __pyx_k_is_coroutine[] = "_is_coroutine"; -static const char __pyx_k_missing_keys[] = "missing_keys"; -static const char __pyx_k_openInterest[] = "openInterest"; -static const char __pyx_k_outaroondown[] = "outaroondown"; -static const char __pyx_k_outnbelement[] = "outnbelement"; -static const char __pyx_k_output_flags[] = "output_flags"; -static const char __pyx_k_output_names[] = "output_names"; -static const char __pyx_k_periods_data[] = "periods_data"; -static const char __pyx_k_price_series[] = "price_series"; -static const char __pyx_k_signalmatype[] = "signalmatype"; -static const char __pyx_k_signalperiod[] = "signalperiod"; -static const char __pyx_k_slowd_matype[] = "slowd_matype"; -static const char __pyx_k_slowd_period[] = "slowd_period"; -static const char __pyx_k_slowk_matype[] = "slowk_matype"; -static const char __pyx_k_slowk_period[] = "slowk_period"; -static const char __pyx_k_stream_ADOSC[] = "stream_ADOSC"; -static const char __pyx_k_stream_AROON[] = "stream_AROON"; -static const char __pyx_k_stream_FLOOR[] = "stream_FLOOR"; -static const char __pyx_k_stream_LOG10[] = "stream_LOG10"; -static const char __pyx_k_stream_STOCH[] = "stream_STOCH"; -static const char __pyx_k_stream_TRIMA[] = "stream_TRIMA"; -static const char __pyx_k_stream_WILLR[] = "stream_WILLR"; -static const char __pyx_k_CDLHANGINGMAN[] = "CDLHANGINGMAN"; -static const char __pyx_k_CDLHIKKAKEMOD[] = "CDLHIKKAKEMOD"; -static const char __pyx_k_Function_info[] = "Function.info"; -static const char __pyx_k_PANDAS_SERIES[] = "__PANDAS_SERIES"; -static const char __pyx_k_POLARS_SERIES[] = "__POLARS_SERIES"; -static const char __pyx_k_TA_CDL3INSIDE[] = "TA_CDL3INSIDE"; -static const char __pyx_k_TA_CDLHIKKAKE[] = "TA_CDLHIKKAKE"; -static const char __pyx_k_TA_CDLKICKING[] = "TA_CDLKICKING"; -static const char __pyx_k_TA_CDLMATHOLD[] = "TA_CDLMATHOLD"; -static const char __pyx_k_TA_CDLTRISTAR[] = "TA_CDLTRISTAR"; -static const char __pyx_k_TA_FUNC_FLAGS[] = "TA_FUNC_FLAGS"; -static const char __pyx_k_TA_HT_DCPHASE[] = "TA_HT_DCPHASE"; -static const char __pyx_k_TA_Initialize[] = "TA_Initialize"; -static const char __pyx_k_Unknown_Error[] = "Unknown Error"; -static const char __pyx_k_call_function[] = "__call_function"; -static const char __pyx_k_class_getitem[] = "__class_getitem__"; -static const char __pyx_k_default_value[] = "default_value"; -static const char __pyx_k_documentation[] = "documentation"; -static const char __pyx_k_function_name[] = "function_name"; -static const char __pyx_k_outmacdsignal[] = "outmacdsignal"; -static const char __pyx_k_outputs_valid[] = "outputs_valid"; -static const char __pyx_k_outquadrature[] = "outquadrature"; -static const char __pyx_k_stream_AVGDEV[] = "stream_AVGDEV"; -static const char __pyx_k_stream_BBANDS[] = "stream_BBANDS"; -static const char __pyx_k_stream_CORREL[] = "stream_CORREL"; -static const char __pyx_k_stream_MINMAX[] = "stream_MINMAX"; -static const char __pyx_k_stream_SAREXT[] = "stream_SAREXT"; -static const char __pyx_k_stream_STDDEV[] = "stream_STDDEV"; -static const char __pyx_k_stream_STOCHF[] = "stream_STOCHF"; -static const char __pyx_k_stream_TRANGE[] = "stream_TRANGE"; -static const char __pyx_k_stream_ULTOSC[] = "stream_ULTOSC"; -static const char __pyx_k_ta_initialize[] = "_ta_initialize"; -static const char __pyx_k_talib__ta_lib[] = "talib._ta_lib"; -static const char __pyx_k_CDL3BLACKCROWS[] = "CDL3BLACKCROWS"; -static const char __pyx_k_CDL3LINESTRIKE[] = "CDL3LINESTRIKE"; -static const char __pyx_k_CDLEVENINGSTAR[] = "CDLEVENINGSTAR"; -static const char __pyx_k_CDLHARAMICROSS[] = "CDLHARAMICROSS"; -static const char __pyx_k_CDLMATCHINGLOW[] = "CDLMATCHINGLOW"; -static const char __pyx_k_CDLMORNINGSTAR[] = "CDLMORNINGSTAR"; -static const char __pyx_k_CDLRICKSHAWMAN[] = "CDLRICKSHAWMAN"; -static const char __pyx_k_CDLSPINNINGTOP[] = "CDLSPINNINGTOP"; -static const char __pyx_k_Function___str[] = "Function.__str__"; -static const char __pyx_k_Function__name[] = "_Function__name"; -static const char __pyx_k_MA_Type___init[] = "MA_Type.__init__"; -static const char __pyx_k_ShadowVeryLong[] = "ShadowVeryLong"; -static const char __pyx_k_TA_CDL3OUTSIDE[] = "TA_CDL3OUTSIDE"; -static const char __pyx_k_TA_CDLBELTHOLD[] = "TA_CDLBELTHOLD"; -static const char __pyx_k_TA_CDLDOJISTAR[] = "TA_CDLDOJISTAR"; -static const char __pyx_k_TA_CDLHIGHWAVE[] = "TA_CDLHIGHWAVE"; -static const char __pyx_k_TA_CDLLONGLINE[] = "TA_CDLLONGLINE"; -static const char __pyx_k_TA_CDLMARUBOZU[] = "TA_CDLMARUBOZU"; -static const char __pyx_k_TA_CDLPIERCING[] = "TA_CDLPIERCING"; -static const char __pyx_k_TA_GetFuncInfo[] = "TA_GetFuncInfo"; -static const char __pyx_k_TA_GetLookback[] = "TA_GetLookback"; -static const char __pyx_k_TA_HT_DCPERIOD[] = "TA_HT_DCPERIOD"; -static const char __pyx_k_TA_INPUT_FLAGS[] = "TA_INPUT_FLAGS"; -static const char __pyx_k_TA_MINMAXINDEX[] = "TA_MINMAXINDEX"; -static const char __pyx_k_function_flags[] = "function_flags"; -static const char __pyx_k_get_parameters[] = "get_parameters"; -static const char __pyx_k_input_arrays_2[] = "[input_arrays]"; -static const char __pyx_k_num_opt_inputs[] = "num_opt_inputs"; -static const char __pyx_k_outmaxidx_data[] = "outmaxidx_data"; -static const char __pyx_k_outminidx_data[] = "outminidx_data"; -static const char __pyx_k_set_parameters[] = "set_parameters"; -static const char __pyx_k_stream_CDLDOJI[] = "stream_CDLDOJI"; -static const char __pyx_k_stream_HT_SINE[] = "stream_HT_SINE"; -static const char __pyx_k_stream_MACDEXT[] = "stream_MACDEXT"; -static const char __pyx_k_stream_MACDFIX[] = "stream_MACDFIX"; -static const char __pyx_k_stream_PLUS_DI[] = "stream_PLUS_DI"; -static const char __pyx_k_stream_PLUS_DM[] = "stream_PLUS_DM"; -static const char __pyx_k_stream_ROCR100[] = "stream_ROCR100"; -static const char __pyx_k_ta_getFuncInfo[] = "_ta_getFuncInfo"; -static const char __pyx_k_A_d_q_4z_q_aq_q[] = "\200A\360\n\000\t\017\210d\220(\230(\240%\240q\330\010\013\2104\210z\230\021\230%\230q\330\014\022\220$\220a\220q\330\010\017\210q"; -static const char __pyx_k_CDLADVANCEBLOCK[] = "CDLADVANCEBLOCK"; -static const char __pyx_k_CDLHOMINGPIGEON[] = "CDLHOMINGPIGEON"; -static const char __pyx_k_CDLLADDERBOTTOM[] = "CDLLADDERBOTTOM"; -static const char __pyx_k_CDLSHOOTINGSTAR[] = "CDLSHOOTINGSTAR"; -static const char __pyx_k_CDLUNIQUE3RIVER[] = "CDLUNIQUE3RIVER"; -static const char __pyx_k_Function___call[] = "Function.__call__"; -static const char __pyx_k_Function___init[] = "Function.__init__"; -static const char __pyx_k_Function___repr[] = "Function.__repr__"; -static const char __pyx_k_Function__local[] = "_Function__local"; -static const char __pyx_k_LINEARREG_ANGLE[] = "LINEARREG_ANGLE"; -static const char __pyx_k_LINEARREG_SLOPE[] = "LINEARREG_SLOPE"; -static const char __pyx_k_ShadowVeryShort[] = "ShadowVeryShort"; -static const char __pyx_k_TA_CDLBREAKAWAY[] = "TA_CDLBREAKAWAY"; -static const char __pyx_k_TA_CDLENGULFING[] = "TA_CDLENGULFING"; -static const char __pyx_k_TA_CDLSHORTLINE[] = "TA_CDLSHORTLINE"; -static const char __pyx_k_TA_CDLTASUKIGAP[] = "TA_CDLTASUKIGAP"; -static const char __pyx_k_TA_CDLTHRUSTING[] = "TA_CDLTHRUSTING"; -static const char __pyx_k_TA_HT_TRENDLINE[] = "TA_HT_TRENDLINE"; -static const char __pyx_k_TA_HT_TRENDMODE[] = "TA_HT_TRENDMODE"; -static const char __pyx_k_TA_OUTPUT_FLAGS[] = "TA_OUTPUT_FLAGS"; -static const char __pyx_k_get_input_names[] = "get_input_names"; -static const char __pyx_k_offsetonreverse[] = "offsetonreverse"; -static const char __pyx_k_outinteger_data[] = "outinteger_data"; -static const char __pyx_k_set_input_names[] = "set_input_names"; -static const char __pyx_k_stream_ACCBANDS[] = "stream_ACCBANDS"; -static const char __pyx_k_stream_AROONOSC[] = "stream_AROONOSC"; -static const char __pyx_k_stream_AVGPRICE[] = "stream_AVGPRICE"; -static const char __pyx_k_stream_MAXINDEX[] = "stream_MAXINDEX"; -static const char __pyx_k_stream_MEDPRICE[] = "stream_MEDPRICE"; -static const char __pyx_k_stream_MIDPOINT[] = "stream_MIDPOINT"; -static const char __pyx_k_stream_MIDPRICE[] = "stream_MIDPRICE"; -static const char __pyx_k_stream_MININDEX[] = "stream_MININDEX"; -static const char __pyx_k_stream_MINUS_DI[] = "stream_MINUS_DI"; -static const char __pyx_k_stream_MINUS_DM[] = "stream_MINUS_DM"; -static const char __pyx_k_stream_STOCHRSI[] = "stream_STOCHRSI"; -static const char __pyx_k_stream_TYPPRICE[] = "stream_TYPPRICE"; -static const char __pyx_k_stream_WCLPRICE[] = "stream_WCLPRICE"; -static const char __pyx_k_ta_getFuncTable[] = "_ta_getFuncTable"; -static const char __pyx_k_talib__func_pxi[] = "talib/_func.pxi"; -static const char __pyx_k_A_A_AQ_6_A_E_A_q[] = "\200A\360\010\000\t\021\220\004\220A\330\010\020\220\005\220[\240\001\240\033\250A\250Q\330\010\013\2106\220\023\220A\330\014\024\220E\230\033\240A\240[\260\001\260\021\330\010\017\210q"; -static const char __pyx_k_CDL3STARSINSOUTH[] = "CDL3STARSINSOUTH"; -static const char __pyx_k_CDLABANDONEDBABY[] = "CDLABANDONEDBABY"; -static const char __pyx_k_CDLCOUNTERATTACK[] = "CDLCOUNTERATTACK"; -static const char __pyx_k_CDLDRAGONFLYDOJI[] = "CDLDRAGONFLYDOJI"; -static const char __pyx_k_CDLSTICKSANDWICH[] = "CDLSTICKSANDWICH"; -static const char __pyx_k_Function___local[] = "Function.__local"; -static const char __pyx_k_Function_outputs[] = "Function.outputs"; -static const char __pyx_k_PANDAS_DATAFRAME[] = "__PANDAS_DATAFRAME"; -static const char __pyx_k_POLARS_DATAFRAME[] = "__POLARS_DATAFRAME"; -static const char __pyx_k_TA_CDLHANGINGMAN[] = "TA_CDLHANGINGMAN"; -static const char __pyx_k_TA_CDLHIKKAKEMOD[] = "TA_CDLHIKKAKEMOD"; -static const char __pyx_k_TA_FuncTableFree[] = "TA_FuncTableFree"; -static const char __pyx_k_TA_GetFuncHandle[] = "TA_GetFuncHandle"; -static const char __pyx_k_accelerationlong[] = "accelerationlong"; -static const char __pyx_k_get_input_arrays[] = "get_input_arrays"; -static const char __pyx_k_opt_input_values[] = "opt_input_values"; -static const char __pyx_k_outreallowerband[] = "outreallowerband"; -static const char __pyx_k_outrealupperband[] = "outrealupperband"; -static const char __pyx_k_set_input_arrays[] = "set_input_arrays"; -static const char __pyx_k_stream_CDL2CROWS[] = "stream_CDL2CROWS"; -static const char __pyx_k_stream_CDLHAMMER[] = "stream_CDLHAMMER"; -static const char __pyx_k_stream_CDLHARAMI[] = "stream_CDLHARAMI"; -static const char __pyx_k_stream_CDLINNECK[] = "stream_CDLINNECK"; -static const char __pyx_k_stream_CDLONNECK[] = "stream_CDLONNECK"; -static const char __pyx_k_stream_CDLTAKURI[] = "stream_CDLTAKURI"; -static const char __pyx_k_stream_HT_PHASOR[] = "stream_HT_PHASOR"; -static const char __pyx_k_stream_LINEARREG[] = "stream_LINEARREG"; -static const char __pyx_k_ta_check_success[] = "_ta_check_success"; -static const char __pyx_k_ta_func_unst_ids[] = "_ta_func_unst_ids"; -static const char __pyx_k_ta_getGroupTable[] = "_ta_getGroupTable"; -static const char __pyx_k_AllCandleSettings[] = "AllCandleSettings"; -static const char __pyx_k_CDL3WHITESOLDIERS[] = "CDL3WHITESOLDIERS"; -static const char __pyx_k_CDLDARKCLOUDCOVER[] = "CDLDARKCLOUDCOVER"; -static const char __pyx_k_CDLGRAVESTONEDOJI[] = "CDLGRAVESTONEDOJI"; -static const char __pyx_k_CDLINVERTEDHAMMER[] = "CDLINVERTEDHAMMER"; -static const char __pyx_k_CDLLONGLEGGEDDOJI[] = "CDLLONGLEGGEDDOJI"; -static const char __pyx_k_CDLSTALLEDPATTERN[] = "CDLSTALLEDPATTERN"; -static const char __pyx_k_CandleSettingType[] = "CandleSettingType"; -static const char __pyx_k_Function__namestr[] = "_Function__namestr"; -static const char __pyx_k_Function_lookback[] = "Function.lookback"; -static const char __pyx_k_MA_Type___getitem[] = "MA_Type.__getitem__"; -static const char __pyx_k_TA_CDL3BLACKCROWS[] = "TA_CDL3BLACKCROWS"; -static const char __pyx_k_TA_CDL3LINESTRIKE[] = "TA_CDL3LINESTRIKE"; -static const char __pyx_k_TA_CDLEVENINGSTAR[] = "TA_CDLEVENINGSTAR"; -static const char __pyx_k_TA_CDLHARAMICROSS[] = "TA_CDLHARAMICROSS"; -static const char __pyx_k_TA_CDLMATCHINGLOW[] = "TA_CDLMATCHINGLOW"; -static const char __pyx_k_TA_CDLMORNINGSTAR[] = "TA_CDLMORNINGSTAR"; -static const char __pyx_k_TA_CDLRICKSHAWMAN[] = "TA_CDLRICKSHAWMAN"; -static const char __pyx_k_TA_CDLSPINNINGTOP[] = "TA_CDLSPINNINGTOP"; -static const char __pyx_k_TA_FUNCTION_NAMES[] = "__TA_FUNCTION_NAMES__"; -static const char __pyx_k_TA_FuncTableAlloc[] = "TA_FuncTableAlloc"; -static const char __pyx_k_TA_GroupTableFree[] = "TA_GroupTableFree"; -static const char __pyx_k_accelerationshort[] = "accelerationshort"; -static const char __pyx_k_flags_lookup_dict[] = "flags_lookup_dict"; -static const char __pyx_k_outrealmiddleband[] = "outrealmiddleband"; -static const char __pyx_k_set_function_args[] = "set_function_args"; -static const char __pyx_k_stream_CDL3INSIDE[] = "stream_CDL3INSIDE"; -static const char __pyx_k_stream_CDLHIKKAKE[] = "stream_CDLHIKKAKE"; -static const char __pyx_k_stream_CDLKICKING[] = "stream_CDLKICKING"; -static const char __pyx_k_stream_CDLMATHOLD[] = "stream_CDLMATHOLD"; -static const char __pyx_k_stream_CDLTRISTAR[] = "stream_CDLTRISTAR"; -static const char __pyx_k_stream_HT_DCPHASE[] = "stream_HT_DCPHASE"; -static const char __pyx_k_talib__common_pxi[] = "talib/_common.pxi"; -static const char __pyx_k_talib__stream_pxi[] = "talib/_stream.pxi"; -static const char __pyx_k_A_A_k_M_a_q_T_7q_q[] = "\200A\360\010\000\t\021\220\004\220A\330\010\016\210k\230\021\330\010\014\210M\230\025\230a\330\014\017\210q\220\r\230T\320!7\260q\270\001\330\010\017\210q"; -static const char __pyx_k_CDLCLOSINGMARUBOZU[] = "CDLCLOSINGMARUBOZU"; -static const char __pyx_k_CDLEVENINGDOJISTAR[] = "CDLEVENINGDOJISTAR"; -static const char __pyx_k_CDLIDENTICAL3CROWS[] = "CDLIDENTICAL3CROWS"; -static const char __pyx_k_CDLKICKINGBYLENGTH[] = "CDLKICKINGBYLENGTH"; -static const char __pyx_k_CDLMORNINGDOJISTAR[] = "CDLMORNINGDOJISTAR"; -static const char __pyx_k_CDLSEPARATINGLINES[] = "CDLSEPARATINGLINES"; -static const char __pyx_k_CDLUPSIDEGAP2CROWS[] = "CDLUPSIDEGAP2CROWS"; -static const char __pyx_k_Function___unicode[] = "Function.__unicode__"; -static const char __pyx_k_INPUT_ARRAYS_TYPES[] = "__INPUT_ARRAYS_TYPES"; -static const char __pyx_k_Output_can_be_zero[] = "Output can be zero"; -static const char __pyx_k_Q_V1E_q_WAQ_Q_aq_1[] = "\200\001\360\n\000\005\026\220Q\320\026.\320.@\300\001\300\027\310\001\310\021\330\004\020\220\001\330\004\010\210\005\210V\2201\220E\230\021\330\010\021\220\027\230\001\230\026\230q\240\005\240W\250A\250Q\330\004\025\220Q\320\026-\320->\270a\270q\330\004\013\2101"; -static const char __pyx_k_TA_CDLADVANCEBLOCK[] = "TA_CDLADVANCEBLOCK"; -static const char __pyx_k_TA_CDLHOMINGPIGEON[] = "TA_CDLHOMINGPIGEON"; -static const char __pyx_k_TA_CDLLADDERBOTTOM[] = "TA_CDLLADDERBOTTOM"; -static const char __pyx_k_TA_CDLSHOOTINGSTAR[] = "TA_CDLSHOOTINGSTAR"; -static const char __pyx_k_TA_CDLUNIQUE3RIVER[] = "TA_CDLUNIQUE3RIVER"; -static const char __pyx_k_TA_GroupTableAlloc[] = "TA_GroupTableAlloc"; -static const char __pyx_k_TA_LINEARREG_ANGLE[] = "TA_LINEARREG_ANGLE"; -static const char __pyx_k_TA_LINEARREG_SLOPE[] = "TA_LINEARREG_SLOPE"; -static const char __pyx_k_TA_ParamHolderFree[] = "TA_ParamHolderFree"; -static const char __pyx_k_asyncio_coroutines[] = "asyncio.coroutines"; -static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; -static const char __pyx_k_stream_CDL3OUTSIDE[] = "stream_CDL3OUTSIDE"; -static const char __pyx_k_stream_CDLBELTHOLD[] = "stream_CDLBELTHOLD"; -static const char __pyx_k_stream_CDLDOJISTAR[] = "stream_CDLDOJISTAR"; -static const char __pyx_k_stream_CDLHIGHWAVE[] = "stream_CDLHIGHWAVE"; -static const char __pyx_k_stream_CDLLONGLINE[] = "stream_CDLLONGLINE"; -static const char __pyx_k_stream_CDLMARUBOZU[] = "stream_CDLMARUBOZU"; -static const char __pyx_k_stream_CDLPIERCING[] = "stream_CDLPIERCING"; -static const char __pyx_k_stream_HT_DCPERIOD[] = "stream_HT_DCPERIOD"; -static const char __pyx_k_stream_MINMAXINDEX[] = "stream_MINMAXINDEX"; -static const char __pyx_k_A_A_gQ_5_q_5_V1_5_U[] = "\200A\360\010\000\t\021\220\004\220A\330\010\013\320\013\036\230g\240Q\330\014\020\220\n\230!\2305\240\017\250q\330\014\023\2205\230\r\240V\2501\340\014\023\2205\230\r\240U\250!"; -static const char __pyx_k_CDLCONCEALBABYSWALL[] = "CDLCONCEALBABYSWALL"; -static const char __pyx_k_CDLGAPSIDESIDEWHITE[] = "CDLGAPSIDESIDEWHITE"; -static const char __pyx_k_CDLRISEFALL3METHODS[] = "CDLRISEFALL3METHODS"; -static const char __pyx_k_CDLXSIDEGAP3METHODS[] = "CDLXSIDEGAP3METHODS"; -static const char __pyx_k_Function__localdata[] = "_Function__localdata"; -static const char __pyx_k_LINEARREG_INTERCEPT[] = "LINEARREG_INTERCEPT"; -static const char __pyx_k_ModuleNotFoundError[] = "ModuleNotFoundError"; -static const char __pyx_k_TA_CDL3STARSINSOUTH[] = "TA_CDL3STARSINSOUTH"; -static const char __pyx_k_TA_CDLABANDONEDBABY[] = "TA_CDLABANDONEDBABY"; -static const char __pyx_k_TA_CDLCOUNTERATTACK[] = "TA_CDLCOUNTERATTACK"; -static const char __pyx_k_TA_CDLDRAGONFLYDOJI[] = "TA_CDLDRAGONFLYDOJI"; -static const char __pyx_k_TA_CDLSTICKSANDWICH[] = "TA_CDLSTICKSANDWICH"; -static const char __pyx_k_TA_ParamHolderAlloc[] = "TA_ParamHolderAlloc"; -static const char __pyx_k_TA_SetCompatibility[] = "TA_SetCompatibility"; -static const char __pyx_k_accelerationmaxlong[] = "accelerationmaxlong"; -static const char __pyx_k_get_opt_input_value[] = "__get_opt_input_value"; -static const char __pyx_k_stream_CDLBREAKAWAY[] = "stream_CDLBREAKAWAY"; -static const char __pyx_k_stream_CDLENGULFING[] = "stream_CDLENGULFING"; -static const char __pyx_k_stream_CDLSHORTLINE[] = "stream_CDLSHORTLINE"; -static const char __pyx_k_stream_CDLTASUKIGAP[] = "stream_CDLTASUKIGAP"; -static const char __pyx_k_stream_CDLTHRUSTING[] = "stream_CDLTHRUSTING"; -static const char __pyx_k_stream_HT_TRENDLINE[] = "stream_HT_TRENDLINE"; -static const char __pyx_k_stream_HT_TRENDMODE[] = "stream_HT_TRENDMODE"; -static const char __pyx_k_talib__abstract_pxi[] = "talib/_abstract.pxi"; -static const char __pyx_k_A_A_L_6_Qk_A_a_QnA_a[] = "\200A\360\010\000\t\021\220\004\220A\330\010\014\210L\320\030(\250\013\2606\270\021\330\014\021\220\034\230Q\230k\250\021\320*<\270A\330\014\021\220\025\220a\220~\240Q\240n\260A\330\010\r\320\r\036\230a"; -static const char __pyx_k_A_A_k_N_q_q_e_q_1A_q[] = "\200A\360\n\000\t\021\220\004\220A\330\010\016\210k\230\021\330\010\014\210N\230%\230q\330\014\017\210q\220\016\230e\240<\250q\260\013\2701\270A\330\010\017\210q"; -static const char __pyx_k_TA_CDL3WHITESOLDIERS[] = "TA_CDL3WHITESOLDIERS"; -static const char __pyx_k_TA_CDLDARKCLOUDCOVER[] = "TA_CDLDARKCLOUDCOVER"; -static const char __pyx_k_TA_CDLGRAVESTONEDOJI[] = "TA_CDLGRAVESTONEDOJI"; -static const char __pyx_k_TA_CDLINVERTEDHAMMER[] = "TA_CDLINVERTEDHAMMER"; -static const char __pyx_k_TA_CDLLONGLEGGEDDOJI[] = "TA_CDLLONGLEGGEDDOJI"; -static const char __pyx_k_TA_CDLSTALLEDPATTERN[] = "TA_CDLSTALLEDPATTERN"; -static const char __pyx_k_TA_SetCandleSettings[] = "TA_SetCandleSettings"; -static const char __pyx_k_TA_SetUnstablePeriod[] = "TA_SetUnstablePeriod"; -static const char __pyx_k_accelerationinitlong[] = "accelerationinitlong"; -static const char __pyx_k_accelerationmaxshort[] = "accelerationmaxshort"; -static const char __pyx_k_stream_CDLHANGINGMAN[] = "stream_CDLHANGINGMAN"; -static const char __pyx_k_stream_CDLHIKKAKEMOD[] = "stream_CDLHIKKAKEMOD"; -static const char __pyx_k_ta_get_compatibility[] = "_ta_get_compatibility"; -static const char __pyx_k_ta_set_compatibility[] = "_ta_set_compatibility"; -static const char __pyx_k_Function_output_flags[] = "Function.output_flags"; -static const char __pyx_k_Function_output_names[] = "Function.output_names"; -static const char __pyx_k_Output_is_over_volume[] = "Output is over volume"; -static const char __pyx_k_Simple_Moving_Average[] = "Simple Moving Average"; -static const char __pyx_k_TA_CDLCLOSINGMARUBOZU[] = "TA_CDLCLOSINGMARUBOZU"; -static const char __pyx_k_TA_CDLEVENINGDOJISTAR[] = "TA_CDLEVENINGDOJISTAR"; -static const char __pyx_k_TA_CDLIDENTICAL3CROWS[] = "TA_CDLIDENTICAL3CROWS"; -static const char __pyx_k_TA_CDLKICKINGBYLENGTH[] = "TA_CDLKICKINGBYLENGTH"; -static const char __pyx_k_TA_CDLMORNINGDOJISTAR[] = "TA_CDLMORNINGDOJISTAR"; -static const char __pyx_k_TA_CDLSEPARATINGLINES[] = "TA_CDLSEPARATINGLINES"; -static const char __pyx_k_TA_CDLUPSIDEGAP2CROWS[] = "TA_CDLUPSIDEGAP2CROWS"; -static const char __pyx_k_accelerationinitshort[] = "accelerationinitshort"; -static const char __pyx_k_check_opt_input_value[] = "__check_opt_input_value"; -static const char __pyx_k_get_defaults_and_docs[] = "_get_defaults_and_docs"; -static const char __pyx_k_stream_CDL3BLACKCROWS[] = "stream_CDL3BLACKCROWS"; -static const char __pyx_k_stream_CDL3LINESTRIKE[] = "stream_CDL3LINESTRIKE"; -static const char __pyx_k_stream_CDLEVENINGSTAR[] = "stream_CDLEVENINGSTAR"; -static const char __pyx_k_stream_CDLHARAMICROSS[] = "stream_CDLHARAMICROSS"; -static const char __pyx_k_stream_CDLMATCHINGLOW[] = "stream_CDLMATCHINGLOW"; -static const char __pyx_k_stream_CDLMORNINGSTAR[] = "stream_CDLMORNINGSTAR"; -static const char __pyx_k_stream_CDLRICKSHAWMAN[] = "stream_CDLRICKSHAWMAN"; -static const char __pyx_k_stream_CDLSPINNINGTOP[] = "stream_CDLSPINNINGTOP"; -static const char __pyx_k_A_A_6_6_6_7_7_81_7_7_5[] = "\200A\330\010\014\210A\330\014\023\2206\230\021\330\014\023\2206\230\021\330\014\023\2206\230\021\330\014\023\2207\230!\330\014\023\2207\230!\330\014\023\2208\2301\330\014\023\2207\230!\330\014\023\2207\230!\330\014\023\2205\230\001"; -static const char __pyx_k_Output_can_be_negative[] = "Output can be negative"; -static const char __pyx_k_Output_can_be_positive[] = "Output can be positive"; -static const char __pyx_k_Q_B_1A_Q_V1E_gQfAU_Q_1[] = "\200\001\360\n\000\005\026\220Q\320\026/\320/B\300!\3001\300A\330\004\r\210Q\330\004\010\210\005\210V\2201\220E\230\021\330\010\016\210g\220Q\220f\230A\230U\240'\250\021\250!\330\004\025\220Q\320\026.\320.@\300\001\300\021\330\004\013\2101"; -static const char __pyx_k_TA_CDLCONCEALBABYSWALL[] = "TA_CDLCONCEALBABYSWALL"; -static const char __pyx_k_TA_CDLGAPSIDESIDEWHITE[] = "TA_CDLGAPSIDESIDEWHITE"; -static const char __pyx_k_TA_CDLRISEFALL3METHODS[] = "TA_CDLRISEFALL3METHODS"; -static const char __pyx_k_TA_CDLXSIDEGAP3METHODS[] = "TA_CDLXSIDEGAP3METHODS"; -static const char __pyx_k_TA_LINEARREG_INTERCEPT[] = "TA_LINEARREG_INTERCEPT"; -static const char __pyx_k_display_name_s_group_s[] = "%(display_name)s (%(group)s)\n"; -static const char __pyx_k_stream_CDLADVANCEBLOCK[] = "stream_CDLADVANCEBLOCK"; -static const char __pyx_k_stream_CDLHOMINGPIGEON[] = "stream_CDLHOMINGPIGEON"; -static const char __pyx_k_stream_CDLLADDERBOTTOM[] = "stream_CDLLADDERBOTTOM"; -static const char __pyx_k_stream_CDLSHOOTINGSTAR[] = "stream_CDLSHOOTINGSTAR"; -static const char __pyx_k_stream_CDLUNIQUE3RIVER[] = "stream_CDLUNIQUE3RIVER"; -static const char __pyx_k_stream_LINEARREG_ANGLE[] = "stream_LINEARREG_ANGLE"; -static const char __pyx_k_stream_LINEARREG_SLOPE[] = "stream_LINEARREG_SLOPE"; -static const char __pyx_k_ta_get_unstable_period[] = "_ta_get_unstable_period"; -static const char __pyx_k_ta_set_candle_settings[] = "_ta_set_candle_settings"; -static const char __pyx_k_ta_set_unstable_period[] = "_ta_set_unstable_period"; -static const char __pyx_k_Function__call_function[] = "_Function__call_function"; -static const char __pyx_k_Function_function_flags[] = "Function.function_flags"; -static const char __pyx_k_Function_get_parameters[] = "Function.get_parameters"; -static const char __pyx_k_Function_set_parameters[] = "Function.set_parameters"; -static const char __pyx_k_Output_is_a_candlestick[] = "Output is a candlestick"; -static const char __pyx_k_TA_SetOptInputParamReal[] = "TA_SetOptInputParamReal"; -static const char __pyx_k_Weighted_Moving_Average[] = "Weighted Moving Average"; -static const char __pyx_k_stream_CDL3STARSINSOUTH[] = "stream_CDL3STARSINSOUTH"; -static const char __pyx_k_stream_CDLABANDONEDBABY[] = "stream_CDLABANDONEDBABY"; -static const char __pyx_k_stream_CDLCOUNTERATTACK[] = "stream_CDLCOUNTERATTACK"; -static const char __pyx_k_stream_CDLDRAGONFLYDOJI[] = "stream_CDLDRAGONFLYDOJI"; -static const char __pyx_k_stream_CDLSTICKSANDWICH[] = "stream_CDLSTICKSANDWICH"; -static const char __pyx_k_A_Jm6_M_Q_Jiq_A_O9F_b_O1[] = "\200A\340\010\014\210J\220m\2406\250\021\330\010\014\210M\230\024\230Q\330\010\014\210J\220i\230q\240\004\240A\360\006\000\t\r\210O\2309\240F\250!\360\006\000\t\r\320\014\036\230b\240\010\250\001\330\010\014\210O\2301"; -static const char __pyx_k_Bad_Object_TA_BAD_OBJECT[] = "Bad Object (TA_BAD_OBJECT)"; -static const char __pyx_k_Function___call_function[] = "Function.__call_function"; -static const char __pyx_k_Function_get_input_names[] = "Function.get_input_names"; -static const char __pyx_k_Function_set_input_names[] = "Function.set_input_names"; -static const char __pyx_k_TA_GetInputParameterInfo[] = "TA_GetInputParameterInfo"; -static const char __pyx_k_input_price_series_names[] = "input_price_series_names"; -static const char __pyx_k_no_existing_input_arrays[] = "no_existing_input_arrays"; -static const char __pyx_k_price_series_name_values[] = "price_series_name_values"; -static const char __pyx_k_stream_CDL3WHITESOLDIERS[] = "stream_CDL3WHITESOLDIERS"; -static const char __pyx_k_stream_CDLDARKCLOUDCOVER[] = "stream_CDLDARKCLOUDCOVER"; -static const char __pyx_k_stream_CDLGRAVESTONEDOJI[] = "stream_CDLGRAVESTONEDOJI"; -static const char __pyx_k_stream_CDLINVERTEDHAMMER[] = "stream_CDLINVERTEDHAMMER"; -static const char __pyx_k_stream_CDLLONGLEGGEDDOJI[] = "stream_CDLLONGLEGGEDDOJI"; -static const char __pyx_k_stream_CDLSTALLEDPATTERN[] = "stream_CDLSTALLEDPATTERN"; -static const char __pyx_k_ta_getInputParameterInfo[] = "_ta_getInputParameterInfo"; -static const char __pyx_k_Function_get_input_arrays[] = "Function.get_input_arrays"; -static const char __pyx_k_Function_set_input_arrays[] = "Function.set_input_arrays"; -static const char __pyx_k_TA_GetOutputParameterInfo[] = "TA_GetOutputParameterInfo"; -static const char __pyx_k_Triangular_Moving_Average[] = "Triangular Moving Average"; -static const char __pyx_k_stream_CDLCLOSINGMARUBOZU[] = "stream_CDLCLOSINGMARUBOZU"; -static const char __pyx_k_stream_CDLEVENINGDOJISTAR[] = "stream_CDLEVENINGDOJISTAR"; -static const char __pyx_k_stream_CDLIDENTICAL3CROWS[] = "stream_CDLIDENTICAL3CROWS"; -static const char __pyx_k_stream_CDLKICKINGBYLENGTH[] = "stream_CDLKICKINGBYLENGTH"; -static const char __pyx_k_stream_CDLMORNINGDOJISTAR[] = "stream_CDLMORNINGDOJISTAR"; -static const char __pyx_k_stream_CDLSEPARATINGLINES[] = "stream_CDLSEPARATINGLINES"; -static const char __pyx_k_stream_CDLUPSIDEGAP2CROWS[] = "stream_CDLUPSIDEGAP2CROWS"; -static const char __pyx_k_ta_getOutputParameterInfo[] = "_ta_getOutputParameterInfo"; -static const char __pyx_k_A_A_1_N_q_5_A_z_HA_G1A_q_q[] = "\200A\330\010\020\220\004\220A\330\010#\2401\330\010\014\210N\230%\230q\330\014\033\2305\240\014\250A\250[\270\001\270\021\330\014\017\210z\230\021\230.\250\001\330\020\024\220H\230A\330\024,\250G\2601\260A\340\020(\250\007\250q\260\001\330\010\017\210q"; -static const char __pyx_k_Bad_Parameter_TA_BAD_PARAM[] = "Bad Parameter (TA_BAD_PARAM)"; -static const char __pyx_k_Exponential_Moving_Average[] = "Exponential Moving Average"; -static const char __pyx_k_Function_set_function_args[] = "Function.set_function_args"; -static const char __pyx_k_Output_scale_same_as_input[] = "Output scale same as input"; -static const char __pyx_k_TA_SetOptInputParamInteger[] = "TA_SetOptInputParamInteger"; -static const char __pyx_k_input_price_series_names_2[] = "__input_price_series_names"; -static const char __pyx_k_stream_CDLCONCEALBABYSWALL[] = "stream_CDLCONCEALBABYSWALL"; -static const char __pyx_k_stream_CDLGAPSIDESIDEWHITE[] = "stream_CDLGAPSIDESIDEWHITE"; -static const char __pyx_k_stream_CDLRISEFALL3METHODS[] = "stream_CDLRISEFALL3METHODS"; -static const char __pyx_k_stream_CDLXSIDEGAP3METHODS[] = "stream_CDLXSIDEGAP3METHODS"; -static const char __pyx_k_stream_LINEARREG_INTERCEPT[] = "stream_LINEARREG_INTERCEPT"; -static const char __pyx_k_INPUT_PRICE_SERIES_DEFAULTS[] = "__INPUT_PRICE_SERIES_DEFAULTS"; -static const char __pyx_k_Invalid_parameter_value_for[] = "Invalid parameter value for "; -static const char __pyx_k_TA_GetOptInputParameterInfo[] = "TA_GetOptInputParameterInfo"; -static const char __pyx_k_ta_getOptInputParameterInfo[] = "_ta_getOptInputParameterInfo"; -static const char __pyx_k_MESA_Adaptive_Moving_Average[] = "MESA Adaptive Moving Average"; -static const char __pyx_k_Q_A_1_G9JfA_t_1G1_q_1_a_U_4q[] = "\320\004\035\230Q\360\010\000\t\021\220\004\220A\330\010\025\220[\240\003\2401\330\010\022\220'\230\021\230!\330\010\014\210G\2209\230J\240f\250A\330\014\017\210t\320\023+\2501\250G\2601\330\020\025\220[\240\001\240\026\240q\250\013\2601\330\010\r\320\r\036\230a\330\010\r\210U\220!\320\023#\2404\240q"; -static const char __pyx_k_Unknown_Error_TA_UNKNOWN_ERR[] = "Unknown Error (TA_UNKNOWN_ERR)"; -static const char __pyx_k_aq_Q_T_q_a_fHBd_a_kkllm_Qj_1[] = "\200\001\360&\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\027\230\002\230&\240\010\250\002\250$\250f\260H\270B\270d\300,\310a\310|\320[\\\320\\k\320kl\320lm\330\004\025\220Q\220j\240\001\330\004\013\2101"; -static const char __pyx_k_Allocation_Error_TA_ALLOC_ERR[] = "Allocation Error (TA_ALLOC_ERR)"; -static const char __pyx_k_Function__get_opt_input_value[] = "_Function__get_opt_input_value"; -static const char __pyx_k_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_w[] = "\200\001\340_`\360.\000\005\014\210;\220a\220q\330\004\n\210+\220Q\220a\330\004\014\210K\220q\230\001\330\004\r\210]\230!\2306\240\025\240a\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3003\300h\310j\320X]\320]^\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\0330\260\002\260!\330\004\027\320\027(\250\001\250\030\260\021\330\004\030\320\030)\250\021\250(\260!\330\004\027\320\027(\250\001\250\030\260\021\330\004\021\220\034\230R\230t\2409\250K\260t\2706\300\021\300)\310;\320VY\320Y_\320_`\320`i\320it\320ty\320y\360\000\000@\002A\002\360\000\000A\002J\002\360\000\000J\002W\002\360\000\000W\002X\002\360\000\000X\002d\002\360\000\000d\002e\002\360\000\000e\002t\002\360\000\000t\002\002\360\000\000\002O\003\360\000\000O\003U\003\360\000\000U\003V\003\360\000\000V\003a\003\360\000\000a\003l\003\360\000\000l\003}\003\360\000\000}\003C\004\360\000\000C\004D\004\360\000\000D\004O\004\360\000\000O\004Z\004\360\000\000Z\004j\004\360\000\000j\004p\004\360\000\000p\004q\004\360\000\000q\004r\004\330\004\025\220Q\220o\240Q\330\004\013\320\013\036\320\0362\260!"; -static const char __pyx_k_01_aq_T_q_8_T_U_7_A_we_7r_q_Bd[] = "\200\001\34001\360&\000\005\014\210;\220a\220q\330\004\r\210T\220\026\220q\230\001\330\004\r\210]\230!\2308\240:\250T\260\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\0337\260r\270\021\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\320\021$\240B\240d\250)\260;\270d\300&\310\001\310\031\320R_\320_`\320`l\320lm\320m|\360\000\000}\001H\002\360\000\000H\002O\002\360\000\000O\002U\002\360\000\000U\002V\002\360\000\000V\002W\002\330\004\025\220Q\320\026,\250A\330\004\013\2101"; -static const char __pyx_k_1_aq_T_q_8_T_U_7_A_we_M_q_r_Yk[] = "\200\001\340#;\2701\360(\000\005\014\210;\220a\220q\330\004\r\210T\220\026\220q\230\001\330\004\r\210]\230!\2308\240:\250T\260\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\230?\250\"\250M\270\021\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\026\220r\230\024\230Y\240k\260\024\260V\2701\270I\300]\320R[\320[\\\320\\h\320hi\320ix\360\000\000y\001D\002\360\000\000D\002K\002\360\000\000K\002Q\002\360\000\000Q\002R\002\360\000\000R\002S\002\330\004\025\220Q\220i\230q\330\004\013\2101"; -static const char __pyx_k_314DAQ_Q_a_4q_a_Qd_c_a_Qd_s_4q[] = "\200\001\360\014\000\005\022\220\037\240\001\320!3\2601\3204D\300A\300Q\330\004\025\220Q\320\026(\250\001\340\004\005\330\010\020\220\t\230\021\230$\230a\330\010\021\220\031\230!\2304\230q\330\010\030\230\t\240\021\240$\240a\330\010\032\230+\240Q\240d\250(\260!\330\010\026\220c\230\021\230$\230a\330\010\032\230#\230Q\230d\240!\330\010\027\220s\230!\2304\230q"; -static const char __pyx_k_BC_Kq_Kq_7_8_U_E_U_7_A_we_Ba_q[] = "\200\001\340BC\360(\000\005\r\210K\220q\230\001\330\004\014\210K\220q\230\001\330\004\r\210]\230!\2307\240!\330\004\r\210]\230!\2308\240:\250U\260(\270*\300E\310\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033,\250B\250a\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\030\230\022\2304\230y\250\013\2605\270\006\270a\270y\310\013\320SX\320X^\320^_\320_h\320hu\320uv\360\000\000w\001C\002\360\000\000C\002D\002\360\000\000D\002S\002\360\000\000S\002^\002\360\000\000^\002e\002\360\000\000e\002k\002\360\000\000k\002l\002\360\000\000l\002m\002\330\004\025\220Q\220k\240\021\330\004\013\2101"; -static const char __pyx_k_BC_aq_Qa_6_8_T_3a_U_7_A_we_r_q[] = "\200\001\340BC\360&\000\005\014\210;\220a\220q\330\004\n\210+\220Q\220a\330\004\r\210]\230!\2306\240\021\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3003\300a\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033/\250r\260\021\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\033\230B\230d\240)\250;\260d\270&\300\001\300\031\310+\320UX\320X^\320^_\320_h\320hu\320uv\360\000\000w\001C\002\360\000\000C\002D\002\360\000\000D\002S\002\360\000\000S\002^\002\360\000\000^\002e\002\360\000\000e\002k\002\360\000\000k\002l\002\360\000\000l\002m\002\330\004\025\220Q\220n\240A\330\004\013\2101"; -static const char __pyx_k_C1_aq_Q_T_q_a_fHBd_m_ccddppq_r[] = "\200\001\340+C\3001\360(\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\027\230\002\230&\240\010\250\002\250$\250f\260H\270B\270d\300,\310m\320[c\320cd\320dp\320pq\360\000\000r\001A\002\360\000\000A\002B\002\360\000\000B\002C\002\330\004\025\220Q\220j\240\001\330\004\013\2101"; -static const char __pyx_k_CD_aq_Qa_6_8_T_3a_U_7_A_we_0_q[] = "\200\001\340CD\360&\000\005\014\210;\220a\220q\330\004\n\210+\220Q\220a\330\004\r\210]\230!\2306\240\021\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3003\300a\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\0330\260\002\260!\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\034\230R\230t\2409\250K\260t\2706\300\021\300)\310;\320VY\320Y_\320_`\320`i\320iv\320vw\360\000\000x\001D\002\360\000\000D\002E\002\360\000\000E\002T\002\360\000\000T\002_\002\360\000\000_\002f\002\360\000\000f\002l\002\360\000\000l\002m\002\360\000\000m\002n\002\330\004\025\220Q\220o\240Q\330\004\013\2101"; -static const char __pyx_k_D_E_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA[] = "\200\001\360\004\000D\002E\002\360,\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\013\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2306\240\026\240u\250A\330\004\021\220\021\330\004\021\220\036\230r\240\026\240x\250r\260\024\260V\2708\3002\300T\310\034\320Ua\320al\320ly\360\000\000z\001H\002\360\000\000H\002I\002\360\000\000I\002U\002\360\000\000U\002V\002\360\000\000V\002e\002\360\000\000e\002f\002\360\000\000f\002g\002\330\004\025\220Q\320\026'\240q\330\004\013\2101"; -static const char __pyx_k_Function___get_opt_input_value[] = "Function.__get_opt_input_value"; -static const char __pyx_k_H_I_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA[] = "\200\001\360\004\000H\002I\002\360,\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\013\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2306\240\026\240u\250A\330\004\021\220\021\330\004\021\320\021#\2402\240V\2508\2602\260T\270\026\270x\300r\310\024\310\\\320Ye\320ep\320p}\360\000\000~\001L\002\360\000\000L\002M\002\360\000\000M\002Y\002\360\000\000Y\002Z\002\360\000\000Z\002i\002\360\000\000i\002j\002\360\000\000j\002k\002\330\004\025\220Q\320\026+\2501\330\004\013\2101"; -static const char __pyx_k_Hb_c_B_B_f_f_F_F_i_i_N_N_o_o_p[] = "\200\001\340Hb\360\000\000c\001B\002\360\000\000B\002f\002\360\000\000f\002F\003\360\000\000F\003i\003\360\000\000i\003N\004\360\000\000N\004o\004\360\000\000o\004p\004\3606\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\r\210]\230!\2306\240\021\330\004\016\210a\330\004\021\220\032\2302\230V\2408\2502\250T\260\026\260x\270r\300\024\300\\\320Q\\\320\\i\320i{\360\000\000|\001S\002\360\000\000S\002f\002\360\000\000f\002|\002\360\000\000|\002T\003\360\000\000T\003h\003\360\000\000h\003\003\360\000\000\003@\004\360\000\000@\004L\004\360\000\000L\004M\004\360\000\000M\004\\\004\360\000\000\\\004]\004\360\000\000]\004^\004\330\004\025\220Q\220m\2401\330\004\013\2101"; -static const char __pyx_k_J_K_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA[] = "\200\001\360\004\000J\002K\002\360,\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\013\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2306\240\026\240u\250A\330\004\021\220\021\330\004\021\320\021%\240R\240v\250X\260R\260t\2706\300\030\310\022\3104\310|\320[g\320gr\320r\360\000\000@\002N\002\360\000\000N\002O\002\360\000\000O\002[\002\360\000\000[\002\\\002\360\000\000\\\002k\002\360\000\000k\002l\002\360\000\000l\002m\002\330\004\025\220Q\320\026-\250Q\330\004\013\2101"; -static const char __pyx_k_K_L_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA[] = "\200\001\360\004\000K\002L\002\360,\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\013\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2306\240\026\240u\250A\330\004\021\220\021\330\004\021\320\021&\240b\250\006\250h\260b\270\004\270F\300(\310\"\310D\320P\\\320\\h\320hs\360\000\000t\001A\002\360\000\000A\002O\002\360\000\000O\002P\002\360\000\000P\002\\\002\360\000\000\\\002]\002\360\000\000]\002l\002\360\000\000l\002m\002\360\000\000m\002n\002\330\004\025\220Q\320\026.\250a\330\004\013\2101"; -static const char __pyx_k_Kq_q_Kq_q_7_a_6_4vXRt_P_jjkkzz[] = "\200\001\360*\000\005\r\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2307\240!\330\004\016\210a\330\004\021\220\030\230\022\2306\240\030\250\022\2504\250v\260X\270R\270t\300=\320P]\320]^\320^j\320jk\320kz\320z{\320{|\330\004\025\220Q\220k\240\021\330\004\013\2101"; -static const char __pyx_k_Kq_q_Kq_q_7_a_fHBd_iijjyyzz_Qj[] = "\200\001\360*\000\005\r\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2307\240!\330\004\016\210a\330\004\021\220\027\230\002\230&\240\010\250\002\250$\250f\260H\270B\270d\300-\310}\320\\]\320]i\320ij\320jy\320yz\320z{\330\004\025\220Q\220j\240\001\330\004\013\2101"; -static const char __pyx_k_L_M_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA[] = "\200\001\360\004\000L\002M\002\360,\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\013\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2306\240\026\240u\250A\330\004\021\220\021\330\004\021\320\021'\240r\250\026\250x\260r\270\024\270V\3008\3102\310T\320Q]\320]i\320it\360\000\000u\001B\002\360\000\000B\002P\002\360\000\000P\002Q\002\360\000\000Q\002]\002\360\000\000]\002^\002\360\000\000^\002m\002\360\000\000m\002n\002\360\000\000n\002o\002\330\004\025\220Q\320\026/\250q\330\004\013\2101"; -static const char __pyx_k_Not_Supported_TA_NOT_SUPPORTED[] = "Not Supported (TA_NOT_SUPPORTED)"; -static const char __pyx_k_Values_represent_a_lower_limit[] = "Values represent a lower limit"; -static const char __pyx_k_YZ_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A[] = "\200\001\340YZ\360&\000\005\014\210;\220a\220q\330\004\n\210+\220Q\220a\330\004\014\210K\220q\230\001\330\004\r\210]\230!\2306\240\025\240a\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3003\300h\310j\320X]\320]^\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\230?\250\"\250A\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\026\220r\230\024\230Y\240k\260\024\260V\2701\270I\300[\320PS\320SY\320YZ\320Zc\320cn\320ns\320sy\320yz\360\000\000{\001D\002\360\000\000D\002Q\002\360\000\000Q\002R\002\360\000\000R\002^\002\360\000\000^\002_\002\360\000\000_\002n\002\360\000\000n\002y\002\360\000\000y\002@\003\360\000\000@\003F\003\360\000\000F\003G\003\360\000\000G\003H\003\330\004\025\220Q\220i\230q\330\004\013\2101"; -static const char __pyx_k_ab_aq_Q_Qa_y_1_Kq_q_6_a_a_fHBd[] = "\200\001\340ab\360*\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2306\240\025\240a\330\004\016\210a\330\004\021\220\027\230\002\230&\240\010\250\002\250$\250f\260H\270B\270d\300,\310k\320Yf\320fs\320st\360\000\000u\001A\002\360\000\000A\002B\002\360\000\000B\002Q\002\360\000\000Q\002R\002\360\000\000R\002S\002\330\004\025\220Q\220j\240\001\330\004\013\2101"; -static const char __pyx_k_aq_Q_Qa_y_1_Kq_q_6_6_gQ_a_fHBd[] = "\200\001\340~\360,\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210[\230\001\230\021\330\004\022\220)\2306\240\021\330\004\r\210]\230!\2306\240\025\240g\250Q\330\004\016\210a\330\004\021\220\027\230\002\230&\240\010\250\002\250$\250f\260H\270B\270d\300,\310k\320Yf\320ft\360\000\000u\001B\002\360\000\000B\002C\002\360\000\000C\002O\002\360\000\000O\002P\002\360\000\000P\002_\002\360\000\000_\002`\002\360\000\000`\002a\002\330\004\025\220Q\220j\240\001\330\004\013\2101"; -static const char __pyx_k_aq_Q_Qa_y_1_Kq_q_6_6_gQ_a_r_xr[] = "\200\001\360,\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210[\230\001\230\021\330\004\022\220)\2306\240\021\330\004\r\210]\230!\2306\240\025\240g\250Q\330\004\016\210a\330\004\021\220\026\220r\230\026\230x\240r\250\024\250V\2608\2702\270T\300\034\310[\320Xe\320es\320st\360\000\000u\001A\002\360\000\000A\002B\002\360\000\000B\002Q\002\360\000\000Q\002R\002\360\000\000R\002S\002\330\004\025\220Q\220i\230q\330\004\013\2101"; -static const char __pyx_k_aq_Q_T_q_Q_Q_2V82T_xr_Q___kkll[] = "\200\001\340./\360*\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\r\210Q\330\004\r\210Q\330\004\021\220\032\2302\230V\2408\2502\250T\260\026\260x\270r\300\024\300\\\320Q^\320^_\320_k\320kl\320l{\320{|\360\000\000}\001F\002\360\000\000F\002G\002\360\000\000G\002H\002\330\004\025\220Q\220m\2401\330\004\013\2109\220A"; -static const char __pyx_k_aq_Q_T_q_a_6_4vXRt_iijjyyzz_Qk[] = "\200\001\340,-\360&\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\030\230\022\2306\240\030\250\022\2504\250v\260X\270R\270t\300<\310}\320\\]\320]i\320ij\320jy\320yz\320z{\330\004\025\220Q\220k\240\021\330\004\013\2101"; -static const char __pyx_k_aq_Q_T_q_a_6_4vXRt_qP_llmmn_Qk[] = "\200\001\360&\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\030\230\022\2306\240\030\250\022\2504\250v\260X\270R\270t\300<\310q\320P\\\320\\]\320]l\320lm\320mn\330\004\025\220Q\220k\240\021\330\004\013\2101"; -static const char __pyx_k_aq_Q_T_q_a_BfHBd_lRSS___ooppzz[] = "\200\001\360*\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\022\220!\330\004\021\220\033\230B\230f\240H\250B\250d\260&\270\010\300\002\300$\300l\320RS\320S_\320_`\320`o\320op\320pz\320z{\320{|\330\004\025\220Q\220n\240A\330\004\013\210:\220Q"; -static const char __pyx_k_aq_Q_T_q_a_F_D_hb_LP_jjkkzz_Ql[] = "\200\001\340-.\360&\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\031\230\"\230F\240(\250\"\250D\260\006\260h\270b\300\004\300L\320P]\320]^\320^j\320jk\320kz\320z{\320{|\330\004\025\220Q\220l\240!\330\004\013\2101"; -static const char __pyx_k_aq_Q_T_q_a_fHBdR_kkllxxy_z_I_I[] = "\200\001\340;<\360&\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\320\021(\250\002\250&\260\010\270\002\270$\270f\300H\310B\310d\320R^\320^k\320kl\320lx\320xy\360\000\000z\001I\002\360\000\000I\002J\002\360\000\000J\002K\002\330\004\025\220Q\320\0260\260\001\330\004\013\2101"; -static const char __pyx_k_aq_Q_T_q_a_fHBd_VWWccddssttu_Q[] = "\200\001\360&\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\037\240\002\240&\250\010\260\002\260$\260f\270H\300B\300d\310,\320VW\320Wc\320cd\320ds\320st\320tu\330\004\025\220Q\320\026(\250\001\330\004\013\2101"; -static const char __pyx_k_aq_Q_T_q_a_fHBd_m_hhiixxyyz_Qj[] = "\200\001\340+,\360&\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\027\230\002\230&\240\010\250\002\250$\250f\260H\270B\270d\300,\310m\320[\\\320\\h\320hi\320ix\320xy\320yz\330\004\025\220Q\220j\240\001\330\004\013\2101"; -static const char __pyx_k_aq_Q_T_q_a_r_xr_V82T_QlZ_jjkkl[] = "\200\001\360&\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\026\220r\230\026\230x\240r\250\024\250V\2608\2702\270T\300\034\310Q\310l\320Z[\320[j\320jk\320kl\330\004\025\220Q\220i\230q\330\004\013\2101"; -static const char __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_F_D[] = "\200\001\360,\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\013\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2306\240\026\240u\250A\330\004\021\220\021\330\004\021\320\021\"\240\"\240F\250(\260\"\260D\270\006\270h\300b\310\004\310L\320Xd\320do\320o|\320|}\360\000\000~\001J\002\360\000\000J\002K\002\360\000\000K\002Z\002\360\000\000Z\002[\002\360\000\000[\002\\\002\330\004\025\220Q\320\026*\250!\330\004\013\2101"; -static const char __pyx_k_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_we[] = "\200\001\340[\\\360&\000\005\014\210;\220a\220q\330\004\n\210+\220Q\220a\330\004\014\210K\220q\230\001\330\004\r\210]\230!\2306\240\025\240a\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3003\300h\310j\320X]\320]^\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033,\250B\250a\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\030\230\022\2304\230y\250\013\2604\260v\270Q\270i\300{\320RU\320U[\320[\\\320\\e\320ep\320pu\320u{\320{|\360\000\000}\001F\002\360\000\000F\002S\002\360\000\000S\002T\002\360\000\000T\002`\002\360\000\000`\002a\002\360\000\000a\002p\002\360\000\000p\002{\002\360\000\000{\002B\003\360\000\000B\003H\003\360\000\000H\003I\003\360\000\000I\003J\003\330\004\025\220Q\220k\240\021\330\004\013\2101"; -static const char __pyx_k_aq_Qa_Kq_6_gQ_8_T_3hjX_eeoouuv[] = "\200\001\360&\000\005\014\210;\220a\220q\330\004\n\210+\220Q\220a\330\004\014\210K\220q\230\001\330\004\r\210[\230\001\230\021\330\004\r\210]\230!\2306\240\025\240g\250Q\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3003\300h\310j\320X]\320]e\320eo\320ou\320uv\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\230?\250!\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\026\220r\230\024\230Y\240k\260\024\260V\2701\270I\300[\320PS\320SY\320YZ\320Zc\320cn\320ns\320sy\320yz\360\000\000{\001D\002\360\000\000D\002O\002\360\000\000O\002U\002\360\000\000U\002[\002\360\000\000[\002\\\002\360\000\000\\\002e\002\360\000\000e\002f\002\360\000\000f\002r\002\360\000\000r\002s\002\360\000\000s\002B\003\360\000\000B\003M\003\360\000\000M\003T\003\360\000\000T\003Z\003\360\000\000Z\003[\003\360\000\000[\003\\\003\330\004\025\220Q\220i\230q\330\004\013\2101"; -static const char __pyx_k_aq_T_q_8_T_U_7_A_we_0_q_Rt9Kt6[] = "\200\001\340)*\360&\000\005\014\210;\220a\220q\330\004\r\210T\220\026\220q\230\001\330\004\r\210]\230!\2308\240:\250T\260\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\0330\260\002\260!\330\004\021\220\036\230q\240\010\250\001\330\004\021\220\034\230R\230t\2409\250K\260t\2706\300\021\300)\310=\320XY\320Ye\320ef\320fu\320u}\360\000\000~\001H\002\360\000\000H\002N\002\360\000\000N\002O\002\360\000\000O\002P\002\330\004\025\220Q\220o\240Q\330\004\026\220f\230J\240a\330\004\010\210\007\320\017\037\230q\330\010\027\220q\230\006\230a\330\004\013\2101"; -static const char __pyx_k_aq_T_q_8_T_U_7_A_we_1_81_Qha_b[] = "\200\001\360*\000\005\014\210;\220a\220q\330\004\r\210T\220\026\220q\230\001\330\004\r\210]\230!\2308\240:\250T\260\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\0331\260\021\330\004\021\320\021\"\240!\2408\2501\330\004\024\320\024%\240Q\240h\250a\330\004\021\220\035\230b\240\004\240I\250[\270\004\270F\300!\3009\310A\310\\\320YZ\320Zi\320it\320t~\360\000\000\001E\002\360\000\000E\002F\002\360\000\000F\002Q\002\360\000\000Q\002\\\002\360\000\000\\\002i\002\360\000\000i\002o\002\360\000\000o\002p\002\360\000\000p\002q\002\330\004\025\220Q\320\026&\240a\330\004\013\210=\230\001"; -static const char __pyx_k_aq_T_q_8_T_U_7_A_we_1_q_i_fAYa[] = "\200\001\360&\000\005\014\210;\220a\220q\330\004\r\210T\220\026\220q\230\001\330\004\r\210]\230!\2308\240:\250T\260\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033+\2501\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\027\230\002\230$\230i\240{\260$\260f\270A\270Y\300a\300|\320ST\320Tc\320cn\320nu\320u{\320{|\320|}\330\004\025\220Q\220j\240\001\330\004\013\2101"; -static const char __pyx_k_aq_T_q_8_T_U_7_A_we_Q_q_D_D_ay[] = "\200\001\360&\000\005\014\210;\220a\220q\330\004\r\210T\220\026\220q\230\001\330\004\r\210]\230!\2308\240:\250T\260\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033-\250Q\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\031\230\"\230D\240\t\250\033\260D\270\006\270a\270y\310\001\310\034\320UV\320Ve\320ep\320pw\320w}\320}~\320~\330\004\025\220Q\220l\240!\330\004\013\2101"; -static const char __pyx_k_aq_T_q_8_T_U_7_A_we_b_q_2T_T_q[] = "\200\001\340'(\360&\000\005\014\210;\220a\220q\330\004\r\210T\220\026\220q\230\001\330\004\r\210]\230!\2308\240:\250T\260\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033.\250b\260\001\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\032\2302\230T\240\031\250+\260T\270\026\270q\300\t\310\035\320VW\320Wc\320cd\320ds\320s~\360\000\000\001F\002\360\000\000F\002L\002\360\000\000L\002M\002\360\000\000M\002N\002\330\004\025\220Q\220m\2401\330\004\013\2101"; -static const char __pyx_k_aq_T_q_8_T_U_7_A_we_q_q_1HA_Bd[] = "\200\001\360*\000\005\014\210;\220a\220q\330\004\r\210T\220\026\220q\230\001\330\004\r\210]\230!\2308\240:\250T\260\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033/\250q\330\004\016\320\016\037\230q\240\010\250\001\330\004\022\320\022#\2401\240H\250A\330\004\021\220\033\230B\230d\240)\250;\260d\270&\300\001\300\031\310!\310<\320WX\320Xg\320gr\320ry\320y\360\000\000@\002A\002\360\000\000A\002L\002\360\000\000L\002W\002\360\000\000W\002b\002\360\000\000b\002h\002\360\000\000h\002i\002\360\000\000i\002j\002\330\004\025\220Q\220n\240A\330\004\013\210:\220Q"; -static const char __pyx_k_d_W_W_X_aq_Q_Qa_y_1_Kq_q_6_a_a[] = "\200\001\340d}\360\000\000~\001W\002\360\000\000W\002X\002\360.\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2306\240\025\240a\330\004\016\210a\330\004\021\220\032\2302\230V\2408\2502\250T\260\026\260x\270r\300\024\300\\\320Q\\\320\\i\320iw\360\000\000x\001F\002\360\000\000F\002T\002\360\000\000T\002U\002\360\000\000U\002a\002\360\000\000a\002b\002\360\000\000b\002q\002\360\000\000q\002r\002\360\000\000r\002s\002\330\004\025\220Q\220m\2401\330\004\013\2101"; -static const char __pyx_k_d_Y_Y_Z_2_aq_Q_Qa_y_1_Kq_q_6_a[] = "\200\001\340d~\360\000\000\001Y\002\360\000\000Y\002Z\002\3602\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2306\240\025\240a\330\004\017\210q\330\004\017\210q\330\004\021\220\032\2302\230V\2408\2502\250T\260\026\260x\270r\300\024\300\\\320Q\\\320\\i\320ix\360\000\000y\001H\002\360\000\000H\002W\002\360\000\000W\002X\002\360\000\000X\002d\002\360\000\000d\002e\002\360\000\000e\002t\002\360\000\000t\002u\002\360\000\000u\002@\003\360\000\000@\003A\003\360\000\000A\003B\003\330\004\025\220Q\220m\2401\330\004\013\210;\220a"; -static const char __pyx_k_input_array_type_is_not_double[] = "input array type is not double"; -static const char __pyx_k_q_9A_1_q_1_1_1A_q_a_1A_4z_A_G1[] = "\200\001\360\014\000\005\020\210q\330\004\020\220\001\220\031\230!\2309\240A\330\004\020\220\001\220\021\330\004\013\2101\330\004\010\210\007\210q\320\0201\260\022\2601\340\004\022\220)\2301\230A\330\004\010\210\007\210q\220\001\330\004\010\210\016\220a\330\010\020\220\013\2301\230A\330\010\013\2104\210z\230\021\230'\240\021\330\014\024\220A\330\010\014\210G\2201\320\024$\240L\260\001\340\004\r\210Y\220a\220q\330\004\007\200q\330\010\014\210G\2201\220A\330\004\010\210\t\220\021\330\010\014\210G\2201\320\024$\240G\2506\260\021\260!\330\010\021\220\027\230\001\230\035\240g\250V\2601\260A\330\010\020\220\001\220\031\230&\240\001\240\021\330\010\013\2106\220\023\220A\330\014\020\220\002\220%\220s\230%\230q\240\001\240\024\240R\240t\2507\260\"\260G\2701\270F\300!\3001\340\004\016\210i\220q\230\001\330\004\010\210\007\210q\220\001\330\004\010\210\n\220!\330\010\013\2107\220#\220Q\330\014\025\220Q\330\010\014\210G\2201\220I\230R\230q\340\004\r\210W\220A\220T\230\025\230a\230q\330\004\r\210W\220A\220Q\330\004\010\210\007\210q\220\003\2202\220U\230!\2301\330\004\024\220D\230\005\230Q\230a\330\004\013\210:\220Q"; -static const char __pyx_k_q_aq_T_q_8_T_U_7_A_we_b_Q_q_2T[] = "\200\001\340'?\270q\360(\000\005\014\210;\220a\220q\330\004\r\210T\220\026\220q\230\001\330\004\r\210]\230!\2308\240:\250T\260\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033.\250b\260\r\270Q\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\032\2302\230T\240\031\250+\260T\270\026\270q\300\t\310\035\320V^\320^_\320_k\320kl\320l{\360\000\000|\001G\002\360\000\000G\002N\002\360\000\000N\002T\002\360\000\000T\002U\002\360\000\000U\002V\002\330\004\025\220Q\220m\2401\330\004\013\2101"; -static const char __pyx_k_v_w_Q_Q_f_f_A_2_aq_Qa_Kq_6_a_8[] = "\200\001\340\\v\360\000\000w\001Q\002\360\000\000Q\002f\002\360\000\000f\002@\003\360\000\000@\003A\003\3602\000\005\014\210;\220a\220q\330\004\n\210+\220Q\220a\330\004\014\210K\220q\230\001\330\004\r\210]\230!\2306\240\025\240a\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3003\300h\310j\320X]\320]^\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033-\250R\250\270o\310_\320\\k\320kl\330\004\017\320\017 \240\001\240\030\250\021\330\004\017\320\017 \240\001\240\030\250\021\330\004\021\220\031\230\"\230D\240\t\250\033\260D\270\006\270a\270y\310\013\320SV\320V\\\320\\]\320]f\320fq\320qv\320v|\320|}\360\000\000~\001G\002\360\000\000G\002V\002\360\000\000V\002e\002\360\000\000e\002t\002\360\000\000t\002C\003\360\000\000C\003R\003\360\000\000R\003S\003\360\000\000S\003_\003\360\000\000_\003`\003\360\000\000`\003o\003\360\000\000o\003z\003\360\000\000z\003B\004\360\000\000B\004H\004\360\000\000H\004I\004\360\000\000I\004T\004\360\000\000T\004_\004\360\000\000_\004g\004\360\000\000g\004m\004\360\000\000m\004n\004\360\000\000n\004o\004\330\004\025\220Q\220l\240!\330\004\013\210;\220a"; -static const char __pyx_k_z_R_R_S_aq_Qa_Kq_6_gQ_8_T_3hjX[] = "\200\001\360\004\000z\001R\002\360\000\000R\002S\002\360(\000\005\014\210;\220a\220q\330\004\n\210+\220Q\220a\330\004\014\210K\220q\230\001\330\004\r\210[\230\001\230\021\330\004\r\210]\230!\2306\240\025\240g\250Q\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3003\300h\310j\320X]\320]e\320eo\320ou\320uv\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033-\250R\250}\270A\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\031\230\"\230D\240\t\250\033\260D\270\006\270a\270y\310\013\320SV\320V\\\320\\]\320]f\320fq\320qv\320v|\320|}\360\000\000~\001G\002\360\000\000G\002R\002\360\000\000R\002X\002\360\000\000X\002^\002\360\000\000^\002_\002\360\000\000_\002h\002\360\000\000h\002u\002\360\000\000u\002B\003\360\000\000B\003C\003\360\000\000C\003O\003\360\000\000O\003P\003\360\000\000P\003_\003\360\000\000_\003j\003\360\000\000j\003q\003\360\000\000q\003w\003\360\000\000w\003x\003\360\000\000x\003y\003\330\004\025\220Q\220l\240!\330\004\013\2101"; -static const char __pyx_k_01_aq_Q_T_q_RvXRt6_4_S_aammnn_Q[] = "\200\001\34001\360&\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\021\220\021\330\004\021\220\034\230R\230v\240X\250R\250t\2606\270\030\300\022\3004\300|\320S`\320`a\320am\320mn\320n}\320}~\320~\330\004\025\220Q\220o\240Q\330\004\013\2101"; -static const char __pyx_k_01_aq_Q_T_q_a_RvXRt6_4_S_aammnn[] = "\200\001\34001\360&\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\034\230R\230v\240X\250R\250t\2606\270\030\300\022\3004\300|\320S`\320`a\320am\320mn\320n}\320}~\320~\330\004\025\220Q\220o\240Q\330\004\013\2101"; -static const char __pyx_k_0HHbb_0_aq_Q_T_q_q_q_RvXRt6_4_S[] = "\200\001\3400H\320Hb\320b|\320|}\3600\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\017\210q\330\004\017\210q\330\004\021\220\034\230R\230v\240X\250R\250t\2606\270\030\300\022\3004\300|\320S`\320`o\320o~\360\000\000\001N\002\360\000\000N\002O\002\360\000\000O\002[\002\360\000\000[\002\\\002\360\000\000\\\002k\002\360\000\000k\002l\002\360\000\000l\002w\002\360\000\000w\002x\002\360\000\000x\002y\002\330\004\025\220Q\220o\240Q\330\004\013\210;\220a"; -static const char __pyx_k_0_aq_Q_T_q_a_A_BfHBd_lRaabbnnoo[] = "\200\001\340/0\360.\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\024\220A\330\004\022\220!\330\004\021\220\033\230B\230f\240H\250B\250d\260&\270\010\300\002\300$\300l\320Ra\320ab\320bn\320no\320o~\320~\360\000\000@\002J\002\360\000\000J\002K\002\360\000\000K\002[\002\360\000\000[\002\\\002\360\000\000\\\002]\002\330\004\025\220Q\220n\240A\330\004\013\210:\320\025%\240Q"; -static const char __pyx_k_0_aq_Q_T_q_a_BfHBd_lR___llmm_Qn[] = "\200\001\340/0\360&\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\033\230B\230f\240H\250B\250d\260&\270\010\300\002\300$\300l\320R_\320_`\320`l\320lm\320m|\320|}\320}~\330\004\025\220Q\220n\240A\330\004\013\2101"; -static const char __pyx_k_12_aq_Q_T_q_a_b_hb_F_D_Taabbnno[] = "\200\001\34012\360&\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\035\230b\240\006\240h\250b\260\004\260F\270(\300\"\300D\310\014\320Ta\320ab\320bn\320no\320o~\320~\360\000\000@\002A\002\330\004\025\220Q\320\026&\240a\330\004\013\2101"; -static const char __pyx_k_1_a_OuTUUV_Q_31_9AT_4q_1HF_wc_d[] = "\200\001\360\014\000\005\022\320\021+\2501\320,>\270a\320?O\310u\320TU\320UV\330\004\025\220Q\320\0263\2601\340\004\013\2109\220A\220T\230\021\330\004\013\2104\210q\220\003\2201\220H\230F\240!\340\004\007\200w\210c\220\025\220d\230%\230x\240x\250y\270\001\330\010\017\210t\2201\220C\220q\230\001\340\004\005\330\010\020\220\001\330\010\021\220\033\230A\230T\240\030\250\021"; -static const char __pyx_k_34_aq_Q_T_q_fHBd_Vccddppq_r_A_A[] = "\200\001\34034\360*\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\020\220\001\330\004\020\220\001\330\004\021\220\037\240\002\240&\250\010\260\002\260$\260f\270H\300B\300d\310,\320Vc\320cd\320dp\320pq\360\000\000r\001A\002\360\000\000A\002B\002\360\000\000B\002N\002\360\000\000N\002O\002\360\000\000O\002P\002\330\004\025\220Q\320\026(\250\001\330\004\013\210<\220q"; -static const char __pyx_k_45_aq_T_q_8_T_U_7_A_we_2Q_q_i_f[] = "\200\001\34045\360&\000\005\014\210;\220a\220q\330\004\r\210T\220\026\220q\230\001\330\004\r\210]\230!\2308\240:\250T\260\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033;\2702\270Q\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\320\021(\250\002\250$\250i\260{\300$\300f\310A\310Y\320Vc\320cd\320dp\320pq\360\000\000r\001A\002\360\000\000A\002L\002\360\000\000L\002S\002\360\000\000S\002Y\002\360\000\000Y\002Z\002\360\000\000Z\002[\002\330\004\025\220Q\320\0260\260\001\330\004\013\2101"; -static const char __pyx_k_5_t_Qm1_d_1_c_d_3a_Q_c_d_3a_Q_u[] = "\200\001\360\014\000\005\023\320\022#\2405\250\001\330\004\007\200t\210:\220Q\220m\2401\330\010\026\220d\230!\2301\330\004\016\210c\220\021\220$\220d\230!\2303\230a\230~\250Q\330\004\016\210c\220\021\220$\220d\230!\2303\230a\230~\250Q\360\006\000\005\010\200u\210B\210b\220\003\2205\230\002\230!\2302\230Q\330\010\017\210q\360\n\000\005\013\210!\330\004\010\210\005\210V\2201\220I\230W\240A\240Q\330\010\013\2101\210B\210b\220\002\220!\330\014\017\210w\220a\320\027(\250\001\250\021\250\"\250A\330\004\013\2101"; -static const char __pyx_k_78_aq_Q_T_q_a_BfHBd_lZgghhttu_v[] = "\200\001\34078\360&\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\320\021$\240B\240f\250H\260B\260d\270&\300\010\310\002\310$\310l\320Zg\320gh\320ht\320tu\360\000\000v\001E\002\360\000\000E\002F\002\360\000\000F\002G\002\330\004\025\220Q\320\026,\250A\330\004\013\2101"; -static const char __pyx_k_AA_uuv0_aq_T_q_8_T_U_7_A_we_0_o[] = "\200\001\340)A\320A[\320[u\320uv\3600\000\005\014\210;\220a\220q\330\004\r\210T\220\026\220q\230\001\330\004\r\210]\230!\2308\240:\250T\260\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\0330\260\002\260-\270\310o\320]^\330\004\017\320\017 \240\001\240\030\250\021\330\004\017\320\017 \240\001\240\030\250\021\330\004\021\220\034\230R\230t\2409\250K\260t\2706\300\021\300)\310=\320Xg\320gv\360\000\000w\001F\002\360\000\000F\002G\002\360\000\000G\002S\002\360\000\000S\002T\002\360\000\000T\002c\002\360\000\000c\002n\002\360\000\000n\002v\002\360\000\000v\002|\002\360\000\000|\002}\002\360\000\000}\002H\003\360\000\000H\003S\003\360\000\000S\003[\003\360\000\000[\003a\003\360\000\000a\003b\003\360\000\000b\003c\003\330\004\025\220Q\220o\240Q\330\004\013\210;\220a"; -static const char __pyx_k_A_A_2_k_Qa_e_e1_2S_AQ_U_t1A_q_4[] = "\200A\360\016\000\t\021\220\004\220A\340\010\033\2302\230\\\250\025\250k\270\021\270+\300Q\300a\330\034 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"\200A\340\010\020\220\004\220A\330\010\013\2104\210w\220a\220w\230a\330\014\021\220\030\230\021\330\014\021\320\021!\240\021\360\006\000\r\022\220\037\240\013\2501\330\014\021\220\036\230{\250!\330\014\021\220\033\230K\240q\330\014\021\320\021\"\240!\360\006\000\r\022\220\030\230\037\250\001\250\024\250Q\360\006\000\r\021\220\005\220V\2301\230E\240\025\240d\250!\2501\330\020\027\320\0270\260\001\260\024\260Y\270a\330\020\035\230T\240\021\240!\330\020\023\2204\220q\320\030(\250\003\2501\330\024\030\230\001\320\031+\320+H\310\001\310\021\330\020\025\220\\\240\021\240.\260\001\330\014\021\220\025\220a\320\027(\250\004\250A\360\006\000\r\021\220\005\220V\2301\230E\240\025\240d\250!\2501\330\020\027\320\0273\2601\260D\270\t\300\021\330\020\035\230T\240\021\240!\330\020\025\220[\240\001\240\036\250q\330\014\021\220\025\220a\320\027'\240t\2501\360\006\000\r\022\220\025\220a\320\027)\250\033\260A\330\014\020\220\005\220V\2301\230E\240\025\240d\250!\2501\330\020\027\320\0271\260\021\260$\260i\270q\330\020\036\230d\240!\2401\330\020\025\220U\230!\230?\250!\250?\270$\270a\270q\330\020\025\220X\230Q\230o\250Q\330\014\021\220\025\220a\320\027)\250\024\250Q\330\010\017\210q"; -static const char __pyx_k_A_A_a_G1_t3e1_aq_4_q_Q_AT_V1A_S[] = "\200A\360\010\000\t\021\220\004\220A\330\010\026\220a\340\010\014\210G\2201\330\014\017\210t\2203\220e\2301\330\020\030\230\006\230a\230q\330\020\023\2204\320\027/\250q\260\005\260Q\330\024\031\230\033\240A\240T\250\021\250+\260V\2701\270A\330\024\"\240!\330\021\025\220S\230\005\230Q\330\020\025\220\\\240\021\240$\240a\320'9\270\026\270q\300\001\330\020\025\220U\230!\230>\250\021\250'\260\026\260q\270\001\340\010\013\2101\330\014\031\230\021\330\014\017\210t\320\023$\240A\240T\250\021\250!\330\020\035\230Q\330\014\017\210s\220!\2206\230\022\2301\330\020\024\220C\220~\240Y\250a\250u\260A\330\024\031\230\021\330\024\027\220r\230\022\2303\230a\230q\330\030 \240\004\240A\240Q\330\030\033\2304\320\0377\260q\270\014\300A\330\034!\240\033\250A\250[\270\001\270\033\300A\330\034*\250!\340\010\013\2105\220\003\2201\330\014\017\210q\330\020\025\220U\230!\320\033+\2504\250q\330\014\021\320\021\"\240!"; -static const char __pyx_k_A_B_aq_aq_Qa_Kq_6_uA_8_T_4xzY_d[] = "\200\001\360\004\000A\002B\002\360&\000\005\014\210;\220a\220q\330\004\013\210;\220a\220q\330\004\n\210+\220Q\220a\330\004\014\210K\220q\230\001\330\004\r\210]\230!\2306\240\026\240u\250A\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3004\300x\310z\320Y\\\320\\d\320dn\320ns\320st\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\0336\260b\270\001\330\004\021\220\036\230q\240\010\250\001\330\004\021\320\021#\2402\240T\250\031\260+\270T\300\026\300q\310\t\320Q\\\320\\`\320`f\320fg\320gp\320p{\320{~\360\000\000\001E\002\360\000\000E\002F\002\360\000\000F\002O\002\360\000\000O\002Z\002\360\000\000Z\002_\002\360\000\000_\002e\002\360\000\000e\002f\002\360\000\000f\002o\002\360\000\000o\002}\002\360\000\000}\002~\002\360\000\000~\002J\003\360\000\000J\003K\003\360\000\000K\003Z\003\360\000\000Z\003b\003\360\000\000b\003l\003\360\000\000l\003r\003\360\000\000r\003s\003\360\000\000s\003t\003\330\004\025\220Q\320\026+\2501\330\004\013\2101"; -static const char __pyx_k_A_Y_Y_Z_aq_Q_Qa_y_1_Kq_q_6_6_gQ[] = "\200\001\360\004\000A\002Y\002\360\000\000Y\002Z\002\360.\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210[\230\001\230\021\330\004\022\220)\2306\240\021\330\004\r\210]\230!\2306\240\025\240g\250Q\330\004\016\210a\330\004\021\220\031\230\"\230F\240(\250\"\250D\260\006\260h\270b\300\004\300L\320P[\320[h\320hv\360\000\000w\001D\002\360\000\000D\002Q\002\360\000\000Q\002R\002\360\000\000R\002^\002\360\000\000^\002_\002\360\000\000_\002n\002\360\000\000n\002o\002\360\000\000o\002p\002\330\004\025\220Q\220l\240!\330\004\013\2101"; -static const char __pyx_k_A_aq_Kq_6_8_T_5_U_7_A_we_2Q_q_i[] = "\200\001\340@A\360&\000\005\014\210;\220a\220q\330\004\014\210K\220q\230\001\330\004\r\210]\230!\2306\240\021\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3005\310\001\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033+\2502\250Q\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\027\230\002\230$\230i\240{\260$\260f\270A\270Y\300k\320QV\320V\\\320\\]\320]f\320fs\320st\360\000\000u\001A\002\360\000\000A\002B\002\360\000\000B\002Q\002\360\000\000Q\002\\\002\360\000\000\\\002c\002\360\000\000c\002i\002\360\000\000i\002j\002\360\000\000j\002k\002\330\004\025\220Q\220j\240\001\330\004\013\2101"; -static const char __pyx_k_A_aq_Qa_6_8_T_3a_U_7_A_we_Rq_AX[] = "\200\001\340@A\360*\000\005\014\210;\220a\220q\330\004\n\210+\220Q\220a\330\004\r\210]\230!\2306\240\021\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3003\300a\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033-\250R\250q\330\004\023\320\023$\240A\240X\250Q\330\004\021\320\021\"\240!\2408\2501\330\004\021\220\031\230\"\230D\240\t\250\033\260D\270\006\270a\270y\310\013\320SV\320V\\\320\\]\320]f\320fs\320st\360\000\000u\001A\002\360\000\000A\002B\002\360\000\000B\002Q\002\360\000\000Q\002\\\002\360\000\000\\\002h\002\360\000\000h\002n\002\360\000\000n\002o\002\360\000\000o\002z\002\360\000\000z\002E\003\360\000\000E\003O\003\360\000\000O\003U\003\360\000\000U\003V\003\360\000\000V\003W\003\330\004\025\220Q\220l\240!\330\004\013\210?\230!"; -static const char __pyx_k_A_aq_T_q_8_T_U_7_A_we_2_q_i_fAY[] = "\200\001\340$<\270A\360(\000\005\014\210;\220a\220q\330\004\r\210T\220\026\220q\230\001\330\004\r\210]\230!\2308\240:\250T\260\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033+\2502\250]\270!\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\027\230\002\230$\230i\240{\260$\260f\270A\270Y\300m\320S[\320[\\\320\\h\320hi\320ix\360\000\000y\001D\002\360\000\000D\002K\002\360\000\000K\002Q\002\360\000\000Q\002R\002\360\000\000R\002S\002\330\004\025\220Q\220j\240\001\330\004\013\2101"; -static const char __pyx_k_A_z_____b_b_G_G_h_h_i_4_aq_Qa_6[] = "\200\001\340A[\320[z\360\000\000{\001_\002\360\000\000_\002\002\360\000\000\002b\003\360\000\000b\003G\004\360\000\000G\004h\004\360\000\000h\004i\004\3604\000\005\014\210;\220a\220q\330\004\n\210+\220Q\220a\330\004\r\210]\230!\2306\240\021\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3003\300a\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033.\250b\260\r\320=O\320Of\320fy\360\000\000z\001P\002\360\000\000P\002h\002\360\000\000h\002|\002\360\000\000|\002}\002\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\032\2302\230T\240\031\250+\260T\270\026\270q\300\t\310\033\320TW\320W]\320]^\320^g\320gt\360\000\000u\001G\002\360\000\000G\002^\002\360\000\000^\002q\002\360\000\000q\002G\003\360\000\000G\003_\003\360\000\000_\003s\003\360\000\000s\003J\004\360\000\000J\004K\004\360\000\000K\004W\004\360\000\000W\004X\004\360\000\000X\004g\004\360\000\000g\004r\004\360\000\000r\004y\004\360\000\000y\004\004\360\000\000\004@\005\360\000\000@\005A\005\330\004\025\220Q\220m\2401\330\004\013\2101"; -static const char __pyx_k_B_aq_Q_T_q_a_r_xr_V82T_Zccddppq[] = "\200\001\340*B\300!\360(\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\026\220r\230\026\230x\240r\250\024\250V\2608\2702\270T\300\034\310]\320Zc\320cd\320dp\320pq\360\000\000r\001A\002\360\000\000A\002B\002\360\000\000B\002C\002\330\004\025\220Q\220i\230q\330\004\013\2101"; -static const char __pyx_k_B_aq_Q_T_q_a_r_xr_V82T_Zddeeqqr[] = "\200\001\340*B\300!\360(\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\026\220r\230\026\230x\240r\250\024\250V\2608\2702\270T\300\034\310]\320Zd\320de\320eq\320qr\360\000\000s\001B\002\360\000\000B\002C\002\360\000\000C\002D\002\330\004\025\220Q\220i\230q\330\004\013\2101"; -static const char __pyx_k_CC_aq_Q_T_q_a_fHBd_m_hhqqrr_O_O[] = "\200\001\340+C\320C[\320[\\\360*\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\027\230\002\230&\240\010\250\002\250$\250f\260H\270B\270d\300,\310m\320[h\320hq\320qr\320r~\320~\360\000\000@\002O\002\360\000\000O\002P\002\360\000\000P\002Q\002\330\004\025\220Q\220j\240\001\330\004\013\2101"; -static const char __pyx_k_CZZqqr_aq_k_6_8_T_7_U_7_A_we_Bl[] = "\200\001\340CZ\320Zq\320qr\360,\000\005\014\210;\220a\220q\330\004\016\210k\230\021\230!\330\004\r\210]\230!\2306\240\021\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3007\310!\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033,\250B\250l\270,\300a\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\030\230\022\2304\230y\250\013\2604\260v\270Q\270i\300{\320RY\320Y_\320_`\320`i\320iu\360\000\000v\001B\002\360\000\000B\002K\002\360\000\000K\002L\002\360\000\000L\002X\002\360\000\000X\002Y\002\360\000\000Y\002h\002\360\000\000h\002s\002\360\000\000s\002z\002\360\000\000z\002@\003\360\000\000@\003A\003\360\000\000A\003B\003\330\004\025\220Q\220k\240\021\330\004\013\2101"; -static const char __pyx_k_C_D_aq_aq_Qa_Kq_6_uA_8_T_4xzY_d[] = "\200\001\360\004\000C\002D\002\360&\000\005\014\210;\220a\220q\330\004\013\210;\220a\220q\330\004\n\210+\220Q\220a\330\004\014\210K\220q\230\001\330\004\r\210]\230!\2306\240\026\240u\250A\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3004\300x\310z\320Y\\\320\\d\320dn\320ns\320st\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\0338\270\002\270!\330\004\021\220\036\230q\240\010\250\001\330\004\021\320\021%\240R\240t\2509\260K\270t\3006\310\021\310)\320S^\320^b\320bh\320hi\320ir\320r}\360\000\000~\001A\002\360\000\000A\002G\002\360\000\000G\002H\002\360\000\000H\002Q\002\360\000\000Q\002\\\002\360\000\000\\\002a\002\360\000\000a\002g\002\360\000\000g\002h\002\360\000\000h\002q\002\360\000\000q\002\002\360\000\000\002@\003\360\000\000@\003L\003\360\000\000L\003M\003\360\000\000M\003\\\003\360\000\000\\\003d\003\360\000\000d\003n\003\360\000\000n\003t\003\360\000\000t\003u\003\360\000\000u\003v\003\330\004\025\220Q\320\026-\250Q\330\004\013\2101"; -static const char __pyx_k_DD_2_aq_Q_T_q_a_A_6_4vXRt_iixxy[] = "\200\001\340,D\320D\\\320\\]\3602\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\024\220A\330\004\022\220!\330\004\021\220\030\230\022\2306\240\030\250\022\2504\250v\260X\270R\270t\300<\310}\320\\i\320ix\320xy\360\000\000z\001F\002\360\000\000F\002G\002\360\000\000G\002V\002\360\000\000V\002W\002\360\000\000W\002a\002\360\000\000a\002b\002\360\000\000b\002r\002\360\000\000r\002s\002\360\000\000s\002t\002\330\004\025\220Q\220k\240\021\330\004\013\210:\320\025%\240Q"; -static const char __pyx_k_DE_Kq_Kq_7_8_U_E_U_7_A_we_b_q_2[] = "\200\001\340DE\360(\000\005\r\210K\220q\230\001\330\004\014\210K\220q\230\001\330\004\r\210]\230!\2307\240!\330\004\r\210]\230!\2308\240:\250U\260(\270*\300E\310\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033.\250b\260\001\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\032\2302\230T\240\031\250+\260U\270&\300\001\300\031\310+\320UZ\320Z`\320`a\320aj\320jw\320wx\360\000\000y\001E\002\360\000\000E\002F\002\360\000\000F\002U\002\360\000\000U\002`\002\360\000\000`\002g\002\360\000\000g\002m\002\360\000\000m\002n\002\360\000\000n\002o\002\330\004\025\220Q\220m\2401\330\004\013\2101"; -static const char __pyx_k_D_E_aq_aq_Qa_Kq_6_uA_8_T_4xzY_d[] = "\200\001\360\004\000D\002E\002\360&\000\005\014\210;\220a\220q\330\004\013\210;\220a\220q\330\004\n\210+\220Q\220a\330\004\014\210K\220q\230\001\330\004\r\210]\230!\2306\240\026\240u\250A\330\004\r\210]\230!\2308\240:\250T\260\030\270\032\3004\300x\310z\320Y\\\320\\d\320dn\320ns\320st\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\0339\270\022\2701\330\004\021\220\036\230q\240\010\250\001\330\004\021\320\021&\240b\250\004\250I\260[\300\004\300F\310!\3109\320T_\320_c\320ci\320ij\320js\320s~\360\000\000\001B\002\360\000\000B\002H\002\360\000\000H\002I\002\360\000\000I\002R\002\360\000\000R\002]\002\360\000\000]\002b\002\360\000\000b\002h\002\360\000\000h\002i\002\360\000\000i\002r\002\360\000\000r\002@\003\360\000\000@\003A\003\360\000\000A\003M\003\360\000\000M\003N\003\360\000\000N\003]\003\360\000\000]\003e\003\360\000\000e\003o\003\360\000\000o\003u\003\360\000\000u\003v\003\360\000\000v\003w\003\330\004\025\220Q\320\026.\250a\330\004\013\2101"; -static const char __pyx_k_EQ_aq_Q_T_q_a_a_6_4vXRt_gghhttu[] = "\200\001\340,E\300Q\360,\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\016\210a\330\004\021\220\030\230\022\2306\240\030\250\022\2504\250v\260X\270R\270t\300<\310|\320[g\320gh\320ht\320tu\360\000\000v\001E\002\360\000\000E\002F\002\360\000\000F\002P\002\360\000\000P\002Q\002\360\000\000Q\002R\002\330\004\025\220Q\220k\240\021\330\004\013\210:\220Q"; -static const char __pyx_k_E_F_aq_aq_Qa_Kq_6_uA_8_T_4xzY_d[] = 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char __pyx_k_E_a_aq_Q_Qa_y_1_6_a_fHBd_kYhhrr[] = "\200\001\340E`\320`a\360*\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\r\210]\230!\2306\240\021\330\004\016\210a\330\004\021\220\027\230\002\230&\240\010\250\002\250$\250f\260H\270B\270d\300,\310k\320Yh\320hr\320rs\320s\360\000\000@\002A\002\360\000\000A\002P\002\360\000\000P\002Q\002\360\000\000Q\002R\002\330\004\025\220Q\220j\240\001\330\004\013\2101"; -static const char __pyx_k_FF_ttu4_aq_Q_T_q_q_q_2V82T_xr_Q[] = "\200\001\340.F\320F]\320]t\320tu\3604\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\027\220q\330\004\030\230\001\330\004\027\220q\330\004\021\220\032\2302\230V\2408\2502\250T\260\026\260x\270r\300\024\300\\\320Q^\320^h\320hr\320r{\320{|\360\000\000}\001I\002\360\000\000I\002J\002\360\000\000J\002Y\002\360\000\000Y\002Z\002\360\000\000Z\002m\002\360\000\000m\002n\002\360\000\000n\002B\003\360\000\000B\003C\003\360\000\000C\003D\003\330\004\025\220Q\220m\2401\330\004\013\320\013\036\320\0362\260!"; -static const char __pyx_k_Fa_aq_Q_T_q_a_2V82T_xr_Q_ffggss[] = "\200\001\340.F\300a\360(\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\021\220\032\2302\230V\2408\2502\250T\260\026\260x\270r\300\024\300\\\320Q^\320^f\320fg\320gs\320st\360\000\000u\001D\002\360\000\000D\002E\002\360\000\000E\002F\002\330\004\025\220Q\220m\2401\330\004\013\2101"; -static const char __pyx_k_Function__check_opt_input_value[] = "_Function__check_opt_input_value"; -static const char __pyx_k_Function__input_price_series_na[] = "_Function__input_price_series_names"; -static const char __pyx_k_Function_has_an_unstable_period[] = "Function has an unstable period"; -static const char __pyx_k_GGZZr_s_F_F_a_8_aq_Q_T_q_a_A_Bf[] = "\200\001\340/G\320GZ\320Zr\360\000\000s\001F\002\360\000\000F\002`\002\360\000\000`\002a\002\3608\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\r\210T\220\026\220q\230\001\330\004\016\210a\330\004\024\220A\330\004\022\220!\330\004\021\220\033\230B\230f\240H\250B\250d\260&\270\010\300\002\300$\300l\320R_\320_l\320ly\360\000\000z\001G\002\360\000\000G\002V\002\360\000\000V\002e\002\360\000\000e\002f\002\360\000\000f\002r\002\360\000\000r\002s\002\360\000\000s\002B\003\360\000\000B\003C\003\360\000\000C\003M\003\360\000\000M\003N\003\360\000\000N\003^\003\360\000\000^\003_\003\360\000\000_\003`\003\330\004\025\220Q\220n\240A\330\004\013\210:\320\025%\240Q"; -static const char __pyx_k_GH_aq_Q_Kq_q_6_a_fHBd_m_hhiiuuv[] = "\200\001\340GH\360(\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2306\240\021\330\004\016\210a\330\004\021\220\027\230\002\230&\240\010\250\002\250$\250f\260H\270B\270d\300,\310m\320[h\320hi\320iu\320uv\360\000\000w\001F\002\360\000\000F\002G\002\360\000\000G\002H\002\330\004\025\220Q\220j\240\001\330\004\013\2101"; -static const char __pyx_k_GH_aq_Q_Qa_y_1_6_1_F_D_hb_LP_hh[] = "\200\001\340GH\360,\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\r\210]\230!\2306\240\021\330\004\023\2201\330\004\021\220\021\330\004\021\220\031\230\"\230F\240(\250\"\250D\260\006\260h\270b\300\004\300L\320P[\320[h\320hi\320iu\320uv\360\000\000w\001F\002\360\000\000F\002G\002\360\000\000G\002V\002\360\000\000V\002W\002\360\000\000W\002X\002\330\004\025\220Q\220l\240!\330\004\013\210?\230!"; -static const char __pyx_k_IJ_Kq_q_Kq_q_7_a_6_4vXRt_P_jjkk[] = "\200\001\340IJ\360*\000\005\r\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2307\240!\330\004\016\210a\330\004\021\220\030\230\022\2306\240\030\250\022\2504\250v\260X\270R\270t\300=\320P]\320]j\320jk\320kw\320wx\360\000\000y\001H\002\360\000\000H\002I\002\360\000\000I\002J\002\330\004\025\220Q\220k\240\021\330\004\013\2101"; -static const char __pyx_k_IJ_aq_Q_Qa_y_1_6_a_BfHBd_lR_jjk[] = "\200\001\340IJ\360(\000\005\014\210;\220a\220q\330\004\020\220\t\230\024\230Q\330\004\n\210+\220Q\220a\330\004\017\210y\230\003\2301\330\004\r\210]\230!\2306\240\021\330\004\016\210a\330\004\021\220\033\230B\230f\240H\250B\250d\260&\270\010\300\002\300$\300l\320R]\320]j\320jk\320kw\320wx\360\000\000y\001H\002\360\000\000H\002I\002\360\000\000I\002J\002\330\004\025\220Q\220n\240A\330\004\013\2101"; -static const char __pyx_k_JK_aq_Q_Qa_y_1_6_a_RvXRt6_4_S_k[] = 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__pyx_k_KL_Kq_q_Kq_q_7_a_2V82T_xr_R__ll[] = "\200\001\340KL\360*\000\005\r\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\014\210K\220q\230\001\330\004\021\220\031\230%\230q\330\004\r\210]\230!\2307\240!\330\004\016\210a\330\004\021\220\032\2302\230V\2408\2502\250T\260\026\260x\270r\300\024\300]\320R_\320_l\320lm\320my\320yz\360\000\000{\001J\002\360\000\000J\002K\002\360\000\000K\002L\002\330\004\025\220Q\220m\2401\330\004\013\2101"; -static const char __pyx_k_Kaufman_Adaptive_Moving_Average[] = "Kaufman Adaptive Moving Average"; -static const char __pyx_k_Kq_Kq_7_8_U_E_U_7_A_we_1_q_i_vQ[] = 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"\200\001\360(\000\005\r\210K\220q\230\001\330\004\014\210K\220q\230\001\330\004\r\210]\230!\2307\240!\330\004\r\210]\230!\2308\240:\250U\260(\270*\300E\310\021\330\004\r\210U\220'\230\022\2307\240\"\240A\330\004\017\210w\220e\320\033,\250A\330\004\016\320\016\037\230q\240\010\250\001\330\004\021\220\030\230\022\2304\230y\250\013\2605\270\006\270a\270y\310\013\320SX\320X^\320^_\320_h\320hi\320iu\320uv\360\000\000w\001F\002\360\000\000F\002Q\002\360\000\000Q\002X\002\360\000\000X\002^\002\360\000\000^\002_\002\360\000\000_\002`\002\330\004\025\220Q\220k\240\021\330\004\013\2101"; -static const char __pyx_k_Out_of_Range_Start_Index_TA_OUT[] = "Out-of-Range Start Index (TA_OUT_OF_RANGE_START_INDEX)"; -static const char __pyx_k_Q_AQQVVWWX_Q_5Q_9AT_4q_1JfA_D_R[] = 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-static const char __pyx_k_TA_RestoreCandleDefaultSettings[] = "TA_RestoreCandleDefaultSettings"; -static const char __pyx_k_TTU_aq_T_q_8_T_U_7_A_we_2_q_q_i[] = "\200\001\340$<\320 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 3)) - #define CYTHON_SMALL_CODE __attribute__((cold)) -#else - #define CYTHON_SMALL_CODE -#endif -#endif - -typedef struct { - PyObject *__pyx_d; - PyObject *__pyx_b; - PyObject *__pyx_cython_runtime; - PyObject *__pyx_empty_tuple; - PyObject *__pyx_empty_bytes; - PyObject *__pyx_empty_unicode; - #ifdef __Pyx_CyFunction_USED - PyTypeObject *__pyx_CyFunctionType; - #endif - #ifdef __Pyx_FusedFunction_USED - PyTypeObject *__pyx_FusedFunctionType; - #endif - #ifdef __Pyx_Generator_USED - PyTypeObject *__pyx_GeneratorType; - #endif - #ifdef __Pyx_IterableCoroutine_USED - PyTypeObject *__pyx_IterableCoroutineType; - #endif - #ifdef __Pyx_Coroutine_USED - PyTypeObject *__pyx_CoroutineAwaitType; - #endif - #ifdef __Pyx_Coroutine_USED - PyTypeObject *__pyx_CoroutineType; - #endif - PyTypeObject *__pyx_ptype_7cpython_4type_type; - PyTypeObject *__pyx_ptype_5numpy_dtype; - PyTypeObject *__pyx_ptype_5numpy_flatiter; - PyTypeObject *__pyx_ptype_5numpy_broadcast; - PyTypeObject *__pyx_ptype_5numpy_ndarray; - PyTypeObject *__pyx_ptype_5numpy_generic; - PyTypeObject *__pyx_ptype_5numpy_number; - PyTypeObject *__pyx_ptype_5numpy_integer; - PyTypeObject *__pyx_ptype_5numpy_signedinteger; - PyTypeObject *__pyx_ptype_5numpy_unsignedinteger; - PyTypeObject *__pyx_ptype_5numpy_inexact; - PyTypeObject *__pyx_ptype_5numpy_floating; - PyTypeObject *__pyx_ptype_5numpy_complexfloating; - PyTypeObject *__pyx_ptype_5numpy_flexible; - PyTypeObject *__pyx_ptype_5numpy_character; - PyTypeObject *__pyx_ptype_5numpy_ufunc; - __Pyx_CachedCFunction __pyx_umethod_PyDict_Type_keys; - __Pyx_CachedCFunction __pyx_umethod_PyDict_Type_pop; - PyObject *__pyx_tuple[10]; - PyObject *__pyx_codeobj_tab[369]; - PyObject *__pyx_string_tab[945]; - PyObject *__pyx_int_0; - PyObject *__pyx_int_1; - PyObject *__pyx_int_2; - PyObject *__pyx_int_3; - PyObject *__pyx_int_4; - PyObject *__pyx_int_8; - PyObject *__pyx_int_9; - PyObject *__pyx_int_12; - PyObject *__pyx_int_16; - PyObject *__pyx_int_32; - PyObject *__pyx_int_64; - PyObject *__pyx_int_128; - PyObject *__pyx_int_256; - PyObject *__pyx_int_512; - PyObject *__pyx_int_1024; - PyObject *__pyx_int_2048; - PyObject *__pyx_int_4096; - PyObject *__pyx_int_16777216; - PyObject *__pyx_int_67108864; - PyObject *__pyx_int_134217728; - PyObject *__pyx_int_268435456; - PyObject *__pyx_int_neg_1; -/* #### Code section: module_state_contents ### */ -/* CommonTypesMetaclass.module_state_decls */ -PyTypeObject *__pyx_CommonTypesMetaclassType; - -/* CachedMethodType.module_state_decls */ -#if CYTHON_COMPILING_IN_LIMITED_API -PyObject *__Pyx_CachedMethodType; -#endif - -/* CodeObjectCache.module_state_decls */ -struct __Pyx_CodeObjectCache __pyx_code_cache; - -/* #### Code section: module_state_end ### */ -} __pyx_mstatetype; - -#if 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-#define __pyx_n_u_ALL __pyx_string_tab[9] -#define __pyx_n_u_APO __pyx_string_tab[10] -#define __pyx_n_u_AROON __pyx_string_tab[11] -#define __pyx_n_u_AROONOSC __pyx_string_tab[12] -#define __pyx_n_u_ARRAY_TYPES __pyx_string_tab[13] -#define __pyx_n_u_ASIN __pyx_string_tab[14] -#define __pyx_n_u_ATAN __pyx_string_tab[15] -#define __pyx_n_u_ATR __pyx_string_tab[16] -#define __pyx_n_u_AVGDEV __pyx_string_tab[17] -#define __pyx_n_u_AVGPRICE __pyx_string_tab[18] -#define __pyx_n_u_AllCandleSettings __pyx_string_tab[19] -#define __pyx_kp_u_Allocation_Error_TA_ALLOC_ERR __pyx_string_tab[20] -#define __pyx_n_u_BBANDS __pyx_string_tab[21] -#define __pyx_n_u_BETA __pyx_string_tab[22] -#define __pyx_n_u_BOP __pyx_string_tab[23] -#define __pyx_kp_u_Bad_Object_TA_BAD_OBJECT __pyx_string_tab[24] -#define __pyx_kp_u_Bad_Parameter_TA_BAD_PARAM __pyx_string_tab[25] -#define __pyx_n_u_BodyDoji __pyx_string_tab[26] -#define __pyx_n_u_BodyLong __pyx_string_tab[27] -#define __pyx_n_u_BodyShort __pyx_string_tab[28] -#define __pyx_n_u_BodyVeryLong __pyx_string_tab[29] -#define __pyx_kp_u_Bull_Bear_Pattern_Bearish_0_Neut __pyx_string_tab[30] -#define __pyx_n_u_CCI __pyx_string_tab[31] -#define __pyx_n_u_CDL2CROWS __pyx_string_tab[32] -#define __pyx_n_u_CDL3BLACKCROWS __pyx_string_tab[33] -#define __pyx_n_u_CDL3INSIDE __pyx_string_tab[34] -#define __pyx_n_u_CDL3LINESTRIKE __pyx_string_tab[35] -#define __pyx_n_u_CDL3OUTSIDE __pyx_string_tab[36] -#define __pyx_n_u_CDL3STARSINSOUTH __pyx_string_tab[37] -#define __pyx_n_u_CDL3WHITESOLDIERS __pyx_string_tab[38] -#define __pyx_n_u_CDLABANDONEDBABY __pyx_string_tab[39] -#define __pyx_n_u_CDLADVANCEBLOCK __pyx_string_tab[40] -#define __pyx_n_u_CDLBELTHOLD __pyx_string_tab[41] -#define __pyx_n_u_CDLBREAKAWAY __pyx_string_tab[42] -#define __pyx_n_u_CDLCLOSINGMARUBOZU __pyx_string_tab[43] -#define __pyx_n_u_CDLCONCEALBABYSWALL __pyx_string_tab[44] -#define __pyx_n_u_CDLCOUNTERATTACK __pyx_string_tab[45] -#define __pyx_n_u_CDLDARKCLOUDCOVER __pyx_string_tab[46] -#define __pyx_n_u_CDLDOJI __pyx_string_tab[47] -#define __pyx_n_u_CDLDOJISTAR __pyx_string_tab[48] -#define __pyx_n_u_CDLDRAGONFLYDOJI __pyx_string_tab[49] -#define __pyx_n_u_CDLENGULFING __pyx_string_tab[50] -#define __pyx_n_u_CDLEVENINGDOJISTAR __pyx_string_tab[51] -#define __pyx_n_u_CDLEVENINGSTAR __pyx_string_tab[52] -#define __pyx_n_u_CDLGAPSIDESIDEWHITE __pyx_string_tab[53] -#define __pyx_n_u_CDLGRAVESTONEDOJI __pyx_string_tab[54] -#define __pyx_n_u_CDLHAMMER __pyx_string_tab[55] -#define __pyx_n_u_CDLHANGINGMAN __pyx_string_tab[56] -#define __pyx_n_u_CDLHARAMI __pyx_string_tab[57] -#define __pyx_n_u_CDLHARAMICROSS __pyx_string_tab[58] -#define __pyx_n_u_CDLHIGHWAVE __pyx_string_tab[59] -#define __pyx_n_u_CDLHIKKAKE __pyx_string_tab[60] -#define __pyx_n_u_CDLHIKKAKEMOD __pyx_string_tab[61] -#define __pyx_n_u_CDLHOMINGPIGEON __pyx_string_tab[62] -#define __pyx_n_u_CDLIDENTICAL3CROWS __pyx_string_tab[63] -#define __pyx_n_u_CDLINNECK __pyx_string_tab[64] -#define __pyx_n_u_CDLINVERTEDHAMMER __pyx_string_tab[65] -#define __pyx_n_u_CDLKICKING __pyx_string_tab[66] -#define __pyx_n_u_CDLKICKINGBYLENGTH __pyx_string_tab[67] -#define __pyx_n_u_CDLLADDERBOTTOM __pyx_string_tab[68] -#define __pyx_n_u_CDLLONGLEGGEDDOJI __pyx_string_tab[69] -#define __pyx_n_u_CDLLONGLINE __pyx_string_tab[70] -#define __pyx_n_u_CDLMARUBOZU __pyx_string_tab[71] -#define __pyx_n_u_CDLMATCHINGLOW __pyx_string_tab[72] -#define __pyx_n_u_CDLMATHOLD __pyx_string_tab[73] -#define __pyx_n_u_CDLMORNINGDOJISTAR __pyx_string_tab[74] -#define __pyx_n_u_CDLMORNINGSTAR __pyx_string_tab[75] -#define __pyx_n_u_CDLONNECK __pyx_string_tab[76] -#define __pyx_n_u_CDLPIERCING __pyx_string_tab[77] -#define __pyx_n_u_CDLRICKSHAWMAN __pyx_string_tab[78] -#define __pyx_n_u_CDLRISEFALL3METHODS __pyx_string_tab[79] -#define __pyx_n_u_CDLSEPARATINGLINES __pyx_string_tab[80] -#define __pyx_n_u_CDLSHOOTINGSTAR __pyx_string_tab[81] -#define __pyx_n_u_CDLSHORTLINE __pyx_string_tab[82] -#define __pyx_n_u_CDLSPINNINGTOP __pyx_string_tab[83] -#define __pyx_n_u_CDLSTALLEDPATTERN __pyx_string_tab[84] -#define __pyx_n_u_CDLSTICKSANDWICH __pyx_string_tab[85] -#define __pyx_n_u_CDLTAKURI __pyx_string_tab[86] -#define __pyx_n_u_CDLTASUKIGAP __pyx_string_tab[87] -#define __pyx_n_u_CDLTHRUSTING __pyx_string_tab[88] -#define __pyx_n_u_CDLTRISTAR __pyx_string_tab[89] -#define __pyx_n_u_CDLUNIQUE3RIVER __pyx_string_tab[90] -#define __pyx_n_u_CDLUPSIDEGAP2CROWS __pyx_string_tab[91] -#define __pyx_n_u_CDLXSIDEGAP3METHODS __pyx_string_tab[92] -#define __pyx_n_u_CEIL __pyx_string_tab[93] -#define __pyx_n_u_CMO __pyx_string_tab[94] -#define __pyx_n_u_CORREL __pyx_string_tab[95] -#define __pyx_n_u_COS __pyx_string_tab[96] -#define __pyx_n_u_COSH __pyx_string_tab[97] -#define __pyx_n_u_CandleSettingType __pyx_string_tab[98] -#define __pyx_n_u_DEMA __pyx_string_tab[99] -#define __pyx_n_u_DIV __pyx_string_tab[100] -#define __pyx_n_u_DX __pyx_string_tab[101] -#define __pyx_kp_u_Dashed_Line __pyx_string_tab[102] -#define __pyx_n_u_DataFrame __pyx_string_tab[103] -#define __pyx_n_u_Dot __pyx_string_tab[104] -#define __pyx_kp_u_Dotted_Line __pyx_string_tab[105] -#define __pyx_kp_u_Double_Exponential_Moving_Averag __pyx_string_tab[106] -#define __pyx_n_u_EMA __pyx_string_tab[107] -#define __pyx_n_u_EXP __pyx_string_tab[108] -#define __pyx_n_u_Equal __pyx_string_tab[109] -#define __pyx_kp_u_Exponential_Moving_Average __pyx_string_tab[110] -#define __pyx_n_u_FLOOR __pyx_string_tab[111] -#define __pyx_n_u_Far __pyx_string_tab[112] -#define __pyx_n_u_Function __pyx_string_tab[113] -#define __pyx_kp_u_Function_Not_Found_TA_FUNC_NOT_F __pyx_string_tab[114] -#define __pyx_n_u_Function___call __pyx_string_tab[115] -#define __pyx_n_u_Function___call_function __pyx_string_tab[116] -#define __pyx_n_u_Function___check_opt_input_value __pyx_string_tab[117] -#define __pyx_n_u_Function___get_opt_input_value __pyx_string_tab[118] -#define __pyx_n_u_Function___init __pyx_string_tab[119] -#define __pyx_n_u_Function___input_price_series_na __pyx_string_tab[120] -#define __pyx_n_u_Function___local __pyx_string_tab[121] -#define __pyx_n_u_Function___repr __pyx_string_tab[122] -#define __pyx_n_u_Function___str __pyx_string_tab[123] -#define __pyx_n_u_Function___unicode __pyx_string_tab[124] -#define __pyx_n_u_Function__call_function __pyx_string_tab[125] -#define __pyx_n_u_Function__check_opt_input_value __pyx_string_tab[126] -#define __pyx_n_u_Function__get_opt_input_value __pyx_string_tab[127] -#define __pyx_n_u_Function__input_price_series_na __pyx_string_tab[128] -#define __pyx_n_u_Function__local __pyx_string_tab[129] -#define __pyx_n_u_Function__localdata __pyx_string_tab[130] -#define __pyx_n_u_Function__name __pyx_string_tab[131] -#define __pyx_n_u_Function__namestr __pyx_string_tab[132] -#define __pyx_n_u_Function_function_flags __pyx_string_tab[133] -#define __pyx_n_u_Function_get_input_arrays __pyx_string_tab[134] -#define __pyx_n_u_Function_get_input_names __pyx_string_tab[135] -#define __pyx_n_u_Function_get_parameters __pyx_string_tab[136] -#define __pyx_kp_u_Function_has_an_unstable_period __pyx_string_tab[137] -#define __pyx_n_u_Function_info __pyx_string_tab[138] -#define __pyx_n_u_Function_lookback __pyx_string_tab[139] -#define __pyx_n_u_Function_output_flags __pyx_string_tab[140] -#define __pyx_n_u_Function_output_names __pyx_string_tab[141] -#define __pyx_n_u_Function_outputs __pyx_string_tab[142] -#define __pyx_n_u_Function_run __pyx_string_tab[143] -#define __pyx_n_u_Function_set_function_args __pyx_string_tab[144] -#define __pyx_n_u_Function_set_input_arrays __pyx_string_tab[145] -#define __pyx_n_u_Function_set_input_names __pyx_string_tab[146] -#define __pyx_n_u_Function_set_parameters __pyx_string_tab[147] -#define __pyx_kp_u_Group_Not_Found_TA_GROUP_NOT_FOU __pyx_string_tab[148] -#define __pyx_n_u_HT_DCPERIOD __pyx_string_tab[149] -#define __pyx_n_u_HT_DCPHASE __pyx_string_tab[150] -#define __pyx_n_u_HT_PHASOR __pyx_string_tab[151] -#define __pyx_n_u_HT_SINE __pyx_string_tab[152] -#define __pyx_n_u_HT_TRENDLINE __pyx_string_tab[153] -#define __pyx_n_u_HT_TRENDMODE __pyx_string_tab[154] -#define __pyx_n_u_HighLow __pyx_string_tab[155] -#define __pyx_n_u_Histogram __pyx_string_tab[156] -#define __pyx_n_u_IMI __pyx_string_tab[157] -#define __pyx_n_u_INPUT_ARRAYS_TYPES __pyx_string_tab[158] -#define __pyx_n_u_INPUT_PRICE_SERIES_DEFAULTS __pyx_string_tab[159] -#define __pyx_n_u_ImportError __pyx_string_tab[160] -#define __pyx_n_u_IndexError __pyx_string_tab[161] -#define __pyx_kp_u_Input_Not_All_Initialized_TA_INP __pyx_string_tab[162] -#define __pyx_kp_u_Inputs __pyx_string_tab[163] -#define __pyx_kp_u_Internal_Error_TA_INTERNAL_ERROR __pyx_string_tab[164] -#define __pyx_kp_u_Invalid_Handle_TA_INVALID_HANDLE __pyx_string_tab[165] -#define __pyx_kp_u_Invalid_List_Type_TA_INVALID_LIS __pyx_string_tab[166] -#define __pyx_kp_u_Invalid_Parameter_Function_TA_IN __pyx_string_tab[167] -#define __pyx_kp_u_Invalid_Parameter_Holder_TA_INVA __pyx_string_tab[168] -#define __pyx_kp_u_Invalid_Parameter_Holder_Type_TA __pyx_string_tab[169] -#define __pyx_kp_u_Invalid_parameter_value_for __pyx_string_tab[170] -#define __pyx_n_u_KAMA __pyx_string_tab[171] -#define __pyx_kp_u_Kaufman_Adaptive_Moving_Average __pyx_string_tab[172] -#define __pyx_n_u_LINEARREG __pyx_string_tab[173] -#define __pyx_n_u_LINEARREG_ANGLE __pyx_string_tab[174] -#define __pyx_n_u_LINEARREG_INTERCEPT __pyx_string_tab[175] -#define __pyx_n_u_LINEARREG_SLOPE __pyx_string_tab[176] -#define __pyx_n_u_LN __pyx_string_tab[177] -#define __pyx_n_u_LOG10 __pyx_string_tab[178] -#define __pyx_kp_u_Library_Not_Initialized_TA_LIB_N __pyx_string_tab[179] -#define __pyx_n_u_Line __pyx_string_tab[180] -#define __pyx_n_u_MA __pyx_string_tab[181] -#define __pyx_n_u_MACD __pyx_string_tab[182] -#define __pyx_n_u_MACDEXT __pyx_string_tab[183] -#define __pyx_n_u_MACDFIX __pyx_string_tab[184] -#define __pyx_n_u_MAMA __pyx_string_tab[185] -#define __pyx_n_u_MAVP __pyx_string_tab[186] -#define __pyx_n_u_MAX __pyx_string_tab[187] -#define __pyx_n_u_MAXINDEX __pyx_string_tab[188] -#define __pyx_n_u_MA_Type __pyx_string_tab[189] -#define __pyx_n_u_MA_Type___getitem __pyx_string_tab[190] -#define __pyx_n_u_MA_Type___init __pyx_string_tab[191] -#define __pyx_n_u_MEDPRICE __pyx_string_tab[192] -#define __pyx_kp_u_MESA_Adaptive_Moving_Average __pyx_string_tab[193] -#define __pyx_n_u_MFI __pyx_string_tab[194] -#define __pyx_n_u_MIDPOINT __pyx_string_tab[195] -#define __pyx_n_u_MIDPRICE __pyx_string_tab[196] -#define __pyx_n_u_MIN __pyx_string_tab[197] -#define __pyx_n_u_MININDEX __pyx_string_tab[198] -#define __pyx_n_u_MINMAX __pyx_string_tab[199] -#define __pyx_n_u_MINMAXINDEX __pyx_string_tab[200] -#define __pyx_n_u_MINUS_DI __pyx_string_tab[201] -#define __pyx_n_u_MINUS_DM __pyx_string_tab[202] -#define __pyx_n_u_MOM __pyx_string_tab[203] -#define __pyx_n_u_MULT __pyx_string_tab[204] -#define __pyx_n_u_ModuleNotFoundError __pyx_string_tab[205] -#define __pyx_n_u_NATR __pyx_string_tab[206] -#define __pyx_n_u_NONE __pyx_string_tab[207] -#define __pyx_n_u_NameError __pyx_string_tab[208] -#define __pyx_n_u_Near __pyx_string_tab[209] -#define __pyx_kp_u_None __pyx_string_tab[210] -#define __pyx_kp_u_Not_Supported_TA_NOT_SUPPORTED __pyx_string_tab[211] -#define __pyx_kp_u_Not_enough_price_arguments_expec __pyx_string_tab[212] -#define __pyx_kp_u_Note_that_Cython_is_deliberately __pyx_string_tab[213] -#define __pyx_n_u_OBV __pyx_string_tab[214] -#define __pyx_n_u_OrderedDict __pyx_string_tab[215] -#define __pyx_kp_u_Out_of_Range_End_Index_TA_OUT_OF __pyx_string_tab[216] -#define __pyx_kp_u_Out_of_Range_Start_Index_TA_OUT __pyx_string_tab[217] -#define __pyx_kp_u_Output_Not_All_Initialized_TA_OU __pyx_string_tab[218] -#define __pyx_kp_u_Output_can_be_negative __pyx_string_tab[219] -#define __pyx_kp_u_Output_can_be_positive __pyx_string_tab[220] -#define __pyx_kp_u_Output_can_be_zero __pyx_string_tab[221] -#define __pyx_kp_u_Output_is_a_candlestick __pyx_string_tab[222] -#define __pyx_kp_u_Output_is_over_volume __pyx_string_tab[223] -#define __pyx_kp_u_Output_scale_same_as_input __pyx_string_tab[224] -#define __pyx_kp_u_Outputs __pyx_string_tab[225] -#define __pyx_n_u_PANDAS_DATAFRAME __pyx_string_tab[226] -#define __pyx_n_u_PANDAS_SERIES __pyx_string_tab[227] -#define __pyx_n_u_PLUS_DI __pyx_string_tab[228] -#define __pyx_n_u_PLUS_DM __pyx_string_tab[229] -#define __pyx_n_u_POLARS_DATAFRAME __pyx_string_tab[230] -#define __pyx_n_u_POLARS_SERIES __pyx_string_tab[231] -#define __pyx_n_u_PPO __pyx_string_tab[232] -#define __pyx_kp_u_Parameters __pyx_string_tab[233] -#define __pyx_kp_u_Pattern_Bool __pyx_string_tab[234] -#define __pyx_n_u_ROC __pyx_string_tab[235] -#define __pyx_n_u_ROCP __pyx_string_tab[236] -#define __pyx_n_u_ROCR __pyx_string_tab[237] -#define __pyx_n_u_ROCR100 __pyx_string_tab[238] -#define __pyx_n_u_RSI __pyx_string_tab[239] -#define __pyx_n_u_RangeType __pyx_string_tab[240] -#define __pyx_n_u_RealBody __pyx_string_tab[241] -#define __pyx_n_u_SAR __pyx_string_tab[242] -#define __pyx_n_u_SAREXT __pyx_string_tab[243] -#define __pyx_n_u_SIN __pyx_string_tab[244] -#define __pyx_n_u_SINH __pyx_string_tab[245] -#define __pyx_n_u_SMA __pyx_string_tab[246] -#define __pyx_n_u_SQRT __pyx_string_tab[247] -#define __pyx_n_u_STDDEV __pyx_string_tab[248] -#define __pyx_n_u_STOCH __pyx_string_tab[249] -#define __pyx_n_u_STOCHF __pyx_string_tab[250] -#define __pyx_n_u_STOCHRSI __pyx_string_tab[251] -#define __pyx_n_u_SUB __pyx_string_tab[252] -#define __pyx_n_u_SUM __pyx_string_tab[253] -#define __pyx_n_u_Series __pyx_string_tab[254] -#define __pyx_n_u_ShadowLong __pyx_string_tab[255] -#define __pyx_n_u_ShadowShort __pyx_string_tab[256] -#define __pyx_n_u_ShadowVeryLong __pyx_string_tab[257] -#define __pyx_n_u_ShadowVeryShort __pyx_string_tab[258] -#define __pyx_n_u_Shadows __pyx_string_tab[259] -#define __pyx_kp_u_Simple_Moving_Average __pyx_string_tab[260] -#define __pyx_kp_u_Strength_Pattern_200_100_Bearish __pyx_string_tab[261] -#define __pyx_n_u_T3 __pyx_string_tab[262] -#define __pyx_n_u_TAN __pyx_string_tab[263] -#define __pyx_n_u_TANH __pyx_string_tab[264] -#define __pyx_n_u_TA_ACCBANDS __pyx_string_tab[265] -#define __pyx_n_u_TA_ACOS __pyx_string_tab[266] -#define __pyx_n_u_TA_AD __pyx_string_tab[267] -#define __pyx_n_u_TA_ADD __pyx_string_tab[268] -#define __pyx_n_u_TA_ADOSC __pyx_string_tab[269] -#define __pyx_n_u_TA_ADX __pyx_string_tab[270] -#define __pyx_n_u_TA_ADXR __pyx_string_tab[271] -#define __pyx_n_u_TA_APO __pyx_string_tab[272] -#define __pyx_n_u_TA_AROON __pyx_string_tab[273] -#define __pyx_n_u_TA_AROONOSC __pyx_string_tab[274] -#define __pyx_n_u_TA_ASIN __pyx_string_tab[275] -#define __pyx_n_u_TA_ATAN __pyx_string_tab[276] -#define __pyx_n_u_TA_ATR __pyx_string_tab[277] -#define __pyx_n_u_TA_AVGDEV __pyx_string_tab[278] -#define __pyx_n_u_TA_AVGPRICE __pyx_string_tab[279] -#define __pyx_n_u_TA_BBANDS __pyx_string_tab[280] -#define __pyx_n_u_TA_BETA __pyx_string_tab[281] -#define __pyx_n_u_TA_BOP __pyx_string_tab[282] -#define __pyx_n_u_TA_CCI __pyx_string_tab[283] -#define __pyx_n_u_TA_CDL2CROWS __pyx_string_tab[284] -#define __pyx_n_u_TA_CDL3BLACKCROWS __pyx_string_tab[285] -#define __pyx_n_u_TA_CDL3INSIDE __pyx_string_tab[286] -#define __pyx_n_u_TA_CDL3LINESTRIKE __pyx_string_tab[287] -#define __pyx_n_u_TA_CDL3OUTSIDE __pyx_string_tab[288] -#define __pyx_n_u_TA_CDL3STARSINSOUTH __pyx_string_tab[289] -#define __pyx_n_u_TA_CDL3WHITESOLDIERS __pyx_string_tab[290] -#define __pyx_n_u_TA_CDLABANDONEDBABY __pyx_string_tab[291] -#define __pyx_n_u_TA_CDLADVANCEBLOCK __pyx_string_tab[292] -#define __pyx_n_u_TA_CDLBELTHOLD __pyx_string_tab[293] -#define __pyx_n_u_TA_CDLBREAKAWAY __pyx_string_tab[294] -#define __pyx_n_u_TA_CDLCLOSINGMARUBOZU __pyx_string_tab[295] -#define __pyx_n_u_TA_CDLCONCEALBABYSWALL __pyx_string_tab[296] -#define __pyx_n_u_TA_CDLCOUNTERATTACK __pyx_string_tab[297] -#define __pyx_n_u_TA_CDLDARKCLOUDCOVER __pyx_string_tab[298] -#define __pyx_n_u_TA_CDLDOJI __pyx_string_tab[299] -#define __pyx_n_u_TA_CDLDOJISTAR __pyx_string_tab[300] -#define __pyx_n_u_TA_CDLDRAGONFLYDOJI __pyx_string_tab[301] -#define __pyx_n_u_TA_CDLENGULFING __pyx_string_tab[302] -#define __pyx_n_u_TA_CDLEVENINGDOJISTAR __pyx_string_tab[303] -#define __pyx_n_u_TA_CDLEVENINGSTAR __pyx_string_tab[304] -#define __pyx_n_u_TA_CDLGAPSIDESIDEWHITE __pyx_string_tab[305] -#define __pyx_n_u_TA_CDLGRAVESTONEDOJI __pyx_string_tab[306] -#define __pyx_n_u_TA_CDLHAMMER __pyx_string_tab[307] -#define __pyx_n_u_TA_CDLHANGINGMAN __pyx_string_tab[308] -#define __pyx_n_u_TA_CDLHARAMI __pyx_string_tab[309] -#define __pyx_n_u_TA_CDLHARAMICROSS __pyx_string_tab[310] -#define __pyx_n_u_TA_CDLHIGHWAVE __pyx_string_tab[311] -#define __pyx_n_u_TA_CDLHIKKAKE __pyx_string_tab[312] -#define __pyx_n_u_TA_CDLHIKKAKEMOD __pyx_string_tab[313] -#define __pyx_n_u_TA_CDLHOMINGPIGEON __pyx_string_tab[314] -#define __pyx_n_u_TA_CDLIDENTICAL3CROWS __pyx_string_tab[315] -#define __pyx_n_u_TA_CDLINNECK __pyx_string_tab[316] -#define __pyx_n_u_TA_CDLINVERTEDHAMMER __pyx_string_tab[317] -#define __pyx_n_u_TA_CDLKICKING __pyx_string_tab[318] -#define __pyx_n_u_TA_CDLKICKINGBYLENGTH __pyx_string_tab[319] -#define __pyx_n_u_TA_CDLLADDERBOTTOM __pyx_string_tab[320] -#define __pyx_n_u_TA_CDLLONGLEGGEDDOJI __pyx_string_tab[321] -#define __pyx_n_u_TA_CDLLONGLINE __pyx_string_tab[322] -#define __pyx_n_u_TA_CDLMARUBOZU __pyx_string_tab[323] -#define __pyx_n_u_TA_CDLMATCHINGLOW __pyx_string_tab[324] -#define __pyx_n_u_TA_CDLMATHOLD __pyx_string_tab[325] -#define __pyx_n_u_TA_CDLMORNINGDOJISTAR __pyx_string_tab[326] -#define __pyx_n_u_TA_CDLMORNINGSTAR __pyx_string_tab[327] -#define __pyx_n_u_TA_CDLONNECK __pyx_string_tab[328] -#define __pyx_n_u_TA_CDLPIERCING __pyx_string_tab[329] -#define __pyx_n_u_TA_CDLRICKSHAWMAN __pyx_string_tab[330] -#define __pyx_n_u_TA_CDLRISEFALL3METHODS __pyx_string_tab[331] -#define __pyx_n_u_TA_CDLSEPARATINGLINES __pyx_string_tab[332] -#define __pyx_n_u_TA_CDLSHOOTINGSTAR __pyx_string_tab[333] -#define __pyx_n_u_TA_CDLSHORTLINE __pyx_string_tab[334] -#define __pyx_n_u_TA_CDLSPINNINGTOP __pyx_string_tab[335] -#define __pyx_n_u_TA_CDLSTALLEDPATTERN __pyx_string_tab[336] -#define __pyx_n_u_TA_CDLSTICKSANDWICH __pyx_string_tab[337] -#define __pyx_n_u_TA_CDLTAKURI __pyx_string_tab[338] -#define __pyx_n_u_TA_CDLTASUKIGAP __pyx_string_tab[339] -#define __pyx_n_u_TA_CDLTHRUSTING __pyx_string_tab[340] -#define __pyx_n_u_TA_CDLTRISTAR __pyx_string_tab[341] -#define __pyx_n_u_TA_CDLUNIQUE3RIVER __pyx_string_tab[342] -#define __pyx_n_u_TA_CDLUPSIDEGAP2CROWS __pyx_string_tab[343] -#define __pyx_n_u_TA_CDLXSIDEGAP3METHODS __pyx_string_tab[344] -#define __pyx_n_u_TA_CEIL __pyx_string_tab[345] -#define __pyx_n_u_TA_CMO __pyx_string_tab[346] -#define __pyx_n_u_TA_CORREL __pyx_string_tab[347] -#define __pyx_n_u_TA_COS __pyx_string_tab[348] -#define __pyx_n_u_TA_COSH __pyx_string_tab[349] -#define __pyx_n_u_TA_DEMA __pyx_string_tab[350] -#define __pyx_n_u_TA_DIV __pyx_string_tab[351] -#define __pyx_n_u_TA_DX __pyx_string_tab[352] -#define __pyx_n_u_TA_EMA __pyx_string_tab[353] -#define __pyx_n_u_TA_EXP __pyx_string_tab[354] -#define __pyx_n_u_TA_FLOOR __pyx_string_tab[355] -#define __pyx_n_u_TA_FUNCTION_NAMES __pyx_string_tab[356] -#define __pyx_n_u_TA_FUNC_FLAGS __pyx_string_tab[357] -#define __pyx_n_u_TA_FuncTableAlloc __pyx_string_tab[358] -#define __pyx_n_u_TA_FuncTableFree __pyx_string_tab[359] -#define __pyx_n_u_TA_GetFuncHandle __pyx_string_tab[360] -#define __pyx_n_u_TA_GetFuncInfo __pyx_string_tab[361] -#define __pyx_n_u_TA_GetInputParameterInfo __pyx_string_tab[362] -#define __pyx_n_u_TA_GetLookback __pyx_string_tab[363] -#define __pyx_n_u_TA_GetOptInputParameterInfo __pyx_string_tab[364] -#define __pyx_n_u_TA_GetOutputParameterInfo __pyx_string_tab[365] -#define __pyx_n_u_TA_GroupTableAlloc __pyx_string_tab[366] -#define __pyx_n_u_TA_GroupTableFree __pyx_string_tab[367] -#define __pyx_n_u_TA_HT_DCPERIOD __pyx_string_tab[368] -#define __pyx_n_u_TA_HT_DCPHASE __pyx_string_tab[369] -#define __pyx_n_u_TA_HT_PHASOR __pyx_string_tab[370] -#define __pyx_n_u_TA_HT_SINE __pyx_string_tab[371] -#define __pyx_n_u_TA_HT_TRENDLINE __pyx_string_tab[372] -#define __pyx_n_u_TA_HT_TRENDMODE __pyx_string_tab[373] -#define __pyx_n_u_TA_IMI __pyx_string_tab[374] -#define __pyx_n_u_TA_INPUT_FLAGS __pyx_string_tab[375] -#define __pyx_n_u_TA_Initialize __pyx_string_tab[376] -#define __pyx_n_u_TA_KAMA __pyx_string_tab[377] -#define __pyx_n_u_TA_LINEARREG __pyx_string_tab[378] -#define __pyx_n_u_TA_LINEARREG_ANGLE __pyx_string_tab[379] -#define __pyx_n_u_TA_LINEARREG_INTERCEPT __pyx_string_tab[380] -#define __pyx_n_u_TA_LINEARREG_SLOPE __pyx_string_tab[381] -#define __pyx_n_u_TA_LN __pyx_string_tab[382] -#define __pyx_n_u_TA_LOG10 __pyx_string_tab[383] -#define __pyx_n_u_TA_MA __pyx_string_tab[384] -#define __pyx_n_u_TA_MACD __pyx_string_tab[385] -#define __pyx_n_u_TA_MACDEXT __pyx_string_tab[386] -#define __pyx_n_u_TA_MACDFIX __pyx_string_tab[387] -#define __pyx_n_u_TA_MAMA __pyx_string_tab[388] -#define __pyx_n_u_TA_MAVP __pyx_string_tab[389] -#define __pyx_n_u_TA_MAX __pyx_string_tab[390] -#define __pyx_n_u_TA_MAXINDEX __pyx_string_tab[391] -#define __pyx_n_u_TA_MEDPRICE __pyx_string_tab[392] -#define __pyx_n_u_TA_MFI __pyx_string_tab[393] -#define __pyx_n_u_TA_MIDPOINT __pyx_string_tab[394] -#define __pyx_n_u_TA_MIDPRICE __pyx_string_tab[395] -#define __pyx_n_u_TA_MIN __pyx_string_tab[396] -#define __pyx_n_u_TA_MININDEX __pyx_string_tab[397] -#define __pyx_n_u_TA_MINMAX __pyx_string_tab[398] -#define __pyx_n_u_TA_MINMAXINDEX __pyx_string_tab[399] -#define __pyx_n_u_TA_MINUS_DI __pyx_string_tab[400] -#define __pyx_n_u_TA_MINUS_DM __pyx_string_tab[401] -#define __pyx_n_u_TA_MOM __pyx_string_tab[402] -#define __pyx_n_u_TA_MULT __pyx_string_tab[403] -#define __pyx_n_u_TA_NATR __pyx_string_tab[404] -#define __pyx_n_u_TA_OBV __pyx_string_tab[405] -#define __pyx_n_u_TA_OUTPUT_FLAGS __pyx_string_tab[406] -#define __pyx_n_u_TA_PLUS_DI __pyx_string_tab[407] -#define __pyx_n_u_TA_PLUS_DM __pyx_string_tab[408] -#define __pyx_n_u_TA_PPO __pyx_string_tab[409] -#define __pyx_n_u_TA_ParamHolderAlloc __pyx_string_tab[410] -#define __pyx_n_u_TA_ParamHolderFree __pyx_string_tab[411] -#define __pyx_n_u_TA_ROC __pyx_string_tab[412] -#define __pyx_n_u_TA_ROCP __pyx_string_tab[413] -#define __pyx_n_u_TA_ROCR __pyx_string_tab[414] -#define __pyx_n_u_TA_ROCR100 __pyx_string_tab[415] -#define __pyx_n_u_TA_RSI __pyx_string_tab[416] -#define __pyx_n_u_TA_RestoreCandleDefaultSettings __pyx_string_tab[417] -#define __pyx_n_u_TA_SAR __pyx_string_tab[418] -#define __pyx_n_u_TA_SAREXT __pyx_string_tab[419] -#define __pyx_n_u_TA_SIN __pyx_string_tab[420] -#define __pyx_n_u_TA_SINH __pyx_string_tab[421] -#define __pyx_n_u_TA_SMA __pyx_string_tab[422] -#define __pyx_n_u_TA_SQRT __pyx_string_tab[423] -#define __pyx_n_u_TA_STDDEV __pyx_string_tab[424] -#define __pyx_n_u_TA_STOCH __pyx_string_tab[425] -#define __pyx_n_u_TA_STOCHF __pyx_string_tab[426] -#define __pyx_n_u_TA_STOCHRSI __pyx_string_tab[427] -#define __pyx_n_u_TA_SUB __pyx_string_tab[428] -#define __pyx_n_u_TA_SUM __pyx_string_tab[429] -#define __pyx_n_u_TA_SetCandleSettings __pyx_string_tab[430] -#define __pyx_n_u_TA_SetCompatibility __pyx_string_tab[431] -#define __pyx_n_u_TA_SetOptInputParamInteger __pyx_string_tab[432] -#define __pyx_n_u_TA_SetOptInputParamReal __pyx_string_tab[433] -#define __pyx_n_u_TA_SetUnstablePeriod __pyx_string_tab[434] -#define __pyx_n_u_TA_Shutdown __pyx_string_tab[435] -#define __pyx_n_u_TA_T3 __pyx_string_tab[436] -#define __pyx_n_u_TA_TAN __pyx_string_tab[437] -#define __pyx_n_u_TA_TANH __pyx_string_tab[438] -#define __pyx_n_u_TA_TEMA __pyx_string_tab[439] -#define __pyx_n_u_TA_TRANGE __pyx_string_tab[440] -#define __pyx_n_u_TA_TRIMA __pyx_string_tab[441] -#define __pyx_n_u_TA_TRIX __pyx_string_tab[442] -#define __pyx_n_u_TA_TSF __pyx_string_tab[443] -#define __pyx_n_u_TA_TYPPRICE __pyx_string_tab[444] -#define __pyx_n_u_TA_ULTOSC __pyx_string_tab[445] -#define __pyx_n_u_TA_VAR __pyx_string_tab[446] -#define __pyx_n_u_TA_WCLPRICE __pyx_string_tab[447] -#define __pyx_n_u_TA_WILLR __pyx_string_tab[448] -#define __pyx_n_u_TA_WMA __pyx_string_tab[449] -#define __pyx_n_u_TEMA __pyx_string_tab[450] -#define __pyx_n_u_TRANGE __pyx_string_tab[451] -#define __pyx_n_u_TRIMA __pyx_string_tab[452] -#define __pyx_n_u_TRIX __pyx_string_tab[453] -#define __pyx_n_u_TSF __pyx_string_tab[454] -#define __pyx_n_u_TYPPRICE __pyx_string_tab[455] -#define __pyx_kp_u_This_is_a_pythonic_wrapper_arou __pyx_string_tab[456] -#define __pyx_kp_u_Too_many_price_arguments_expecte __pyx_string_tab[457] -#define __pyx_kp_u_Triangular_Moving_Average __pyx_string_tab[458] -#define __pyx_kp_u_Triple_Exponential_Moving_Averag __pyx_string_tab[459] -#define __pyx_kp_u_Triple_Generalized_Double_Expone __pyx_string_tab[460] -#define __pyx_n_u_TypeError __pyx_string_tab[461] -#define __pyx_n_u_ULTOSC __pyx_string_tab[462] -#define __pyx_kp_u_Unknown_Error __pyx_string_tab[463] -#define __pyx_kp_u_Unknown_Error_TA_UNKNOWN_ERR __pyx_string_tab[464] -#define __pyx_n_u_VAR __pyx_string_tab[465] -#define __pyx_kp_u_Values_represent_a_lower_limit __pyx_string_tab[466] -#define __pyx_kp_u_Values_represent_an_upper_limit __pyx_string_tab[467] -#define __pyx_n_u_WCLPRICE __pyx_string_tab[468] -#define __pyx_n_u_WILLR __pyx_string_tab[469] -#define __pyx_n_u_WMA __pyx_string_tab[470] -#define __pyx_kp_u_Weighted_Moving_Average __pyx_string_tab[471] -#define __pyx_kp_u__10 __pyx_string_tab[472] -#define __pyx_kp_u__11 __pyx_string_tab[473] -#define __pyx_kp_u__12 __pyx_string_tab[474] -#define __pyx_kp_u__13 __pyx_string_tab[475] -#define __pyx_kp_u__14 __pyx_string_tab[476] -#define __pyx_kp_u__15 __pyx_string_tab[477] -#define __pyx_kp_u__2 __pyx_string_tab[478] -#define __pyx_kp_u__3 __pyx_string_tab[479] -#define __pyx_kp_u__4 __pyx_string_tab[480] -#define __pyx_kp_u__5 __pyx_string_tab[481] -#define __pyx_kp_u__6 __pyx_string_tab[482] -#define __pyx_kp_u__7 __pyx_string_tab[483] -#define __pyx_kp_u__8 __pyx_string_tab[484] -#define __pyx_kp_u__9 __pyx_string_tab[485] -#define __pyx_n_u_acceleration __pyx_string_tab[486] -#define __pyx_n_u_accelerationinitlong __pyx_string_tab[487] -#define __pyx_n_u_accelerationinitshort __pyx_string_tab[488] -#define __pyx_n_u_accelerationlong __pyx_string_tab[489] -#define __pyx_n_u_accelerationmaxlong __pyx_string_tab[490] -#define __pyx_n_u_accelerationmaxshort __pyx_string_tab[491] -#define __pyx_n_u_accelerationshort __pyx_string_tab[492] -#define __pyx_kp_u_add_note __pyx_string_tab[493] -#define __pyx_n_u_all __pyx_string_tab[494] -#define __pyx_kp_u_any_ndarray __pyx_string_tab[495] -#define __pyx_n_u_append __pyx_string_tab[496] -#define __pyx_n_u_arg __pyx_string_tab[497] -#define __pyx_n_u_args __pyx_string_tab[498] -#define __pyx_n_u_ascii __pyx_string_tab[499] -#define __pyx_n_u_astype __pyx_string_tab[500] -#define __pyx_n_u_asyncio_coroutines __pyx_string_tab[501] -#define __pyx_n_u_avgperiod __pyx_string_tab[502] -#define __pyx_n_u_b __pyx_string_tab[503] -#define __pyx_n_u_begidx __pyx_string_tab[504] -#define __pyx_n_u_bytes2str __pyx_string_tab[505] -#define __pyx_n_u_call __pyx_string_tab[506] -#define __pyx_n_u_call_function __pyx_string_tab[507] -#define __pyx_n_u_check_opt_input_value __pyx_string_tab[508] -#define __pyx_n_u_class_getitem __pyx_string_tab[509] -#define __pyx_n_u_cline_in_traceback __pyx_string_tab[510] -#define __pyx_n_u_clone __pyx_string_tab[511] -#define __pyx_n_u_close __pyx_string_tab[512] -#define __pyx_n_u_close_data __pyx_string_tab[513] -#define __pyx_n_u_collections __pyx_string_tab[514] -#define __pyx_n_u_column_stack __pyx_string_tab[515] -#define __pyx_n_u_columns __pyx_string_tab[516] -#define __pyx_n_u_copy __pyx_string_tab[517] -#define __pyx_n_u_d __pyx_string_tab[518] -#define __pyx_n_u_decode __pyx_string_tab[519] -#define __pyx_n_u_default_value __pyx_string_tab[520] -#define __pyx_n_u_defaults __pyx_string_tab[521] -#define __pyx_n_u_display_name __pyx_string_tab[522] -#define __pyx_kp_u_display_name_s_group_s __pyx_string_tab[523] -#define __pyx_n_u_doc __pyx_string_tab[524] -#define __pyx_n_u_docs __pyx_string_tab[525] -#define __pyx_n_u_documentation __pyx_string_tab[526] -#define __pyx_n_u_empty __pyx_string_tab[527] -#define __pyx_n_u_endidx __pyx_string_tab[528] -#define __pyx_n_u_enumerate __pyx_string_tab[529] -#define __pyx_kp_u_expected __pyx_string_tab[530] -#define __pyx_n_u_factor __pyx_string_tab[531] -#define __pyx_n_u_fastd_matype __pyx_string_tab[532] -#define __pyx_n_u_fastd_period __pyx_string_tab[533] -#define __pyx_n_u_fastk_period __pyx_string_tab[534] -#define __pyx_n_u_fastlimit __pyx_string_tab[535] -#define __pyx_n_u_fastmatype __pyx_string_tab[536] -#define __pyx_n_u_fastperiod __pyx_string_tab[537] -#define __pyx_n_u_flag __pyx_string_tab[538] -#define __pyx_n_u_flags __pyx_string_tab[539] -#define __pyx_n_u_flags_lookup_dict __pyx_string_tab[540] -#define __pyx_n_u_func __pyx_string_tab[541] -#define __pyx_n_u_func_args __pyx_string_tab[542] -#define __pyx_n_u_func_info __pyx_string_tab[543] -#define __pyx_n_u_func_line __pyx_string_tab[544] -#define __pyx_n_u_func_object __pyx_string_tab[545] -#define __pyx_kp_u_function_failed_with_error_code __pyx_string_tab[546] -#define __pyx_n_u_function_flags __pyx_string_tab[547] -#define __pyx_n_u_function_name __pyx_string_tab[548] -#define __pyx_n_u_functions __pyx_string_tab[549] -#define __pyx_n_u_get_defaults_and_docs __pyx_string_tab[550] -#define __pyx_n_u_get_flags __pyx_string_tab[551] -#define __pyx_n_u_get_input_arrays __pyx_string_tab[552] -#define __pyx_n_u_get_input_names __pyx_string_tab[553] -#define __pyx_n_u_get_opt_input_value __pyx_string_tab[554] -#define __pyx_n_u_get_parameters __pyx_string_tab[555] -#define __pyx_n_u_getitem __pyx_string_tab[556] -#define __pyx_kp_u_got __pyx_string_tab[557] -#define __pyx_n_u_group __pyx_string_tab[558] -#define __pyx_n_u_groups __pyx_string_tab[559] -#define __pyx_n_u_help __pyx_string_tab[560] -#define __pyx_n_u_high __pyx_string_tab[561] -#define __pyx_n_u_high_data __pyx_string_tab[562] -#define __pyx_n_u_holder __pyx_string_tab[563] -#define __pyx_n_u_i __pyx_string_tab[564] -#define __pyx_n_u_id __pyx_string_tab[565] -#define __pyx_n_u_idx __pyx_string_tab[566] -#define __pyx_n_u_import_error __pyx_string_tab[567] -#define __pyx_n_u_in __pyx_string_tab[568] -#define __pyx_n_u_index __pyx_string_tab[569] -#define __pyx_n_u_info __pyx_string_tab[570] -#define __pyx_n_u_init __pyx_string_tab[571] -#define __pyx_n_u_initializing __pyx_string_tab[572] -#define __pyx_kp_u_input_array_has_wrong_dimensions __pyx_string_tab[573] -#define __pyx_kp_u_input_array_lengths_are_differen __pyx_string_tab[574] -#define __pyx_kp_u_input_array_type_is_not_double __pyx_string_tab[575] -#define __pyx_n_u_input_arrays __pyx_string_tab[576] -#define __pyx_kp_u_input_arrays_2 __pyx_string_tab[577] -#define __pyx_kp_u_input_arrays_parameter_missing_r __pyx_string_tab[578] -#define __pyx_n_u_input_name __pyx_string_tab[579] -#define __pyx_n_u_input_names __pyx_string_tab[580] -#define __pyx_n_u_input_price_series_names __pyx_string_tab[581] -#define __pyx_n_u_input_price_series_names_2 __pyx_string_tab[582] -#define __pyx_n_u_integer __pyx_string_tab[583] -#define __pyx_kp_u_integer_values_are_100_0_or_100 __pyx_string_tab[584] -#define __pyx_n_u_is_coroutine __pyx_string_tab[585] -#define __pyx_n_u_is_empty __pyx_string_tab[586] -#define __pyx_n_u_items __pyx_string_tab[587] -#define __pyx_n_u_key __pyx_string_tab[588] -#define __pyx_n_u_keys __pyx_string_tab[589] -#define __pyx_n_u_kwargs __pyx_string_tab[590] -#define __pyx_n_u_length __pyx_string_tab[591] -#define __pyx_n_u_local __pyx_string_tab[592] -#define __pyx_n_u_local_2 __pyx_string_tab[593] -#define __pyx_n_u_log __pyx_string_tab[594] -#define __pyx_n_u_lookback __pyx_string_tab[595] -#define __pyx_n_u_lookup __pyx_string_tab[596] -#define __pyx_n_u_low __pyx_string_tab[597] -#define __pyx_n_u_low_data __pyx_string_tab[598] -#define __pyx_n_u_lower __pyx_string_tab[599] -#define __pyx_n_u_main __pyx_string_tab[600] -#define __pyx_n_u_math __pyx_string_tab[601] -#define __pyx_n_u_matype __pyx_string_tab[602] -#define __pyx_n_u_max __pyx_string_tab[603] -#define __pyx_n_u_max_int __pyx_string_tab[604] -#define __pyx_n_u_maximum __pyx_string_tab[605] -#define __pyx_n_u_maxperiod __pyx_string_tab[606] -#define __pyx_n_u_metaclass __pyx_string_tab[607] -#define __pyx_n_u_min __pyx_string_tab[608] -#define __pyx_n_u_min_int __pyx_string_tab[609] -#define __pyx_n_u_minperiod __pyx_string_tab[610] -#define __pyx_n_u_missing __pyx_string_tab[611] -#define __pyx_n_u_missing_keys __pyx_string_tab[612] -#define __pyx_n_u_module __pyx_string_tab[613] -#define __pyx_n_u_mro_entries __pyx_string_tab[614] -#define __pyx_n_u_msg __pyx_string_tab[615] -#define __pyx_n_u_n __pyx_string_tab[616] -#define __pyx_n_u_name __pyx_string_tab[617] -#define __pyx_n_u_name_2 __pyx_string_tab[618] -#define __pyx_n_u_nan __pyx_string_tab[619] -#define __pyx_n_u_nbdev __pyx_string_tab[620] -#define __pyx_n_u_nbdevdn __pyx_string_tab[621] -#define __pyx_n_u_nbdevup __pyx_string_tab[622] -#define __pyx_n_u_no_existing_input_arrays __pyx_string_tab[623] -#define __pyx_n_u_num_inputs __pyx_string_tab[624] -#define __pyx_n_u_num_opt_inputs __pyx_string_tab[625] -#define __pyx_n_u_num_outputs __pyx_string_tab[626] -#define __pyx_n_u_numpy __pyx_string_tab[627] -#define __pyx_kp_u_numpy__core_multiarray_failed_to __pyx_string_tab[628] -#define __pyx_kp_u_numpy__core_umath_failed_to_impo __pyx_string_tab[629] -#define __pyx_n_u_object __pyx_string_tab[630] -#define __pyx_n_u_offsetonreverse __pyx_string_tab[631] -#define __pyx_n_u_open __pyx_string_tab[632] -#define __pyx_n_u_openInterest __pyx_string_tab[633] -#define __pyx_n_u_open_data __pyx_string_tab[634] -#define __pyx_n_u_optIn __pyx_string_tab[635] -#define __pyx_n_u_opt_input __pyx_string_tab[636] -#define __pyx_n_u_opt_input_values __pyx_string_tab[637] -#define __pyx_n_u_opt_inputs __pyx_string_tab[638] -#define __pyx_n_u_ordereddict __pyx_string_tab[639] -#define __pyx_n_u_out __pyx_string_tab[640] -#define __pyx_n_u_outaroondown __pyx_string_tab[641] -#define __pyx_n_u_outaroonup __pyx_string_tab[642] -#define __pyx_n_u_outbegidx __pyx_string_tab[643] -#define __pyx_n_u_outfama __pyx_string_tab[644] -#define __pyx_n_u_outfastd __pyx_string_tab[645] -#define __pyx_n_u_outfastk __pyx_string_tab[646] -#define __pyx_n_u_outinphase __pyx_string_tab[647] -#define __pyx_n_u_outinteger __pyx_string_tab[648] -#define __pyx_n_u_outinteger_data __pyx_string_tab[649] -#define __pyx_n_u_outleadsine __pyx_string_tab[650] -#define __pyx_n_u_outmacd __pyx_string_tab[651] -#define __pyx_n_u_outmacdhist __pyx_string_tab[652] -#define __pyx_n_u_outmacdsignal __pyx_string_tab[653] -#define __pyx_n_u_outmama __pyx_string_tab[654] -#define __pyx_n_u_outmax __pyx_string_tab[655] -#define __pyx_n_u_outmaxidx __pyx_string_tab[656] -#define __pyx_n_u_outmaxidx_data __pyx_string_tab[657] -#define __pyx_n_u_outmin __pyx_string_tab[658] -#define __pyx_n_u_outminidx __pyx_string_tab[659] -#define __pyx_n_u_outminidx_data __pyx_string_tab[660] -#define __pyx_n_u_outnbelement __pyx_string_tab[661] -#define __pyx_n_u_output __pyx_string_tab[662] -#define __pyx_n_u_output_flags __pyx_string_tab[663] -#define __pyx_n_u_output_name __pyx_string_tab[664] -#define __pyx_n_u_output_names __pyx_string_tab[665] -#define __pyx_n_u_outputs __pyx_string_tab[666] -#define __pyx_n_u_outputs_valid __pyx_string_tab[667] -#define __pyx_n_u_outquadrature __pyx_string_tab[668] -#define __pyx_n_u_outreal __pyx_string_tab[669] -#define __pyx_n_u_outreallowerband __pyx_string_tab[670] -#define __pyx_n_u_outrealmiddleband __pyx_string_tab[671] -#define __pyx_n_u_outrealupperband __pyx_string_tab[672] -#define __pyx_n_u_outsine __pyx_string_tab[673] -#define __pyx_n_u_outslowd __pyx_string_tab[674] -#define __pyx_n_u_outslowk __pyx_string_tab[675] -#define __pyx_n_u_pandas __pyx_string_tab[676] -#define __pyx_n_u_param __pyx_string_tab[677] -#define __pyx_n_u_param_name __pyx_string_tab[678] -#define __pyx_n_u_parameters __pyx_string_tab[679] -#define __pyx_n_u_params __pyx_string_tab[680] -#define __pyx_n_u_penetration __pyx_string_tab[681] -#define __pyx_n_u_period __pyx_string_tab[682] -#define __pyx_n_u_periods __pyx_string_tab[683] -#define __pyx_n_u_periods_data __pyx_string_tab[684] -#define __pyx_n_u_polars __pyx_string_tab[685] -#define __pyx_n_u_pop __pyx_string_tab[686] -#define __pyx_n_u_prepare __pyx_string_tab[687] -#define __pyx_n_u_price __pyx_string_tab[688] -#define __pyx_n_u_price0 __pyx_string_tab[689] -#define __pyx_n_u_price1 __pyx_string_tab[690] -#define __pyx_n_u_price_series __pyx_string_tab[691] -#define __pyx_n_u_price_series_name_values __pyx_string_tab[692] -#define __pyx_n_u_prices __pyx_string_tab[693] -#define __pyx_n_u_property __pyx_string_tab[694] -#define __pyx_n_u_qualname __pyx_string_tab[695] -#define __pyx_n_u_range __pyx_string_tab[696] -#define __pyx_n_u_rangetype __pyx_string_tab[697] -#define __pyx_n_u_real __pyx_string_tab[698] -#define __pyx_n_u_real0 __pyx_string_tab[699] -#define __pyx_n_u_real0_data __pyx_string_tab[700] -#define __pyx_n_u_real1 __pyx_string_tab[701] -#define __pyx_n_u_real1_data __pyx_string_tab[702] -#define __pyx_n_u_real_data __pyx_string_tab[703] -#define __pyx_n_u_replace __pyx_string_tab[704] -#define __pyx_n_u_repr __pyx_string_tab[705] -#define __pyx_n_u_results __pyx_string_tab[706] -#define __pyx_n_u_ret __pyx_string_tab[707] -#define __pyx_n_u_retCode __pyx_string_tab[708] -#define __pyx_n_u_ret_code __pyx_string_tab[709] -#define __pyx_n_u_run __pyx_string_tab[710] -#define __pyx_n_u_s __pyx_string_tab[711] -#define __pyx_kp_u_s_2 __pyx_string_tab[712] -#define __pyx_kp_u_s_3 __pyx_string_tab[713] -#define __pyx_kp_u_s_4 __pyx_string_tab[714] -#define __pyx_n_u_schema __pyx_string_tab[715] -#define __pyx_n_u_self __pyx_string_tab[716] -#define __pyx_n_u_series __pyx_string_tab[717] -#define __pyx_n_u_set_function_args __pyx_string_tab[718] -#define __pyx_n_u_set_input_arrays __pyx_string_tab[719] -#define __pyx_n_u_set_input_names __pyx_string_tab[720] -#define __pyx_n_u_set_name __pyx_string_tab[721] -#define __pyx_n_u_set_parameters __pyx_string_tab[722] -#define __pyx_n_u_settingtype __pyx_string_tab[723] -#define __pyx_n_u_signalmatype __pyx_string_tab[724] -#define __pyx_n_u_signalperiod __pyx_string_tab[725] -#define __pyx_n_u_skip_first __pyx_string_tab[726] -#define __pyx_n_u_slowd_matype __pyx_string_tab[727] -#define __pyx_n_u_slowd_period __pyx_string_tab[728] -#define __pyx_n_u_slowk_matype __pyx_string_tab[729] -#define __pyx_n_u_slowk_period __pyx_string_tab[730] -#define __pyx_n_u_slowlimit __pyx_string_tab[731] -#define __pyx_n_u_slowmatype __pyx_string_tab[732] -#define __pyx_n_u_slowperiod __pyx_string_tab[733] -#define __pyx_n_u_spec __pyx_string_tab[734] -#define __pyx_n_u_startvalue __pyx_string_tab[735] -#define __pyx_n_u_str __pyx_string_tab[736] -#define __pyx_n_u_str2bytes __pyx_string_tab[737] -#define __pyx_n_u_stream_ACCBANDS __pyx_string_tab[738] -#define __pyx_n_u_stream_ACOS __pyx_string_tab[739] -#define __pyx_n_u_stream_AD __pyx_string_tab[740] -#define __pyx_n_u_stream_ADD __pyx_string_tab[741] -#define __pyx_n_u_stream_ADOSC __pyx_string_tab[742] -#define __pyx_n_u_stream_ADX __pyx_string_tab[743] -#define __pyx_n_u_stream_ADXR __pyx_string_tab[744] -#define __pyx_n_u_stream_APO __pyx_string_tab[745] -#define __pyx_n_u_stream_AROON __pyx_string_tab[746] -#define __pyx_n_u_stream_AROONOSC __pyx_string_tab[747] -#define __pyx_n_u_stream_ASIN __pyx_string_tab[748] -#define __pyx_n_u_stream_ATAN __pyx_string_tab[749] -#define __pyx_n_u_stream_ATR __pyx_string_tab[750] -#define __pyx_n_u_stream_AVGDEV __pyx_string_tab[751] -#define __pyx_n_u_stream_AVGPRICE __pyx_string_tab[752] -#define __pyx_n_u_stream_BBANDS __pyx_string_tab[753] -#define __pyx_n_u_stream_BETA __pyx_string_tab[754] -#define __pyx_n_u_stream_BOP __pyx_string_tab[755] -#define __pyx_n_u_stream_CCI __pyx_string_tab[756] -#define __pyx_n_u_stream_CDL2CROWS __pyx_string_tab[757] -#define __pyx_n_u_stream_CDL3BLACKCROWS __pyx_string_tab[758] -#define __pyx_n_u_stream_CDL3INSIDE __pyx_string_tab[759] -#define __pyx_n_u_stream_CDL3LINESTRIKE __pyx_string_tab[760] -#define __pyx_n_u_stream_CDL3OUTSIDE __pyx_string_tab[761] -#define __pyx_n_u_stream_CDL3STARSINSOUTH __pyx_string_tab[762] -#define __pyx_n_u_stream_CDL3WHITESOLDIERS __pyx_string_tab[763] -#define __pyx_n_u_stream_CDLABANDONEDBABY __pyx_string_tab[764] -#define __pyx_n_u_stream_CDLADVANCEBLOCK __pyx_string_tab[765] -#define __pyx_n_u_stream_CDLBELTHOLD __pyx_string_tab[766] -#define __pyx_n_u_stream_CDLBREAKAWAY __pyx_string_tab[767] -#define __pyx_n_u_stream_CDLCLOSINGMARUBOZU __pyx_string_tab[768] -#define __pyx_n_u_stream_CDLCONCEALBABYSWALL __pyx_string_tab[769] -#define __pyx_n_u_stream_CDLCOUNTERATTACK __pyx_string_tab[770] -#define __pyx_n_u_stream_CDLDARKCLOUDCOVER __pyx_string_tab[771] -#define __pyx_n_u_stream_CDLDOJI __pyx_string_tab[772] -#define __pyx_n_u_stream_CDLDOJISTAR __pyx_string_tab[773] -#define __pyx_n_u_stream_CDLDRAGONFLYDOJI __pyx_string_tab[774] -#define __pyx_n_u_stream_CDLENGULFING __pyx_string_tab[775] -#define __pyx_n_u_stream_CDLEVENINGDOJISTAR __pyx_string_tab[776] -#define __pyx_n_u_stream_CDLEVENINGSTAR __pyx_string_tab[777] -#define __pyx_n_u_stream_CDLGAPSIDESIDEWHITE __pyx_string_tab[778] -#define __pyx_n_u_stream_CDLGRAVESTONEDOJI __pyx_string_tab[779] -#define __pyx_n_u_stream_CDLHAMMER __pyx_string_tab[780] -#define __pyx_n_u_stream_CDLHANGINGMAN __pyx_string_tab[781] -#define __pyx_n_u_stream_CDLHARAMI __pyx_string_tab[782] -#define __pyx_n_u_stream_CDLHARAMICROSS __pyx_string_tab[783] -#define __pyx_n_u_stream_CDLHIGHWAVE __pyx_string_tab[784] -#define __pyx_n_u_stream_CDLHIKKAKE __pyx_string_tab[785] -#define __pyx_n_u_stream_CDLHIKKAKEMOD __pyx_string_tab[786] -#define __pyx_n_u_stream_CDLHOMINGPIGEON __pyx_string_tab[787] -#define __pyx_n_u_stream_CDLIDENTICAL3CROWS __pyx_string_tab[788] -#define __pyx_n_u_stream_CDLINNECK __pyx_string_tab[789] -#define __pyx_n_u_stream_CDLINVERTEDHAMMER __pyx_string_tab[790] -#define __pyx_n_u_stream_CDLKICKING __pyx_string_tab[791] -#define __pyx_n_u_stream_CDLKICKINGBYLENGTH __pyx_string_tab[792] -#define __pyx_n_u_stream_CDLLADDERBOTTOM __pyx_string_tab[793] -#define __pyx_n_u_stream_CDLLONGLEGGEDDOJI __pyx_string_tab[794] -#define __pyx_n_u_stream_CDLLONGLINE 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unsigned int line_table_length : 14; - } __Pyx_PyCode_New_function_description; -/* NewCodeObj.proto */ -static PyObject* __Pyx_PyCode_New( - const __Pyx_PyCode_New_function_description descr, - PyObject * const *varnames, - PyObject *filename, - PyObject *funcname, - const char *line_table, - PyObject *tuple_dedup_map -); - - -static int __Pyx_CreateCodeObjects(__pyx_mstatetype *__pyx_mstate) { - PyObject* tuple_dedup_map = PyDict_New(); - if (unlikely(!tuple_dedup_map)) return -1; - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 2, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 6, 253}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_function_name, __pyx_mstate->__pyx_n_u_ret_code}; - __pyx_mstate_global->__pyx_codeobj_tab[0] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__common_pxi, __pyx_mstate->__pyx_n_u_ta_check_success, __pyx_k_y_1_q_Q_a_Q_a_Q_a_Q_a_Q_a_Q_a_Q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[0])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {0, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 50, 19}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_ret_code}; - __pyx_mstate_global->__pyx_codeobj_tab[1] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__common_pxi, __pyx_mstate->__pyx_n_u_ta_initialize, __pyx_k_Q_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[1])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {0, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 55, 18}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_ret_code}; - __pyx_mstate_global->__pyx_codeobj_tab[2] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__common_pxi, __pyx_mstate->__pyx_n_u_ta_shutdown, __pyx_k_a_QoQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[2])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 63, 70}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self}; - __pyx_mstate_global->__pyx_codeobj_tab[3] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__common_pxi, __pyx_mstate->__pyx_n_u_init, __pyx_k_A_A_6_6_6_7_7_81_7_7_5, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[3])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 2, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 76, 13}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_type}; - __pyx_mstate_global->__pyx_codeobj_tab[4] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__common_pxi, __pyx_mstate->__pyx_n_u_getitem, __pyx_k_A_t81A, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[4])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 4, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 90, 34}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_name, __pyx_mstate->__pyx_n_u_period, __pyx_mstate->__pyx_n_u_ret_code, __pyx_mstate->__pyx_n_u_id}; - __pyx_mstate_global->__pyx_codeobj_tab[5] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__common_pxi, __pyx_mstate->__pyx_n_u_ta_set_unstable_period, __pyx_k_Qa_q_A_Q_a, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[5])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 3, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 96, 27}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_name, __pyx_mstate->__pyx_n_u_period, __pyx_mstate->__pyx_n_u_id}; - __pyx_mstate_global->__pyx_codeobj_tab[6] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__common_pxi, __pyx_mstate->__pyx_n_u_ta_get_unstable_period, __pyx_k_Qa_Qa_1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[6])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 2, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 102, 22}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_value, __pyx_mstate->__pyx_n_u_ret_code}; - __pyx_mstate_global->__pyx_codeobj_tab[7] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__common_pxi, __pyx_mstate->__pyx_n_u_ta_set_compatibility, __pyx_k_aq_Q_Q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[7])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {0, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 107, 15}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_value}; - __pyx_mstate_global->__pyx_codeobj_tab[8] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__common_pxi, __pyx_mstate->__pyx_n_u_ta_get_compatibility, __pyx_k_1_1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[8])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 5, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 124, 28}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_settingtype, __pyx_mstate->__pyx_n_u_rangetype, __pyx_mstate->__pyx_n_u_avgperiod, __pyx_mstate->__pyx_n_u_factor, __pyx_mstate->__pyx_n_u_ret_code}; - __pyx_mstate_global->__pyx_codeobj_tab[9] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__common_pxi, __pyx_mstate->__pyx_n_u_ta_set_candle_settings, __pyx_k_q_1_Q_a, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[9])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 2, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 129, 22}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_settingtype, __pyx_mstate->__pyx_n_u_ret_code}; - __pyx_mstate_global->__pyx_codeobj_tab[10] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__common_pxi, __pyx_mstate->__pyx_n_u_ta_restore_candle_default_setti, __pyx_k_2_1_Q_9, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[10])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 142, 359}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outrealupperband, __pyx_mstate->__pyx_n_u_outrealmiddleband, __pyx_mstate->__pyx_n_u_outreallowerband}; - __pyx_mstate_global->__pyx_codeobj_tab[11] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ACCBANDS, __pyx_k_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_w, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[11])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 181, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[12] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ACOS, __pyx_k_aq_T_q_8_T_U_7_A_we_A_q_4y_4vQi, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[12])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 210, 297}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_volume, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[13] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_AD, __pyx_k_aq_Qa_Kq_6_gQ_8_T_3hjX_eeoouuv, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[13])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 242, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real0, __pyx_mstate->__pyx_n_u_real1, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[14] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ADD, __pyx_k_Kq_Kq_7_8_U_E_U_7_A_we_1_q_i_vQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[14])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {6, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 273, 330}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_volume, __pyx_mstate->__pyx_n_u_fastperiod, __pyx_mstate->__pyx_n_u_slowperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[15] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ADOSC, __pyx_k_z_R_R_S_aq_Qa_Kq_6_gQ_8_T_3hjX, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[15])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 308, 255}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[16] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ADX, __pyx_k_Z_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_w, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[16])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 341, 255}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[17] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ADXR, __pyx_k_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_we, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[17])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 374, 187}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_fastperiod, __pyx_mstate->__pyx_n_u_slowperiod, __pyx_mstate->__pyx_n_u_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[18] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_APO, __pyx_k_TTU_aq_T_q_8_T_U_7_A_we_2_q_q_i, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[18])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 407, 258}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outaroondown, __pyx_mstate->__pyx_n_u_outaroonup}; - __pyx_mstate_global->__pyx_codeobj_tab[19] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_AROON, __pyx_k_A_aq_Qa_6_8_T_3a_U_7_A_we_Rq_AX, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[19])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 442, 209}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[20] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_AROONOSC, __pyx_k_CD_aq_Qa_6_8_T_3a_U_7_A_we_0_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[20])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 474, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[21] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ASIN, __pyx_k_aq_T_q_8_T_U_7_A_we_A_q_4y_4vQi, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[21])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 503, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[22] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ATAN, __pyx_k_aq_T_q_8_T_U_7_A_we_A_q_4y_4vQi, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[22])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 532, 255}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[23] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ATR, __pyx_k_Z_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_w, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[23])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 565, 298}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[24] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_AVGPRICE, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[24])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 597, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[25] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_AVGDEV, __pyx_k_aq_T_q_8_T_U_7_A_we_b_q_2T_T_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[25])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 15, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 628, 304}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_nbdevup, __pyx_mstate->__pyx_n_u_nbdevdn, __pyx_mstate->__pyx_n_u_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outrealupperband, __pyx_mstate->__pyx_n_u_outrealmiddleband, __pyx_mstate->__pyx_n_u_outreallowerband}; - __pyx_mstate_global->__pyx_codeobj_tab[26] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_BBANDS, __pyx_k_VVmmn4_aq_T_q_8_T_U_7_A_we_b_Zz, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[26])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 668, 209}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real0, __pyx_mstate->__pyx_n_u_real1, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[27] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_BETA, __pyx_k_BC_Kq_Kq_7_8_U_E_U_7_A_we_Ba_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[27])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 701, 298}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[28] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_BOP, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[28])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 733, 255}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[29] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CCI, __pyx_k_Z_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_w, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[29])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 766, 302}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[30] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDL2CROWS, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_3, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[30])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 798, 308}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[31] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDL3BLACKCROWS, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_4, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[31])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 830, 306}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[32] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDL3INSIDE, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_5, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[32])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 862, 308}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[33] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDL3LINESTRIKE, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_4, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[33])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 894, 306}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[34] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDL3OUTSIDE, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_6, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[34])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 926, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[35] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDL3STARSINSOUTH, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_7, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[35])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 958, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[36] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDL3WHITESOLDIERS, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_8, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[36])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 990, 328}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[37] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLABANDONEDBABY, __pyx_k_C_D_aq_aq_Qa_Kq_6_uA_8_T_4xzY_d, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[37])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1024, 308}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[38] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLADVANCEBLOCK, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_9, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[38])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1056, 306}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[39] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLBELTHOLD, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_6, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[39])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1088, 307}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[40] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLBREAKAWAY, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_10, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[40])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1120, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[41] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLCLOSINGMARUBOZU, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_11, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[41])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1152, 316}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[42] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLCONCEALBABYSWALL, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_12, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[42])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1184, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[43] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLCOUNTERATTACK, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_7, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[43])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1216, 328}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[44] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLDARKCLOUDCOVER, __pyx_k_D_E_aq_aq_Qa_Kq_6_uA_8_T_4xzY_d, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[44])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1250, 297}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[45] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLDOJI, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_13, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[45])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1282, 306}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[46] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLDOJISTAR, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_6, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[46])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1314, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[47] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLDRAGONFLYDOJI, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_7, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[47])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1346, 307}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[48] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLENGULFING, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_10, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[48])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1378, 328}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[49] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLEVENINGDOJISTAR, __pyx_k_E_F_aq_aq_Qa_Kq_6_uA_8_T_4xzY_d, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[49])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1412, 324}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[50] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLEVENINGSTAR, __pyx_k_A_B_aq_aq_Qa_Kq_6_uA_8_T_4xzY_d, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[50])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1446, 316}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[51] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLGAPSIDESIDEWHITE, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_12, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[51])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1478, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[52] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLGRAVESTONEDOJI, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_8, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[52])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1510, 302}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[53] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLHAMMER, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_3, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[53])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1542, 308}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[54] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLHANGINGMAN, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_14, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[54])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1574, 302}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[55] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLHARAMI, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_3, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[55])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1606, 308}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[56] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLHARAMICROSS, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_4, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[56])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1638, 306}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[57] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLHIGHWAVE, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_6, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[57])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1670, 306}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[58] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLHIKKAKE, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_5, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[58])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1702, 308}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[59] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLHIKKAKEMOD, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_14, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[59])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1734, 308}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[60] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLHOMINGPIGEON, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_9, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[60])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1766, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[61] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLIDENTICAL3CROWS, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_11, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[61])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1798, 302}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[62] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLINNECK, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_3, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[62])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1830, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[63] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLINVERTEDHAMMER, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_8, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[63])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1862, 306}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[64] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLKICKING, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_5, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[64])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1894, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[65] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLKICKINGBYLENGTH, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_11, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[65])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1926, 308}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[66] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLLADDERBOTTOM, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_9, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[66])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1958, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[67] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLLONGLEGGEDDOJI, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_8, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[67])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1990, 306}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[68] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLLONGLINE, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_6, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[68])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2022, 306}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[69] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLMARUBOZU, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_6, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[69])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2054, 308}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[70] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLMATCHINGLOW, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_4, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[70])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2086, 318}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[71] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLMATHOLD, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_15, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[71])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2120, 328}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[72] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLMORNINGDOJISTAR, __pyx_k_E_F_aq_aq_Qa_Kq_6_uA_8_T_4xzY_d, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[72])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2154, 324}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[73] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLMORNINGSTAR, __pyx_k_A_B_aq_aq_Qa_Kq_6_uA_8_T_4xzY_d, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[73])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2188, 302}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[74] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLONNECK, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_3, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[74])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2220, 306}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[75] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLPIERCING, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_6, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[75])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2252, 308}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[76] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLRICKSHAWMAN, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_4, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[76])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2284, 316}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[77] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLRISEFALL3METHODS, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_12, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[77])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2316, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[78] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLSEPARATINGLINES, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_11, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[78])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2348, 308}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[79] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLSHOOTINGSTAR, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_9, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[79])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2380, 307}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[80] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLSHORTLINE, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_10, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[80])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2412, 308}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[81] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLSPINNINGTOP, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_4, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[81])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2444, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[82] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLSTALLEDPATTERN, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_8, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[82])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2476, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[83] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLSTICKSANDWICH, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_7, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[83])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2508, 302}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[84] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLTAKURI, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_3, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[84])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2540, 307}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[85] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLTASUKIGAP, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_10, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[85])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2572, 307}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[86] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLTHRUSTING, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_10, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[86])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2604, 306}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[87] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLTRISTAR, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_5, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[87])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2636, 308}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[88] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLUNIQUE3RIVER, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_9, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[88])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2668, 312}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[89] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLUPSIDEGAP2CROWS, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_11, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[89])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2700, 316}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[90] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CDLXSIDEGAP3METHODS, __pyx_k_aq_aq_Qa_Kq_6_uA_8_T_4xzY_ddnns_12, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[90])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2732, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[91] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CEIL, __pyx_k_aq_T_q_8_T_U_7_A_we_A_q_4y_4vQi, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[91])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2761, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[92] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CMO, __pyx_k_aq_T_q_8_T_U_7_A_we_2Q_q_i_fAYm, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[92])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2792, 209}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real0, __pyx_mstate->__pyx_n_u_real1, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[93] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_CORREL, __pyx_k_DE_Kq_Kq_7_8_U_E_U_7_A_we_b_q_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[93])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2825, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[94] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_COS, __pyx_k_aq_T_q_8_T_U_7_A_we_1_q_i_fAYa, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[94])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2854, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[95] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_COSH, __pyx_k_aq_T_q_8_T_U_7_A_we_A_q_4y_4vQi, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[95])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2883, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[96] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_DEMA, __pyx_k_aq_T_q_8_T_U_7_A_we_Ba_q_4y_4vQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[96])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2914, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real0, __pyx_mstate->__pyx_n_u_real1, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[97] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_DIV, __pyx_k_Kq_Kq_7_8_U_E_U_7_A_we_1_q_i_vQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[97])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2945, 254}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[98] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_DX, __pyx_k_YZ_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[98])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2978, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[99] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_EMA, __pyx_k_aq_T_q_8_T_U_7_A_we_2Q_q_i_fAYm, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[99])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3009, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[100] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_EXP, __pyx_k_aq_T_q_8_T_U_7_A_we_1_q_i_fAYa, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[100])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3038, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[101] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_FLOOR, __pyx_k_aq_T_q_8_T_U_7_A_we_Q_q_D_D_ay, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[101])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3067, 151}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[102] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_HT_DCPERIOD, __pyx_k_aq_T_q_8_T_U_7_A_we_31_q_i_fAYa, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[102])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3096, 151}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[103] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_HT_DCPHASE, __pyx_k_aq_T_q_8_T_U_7_A_we_2_q_r_Yk_V1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[103])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3125, 200}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinphase, __pyx_mstate->__pyx_n_u_outquadrature}; - __pyx_mstate_global->__pyx_codeobj_tab[104] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_HT_PHASOR, __pyx_k_aq_T_q_8_T_U_7_A_we_1_81_Qha_b, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[104])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3157, 195}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outsine, __pyx_mstate->__pyx_n_u_outleadsine}; - __pyx_mstate_global->__pyx_codeobj_tab[105] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_HT_SINE, __pyx_k_aq_T_q_8_T_U_7_A_we_q_q_1HA_Bd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[105])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3189, 153}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[106] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_HT_TRENDLINE, __pyx_k_aq_T_q_8_T_U_7_A_we_4A_q_4y_4vQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[106])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3218, 152}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[107] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_HT_TRENDMODE, __pyx_k_aq_T_q_8_T_U_7_A_we_4A_q_4y_4vQ_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[107])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3247, 209}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[108] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_IMI, __pyx_k_A_aq_Kq_6_8_T_5_U_7_A_we_2Q_q_i, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[108])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3279, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[109] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_KAMA, __pyx_k_aq_T_q_8_T_U_7_A_we_Ba_q_4y_4vQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[109])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3310, 168}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[110] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_LINEARREG, __pyx_k_aq_T_q_8_T_U_7_A_we_1_1_q_b_I_F, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[110])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3341, 170}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[111] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_LINEARREG_ANGLE, __pyx_k_01_aq_T_q_8_T_U_7_A_we_7r_q_Bd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[111])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3372, 174}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[112] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_LINEARREG_INTERCEPT, __pyx_k_45_aq_T_q_8_T_U_7_A_we_2Q_q_i_f, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[112])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3403, 170}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[113] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_LINEARREG_SLOPE, __pyx_k_01_aq_T_q_8_T_U_7_A_we_7r_q_Bd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[113])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3434, 137}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[114] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_LN, __pyx_k_aq_T_q_8_T_U_7_A_we_q_r_Yk_V1IQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[114])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3463, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[115] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_LOG10, __pyx_k_aq_T_q_8_T_U_7_A_we_Q_q_D_D_ay, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[115])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3492, 173}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[116] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MA, __pyx_k_1_aq_T_q_8_T_U_7_A_we_M_q_r_Yk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[116])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3524, 286}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_fastperiod, __pyx_mstate->__pyx_n_u_slowperiod, __pyx_mstate->__pyx_n_u_signalperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outmacd, __pyx_mstate->__pyx_n_u_outmacdsignal, __pyx_mstate->__pyx_n_u_outmacdhist}; - __pyx_mstate_global->__pyx_codeobj_tab[117] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MACD, __pyx_k_UUV2_aq_T_q_8_T_U_7_A_we_Bm_q_Q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[117])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {7, 0, 0, 17, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3563, 341}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_fastperiod, __pyx_mstate->__pyx_n_u_fastmatype, __pyx_mstate->__pyx_n_u_slowperiod, __pyx_mstate->__pyx_n_u_slowmatype, __pyx_mstate->__pyx_n_u_signalperiod, __pyx_mstate->__pyx_n_u_signalmatype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outmacd, __pyx_mstate->__pyx_n_u_outmacdsignal, __pyx_mstate->__pyx_n_u_outmacdhist}; - __pyx_mstate_global->__pyx_codeobj_tab[118] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MACDEXT, __pyx_k_SSkk_Y_Y_Z_8_aq_T_q_8_T_U_7_A_w, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[118])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3605, 266}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_signalperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outmacd, __pyx_mstate->__pyx_n_u_outmacdsignal, __pyx_mstate->__pyx_n_u_outmacdhist}; - __pyx_mstate_global->__pyx_codeobj_tab[119] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MACDFIX, __pyx_k_aq_T_q_8_T_U_7_A_we_r_q_Qha_1HA, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[119])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3642, 223}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_fastlimit, __pyx_mstate->__pyx_n_u_slowlimit, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outmama, __pyx_mstate->__pyx_n_u_outfama}; - __pyx_mstate_global->__pyx_codeobj_tab[120] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MAMA, __pyx_k_a_aq_T_q_8_T_U_7_A_we_Bl_q_q_4y, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[120])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3677, 237}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_periods, __pyx_mstate->__pyx_n_u_minperiod, __pyx_mstate->__pyx_n_u_maxperiod, __pyx_mstate->__pyx_n_u_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[121] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MAVP, __pyx_k_CZZqqr_aq_k_6_8_T_7_U_7_A_we_Bl, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[121])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3712, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[122] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MAX, __pyx_k_aq_T_q_8_T_U_7_A_we_2Q_q_i_fAYm, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[122])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3743, 190}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger, __pyx_mstate->__pyx_n_u_outinteger_data, __pyx_mstate->__pyx_n_u_i}; - __pyx_mstate_global->__pyx_codeobj_tab[123] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MAXINDEX, __pyx_k_aq_T_q_8_T_U_7_A_we_0_q_Rt9Kt6, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[123])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3777, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[124] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MEDPRICE, __pyx_k_aq_Qa_6_8_T_3a_U_7_A_we_0_q_Rt9, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[124])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3807, 310}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_volume, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[125] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MFI, __pyx_k_wx_aq_Qa_Kq_6_gQ_8_T_3hjX_eeoou, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[125])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3841, 167}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[126] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MIDPOINT, __pyx_k_aq_T_q_8_T_U_7_A_we_0_q_Rt9Kt6_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[126])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3872, 209}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[127] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MIDPRICE, __pyx_k_CD_aq_Qa_6_8_T_3a_U_7_A_we_0_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[127])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3904, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[128] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MIN, __pyx_k_aq_T_q_8_T_U_7_A_we_2Q_q_i_fAYm, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[128])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3935, 190}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger, __pyx_mstate->__pyx_n_u_outinteger_data, __pyx_mstate->__pyx_n_u_i}; - __pyx_mstate_global->__pyx_codeobj_tab[129] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MININDEX, __pyx_k_aq_T_q_8_T_U_7_A_we_0_q_Rt9Kt6, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[129])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3969, 212}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outmin, __pyx_mstate->__pyx_n_u_outmax}; - __pyx_mstate_global->__pyx_codeobj_tab[130] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MINMAX, __pyx_k_aq_T_q_8_T_U_7_A_we_b_axq_axq_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[130])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4003, 271}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outminidx, __pyx_mstate->__pyx_n_u_outmaxidx, __pyx_mstate->__pyx_n_u_outminidx_data, __pyx_mstate->__pyx_n_u_i, __pyx_mstate->__pyx_n_u_outmaxidx_data}; - __pyx_mstate_global->__pyx_codeobj_tab[131] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MINMAXINDEX, __pyx_k_aq_T_q_8_T_U_7_A_we_32Q_axq_axq, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[131])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4043, 259}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[132] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MINUS_DI, __pyx_k_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_w_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[132])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4076, 209}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[133] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MINUS_DM, __pyx_k_CD_aq_Qa_6_8_T_3a_U_7_A_we_0_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[133])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4108, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[134] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MOM, __pyx_k_aq_T_q_8_T_U_7_A_we_2Q_q_i_fAYm, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[134])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4139, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real0, __pyx_mstate->__pyx_n_u_real1, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[135] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_MULT, __pyx_k_Kq_Kq_7_8_U_E_U_7_A_we_A_q_4y_5, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[135])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4170, 255}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[136] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_NATR, __pyx_k_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_we, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[136])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4203, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_volume, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[137] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_OBV, __pyx_k_aq_6_8_T_6_U_7_A_we_1_q_i_fAYkQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[137])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4234, 255}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[138] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_PLUS_DI, __pyx_k_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_w_3, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[138])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4267, 209}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[139] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_PLUS_DM, __pyx_k_BC_aq_Qa_6_8_T_3a_U_7_A_we_r_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[139])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4299, 187}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_fastperiod, __pyx_mstate->__pyx_n_u_slowperiod, __pyx_mstate->__pyx_n_u_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[140] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_PPO, __pyx_k_TTU_aq_T_q_8_T_U_7_A_we_2_q_q_i, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[140])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4332, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[141] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ROC, __pyx_k_aq_T_q_8_T_U_7_A_we_2Q_q_i_fAYm, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[141])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4363, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[142] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ROCP, __pyx_k_aq_T_q_8_T_U_7_A_we_Ba_q_4y_4vQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[142])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4394, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[143] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ROCR, __pyx_k_aq_T_q_8_T_U_7_A_we_Ba_q_4y_4vQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[143])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4425, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[144] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ROCR100, __pyx_k_aq_T_q_8_T_U_7_A_we_r_q_Bd_d_WX, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[144])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4456, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[145] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_RSI, __pyx_k_aq_T_q_8_T_U_7_A_we_2Q_q_i_fAYm, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[145])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4487, 217}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_acceleration, __pyx_mstate->__pyx_n_u_maximum, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[146] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_SAR, __pyx_k_YYZ_aq_Qa_6_8_T_3a_U_7_A_we_2_A, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[146])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {10, 0, 0, 18, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4520, 344}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_startvalue, __pyx_mstate->__pyx_n_u_offsetonreverse, __pyx_mstate->__pyx_n_u_accelerationinitlong, __pyx_mstate->__pyx_n_u_accelerationlong, __pyx_mstate->__pyx_n_u_accelerationmaxlong, __pyx_mstate->__pyx_n_u_accelerationinitshort, __pyx_mstate->__pyx_n_u_accelerationshort, __pyx_mstate->__pyx_n_u_accelerationmaxshort, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[147] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_SAREXT, __pyx_k_A_z_____b_b_G_G_h_h_i_4_aq_Qa_6, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[147])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4559, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[148] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_SIN, __pyx_k_aq_T_q_8_T_U_7_A_we_1_q_i_fAYa, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[148])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4588, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[149] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_SINH, __pyx_k_aq_T_q_8_T_U_7_A_we_A_q_4y_4vQi, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[149])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4617, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[150] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_SMA, __pyx_k_aq_T_q_8_T_U_7_A_we_2Q_q_i_fAYm, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[150])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4648, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[151] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_SQRT, __pyx_k_aq_T_q_8_T_U_7_A_we_A_q_4y_4vQi, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[151])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4677, 174}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_nbdev, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[152] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_STDDEV, __pyx_k_q_aq_T_q_8_T_U_7_A_we_b_Q_q_2T, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[152])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {8, 0, 0, 17, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4709, 370}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_fastk_period, __pyx_mstate->__pyx_n_u_slowk_period, __pyx_mstate->__pyx_n_u_slowk_matype, __pyx_mstate->__pyx_n_u_slowd_period, __pyx_mstate->__pyx_n_u_slowd_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outslowk, __pyx_mstate->__pyx_n_u_outslowd}; - __pyx_mstate_global->__pyx_codeobj_tab[153] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_STOCH, __pyx_k_v_w_Q_Q_f_f_A_2_aq_Qa_Kq_6_a_8, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[153])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {6, 0, 0, 15, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4749, 336}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_fastk_period, __pyx_mstate->__pyx_n_u_fastd_period, __pyx_mstate->__pyx_n_u_fastd_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outfastk, __pyx_mstate->__pyx_n_u_outfastd}; - __pyx_mstate_global->__pyx_codeobj_tab[154] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_STOCHF, __pyx_k_w_x_R_R_S_aq_Qa_Kq_6_a_8_T_3hjX, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[154])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4787, 261}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_fastk_period, __pyx_mstate->__pyx_n_u_fastd_period, __pyx_mstate->__pyx_n_u_fastd_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outfastk, __pyx_mstate->__pyx_n_u_outfastd}; - __pyx_mstate_global->__pyx_codeobj_tab[155] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_STOCHRSI, __pyx_k_AA_uuv0_aq_T_q_8_T_U_7_A_we_0_o, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[155])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4824, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real0, __pyx_mstate->__pyx_n_u_real1, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[156] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_SUB, __pyx_k_Kq_Kq_7_8_U_E_U_7_A_we_1_q_i_vQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[156])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4855, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[157] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_SUM, __pyx_k_aq_T_q_8_T_U_7_A_we_2Q_q_i_fAYm, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[157])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4886, 173}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_vfactor, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[158] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_T3, __pyx_k_1_aq_T_q_8_T_U_7_A_we_M_q_r_Yk_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[158])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4918, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[159] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_TAN, __pyx_k_aq_T_q_8_T_U_7_A_we_1_q_i_fAYa, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[159])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4947, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[160] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_TANH, __pyx_k_aq_T_q_8_T_U_7_A_we_A_q_4y_4vQi, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[160])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4976, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[161] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_TEMA, __pyx_k_aq_T_q_8_T_U_7_A_we_Ba_q_4y_4vQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[161])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5007, 243}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[162] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_TRANGE, __pyx_k_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_we_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[162])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5038, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[163] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_TRIMA, __pyx_k_aq_T_q_8_T_U_7_A_we_Rq_q_D_D_ay, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[163])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5069, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[164] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_TRIX, __pyx_k_aq_T_q_8_T_U_7_A_we_Ba_q_4y_4vQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[164])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5100, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[165] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_TSF, __pyx_k_aq_T_q_8_T_U_7_A_we_2Q_q_i_fAYm, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[165])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5131, 247}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[166] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_TYPPRICE, __pyx_k_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_we_3, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[166])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {6, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5162, 287}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod1, __pyx_mstate->__pyx_n_u_timeperiod2, __pyx_mstate->__pyx_n_u_timeperiod3, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[167] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_ULTOSC, __pyx_k_v_w_P_P_Q_aq_Qa_Kq_6_a_8_T_3hjX, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[167])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5197, 174}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_nbdev, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[168] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_VAR, __pyx_k_A_aq_T_q_8_T_U_7_A_we_2_q_i_fAY, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[168])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5229, 247}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[169] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_WCLPRICE, __pyx_k_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_we_3, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[169])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5260, 255}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[170] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_WILLR, __pyx_k_aq_Qa_Kq_6_a_8_T_3hjX_U_7_A_we_4, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[170])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5293, 163}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_begidx, __pyx_mstate->__pyx_n_u_endidx, __pyx_mstate->__pyx_n_u_lookback, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[171] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__func_pxi, __pyx_mstate->__pyx_n_u_WMA, __pyx_k_aq_T_q_8_T_U_7_A_we_2Q_q_i_fAYm, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[171])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 74, 13}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_s}; - __pyx_mstate_global->__pyx_codeobj_tab[172] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_str2bytes, __pyx_k_A_uAS, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[172])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 77, 13}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_b}; - __pyx_mstate_global->__pyx_codeobj_tab[173] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_bytes2str, __pyx_k_A_q_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[173])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 82, 7}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_s}; - __pyx_mstate_global->__pyx_codeobj_tab[174] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_str2bytes, __pyx_k_A_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[174])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 85, 7}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_b}; - __pyx_mstate_global->__pyx_codeobj_tab[175] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_bytes2str, __pyx_k_A_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[175])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 5, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS|CO_VARARGS|CO_VARKEYWORDS), 117, 69}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_function_name, __pyx_mstate->__pyx_n_u_func_object, __pyx_mstate->__pyx_n_u_args, __pyx_mstate->__pyx_n_u_kwargs}; - __pyx_mstate_global->__pyx_codeobj_tab[176] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_init, __pyx_k_A_Jm6_M_Q_Jiq_A_O9F_b_O1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[176])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 130, 363}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_local, __pyx_mstate->__pyx_n_u_i, __pyx_mstate->__pyx_n_u_info, __pyx_mstate->__pyx_n_u_input_name, __pyx_mstate->__pyx_n_u_param_name, __pyx_mstate->__pyx_n_u_output_name}; - __pyx_mstate_global->__pyx_codeobj_tab[177] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_local_2, __pyx_k_A_A_4wawa_1_Kq_Q_V1E_d_1_0_Ya_T, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[177])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 172, 17}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self}; - __pyx_mstate_global->__pyx_codeobj_tab[178] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_info, __pyx_k_A_t85_Q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[178])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 179, 17}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self}; - __pyx_mstate_global->__pyx_codeobj_tab[179] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_function_flags, __pyx_k_A_t85, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[179])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 186, 21}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self}; - __pyx_mstate_global->__pyx_codeobj_tab[180] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_output_flags, __pyx_k_A_t85_Q_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[180])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 4, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 193, 51}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_local, __pyx_mstate->__pyx_n_u_ret, __pyx_mstate->__pyx_n_u_input_name}; - __pyx_mstate_global->__pyx_codeobj_tab[181] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_get_input_names, __pyx_k_A_A_k_N_q_q_e_q_1A_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[181])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 5, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 204, 64}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_input_names, __pyx_mstate->__pyx_n_u_local, __pyx_mstate->__pyx_n_u_input_name, __pyx_mstate->__pyx_n_u_price_series}; - __pyx_mstate_global->__pyx_codeobj_tab[182] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_set_input_names, __pyx_k_A_A_L_6_Qk_A_a_QnA_a, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[182])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 2, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 216, 56}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_local}; - __pyx_mstate_global->__pyx_codeobj_tab[183] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_get_input_arrays, __pyx_k_A_A_gQ_5_q_5_V1_5_U, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[183])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 6, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 227, 167}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_input_arrays, __pyx_mstate->__pyx_n_u_local, __pyx_mstate->__pyx_n_u_missing_keys, __pyx_mstate->__pyx_n_u_key, __pyx_mstate->__pyx_n_u_missing}; - __pyx_mstate_global->__pyx_codeobj_tab[184] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_set_input_arrays, __pyx_k_A2_A_QnA_1_t_6a_gQ_d_Q_d_1_q_s_A, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[184])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 4, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 276, 48}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_local, __pyx_mstate->__pyx_n_u_ret, __pyx_mstate->__pyx_n_u_opt_input}; - __pyx_mstate_global->__pyx_codeobj_tab[185] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_get_parameters, __pyx_k_A_A_k_M_a_q_T_7q_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[185])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 6, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS|CO_VARKEYWORDS), 286, 96}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_parameters, __pyx_mstate->__pyx_n_u_kwargs, __pyx_mstate->__pyx_n_u_local, __pyx_mstate->__pyx_n_u_param, __pyx_mstate->__pyx_n_u_value}; - __pyx_mstate_global->__pyx_codeobj_tab[186] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_set_parameters, __pyx_k_Q_A_1_G9JfA_t_1G1_q_1_a_U_4q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[186])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS|CO_VARARGS|CO_VARKEYWORDS), 301, 285}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_args, __pyx_mstate->__pyx_n_u_kwargs, __pyx_mstate->__pyx_n_u_local, __pyx_mstate->__pyx_n_u_update_info, __pyx_mstate->__pyx_n_u_key, __pyx_mstate->__pyx_n_u_value, __pyx_mstate->__pyx_n_u_skip_first, __pyx_mstate->__pyx_n_u_i, __pyx_mstate->__pyx_n_u_param_name}; - __pyx_mstate_global->__pyx_codeobj_tab[187] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_set_function_args, __pyx_k_A_A_a_G1_t3e1_aq_4_q_Q_AT_V1A_S, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[187])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 336, 143}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_local, __pyx_mstate->__pyx_n_u_holder, __pyx_mstate->__pyx_n_u_i, __pyx_mstate->__pyx_n_u_opt_input, __pyx_mstate->__pyx_n_u_value, __pyx_mstate->__pyx_n_u_type, __pyx_mstate->__pyx_n_u_lookback}; - __pyx_mstate_global->__pyx_codeobj_tab[188] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_lookback, __pyx_k_A_A_at1_C_IQe1_D_aq_E_AZq_vV_2_V, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[188])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 2, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 357, 44}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_ret}; - __pyx_mstate_global->__pyx_codeobj_tab[189] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_output_names, __pyx_k_A_d_q_4z_q_aq_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[189])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 4, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 367, 241}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_local, __pyx_mstate->__pyx_n_u_ret, __pyx_mstate->__pyx_n_u_index}; - __pyx_mstate_global->__pyx_codeobj_tab[190] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_outputs, __pyx_k_A_A_4uA_e87_4z_q_aq_gU_5_q_E_a_s, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[190])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 2, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 399, 36}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_input_arrays}; - __pyx_mstate_global->__pyx_codeobj_tab[191] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_run, __pyx_k_N_1_A_t1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[191])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 16, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS|CO_VARARGS|CO_VARKEYWORDS), 411, 497}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_args, __pyx_mstate->__pyx_n_u_kwargs, __pyx_mstate->__pyx_n_u_local, __pyx_mstate->__pyx_n_u_opt_input_values, __pyx_mstate->__pyx_n_u_price_series_name_values, __pyx_mstate->__pyx_n_u_input_arrays, __pyx_mstate->__pyx_n_u_input_price_series_names, __pyx_mstate->__pyx_n_u_i, __pyx_mstate->__pyx_n_u_arg, __pyx_mstate->__pyx_n_u_msg, __pyx_mstate->__pyx_n_u_no_existing_input_arrays, __pyx_mstate->__pyx_n_u_param_name, __pyx_mstate->__pyx_n_u_value, __pyx_mstate->__pyx_n_u_input_name, __pyx_mstate->__pyx_n_u_n}; - __pyx_mstate_global->__pyx_codeobj_tab[192] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_call, __pyx_k_A_A_2_k_Qa_e_e1_2S_AQ_U_t1A_q_4, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[192])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 6, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 477, 79}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_local, __pyx_mstate->__pyx_n_u_input_price_series_names, __pyx_mstate->__pyx_n_u_input_name, __pyx_mstate->__pyx_n_u_price_series, __pyx_mstate->__pyx_n_u_name}; - __pyx_mstate_global->__pyx_codeobj_tab[193] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_input_price_series_names_2, __pyx_k_A_A_1_N_q_5_A_z_HA_G1A_q_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[193])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 489, 261}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_local, __pyx_mstate->__pyx_n_u_input_price_series_names, __pyx_mstate->__pyx_n_u_args, __pyx_mstate->__pyx_n_u_price_series, __pyx_mstate->__pyx_n_u_series, __pyx_mstate->__pyx_n_u_opt_input, __pyx_mstate->__pyx_n_u_value, __pyx_mstate->__pyx_n_u_results, __pyx_mstate->__pyx_n_u_keys, __pyx_mstate->__pyx_n_u_i, __pyx_mstate->__pyx_n_u_output}; - __pyx_mstate_global->__pyx_codeobj_tab[194] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_call_function, __pyx_k_A_A_4_B_q_A_U_q_we1_axq_wgQa_Q_a, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[194])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 4, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 520, 104}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_input_name, __pyx_mstate->__pyx_n_u_value, __pyx_mstate->__pyx_n_u_type}; - __pyx_mstate_global->__pyx_codeobj_tab[195] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_check_opt_input_value, __pyx_k_A_HKq_1A_6_5Q_A_7_4A_A_QgQ_7_1_A, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[195])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 4, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 535, 55}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self, __pyx_mstate->__pyx_n_u_input_name, __pyx_mstate->__pyx_n_u_local, __pyx_mstate->__pyx_n_u_value}; - __pyx_mstate_global->__pyx_codeobj_tab[196] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_get_opt_input_value, __pyx_k_A_A_AQ_6_A_E_A_q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[196])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 545, 13}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self}; - __pyx_mstate_global->__pyx_codeobj_tab[197] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_repr, __pyx_k_A_uBd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[197])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 548, 15}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self}; - __pyx_mstate_global->__pyx_codeobj_tab[198] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_unicode, __pyx_k_A_wat81, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[198])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 1, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 551, 18}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_self}; - __pyx_mstate_global->__pyx_codeobj_tab[199] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_str, __pyx_k_A_Qd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[199])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {0, 0, 0, 3, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 565, 78}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_table, __pyx_mstate->__pyx_n_u_groups, __pyx_mstate->__pyx_n_u_i}; - __pyx_mstate_global->__pyx_codeobj_tab[200] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_ta_getGroupTable, __pyx_k_Q_B_1A_Q_V1E_gQfAU_Q_1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[200])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 4, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 577, 80}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_group, __pyx_mstate->__pyx_n_u_table, __pyx_mstate->__pyx_n_u_functions, __pyx_mstate->__pyx_n_u_i}; - __pyx_mstate_global->__pyx_codeobj_tab[201] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_ta_getFuncTable, __pyx_k_Q_V1E_q_WAQ_Q_aq_1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[201])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 589, 166}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_flag, __pyx_mstate->__pyx_n_u_flags_lookup_dict, __pyx_mstate->__pyx_n_u_value_range, __pyx_mstate->__pyx_n_u_min_int, __pyx_mstate->__pyx_n_u_max_int, __pyx_mstate->__pyx_n_u_ret, __pyx_mstate->__pyx_n_u_i}; - __pyx_mstate_global->__pyx_codeobj_tab[202] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_get_flags, __pyx_k_5_t_Qm1_d_1_c_d_3a_Q_c_d_3a_Q_u, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[202])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 3, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 648, 115}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_function_name, __pyx_mstate->__pyx_n_u_info, __pyx_mstate->__pyx_n_u_retCode}; - __pyx_mstate_global->__pyx_codeobj_tab[203] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_ta_getFuncInfo, __pyx_k_314DAQ_Q_a_4q_a_Qd_c_a_Qd_s_4q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[203])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 5, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 667, 121}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_function_name, __pyx_mstate->__pyx_n_u_idx, __pyx_mstate->__pyx_n_u_info, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_name}; - __pyx_mstate_global->__pyx_codeobj_tab[204] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_ta_getInputParameterInfo, __pyx_k_Q_NeSTTU_Q_2_9AT_4q_1G6_wc_t81H, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[204])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 6, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 688, 153}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_function_name, __pyx_mstate->__pyx_n_u_idx, __pyx_mstate->__pyx_n_u_info, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_name, __pyx_mstate->__pyx_n_u_default_value}; - __pyx_mstate_global->__pyx_codeobj_tab[205] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_ta_getOptInputParameterInfo, __pyx_k_Q_AQQVVWWX_Q_5Q_9AT_4q_1JfA_D_R, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[205])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 5, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 712, 121}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_function_name, __pyx_mstate->__pyx_n_u_idx, __pyx_mstate->__pyx_n_u_info, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_name}; - __pyx_mstate_global->__pyx_codeobj_tab[206] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_ta_getOutputParameterInfo, __pyx_k_1_a_OuTUUV_Q_31_9AT_4q_1HF_wc_d, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[206])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 732, 347}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_func_info, __pyx_mstate->__pyx_n_u_defaults, __pyx_mstate->__pyx_n_u_func_line, __pyx_mstate->__pyx_n_u_func_args, __pyx_mstate->__pyx_n_u_docs, __pyx_mstate->__pyx_n_u_input_names, __pyx_mstate->__pyx_n_u_input_name, __pyx_mstate->__pyx_n_u_value, __pyx_mstate->__pyx_n_u_params, __pyx_mstate->__pyx_n_u_param, __pyx_mstate->__pyx_n_u_outputs, __pyx_mstate->__pyx_n_u_output, __pyx_mstate->__pyx_n_u_documentation}; - __pyx_mstate_global->__pyx_codeobj_tab[207] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__abstract_pxi, __pyx_mstate->__pyx_n_u_get_defaults_and_docs, __pyx_k_q_9A_1_q_1_1_1A_q_a_1A_4z_A_G1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[207])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 9, 209}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outrealupperband, __pyx_mstate->__pyx_n_u_outrealmiddleband, __pyx_mstate->__pyx_n_u_outreallowerband}; - __pyx_mstate_global->__pyx_codeobj_tab[208] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ACCBANDS, __pyx_k_fg2_aq_Q_Qa_y_1_Kq_q_6_a_q_q_Rv, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[208])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 50, 94}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[209] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ACOS, __pyx_k_aq_Q_T_q_a_6_4vXRt_qP_llmmn_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[209])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 77, 181}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_volume, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_volume_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[210] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_AD, __pyx_k_aq_Q_Qa_y_1_Kq_q_6_6_gQ_a_r_xr, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[210])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 113, 115}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real0, __pyx_mstate->__pyx_n_u_real1, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real0_data, __pyx_mstate->__pyx_n_u_real1_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[211] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ADD, __pyx_k_Kq_q_Kq_q_7_a_fHBd_iijjyyzz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[211])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {6, 0, 0, 15, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 144, 214}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_volume, __pyx_mstate->__pyx_n_u_fastperiod, __pyx_mstate->__pyx_n_u_slowperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_volume_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[212] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ADOSC, __pyx_k_A_Y_Y_Z_aq_Q_Qa_y_1_Kq_q_6_6_gQ, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[212])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 183, 164}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[213] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ADX, __pyx_k_ab_aq_Q_Qa_y_1_Kq_q_6_a_a_fHBd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[213])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 218, 164}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[214] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ADXR, __pyx_k_bc_aq_Q_Qa_y_1_Kq_q_6_a_a_6_4vX, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[214])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 253, 124}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_fastperiod, __pyx_mstate->__pyx_n_u_slowperiod, __pyx_mstate->__pyx_n_u_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[215] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_APO, __pyx_k_CC_aq_Q_T_q_a_fHBd_m_hhqqrr_O_O, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[215])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 284, 155}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outaroondown, __pyx_mstate->__pyx_n_u_outaroonup}; - __pyx_mstate_global->__pyx_codeobj_tab[216] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_AROON, __pyx_k_GH_aq_Q_Qa_y_1_6_1_F_D_hb_LP_hh, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[216])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 319, 134}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[217] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_AROONOSC, __pyx_k_JK_aq_Q_Qa_y_1_6_a_RvXRt6_4_S_k, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[217])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 351, 94}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[218] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ASIN, __pyx_k_aq_Q_T_q_a_6_4vXRt_qP_llmmn_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[218])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 378, 94}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[219] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ATAN, __pyx_k_aq_Q_T_q_a_6_4vXRt_qP_llmmn_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[219])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 405, 164}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[220] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ATR, __pyx_k_ab_aq_Q_Qa_y_1_Kq_q_6_a_a_fHBd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[220])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 440, 182}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[221] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_AVGPRICE, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_a_Rv, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[221])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 476, 101}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[222] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_AVGDEV, __pyx_k_aq_Q_T_q_a_2V82T_xr_Q___kkll_Qm, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[222])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 505, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_nbdevup, __pyx_mstate->__pyx_n_u_nbdevdn, __pyx_mstate->__pyx_n_u_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outrealupperband, __pyx_mstate->__pyx_n_u_outrealmiddleband, __pyx_mstate->__pyx_n_u_outreallowerband}; - __pyx_mstate_global->__pyx_codeobj_tab[223] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_BBANDS, __pyx_k_FF_ttu4_aq_Q_T_q_q_q_2V82T_xr_Q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[223])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 543, 134}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real0, __pyx_mstate->__pyx_n_u_real1, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real0_data, __pyx_mstate->__pyx_n_u_real1_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[224] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_BETA, __pyx_k_IJ_Kq_q_Kq_q_7_a_6_4vXRt_P_jjkk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[224])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 576, 177}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[225] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_BOP, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_a_fH, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[225])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 612, 164}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[226] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CCI, __pyx_k_ab_aq_Q_Qa_y_1_Kq_q_6_a_a_fHBd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[226])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 647, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[227] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDL2CROWS, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_b_hb, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[227])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 683, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[228] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDL3BLACKCROWS, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_2V82, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[228])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 719, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[229] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDL3INSIDE, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_r_xr, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[229])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 755, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[230] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDL3LINESTRIKE, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_2V82, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[230])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 791, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[231] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDL3OUTSIDE, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_fHBd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[231])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 827, 188}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[232] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDL3STARSINSOUTH, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_RvXR, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[232])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 863, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[233] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDL3WHITESOLDIERS, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_b_hb_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[233])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 899, 202}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[234] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLABANDONEDBABY, __pyx_k_J_K_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[234])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 937, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[235] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLADVANCEBLOCK, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_BfHB, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[235])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 973, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[236] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLBELTHOLD, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_fHBd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[236])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1009, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[237] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLBREAKAWAY, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_6_4v, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[237])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1045, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[238] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLCLOSINGMARUBOZU, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_r_xr_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[238])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1081, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[239] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLCONCEALBABYSWALL, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_fHBd_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[239])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1117, 188}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[240] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLCOUNTERATTACK, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_RvXR, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[240])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1153, 207}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[241] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLDARKCLOUDCOVER, __pyx_k_K_L_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[241])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1191, 182}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[242] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLDOJI, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_BfHB_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[242])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1227, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[243] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLDOJISTAR, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_fHBd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[243])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1263, 188}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[244] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLDRAGONFLYDOJI, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_RvXR, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[244])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1299, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[245] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLENGULFING, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_6_4v, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[245])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1335, 207}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[246] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLEVENINGDOJISTAR, __pyx_k_L_M_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[246])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1373, 202}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[247] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLEVENINGSTAR, __pyx_k_H_I_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[247])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1411, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[248] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLGAPSIDESIDEWHITE, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_fHBd_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[248])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1447, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[249] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLGRAVESTONEDOJI, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_b_hb_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[249])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1483, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[250] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLHAMMER, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_b_hb, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[250])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1519, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[251] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLHANGINGMAN, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_F_D, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[251])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1555, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[252] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLHARAMI, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_b_hb, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[252])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1591, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[253] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLHARAMICROSS, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_2V82, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[253])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1627, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[254] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLHIGHWAVE, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_fHBd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[254])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1663, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[255] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLHIKKAKE, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_r_xr, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[255])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1699, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[256] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLHIKKAKEMOD, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_F_D, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[256])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1735, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[257] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLHOMINGPIGEON, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_BfHB, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[257])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1771, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[258] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLIDENTICAL3CROWS, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_r_xr_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[258])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1807, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[259] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLINNECK, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_b_hb, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[259])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1843, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[260] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLINVERTEDHAMMER, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_b_hb_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[260])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1879, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[261] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLKICKING, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_r_xr, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[261])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1915, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[262] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLKICKINGBYLENGTH, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_r_xr_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[262])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1951, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[263] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLLADDERBOTTOM, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_BfHB, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[263])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 1987, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[264] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLLONGLEGGEDDOJI, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_b_hb_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[264])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2023, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[265] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLLONGLINE, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_fHBd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[265])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2059, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[266] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLMARUBOZU, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_fHBd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[266])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2095, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[267] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLMATCHINGLOW, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_2V82, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[267])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2131, 201}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[268] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLMATHOLD, __pyx_k_D_E_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[268])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2169, 207}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[269] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLMORNINGDOJISTAR, __pyx_k_L_M_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[269])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2207, 202}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_penetration, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[270] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLMORNINGSTAR, __pyx_k_H_I_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[270])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2245, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[271] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLONNECK, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_b_hb, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[271])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2281, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[272] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLPIERCING, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_fHBd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[272])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2317, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[273] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLRICKSHAWMAN, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_2V82, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[273])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2353, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[274] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLRISEFALL3METHODS, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_fHBd_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[274])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2389, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[275] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLSEPARATINGLINES, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_r_xr_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[275])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2425, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[276] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLSHOOTINGSTAR, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_BfHB, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[276])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2461, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[277] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLSHORTLINE, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_6_4v, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[277])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2497, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[278] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLSPINNINGTOP, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_2V82, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[278])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2533, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[279] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLSTALLEDPATTERN, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_b_hb_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[279])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2569, 188}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[280] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLSTICKSANDWICH, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_RvXR, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[280])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2605, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[281] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLTAKURI, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_b_hb, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[281])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2641, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[282] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLTASUKIGAP, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_6_4v, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[282])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2677, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[283] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLTHRUSTING, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_6_4v, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[283])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2713, 183}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[284] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLTRISTAR, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_r_xr, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[284])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2749, 184}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[285] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLUNIQUE3RIVER, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_BfHB, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[285])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2785, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[286] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLUPSIDEGAP2CROWS, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_r_xr_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[286])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 13, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2821, 193}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[287] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CDLXSIDEGAP3METHODS, __pyx_k_aq_Q_aq_Q_Qa_y_1_Kq_q_6_uA_fHBd_2, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[287])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2857, 94}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[288] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CEIL, __pyx_k_aq_Q_T_q_a_6_4vXRt_qP_llmmn_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[288])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2884, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[289] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CMO, __pyx_k_aq_Q_T_q_a_fHBd_m_hhiixxyyz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[289])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2913, 134}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real0, __pyx_mstate->__pyx_n_u_real1, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real0_data, __pyx_mstate->__pyx_n_u_real1_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[290] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_CORREL, __pyx_k_KL_Kq_q_Kq_q_7_a_2V82T_xr_R__ll, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[290])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2946, 93}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[291] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_COS, __pyx_k_aq_Q_T_q_a_fHBd_a_kkllm_Qj_1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[291])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 2973, 94}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[292] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_COSH, __pyx_k_aq_Q_T_q_a_6_4vXRt_qP_llmmn_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[292])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3000, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[293] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_DEMA, __pyx_k_aq_Q_T_q_a_6_4vXRt_iijjyyzz_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[293])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3029, 115}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real0, __pyx_mstate->__pyx_n_u_real1, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real0_data, __pyx_mstate->__pyx_n_u_real1_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[294] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_DIV, __pyx_k_Kq_q_Kq_q_7_a_fHBd_iijjyyzz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[294])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3060, 160}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[295] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_DX, __pyx_k_a_aq_Q_Qa_y_1_Kq_q_6_a_a_r_xr_V, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[295])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3095, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[296] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_EMA, __pyx_k_aq_Q_T_q_a_fHBd_m_hhiixxyyz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[296])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3124, 93}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[297] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_EXP, __pyx_k_aq_Q_T_q_a_fHBd_a_kkllm_Qj_1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[297])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3151, 95}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[298] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_FLOOR, __pyx_k_aq_Q_T_q_a_F_D_hb_LPQQ_mmnno_Ql, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[298])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3178, 96}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[299] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_HT_DCPERIOD, __pyx_k_aq_Q_T_q_a_fHBd_VWWccddssttu_Q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[299])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3205, 96}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[300] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_HT_DCPHASE, __pyx_k_aq_Q_T_q_a_r_xr_V82T_UVVbbccrrs, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[300])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3232, 117}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinphase, __pyx_mstate->__pyx_n_u_outquadrature}; - __pyx_mstate_global->__pyx_codeobj_tab[301] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_HT_PHASOR, __pyx_k_aq_Q_T_q_A_b_hb_F_D_TUUaabbqqrr, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[301])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3262, 108}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outsine, __pyx_mstate->__pyx_n_u_outleadsine}; - __pyx_mstate_global->__pyx_codeobj_tab[302] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_HT_SINE, __pyx_k_aq_Q_T_q_a_BfHBd_lRSS___ooppzz, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[302])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3292, 97}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[303] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_HT_TRENDLINE, __pyx_k_aq_Q_T_q_a_6_4vXRt_WXXddeettuuv, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[303])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3319, 97}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[304] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_HT_TRENDMODE, __pyx_k_aq_Q_T_q_6_4vXRt_WXXddeettuuv_Q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[304])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3346, 133}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_open, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_open_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[305] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_IMI, __pyx_k_GH_aq_Q_Kq_q_6_a_fHBd_m_hhiiuuv, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[305])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3378, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[306] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_KAMA, __pyx_k_aq_Q_T_q_a_6_4vXRt_iijjyyzz_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[306])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3407, 106}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[307] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_LINEARREG, __pyx_k_12_aq_Q_T_q_a_b_hb_F_D_Taabbnno, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[307])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3436, 115}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[308] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_LINEARREG_ANGLE, __pyx_k_78_aq_Q_T_q_a_BfHBd_lZgghhttu_v, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[308])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3465, 116}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[309] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_LINEARREG_INTERCEPT, __pyx_k_aq_Q_T_q_a_fHBdR_kkllxxy_z_I_I, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[309])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3494, 115}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[310] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_LINEARREG_SLOPE, __pyx_k_78_aq_Q_T_q_a_BfHBd_lZgghhttu_v, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[310])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3523, 93}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[311] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_LN, __pyx_k_aq_Q_T_q_a_r_xr_V82T_QlZ_jjkkl, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[311])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3550, 95}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[312] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_LOG10, __pyx_k_aq_Q_T_q_a_F_D_hb_LPQQ_mmnno_Ql, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[312])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3577, 117}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[313] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MA, __pyx_k_B_aq_Q_T_q_a_r_xr_V82T_Zccddppq, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[313])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3607, 175}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_fastperiod, __pyx_mstate->__pyx_n_u_slowperiod, __pyx_mstate->__pyx_n_u_signalperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outmacd, __pyx_mstate->__pyx_n_u_outmacdsignal, __pyx_mstate->__pyx_n_u_outmacdhist}; - __pyx_mstate_global->__pyx_codeobj_tab[314] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MACD, __pyx_k_DD_2_aq_Q_T_q_a_A_6_4vXRt_iixxy, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[314])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {7, 0, 0, 15, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3644, 222}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_fastperiod, __pyx_mstate->__pyx_n_u_fastmatype, __pyx_mstate->__pyx_n_u_slowperiod, __pyx_mstate->__pyx_n_u_slowmatype, __pyx_mstate->__pyx_n_u_signalperiod, __pyx_mstate->__pyx_n_u_signalmatype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outmacd, __pyx_mstate->__pyx_n_u_outmacdsignal, __pyx_mstate->__pyx_n_u_outmacdhist}; - __pyx_mstate_global->__pyx_codeobj_tab[315] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MACDEXT, __pyx_k_GGZZr_s_F_F_a_8_aq_Q_T_q_a_A_Bf, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[315])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3684, 148}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_signalperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outmacd, __pyx_mstate->__pyx_n_u_outmacdsignal, __pyx_mstate->__pyx_n_u_outmacdhist}; - __pyx_mstate_global->__pyx_codeobj_tab[316] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MACDFIX, __pyx_k_0_aq_Q_T_q_a_A_BfHBd_lRaabbnnoo, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[316])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3719, 138}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_fastlimit, __pyx_mstate->__pyx_n_u_slowlimit, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outmama, __pyx_mstate->__pyx_n_u_outfama}; - __pyx_mstate_global->__pyx_codeobj_tab[317] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MAMA, __pyx_k_EQ_aq_Q_T_q_a_a_6_4vXRt_gghhttu, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[317])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3752, 157}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_periods, __pyx_mstate->__pyx_n_u_minperiod, __pyx_mstate->__pyx_n_u_maxperiod, __pyx_mstate->__pyx_n_u_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_periods_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[318] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MAVP, __pyx_k_Jaaxxy_aq_Q_k_9G1_6_a_6_4vXRt_j, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[318])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3787, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[319] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MAX, __pyx_k_aq_Q_T_q_a_fHBd_m_hhiixxyyz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[319])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3816, 101}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[320] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MAXINDEX, __pyx_k_01_aq_Q_T_q_RvXRt6_4_S_aammnn_Q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[320])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3845, 116}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[321] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MEDPRICE, __pyx_k_aq_Q_Qa_y_1_6_a_RvXRt6_4_S___kk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[321])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3875, 195}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_volume, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_volume_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[322] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MFI, __pyx_k_aq_Q_Qa_y_1_Kq_q_6_6_gQ_a_fHBd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[322])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3913, 101}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[323] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MIDPOINT, __pyx_k_01_aq_Q_T_q_a_RvXRt6_4_S_aammnn, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[323])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3942, 134}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[324] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MIDPRICE, __pyx_k_JK_aq_Q_Qa_y_1_6_a_RvXRt6_4_S_k, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[324])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 3974, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[325] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MIN, __pyx_k_aq_Q_T_q_a_fHBd_m_hhiixxyyz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[325])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4003, 101}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outinteger}; - __pyx_mstate_global->__pyx_codeobj_tab[326] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MININDEX, __pyx_k_01_aq_Q_T_q_RvXRt6_4_S_aammnn_Q, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[326])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4032, 126}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outmin, __pyx_mstate->__pyx_n_u_outmax}; - __pyx_mstate_global->__pyx_codeobj_tab[327] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MINMAX, __pyx_k_aq_Q_T_q_Q_Q_2V82T_xr_Q___kkll, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[327])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4064, 135}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outminidx, __pyx_mstate->__pyx_n_u_outmaxidx}; - __pyx_mstate_global->__pyx_codeobj_tab[328] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MINMAXINDEX, __pyx_k_34_aq_Q_T_q_fHBd_Vccddppq_r_A_A, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[328])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4096, 165}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[329] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MINUS_DI, __pyx_k_fg_aq_Q_Qa_y_1_Kq_q_6_a_a_RvXRt, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[329])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4131, 134}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[330] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MINUS_DM, __pyx_k_JK_aq_Q_Qa_y_1_6_a_RvXRt6_4_S_k, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[330])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4163, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[331] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MOM, __pyx_k_aq_Q_T_q_a_fHBd_m_hhiixxyyz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[331])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4192, 116}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real0, __pyx_mstate->__pyx_n_u_real1, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real0_data, __pyx_mstate->__pyx_n_u_real1_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[332] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_MULT, __pyx_k_Kq_q_Kq_q_7_a_6_4vXRt_P_jjkkzz, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[332])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4223, 164}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[333] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_NATR, __pyx_k_bc_aq_Q_Qa_y_1_Kq_q_6_a_a_6_4vX, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[333])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4258, 115}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_volume, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_volume_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[334] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_OBV, __pyx_k_aq_Q_6_6_a_fHBd_n_iijjyyzz_Qj_1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[334])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4289, 165}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[335] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_PLUS_DI, __pyx_k_ef_aq_Q_Qa_y_1_Kq_q_6_a_a_BfHBd, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[335])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4324, 134}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[336] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_PLUS_DM, __pyx_k_IJ_aq_Q_Qa_y_1_6_a_BfHBd_lR_jjk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[336])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 10, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4356, 124}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_fastperiod, __pyx_mstate->__pyx_n_u_slowperiod, __pyx_mstate->__pyx_n_u_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[337] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_PPO, __pyx_k_CC_aq_Q_T_q_a_fHBd_m_hhqqrr_O_O, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[337])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4387, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[338] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ROC, __pyx_k_aq_Q_T_q_a_fHBd_m_hhiixxyyz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[338])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4416, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[339] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ROCP, __pyx_k_aq_Q_T_q_a_6_4vXRt_iijjyyzz_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[339])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4445, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[340] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ROCR, __pyx_k_aq_Q_T_q_a_6_4vXRt_iijjyyzz_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[340])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4474, 101}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[341] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ROCR100, __pyx_k_0_aq_Q_T_q_a_BfHBd_lR___llmm_Qn, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[341])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4503, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[342] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_RSI, __pyx_k_aq_Q_T_q_a_fHBd_m_hhiixxyyz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[342])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4532, 143}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_acceleration, __pyx_mstate->__pyx_n_u_maximum, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[343] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_SAR, __pyx_k_E_a_aq_Q_Qa_y_1_6_a_fHBd_kYhhrr, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[343])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {10, 0, 0, 17, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4565, 240}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_startvalue, __pyx_mstate->__pyx_n_u_offsetonreverse, __pyx_mstate->__pyx_n_u_accelerationinitlong, __pyx_mstate->__pyx_n_u_accelerationlong, __pyx_mstate->__pyx_n_u_accelerationmaxlong, __pyx_mstate->__pyx_n_u_accelerationinitshort, __pyx_mstate->__pyx_n_u_accelerationshort, __pyx_mstate->__pyx_n_u_accelerationmaxshort, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[344] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_SAREXT, __pyx_k_Hb_c_B_B_f_f_F_F_i_i_N_N_o_o_p, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[344])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4604, 93}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[345] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_SIN, __pyx_k_aq_Q_T_q_a_fHBd_a_kkllm_Qj_1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[345])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4631, 94}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[346] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_SINH, __pyx_k_aq_Q_T_q_a_6_4vXRt_qP_llmmn_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[346])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4658, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[347] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_SMA, __pyx_k_aq_Q_T_q_a_fHBd_m_hhiixxyyz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[347])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4687, 94}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[348] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_SQRT, __pyx_k_aq_Q_T_q_a_6_4vXRt_qP_llmmn_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[348])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4714, 118}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_nbdev, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[349] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_STDDEV, __pyx_k_Fa_aq_Q_T_q_a_2V82T_xr_Q_ffggss, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[349])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {8, 0, 0, 17, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4744, 246}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_fastk_period, __pyx_mstate->__pyx_n_u_slowk_period, __pyx_mstate->__pyx_n_u_slowk_matype, __pyx_mstate->__pyx_n_u_slowd_period, __pyx_mstate->__pyx_n_u_slowd_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outslowk, __pyx_mstate->__pyx_n_u_outslowd}; - __pyx_mstate_global->__pyx_codeobj_tab[350] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_STOCH, __pyx_k_c_X_X_m_m_G_G_H_6_aq_Q_Qa_y_1_K, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[350])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {6, 0, 0, 15, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4786, 218}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_fastk_period, __pyx_mstate->__pyx_n_u_fastd_period, __pyx_mstate->__pyx_n_u_fastd_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outfastk, __pyx_mstate->__pyx_n_u_outfastd}; - __pyx_mstate_global->__pyx_codeobj_tab[351] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_STOCHF, __pyx_k_d_Y_Y_Z_2_aq_Q_Qa_y_1_Kq_q_6_a, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[351])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {5, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4826, 168}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_fastk_period, __pyx_mstate->__pyx_n_u_fastd_period, __pyx_mstate->__pyx_n_u_fastd_matype, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outfastk, __pyx_mstate->__pyx_n_u_outfastd}; - __pyx_mstate_global->__pyx_codeobj_tab[352] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_STOCHRSI, __pyx_k_0HHbb_0_aq_Q_T_q_q_q_RvXRt6_4_S, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[352])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4861, 115}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real0, __pyx_mstate->__pyx_n_u_real1, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real0_data, __pyx_mstate->__pyx_n_u_real1_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[353] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_SUB, __pyx_k_Kq_q_Kq_q_7_a_fHBd_iijjyyzz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[353])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4892, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[354] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_SUM, __pyx_k_aq_Q_T_q_a_fHBd_m_hhiixxyyz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[354])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4921, 117}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_vfactor, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[355] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_T3, __pyx_k_B_aq_Q_T_q_a_r_xr_V82T_Zddeeqqr, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[355])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4951, 93}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[356] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_TAN, __pyx_k_aq_Q_T_q_a_fHBd_a_kkllm_Qj_1, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[356])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {1, 0, 0, 7, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 4978, 94}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[357] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_TANH, __pyx_k_aq_Q_T_q_a_6_4vXRt_qP_llmmn_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[357])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5005, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[358] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_TEMA, __pyx_k_aq_Q_T_q_a_6_4vXRt_iijjyyzz_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[358])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5034, 151}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[359] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_TRANGE, __pyx_k_aq_Q_Qa_y_1_Kq_q_6_a_a_2V82T_xr, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[359])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5067, 101}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[360] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_TRIMA, __pyx_k_aq_Q_T_q_a_F_D_hb_LP_jjkkzz_Ql, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[360])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5096, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[361] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_TRIX, __pyx_k_aq_Q_T_q_a_6_4vXRt_iijjyyzz_Qk, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[361])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5125, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[362] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_TSF, __pyx_k_aq_Q_T_q_a_fHBd_m_hhiixxyyz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[362])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5154, 151}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[363] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_TYPPRICE, __pyx_k_aq_Q_Qa_y_1_Kq_q_6_a_a_RvXRt6_4, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[363])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {6, 0, 0, 14, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5187, 197}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod1, __pyx_mstate->__pyx_n_u_timeperiod2, __pyx_mstate->__pyx_n_u_timeperiod3, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[364] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_ULTOSC, __pyx_k_d_W_W_X_aq_Q_Qa_y_1_Kq_q_6_a_a, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[364])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 9, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5224, 117}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_nbdev, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[365] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_VAR, __pyx_k_C1_aq_Q_T_q_a_fHBd_m_ccddppq_r, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[365])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {3, 0, 0, 11, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5254, 151}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[366] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_WCLPRICE, __pyx_k_aq_Q_Qa_y_1_Kq_q_6_a_a_RvXRt6_4, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[366])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {4, 0, 0, 12, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5287, 165}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_high, __pyx_mstate->__pyx_n_u_low, __pyx_mstate->__pyx_n_u_close, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_high_data, __pyx_mstate->__pyx_n_u_low_data, __pyx_mstate->__pyx_n_u_close_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[367] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_WILLR, __pyx_k_cd_aq_Q_Qa_y_1_Kq_q_6_a_a_F_D_h, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[367])) goto bad; - } - { - const __Pyx_PyCode_New_function_description descr = {2, 0, 0, 8, (unsigned int)(CO_OPTIMIZED|CO_NEWLOCALS), 5322, 100}; - PyObject* const varnames[] = {__pyx_mstate->__pyx_n_u_real, __pyx_mstate->__pyx_n_u_timeperiod, __pyx_mstate->__pyx_n_u_length, __pyx_mstate->__pyx_n_u_retCode, __pyx_mstate->__pyx_n_u_real_data, __pyx_mstate->__pyx_n_u_outbegidx, __pyx_mstate->__pyx_n_u_outnbelement, __pyx_mstate->__pyx_n_u_outreal}; - __pyx_mstate_global->__pyx_codeobj_tab[368] = __Pyx_PyCode_New(descr, varnames, __pyx_mstate->__pyx_kp_u_talib__stream_pxi, __pyx_mstate->__pyx_n_u_stream_WMA, __pyx_k_aq_Q_T_q_a_fHBd_m_hhiixxyyz_Qj, tuple_dedup_map); if (unlikely(!__pyx_mstate_global->__pyx_codeobj_tab[368])) goto bad; - } - Py_DECREF(tuple_dedup_map); - return 0; - bad: - Py_DECREF(tuple_dedup_map); - return -1; -} -/* #### Code section: init_globals ### */ - -static int __Pyx_InitGlobals(void) { - /* PythonCompatibility.init */ - if (likely(__Pyx_init_co_variables() == 0)); else - -if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 1, __pyx_L1_error) - - /* CachedMethodType.init */ - #if CYTHON_COMPILING_IN_LIMITED_API -{ - PyObject *typesModule=NULL; - typesModule = PyImport_ImportModule("types"); - if (typesModule) { - __pyx_mstate_global->__Pyx_CachedMethodType = PyObject_GetAttrString(typesModule, "MethodType"); - Py_DECREF(typesModule); - } -} // error handling follows -#endif - -if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 1, __pyx_L1_error) - - return 0; - __pyx_L1_error:; - return -1; -} -/* #### Code section: cleanup_globals ### */ -/* #### Code section: cleanup_module ### */ -/* #### Code section: main_method ### */ -/* #### Code section: utility_code_pragmas ### */ -#ifdef _MSC_VER -#pragma warning( push ) -/* Warning 4127: conditional expression is constant - * Cython uses constant conditional expressions to allow in inline functions to be optimized at - * compile-time, so this warning is not useful - */ -#pragma warning( disable : 4127 ) -#endif - - - -/* #### Code section: utility_code_def ### */ - -/* --- Runtime support code --- */ -/* Refnanny */ -#if CYTHON_REFNANNY -static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) { - 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result = __Pyx_PyErr_GivenExceptionMatches(exc_type, err); - } - #if CYTHON_AVOID_BORROWED_REFS - Py_DECREF(exc_type); - #endif - return result; -} -#endif - -/* PyErrFetchRestore */ -#if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { -#if PY_VERSION_HEX >= 0x030C00A6 - PyObject *tmp_value; - assert(type == NULL || (value != NULL && type == (PyObject*) Py_TYPE(value))); - if (value) { - #if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(((PyBaseExceptionObject*) value)->traceback != tb)) - #endif - PyException_SetTraceback(value, tb); - } - tmp_value = tstate->current_exception; - tstate->current_exception = value; - Py_XDECREF(tmp_value); - Py_XDECREF(type); - Py_XDECREF(tb); -#else - PyObject *tmp_type, *tmp_value, *tmp_tb; - tmp_type = tstate->curexc_type; - tmp_value = tstate->curexc_value; - tmp_tb = tstate->curexc_traceback; - tstate->curexc_type = type; - tstate->curexc_value = value; - tstate->curexc_traceback = tb; - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -#endif -} -static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { -#if PY_VERSION_HEX >= 0x030C00A6 - PyObject* exc_value; - exc_value = tstate->current_exception; - tstate->current_exception = 0; - *value = exc_value; - *type = NULL; - *tb = NULL; - if (exc_value) { - *type = (PyObject*) Py_TYPE(exc_value); - Py_INCREF(*type); - #if CYTHON_COMPILING_IN_CPYTHON - *tb = ((PyBaseExceptionObject*) exc_value)->traceback; - Py_XINCREF(*tb); - #else - *tb = PyException_GetTraceback(exc_value); - #endif - } -#else - *type = tstate->curexc_type; - *value = tstate->curexc_value; - *tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; -#endif -} -#endif - -/* PyObjectGetAttrStr */ -#if CYTHON_USE_TYPE_SLOTS -static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) { - PyTypeObject* tp = Py_TYPE(obj); - if (likely(tp->tp_getattro)) - return tp->tp_getattro(obj, attr_name); - return PyObject_GetAttr(obj, attr_name); -} -#endif - -/* PyObjectGetAttrStrNoError */ -#if __PYX_LIMITED_VERSION_HEX < 0x030d0000 -static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) { - __Pyx_PyThreadState_declare - __Pyx_PyThreadState_assign - if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError))) - __Pyx_PyErr_Clear(); -} -#endif -static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) { - PyObject *result; -#if __PYX_LIMITED_VERSION_HEX >= 0x030d0000 - (void) PyObject_GetOptionalAttr(obj, attr_name, &result); - return result; -#else -#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS - PyTypeObject* tp = Py_TYPE(obj); - if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) { - return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1); - } -#endif - result = __Pyx_PyObject_GetAttrStr(obj, attr_name); - if (unlikely(!result)) { - __Pyx_PyObject_GetAttrStr_ClearAttributeError(); - } - return result; -#endif -} - -/* GetBuiltinName */ -static PyObject *__Pyx_GetBuiltinName(PyObject *name) { - PyObject* result = __Pyx_PyObject_GetAttrStrNoError(__pyx_mstate_global->__pyx_b, name); - if (unlikely(!result) && !PyErr_Occurred()) { - PyErr_Format(PyExc_NameError, - "name '%U' is not defined", name); - } - return result; -} - -/* GetTopmostException */ -#if CYTHON_USE_EXC_INFO_STACK && CYTHON_FAST_THREAD_STATE -static _PyErr_StackItem * -__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) -{ - _PyErr_StackItem *exc_info = tstate->exc_info; - while ((exc_info->exc_value == NULL || exc_info->exc_value == Py_None) && - exc_info->previous_item != NULL) - { - exc_info = exc_info->previous_item; - } - return exc_info; -} -#endif - -/* SaveResetException */ -#if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - #if CYTHON_USE_EXC_INFO_STACK && PY_VERSION_HEX >= 0x030B00a4 - _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); - PyObject *exc_value = exc_info->exc_value; - if (exc_value == NULL || exc_value == Py_None) { - *value = NULL; - *type = NULL; - *tb = NULL; - } else { - *value = exc_value; - Py_INCREF(*value); - *type = (PyObject*) Py_TYPE(exc_value); - Py_INCREF(*type); - *tb = PyException_GetTraceback(exc_value); - } - #elif CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); - *type = exc_info->exc_type; - *value = exc_info->exc_value; - *tb = exc_info->exc_traceback; - Py_XINCREF(*type); - Py_XINCREF(*value); - Py_XINCREF(*tb); - #else - *type = tstate->exc_type; - *value = tstate->exc_value; - *tb = tstate->exc_traceback; - Py_XINCREF(*type); - Py_XINCREF(*value); - Py_XINCREF(*tb); - #endif -} -static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { - #if CYTHON_USE_EXC_INFO_STACK && PY_VERSION_HEX >= 0x030B00a4 - _PyErr_StackItem *exc_info = tstate->exc_info; - PyObject *tmp_value = exc_info->exc_value; - exc_info->exc_value = value; - Py_XDECREF(tmp_value); - Py_XDECREF(type); - Py_XDECREF(tb); - #else - PyObject *tmp_type, *tmp_value, *tmp_tb; - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = type; - exc_info->exc_value = value; - exc_info->exc_traceback = tb; - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = type; - tstate->exc_value = value; - tstate->exc_traceback = tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); - #endif -} -#endif - -/* GetException */ -#if CYTHON_FAST_THREAD_STATE -static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) -#else -static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) -#endif -{ - PyObject *local_type = NULL, *local_value, *local_tb = NULL; -#if CYTHON_FAST_THREAD_STATE - PyObject *tmp_type, *tmp_value, *tmp_tb; - #if PY_VERSION_HEX >= 0x030C0000 - local_value = tstate->current_exception; - tstate->current_exception = 0; - #else - local_type = tstate->curexc_type; - local_value = tstate->curexc_value; - local_tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; - #endif -#elif __PYX_LIMITED_VERSION_HEX > 0x030C0000 - local_value = PyErr_GetRaisedException(); -#else - PyErr_Fetch(&local_type, &local_value, &local_tb); -#endif -#if __PYX_LIMITED_VERSION_HEX > 0x030C0000 - if (likely(local_value)) { - local_type = (PyObject*) Py_TYPE(local_value); - Py_INCREF(local_type); - local_tb = PyException_GetTraceback(local_value); - } -#else - PyErr_NormalizeException(&local_type, &local_value, &local_tb); -#if CYTHON_FAST_THREAD_STATE - if (unlikely(tstate->curexc_type)) -#else - if (unlikely(PyErr_Occurred())) -#endif - goto bad; - if (local_tb) { - if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) - goto bad; - } -#endif // __PYX_LIMITED_VERSION_HEX > 0x030C0000 - Py_XINCREF(local_tb); - Py_XINCREF(local_type); - Py_XINCREF(local_value); - *type = local_type; - *value = local_value; - *tb = local_tb; -#if CYTHON_FAST_THREAD_STATE - #if CYTHON_USE_EXC_INFO_STACK - { - _PyErr_StackItem *exc_info = tstate->exc_info; - #if PY_VERSION_HEX >= 0x030B00a4 - tmp_value = exc_info->exc_value; - exc_info->exc_value = local_value; - tmp_type = NULL; - tmp_tb = NULL; - Py_XDECREF(local_type); - Py_XDECREF(local_tb); - #else - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = local_type; - exc_info->exc_value = local_value; - exc_info->exc_traceback = local_tb; - #endif - } - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = local_type; - tstate->exc_value = local_value; - tstate->exc_traceback = local_tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -#elif __PYX_LIMITED_VERSION_HEX >= 0x030b0000 - PyErr_SetHandledException(local_value); - Py_XDECREF(local_value); - Py_XDECREF(local_type); - Py_XDECREF(local_tb); -#else - PyErr_SetExcInfo(local_type, local_value, local_tb); -#endif - return 0; -#if __PYX_LIMITED_VERSION_HEX <= 0x030C0000 -bad: - *type = 0; - *value = 0; - *tb = 0; - Py_XDECREF(local_type); - Py_XDECREF(local_value); - Py_XDECREF(local_tb); - return -1; -#endif -} - -/* PyFunctionFastCall */ -#if CYTHON_FAST_PYCALL && !CYTHON_VECTORCALL -static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject *const *args, Py_ssize_t na, - PyObject *globals) { - PyFrameObject *f; - PyThreadState *tstate = __Pyx_PyThreadState_Current; - PyObject **fastlocals; - Py_ssize_t i; - PyObject *result; - assert(globals != NULL); - /* XXX Perhaps we should create a specialized - PyFrame_New() that doesn't take locals, but does - take builtins without sanity checking them. - */ - assert(tstate != NULL); - f = PyFrame_New(tstate, co, globals, NULL); - if (f == NULL) { - return NULL; - } - fastlocals = __Pyx_PyFrame_GetLocalsplus(f); - for (i = 0; i < na; i++) { - Py_INCREF(*args); - fastlocals[i] = *args++; - } - result = PyEval_EvalFrameEx(f,0); - ++tstate->recursion_depth; - Py_DECREF(f); - --tstate->recursion_depth; - return result; -} -static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject *const *args, Py_ssize_t nargs, PyObject *kwargs) { - PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); - PyObject *globals = PyFunction_GET_GLOBALS(func); - PyObject *argdefs = PyFunction_GET_DEFAULTS(func); - PyObject *closure; - PyObject *kwdefs; - PyObject *kwtuple, **k; - PyObject **d; - Py_ssize_t nd; - Py_ssize_t nk; - PyObject *result; - assert(kwargs == NULL || PyDict_Check(kwargs)); - nk = kwargs ? PyDict_Size(kwargs) : 0; - if (unlikely(Py_EnterRecursiveCall(" while calling a Python object"))) { - return NULL; - } - if ( - co->co_kwonlyargcount == 0 && - likely(kwargs == NULL || nk == 0) && - co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { - if (argdefs == NULL && co->co_argcount == nargs) { - result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); - goto done; - } - else if (nargs == 0 && argdefs != NULL - && co->co_argcount == Py_SIZE(argdefs)) { - /* function called with no arguments, but all parameters have - a default value: use default values as arguments .*/ - args = &PyTuple_GET_ITEM(argdefs, 0); - result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); - goto done; - } - } - if (kwargs != NULL) { - Py_ssize_t pos, i; - kwtuple = PyTuple_New(2 * nk); - if (kwtuple == NULL) { - result = NULL; - goto done; - } - k = &PyTuple_GET_ITEM(kwtuple, 0); - pos = i = 0; - while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { - Py_INCREF(k[i]); - Py_INCREF(k[i+1]); - i += 2; - } - nk = i / 2; - } - else { - kwtuple = NULL; - k = NULL; - } - closure = PyFunction_GET_CLOSURE(func); - kwdefs = PyFunction_GET_KW_DEFAULTS(func); - if (argdefs != NULL) { - d = &PyTuple_GET_ITEM(argdefs, 0); - nd = Py_SIZE(argdefs); - } - else { - d = NULL; - nd = 0; - } - result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, - args, (int)nargs, - k, (int)nk, - d, (int)nd, kwdefs, closure); - Py_XDECREF(kwtuple); -done: - Py_LeaveRecursiveCall(); - return result; -} -#endif - -/* PyObjectCall */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { - PyObject *result; - ternaryfunc call = Py_TYPE(func)->tp_call; - if (unlikely(!call)) - return PyObject_Call(func, arg, kw); - if (unlikely(Py_EnterRecursiveCall(" while calling a Python object"))) - return NULL; - result = (*call)(func, arg, kw); - Py_LeaveRecursiveCall(); - if (unlikely(!result) && unlikely(!PyErr_Occurred())) { - PyErr_SetString( - PyExc_SystemError, - "NULL result without error in PyObject_Call"); - } - return result; -} -#endif - -/* PyObjectCallMethO */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { - PyObject *self, *result; - PyCFunction cfunc; - cfunc = __Pyx_CyOrPyCFunction_GET_FUNCTION(func); - self = __Pyx_CyOrPyCFunction_GET_SELF(func); - if (unlikely(Py_EnterRecursiveCall(" while calling a Python object"))) - return NULL; - result = cfunc(self, arg); - Py_LeaveRecursiveCall(); - if (unlikely(!result) && unlikely(!PyErr_Occurred())) { - PyErr_SetString( - PyExc_SystemError, - "NULL result without error in PyObject_Call"); - } - return result; -} -#endif - -/* PyObjectFastCall */ -#if PY_VERSION_HEX < 0x03090000 || CYTHON_COMPILING_IN_LIMITED_API -static PyObject* __Pyx_PyObject_FastCall_fallback(PyObject *func, PyObject * const*args, size_t nargs, PyObject *kwargs) { - PyObject *argstuple; - PyObject *result = 0; - size_t i; - argstuple = PyTuple_New((Py_ssize_t)nargs); - if (unlikely(!argstuple)) return NULL; - for (i = 0; i < nargs; i++) { - Py_INCREF(args[i]); - if (__Pyx_PyTuple_SET_ITEM(argstuple, (Py_ssize_t)i, args[i]) != (0)) goto bad; - } - result = __Pyx_PyObject_Call(func, argstuple, kwargs); - bad: - Py_DECREF(argstuple); - return result; -} -#endif -#if CYTHON_VECTORCALL && !CYTHON_COMPILING_IN_LIMITED_API - #if PY_VERSION_HEX < 0x03090000 - #define __Pyx_PyVectorcall_Function(callable) _PyVectorcall_Function(callable) - #elif CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE vectorcallfunc __Pyx_PyVectorcall_Function(PyObject *callable) { - PyTypeObject *tp = Py_TYPE(callable); - #if defined(__Pyx_CyFunction_USED) - if (__Pyx_CyFunction_CheckExact(callable)) { - return __Pyx_CyFunction_func_vectorcall(callable); - } - #endif - if (!PyType_HasFeature(tp, Py_TPFLAGS_HAVE_VECTORCALL)) { - return NULL; - } - assert(PyCallable_Check(callable)); - Py_ssize_t offset = tp->tp_vectorcall_offset; - assert(offset > 0); - vectorcallfunc ptr; - memcpy(&ptr, (char *) callable + offset, sizeof(ptr)); - return ptr; -} - #else - #define __Pyx_PyVectorcall_Function(callable) PyVectorcall_Function(callable) - #endif -#endif -static CYTHON_INLINE PyObject* __Pyx_PyObject_FastCallDict(PyObject *func, PyObject *const *args, size_t _nargs, PyObject *kwargs) { - Py_ssize_t nargs = __Pyx_PyVectorcall_NARGS(_nargs); -#if CYTHON_COMPILING_IN_CPYTHON - if (nargs == 0 && kwargs == NULL) { - if (__Pyx_CyOrPyCFunction_Check(func) && likely( __Pyx_CyOrPyCFunction_GET_FLAGS(func) & METH_NOARGS)) - return __Pyx_PyObject_CallMethO(func, NULL); - } - else if (nargs == 1 && kwargs == NULL) { - if (__Pyx_CyOrPyCFunction_Check(func) && likely( __Pyx_CyOrPyCFunction_GET_FLAGS(func) & METH_O)) - return __Pyx_PyObject_CallMethO(func, args[0]); - } -#endif - #if PY_VERSION_HEX < 0x030800B1 - #if CYTHON_FAST_PYCCALL - if (PyCFunction_Check(func)) { - if (kwargs) { - return _PyCFunction_FastCallDict(func, args, nargs, kwargs); - } else { - return _PyCFunction_FastCallKeywords(func, args, nargs, NULL); - } - } - if (!kwargs && __Pyx_IS_TYPE(func, &PyMethodDescr_Type)) { - return _PyMethodDescr_FastCallKeywords(func, args, nargs, NULL); - } - #endif - #if CYTHON_FAST_PYCALL - if (PyFunction_Check(func)) { - return __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs); - } - #endif - #endif - if (kwargs == NULL) { - #if CYTHON_VECTORCALL && !CYTHON_COMPILING_IN_LIMITED_API - vectorcallfunc f = __Pyx_PyVectorcall_Function(func); - if (f) { - return f(func, args, _nargs, NULL); - } - #elif defined(__Pyx_CyFunction_USED) && CYTHON_BACKPORT_VECTORCALL - if (__Pyx_CyFunction_CheckExact(func)) { - __pyx_vectorcallfunc f = __Pyx_CyFunction_func_vectorcall(func); - if (f) return f(func, args, _nargs, NULL); - } - #elif CYTHON_COMPILING_IN_LIMITED_API && CYTHON_VECTORCALL - return PyObject_Vectorcall(func, args, _nargs, NULL); - #endif - } - if (nargs == 0) { - return __Pyx_PyObject_Call(func, __pyx_mstate_global->__pyx_empty_tuple, kwargs); - } - #if PY_VERSION_HEX >= 0x03090000 && !CYTHON_COMPILING_IN_LIMITED_API - return PyObject_VectorcallDict(func, args, (size_t)nargs, kwargs); - #else - return __Pyx_PyObject_FastCall_fallback(func, args, (size_t)nargs, kwargs); - #endif -} - -/* RaiseException */ -static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { - PyObject* owned_instance = NULL; - if (tb == Py_None) { - tb = 0; - } else if (tb && !PyTraceBack_Check(tb)) { - PyErr_SetString(PyExc_TypeError, - "raise: arg 3 must be a traceback or None"); - goto bad; - } - if (value == Py_None) - value = 0; - if (PyExceptionInstance_Check(type)) { - if (value) { - PyErr_SetString(PyExc_TypeError, - "instance exception may not have a separate value"); - goto bad; - } - value = type; - type = (PyObject*) Py_TYPE(value); - } else if (PyExceptionClass_Check(type)) { - PyObject *instance_class = NULL; - if (value && PyExceptionInstance_Check(value)) { - instance_class = (PyObject*) Py_TYPE(value); - if (instance_class != type) { - int is_subclass = PyObject_IsSubclass(instance_class, type); - if (!is_subclass) { - instance_class = NULL; - } else if (unlikely(is_subclass == -1)) { - goto bad; - } else { - type = instance_class; - } - } - } - if (!instance_class) { - PyObject *args; - if (!value) - args = PyTuple_New(0); - else if (PyTuple_Check(value)) { - Py_INCREF(value); - args = value; - } else - args = PyTuple_Pack(1, value); - if (!args) - goto bad; - owned_instance = PyObject_Call(type, args, NULL); - Py_DECREF(args); - if (!owned_instance) - goto bad; - value = owned_instance; - if (!PyExceptionInstance_Check(value)) { - PyErr_Format(PyExc_TypeError, - "calling %R should have returned an instance of " - "BaseException, not %R", - type, Py_TYPE(value)); - goto bad; - } - } - } else { - PyErr_SetString(PyExc_TypeError, - "raise: exception class must be a subclass of BaseException"); - goto bad; - } - if (cause) { - PyObject *fixed_cause; - if (cause == Py_None) { - fixed_cause = NULL; - } else if (PyExceptionClass_Check(cause)) { - fixed_cause = PyObject_CallObject(cause, NULL); - if (fixed_cause == NULL) - goto bad; - } else if (PyExceptionInstance_Check(cause)) { - fixed_cause = cause; - Py_INCREF(fixed_cause); - } else { - PyErr_SetString(PyExc_TypeError, - "exception causes must derive from " - "BaseException"); - goto bad; - } - PyException_SetCause(value, fixed_cause); - } - PyErr_SetObject(type, value); - if (tb) { -#if PY_VERSION_HEX >= 0x030C00A6 - PyException_SetTraceback(value, tb); -#elif CYTHON_FAST_THREAD_STATE - PyThreadState *tstate = __Pyx_PyThreadState_Current; - PyObject* tmp_tb = tstate->curexc_traceback; - if (tb != tmp_tb) { - Py_INCREF(tb); - tstate->curexc_traceback = tb; - Py_XDECREF(tmp_tb); - } -#else - PyObject *tmp_type, *tmp_value, *tmp_tb; - PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); - Py_INCREF(tb); - PyErr_Restore(tmp_type, tmp_value, tb); - Py_XDECREF(tmp_tb); -#endif - } -bad: - Py_XDECREF(owned_instance); - return; -} - -/* PyUnicode_Unicode */ -static CYTHON_INLINE PyObject* __Pyx_PyUnicode_Unicode(PyObject *obj) { - if (unlikely(obj == Py_None)) - obj = __pyx_mstate_global->__pyx_kp_u_None; - return __Pyx_NewRef(obj); -} - -/* PyObjectFormatAndDecref */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_FormatSimpleAndDecref(PyObject* s, PyObject* f) { - if (unlikely(!s)) return NULL; - if (likely(PyUnicode_CheckExact(s))) return s; - return __Pyx_PyObject_FormatAndDecref(s, f); -} -static CYTHON_INLINE PyObject* __Pyx_PyObject_FormatAndDecref(PyObject* s, PyObject* f) { - PyObject *result; - if (unlikely(!s)) return NULL; - result = PyObject_Format(s, f); - Py_DECREF(s); - return result; -} - -/* JoinPyUnicode */ -static PyObject* __Pyx_PyUnicode_Join(PyObject** values, Py_ssize_t value_count, Py_ssize_t result_ulength, - Py_UCS4 max_char) { -#if CYTHON_USE_UNICODE_INTERNALS && CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS - PyObject *result_uval; - int result_ukind, kind_shift; - Py_ssize_t i, char_pos; - void *result_udata; - if (max_char > 1114111) max_char = 1114111; - result_uval = PyUnicode_New(result_ulength, max_char); - if (unlikely(!result_uval)) return NULL; - result_ukind = (max_char <= 255) ? PyUnicode_1BYTE_KIND : (max_char <= 65535) ? PyUnicode_2BYTE_KIND : PyUnicode_4BYTE_KIND; - kind_shift = (result_ukind == PyUnicode_4BYTE_KIND) ? 2 : result_ukind - 1; - result_udata = PyUnicode_DATA(result_uval); - assert(kind_shift == 2 || kind_shift == 1 || kind_shift == 0); - if (unlikely((PY_SSIZE_T_MAX >> kind_shift) - result_ulength < 0)) - goto overflow; - char_pos = 0; - for (i=0; i < value_count; i++) { - int ukind; - Py_ssize_t ulength; - void *udata; - PyObject *uval = values[i]; - #if !CYTHON_COMPILING_IN_LIMITED_API - if (__Pyx_PyUnicode_READY(uval) == (-1)) - goto bad; - #endif - ulength = __Pyx_PyUnicode_GET_LENGTH(uval); - #if !CYTHON_ASSUME_SAFE_SIZE - if (unlikely(ulength < 0)) goto bad; - #endif - if (unlikely(!ulength)) - continue; - if (unlikely((PY_SSIZE_T_MAX >> kind_shift) - ulength < char_pos)) - goto overflow; - ukind = __Pyx_PyUnicode_KIND(uval); - udata = __Pyx_PyUnicode_DATA(uval); - if (ukind == result_ukind) { - memcpy((char *)result_udata + (char_pos << kind_shift), udata, (size_t) (ulength << kind_shift)); - } else { - #if PY_VERSION_HEX >= 0x030d0000 - if (unlikely(PyUnicode_CopyCharacters(result_uval, char_pos, uval, 0, ulength) < 0)) goto bad; - #elif CYTHON_COMPILING_IN_CPYTHON || defined(_PyUnicode_FastCopyCharacters) - _PyUnicode_FastCopyCharacters(result_uval, char_pos, uval, 0, ulength); - #else - Py_ssize_t j; - for (j=0; j < ulength; j++) { - Py_UCS4 uchar = __Pyx_PyUnicode_READ(ukind, udata, j); - __Pyx_PyUnicode_WRITE(result_ukind, result_udata, char_pos+j, uchar); - } - #endif - } - char_pos += ulength; - } - return result_uval; -overflow: - PyErr_SetString(PyExc_OverflowError, "join() result is too long for a Python string"); -bad: - Py_DECREF(result_uval); - return NULL; -#else - Py_ssize_t i; - PyObject *result = NULL; - PyObject *value_tuple = PyTuple_New(value_count); - if (unlikely(!value_tuple)) return NULL; - CYTHON_UNUSED_VAR(max_char); - CYTHON_UNUSED_VAR(result_ulength); - for (i=0; i__pyx_empty_unicode, value_tuple); -bad: - Py_DECREF(value_tuple); - return result; -#endif -} - -/* TupleAndListFromArray */ -#if !CYTHON_COMPILING_IN_CPYTHON && CYTHON_METH_FASTCALL -static CYTHON_INLINE PyObject * -__Pyx_PyTuple_FromArray(PyObject *const *src, Py_ssize_t n) -{ - PyObject *res; - Py_ssize_t i; - if (n <= 0) { - return __Pyx_NewRef(__pyx_mstate_global->__pyx_empty_tuple); - } - res = PyTuple_New(n); - if (unlikely(res == NULL)) return NULL; - for (i = 0; i < n; i++) { - if (unlikely(__Pyx_PyTuple_SET_ITEM(res, i, src[i]) < 0)) { - Py_DECREF(res); - return NULL; - } - Py_INCREF(src[i]); - } - return res; -} -#elif CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE void __Pyx_copy_object_array(PyObject *const *CYTHON_RESTRICT src, PyObject** CYTHON_RESTRICT dest, Py_ssize_t length) { - PyObject *v; - Py_ssize_t i; - for (i = 0; i < length; i++) { - v = dest[i] = src[i]; - Py_INCREF(v); - } -} -static CYTHON_INLINE PyObject * -__Pyx_PyTuple_FromArray(PyObject *const *src, Py_ssize_t n) -{ - PyObject *res; - if (n <= 0) { - return __Pyx_NewRef(__pyx_mstate_global->__pyx_empty_tuple); - } - res = PyTuple_New(n); - if (unlikely(res == NULL)) return NULL; - __Pyx_copy_object_array(src, ((PyTupleObject*)res)->ob_item, n); - return res; -} -static CYTHON_INLINE PyObject * -__Pyx_PyList_FromArray(PyObject *const *src, Py_ssize_t n) -{ - PyObject *res; - if (n <= 0) { - return PyList_New(0); - } - res = PyList_New(n); - if (unlikely(res == NULL)) return NULL; - __Pyx_copy_object_array(src, ((PyListObject*)res)->ob_item, n); - return res; -} -#endif - -/* BytesEquals */ -static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { -#if CYTHON_COMPILING_IN_PYPY || CYTHON_COMPILING_IN_LIMITED_API || CYTHON_COMPILING_IN_GRAAL ||\ - !(CYTHON_ASSUME_SAFE_SIZE && CYTHON_ASSUME_SAFE_MACROS) - return PyObject_RichCompareBool(s1, s2, equals); -#else - if (s1 == s2) { - return (equals == Py_EQ); - } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { - const char *ps1, *ps2; - Py_ssize_t length = PyBytes_GET_SIZE(s1); - if (length != PyBytes_GET_SIZE(s2)) - return (equals == Py_NE); - ps1 = PyBytes_AS_STRING(s1); - ps2 = PyBytes_AS_STRING(s2); - if (ps1[0] != ps2[0]) { - return (equals == Py_NE); - } else if (length == 1) { - return (equals == Py_EQ); - } else { - int result; -#if CYTHON_USE_UNICODE_INTERNALS && (PY_VERSION_HEX < 0x030B0000) - Py_hash_t hash1, hash2; - hash1 = ((PyBytesObject*)s1)->ob_shash; - hash2 = ((PyBytesObject*)s2)->ob_shash; - if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { - return (equals == Py_NE); - } -#endif - result = memcmp(ps1, ps2, (size_t)length); - return (equals == Py_EQ) ? (result == 0) : (result != 0); - } - } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { - return (equals == Py_NE); - } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { - return (equals == Py_NE); - } else { - int result; - PyObject* py_result = PyObject_RichCompare(s1, s2, equals); - if (!py_result) - return -1; - result = __Pyx_PyObject_IsTrue(py_result); - Py_DECREF(py_result); - return result; - } -#endif -} - -/* UnicodeEquals */ -static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { -#if CYTHON_COMPILING_IN_PYPY || CYTHON_COMPILING_IN_LIMITED_API || CYTHON_COMPILING_IN_GRAAL - return PyObject_RichCompareBool(s1, s2, equals); -#else - int s1_is_unicode, s2_is_unicode; - if (s1 == s2) { - goto return_eq; - } - s1_is_unicode = PyUnicode_CheckExact(s1); - s2_is_unicode = PyUnicode_CheckExact(s2); - if (s1_is_unicode & s2_is_unicode) { - Py_ssize_t length, length2; - int kind; - void *data1, *data2; - #if !CYTHON_COMPILING_IN_LIMITED_API - if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) - return -1; - #endif - length = __Pyx_PyUnicode_GET_LENGTH(s1); - #if !CYTHON_ASSUME_SAFE_SIZE - if (unlikely(length < 0)) return -1; - #endif - length2 = __Pyx_PyUnicode_GET_LENGTH(s2); - #if !CYTHON_ASSUME_SAFE_SIZE - if (unlikely(length2 < 0)) return -1; - #endif - if (length != length2) { - goto return_ne; - } -#if CYTHON_USE_UNICODE_INTERNALS - { - Py_hash_t hash1, hash2; - hash1 = ((PyASCIIObject*)s1)->hash; - hash2 = ((PyASCIIObject*)s2)->hash; - if (hash1 != hash2 && hash1 != -1 && hash2 != -1) { - goto return_ne; - } - } -#endif - kind = __Pyx_PyUnicode_KIND(s1); - if (kind != __Pyx_PyUnicode_KIND(s2)) { - goto return_ne; - } - data1 = __Pyx_PyUnicode_DATA(s1); - data2 = __Pyx_PyUnicode_DATA(s2); - if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { - goto return_ne; - } else if (length == 1) { - goto return_eq; - } else { - int result = memcmp(data1, data2, (size_t)(length * kind)); - return (equals == Py_EQ) ? (result == 0) : (result != 0); - } - } else if ((s1 == Py_None) & s2_is_unicode) { - goto return_ne; - } else if ((s2 == Py_None) & s1_is_unicode) { - goto return_ne; - } else { - int result; - PyObject* py_result = PyObject_RichCompare(s1, s2, equals); - if (!py_result) - return -1; - result = __Pyx_PyObject_IsTrue(py_result); - Py_DECREF(py_result); - return result; - } -return_eq: - return (equals == Py_EQ); -return_ne: - return (equals == Py_NE); -#endif -} - -/* fastcall */ -#if CYTHON_METH_FASTCALL -static CYTHON_INLINE PyObject * __Pyx_GetKwValue_FASTCALL(PyObject *kwnames, PyObject *const *kwvalues, PyObject *s) -{ - Py_ssize_t i, n = __Pyx_PyTuple_GET_SIZE(kwnames); - #if !CYTHON_ASSUME_SAFE_SIZE - if (unlikely(n == -1)) return NULL; - #endif - for (i = 0; i < n; i++) - { - PyObject *namei = __Pyx_PyTuple_GET_ITEM(kwnames, i); - #if !CYTHON_ASSUME_SAFE_MACROS - if (unlikely(!namei)) return NULL; - #endif - if (s == namei) return kwvalues[i]; - } - for (i = 0; i < n; i++) - { - PyObject *namei = __Pyx_PyTuple_GET_ITEM(kwnames, i); - #if !CYTHON_ASSUME_SAFE_MACROS - if (unlikely(!namei)) return NULL; - #endif - int eq = __Pyx_PyUnicode_Equals(s, namei, Py_EQ); - if (unlikely(eq != 0)) { - if (unlikely(eq < 0)) return NULL; - return kwvalues[i]; - } - } - return NULL; -} -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030d0000 || CYTHON_COMPILING_IN_LIMITED_API -CYTHON_UNUSED static PyObject *__Pyx_KwargsAsDict_FASTCALL(PyObject *kwnames, PyObject *const *kwvalues) { - Py_ssize_t i, nkwargs; - PyObject *dict; -#if !CYTHON_ASSUME_SAFE_SIZE - nkwargs = PyTuple_Size(kwnames); - if (unlikely(nkwargs < 0)) return NULL; -#else - nkwargs = PyTuple_GET_SIZE(kwnames); -#endif - dict = PyDict_New(); - if (unlikely(!dict)) - return NULL; - for (i=0; itype, *target->method_name); - if (unlikely(!method)) - return -1; - result = method; -#if CYTHON_COMPILING_IN_CPYTHON - if (likely(__Pyx_TypeCheck(method, &PyMethodDescr_Type))) - { - PyMethodDescrObject *descr = (PyMethodDescrObject*) method; - target->func = descr->d_method->ml_meth; - target->flag = descr->d_method->ml_flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_STACKLESS); - } else -#endif -#if CYTHON_COMPILING_IN_PYPY -#else - if (PyCFunction_Check(method)) -#endif - { - PyObject *self; - int self_found; -#if CYTHON_COMPILING_IN_LIMITED_API || CYTHON_COMPILING_IN_PYPY - self = PyObject_GetAttrString(method, "__self__"); - if (!self) { - PyErr_Clear(); - } -#else - self = PyCFunction_GET_SELF(method); -#endif - self_found = (self && self != Py_None); -#if CYTHON_COMPILING_IN_LIMITED_API || CYTHON_COMPILING_IN_PYPY - Py_XDECREF(self); -#endif - if (self_found) { - PyObject *unbound_method = PyCFunction_New(&__Pyx_UnboundCMethod_Def, method); - if (unlikely(!unbound_method)) return -1; - Py_DECREF(method); - result = unbound_method; - } - } -#if !CYTHON_COMPILING_IN_CPYTHON_FREETHREADING - if (unlikely(target->method)) { - Py_DECREF(result); - } else -#endif - target->method = result; - return 0; -} - -/* CallUnboundCMethod2 */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject *__Pyx_CallUnboundCMethod2(__Pyx_CachedCFunction *cfunc, PyObject *self, PyObject *arg1, PyObject *arg2) { - int was_initialized = __Pyx_CachedCFunction_GetAndSetInitializing(cfunc); - if (likely(was_initialized == 2 && cfunc->func)) { - PyObject *args[2] = {arg1, arg2}; - if (cfunc->flag == METH_FASTCALL) { - return __Pyx_CallCFunctionFast(cfunc, self, args, 2); - } - if (cfunc->flag == (METH_FASTCALL | METH_KEYWORDS)) - return __Pyx_CallCFunctionFastWithKeywords(cfunc, self, args, 2, NULL); - } -#if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING - else if (unlikely(was_initialized == 1)) { - __Pyx_CachedCFunction tmp_cfunc = { -#ifndef __cplusplus - 0 -#endif - }; - tmp_cfunc.type = cfunc->type; - tmp_cfunc.method_name = cfunc->method_name; - return __Pyx__CallUnboundCMethod2(&tmp_cfunc, self, arg1, arg2); - } -#endif - PyObject *result = __Pyx__CallUnboundCMethod2(cfunc, self, arg1, arg2); - __Pyx_CachedCFunction_SetFinishedInitializing(cfunc); - return result; -} -#endif -static PyObject* __Pyx__CallUnboundCMethod2(__Pyx_CachedCFunction* cfunc, PyObject* self, PyObject* arg1, PyObject* arg2){ - if (unlikely(!cfunc->func && !cfunc->method) && unlikely(__Pyx_TryUnpackUnboundCMethod(cfunc) < 0)) return NULL; -#if CYTHON_COMPILING_IN_CPYTHON - if (cfunc->func && (cfunc->flag & METH_VARARGS)) { - PyObject *result = NULL; - PyObject *args = PyTuple_New(2); - if (unlikely(!args)) return NULL; - Py_INCREF(arg1); - PyTuple_SET_ITEM(args, 0, arg1); - Py_INCREF(arg2); - PyTuple_SET_ITEM(args, 1, arg2); - if (cfunc->flag & METH_KEYWORDS) - result = __Pyx_CallCFunctionWithKeywords(cfunc, self, args, NULL); - else - result = __Pyx_CallCFunction(cfunc, self, args); - Py_DECREF(args); - return result; - } -#endif - { - PyObject *args[4] = {NULL, self, arg1, arg2}; - return __Pyx_PyObject_FastCall(cfunc->method, args+1, 3 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET); - } -} - -/* ParseKeywords */ -static int __Pyx_ValidateDuplicatePosArgs( - PyObject *kwds, - PyObject ** const argnames[], - PyObject ** const *first_kw_arg, - const char* function_name) -{ - PyObject ** const *name = argnames; - while (name != first_kw_arg) { - PyObject *key = **name; - int found = PyDict_Contains(kwds, key); - if (unlikely(found)) { - if (found == 1) __Pyx_RaiseDoubleKeywordsError(function_name, key); - goto bad; - } - name++; - } - return 0; -bad: - return -1; -} -#if CYTHON_USE_UNICODE_INTERNALS -static CYTHON_INLINE int __Pyx_UnicodeKeywordsEqual(PyObject *s1, PyObject *s2) { - int kind; - Py_ssize_t len = PyUnicode_GET_LENGTH(s1); - if (len != PyUnicode_GET_LENGTH(s2)) return 0; - kind = PyUnicode_KIND(s1); - if (kind != PyUnicode_KIND(s2)) return 0; - const void *data1 = PyUnicode_DATA(s1); - const void *data2 = PyUnicode_DATA(s2); - return (memcmp(data1, data2, (size_t) len * (size_t) kind) == 0); -} -#endif -static int __Pyx_MatchKeywordArg_str( - PyObject *key, - PyObject ** const argnames[], - PyObject ** const *first_kw_arg, - size_t *index_found, - const char *function_name) -{ - PyObject ** const *name; - #if CYTHON_USE_UNICODE_INTERNALS - Py_hash_t key_hash = ((PyASCIIObject*)key)->hash; - if (unlikely(key_hash == -1)) { - key_hash = PyObject_Hash(key); - if (unlikely(key_hash == -1)) - goto bad; - } - #endif - name = first_kw_arg; - while (*name) { - PyObject *name_str = **name; - #if CYTHON_USE_UNICODE_INTERNALS - if (key_hash == ((PyASCIIObject*)name_str)->hash && __Pyx_UnicodeKeywordsEqual(name_str, key)) { - *index_found = (size_t) (name - argnames); - return 1; - } - #else - #if CYTHON_ASSUME_SAFE_SIZE - if (PyUnicode_GET_LENGTH(name_str) == PyUnicode_GET_LENGTH(key)) - #endif - { - int cmp = PyUnicode_Compare(name_str, key); - if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; - if (cmp == 0) { - *index_found = (size_t) (name - argnames); - return 1; - } - } - #endif - name++; - } - name = argnames; - while (name != first_kw_arg) { - PyObject *name_str = **name; - #if CYTHON_USE_UNICODE_INTERNALS - if (unlikely(key_hash == ((PyASCIIObject*)name_str)->hash)) { - if (__Pyx_UnicodeKeywordsEqual(name_str, key)) - goto arg_passed_twice; - } - #else - #if CYTHON_ASSUME_SAFE_SIZE - if (PyUnicode_GET_LENGTH(name_str) == PyUnicode_GET_LENGTH(key)) - #endif - { - if (unlikely(name_str == key)) goto arg_passed_twice; - int cmp = PyUnicode_Compare(name_str, key); - if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; - if (cmp == 0) goto arg_passed_twice; - } - #endif - name++; - } - return 0; -arg_passed_twice: - __Pyx_RaiseDoubleKeywordsError(function_name, key); - goto bad; -bad: - return -1; -} -static int __Pyx_MatchKeywordArg_nostr( - PyObject *key, - PyObject ** const argnames[], - PyObject ** const *first_kw_arg, - size_t *index_found, - const char *function_name) -{ - PyObject ** const *name; - if (unlikely(!PyUnicode_Check(key))) goto invalid_keyword_type; - name = first_kw_arg; - while (*name) { - int cmp = PyObject_RichCompareBool(**name, key, Py_EQ); - if (cmp == 1) { - *index_found = (size_t) (name - argnames); - return 1; - } - if (unlikely(cmp == -1)) goto bad; - name++; - } - name = argnames; - while (name != first_kw_arg) { - int cmp = PyObject_RichCompareBool(**name, key, Py_EQ); - if (unlikely(cmp != 0)) { - if (cmp == 1) goto arg_passed_twice; - else goto bad; - } - name++; - } - return 0; -arg_passed_twice: - __Pyx_RaiseDoubleKeywordsError(function_name, key); - goto bad; -invalid_keyword_type: - PyErr_Format(PyExc_TypeError, - "%.200s() keywords must be strings", function_name); - goto bad; -bad: - return -1; -} -static CYTHON_INLINE int __Pyx_MatchKeywordArg( - PyObject *key, - PyObject ** const argnames[], - PyObject ** const *first_kw_arg, - size_t *index_found, - const char *function_name) -{ - return likely(PyUnicode_CheckExact(key)) ? - __Pyx_MatchKeywordArg_str(key, argnames, first_kw_arg, index_found, function_name) : - __Pyx_MatchKeywordArg_nostr(key, argnames, first_kw_arg, index_found, function_name); -} -static void __Pyx_RejectUnknownKeyword( - PyObject *kwds, - PyObject ** const argnames[], - PyObject ** const *first_kw_arg, - const char *function_name) -{ - Py_ssize_t pos = 0; - PyObject *key = NULL; - __Pyx_BEGIN_CRITICAL_SECTION(kwds); - while (PyDict_Next(kwds, &pos, &key, NULL)) { - PyObject** const *name = first_kw_arg; - while (*name && (**name != key)) name++; - if (!*name) { - #if CYTHON_AVOID_BORROWED_REFS - Py_INCREF(key); - #endif - size_t index_found = 0; - int cmp = __Pyx_MatchKeywordArg(key, argnames, first_kw_arg, &index_found, function_name); - if (cmp != 1) { - if (cmp == 0) { - PyErr_Format(PyExc_TypeError, - "%s() got an unexpected keyword argument '%U'", - function_name, key); - } - #if CYTHON_AVOID_BORROWED_REFS - Py_DECREF(key); - #endif - break; - } - #if CYTHON_AVOID_BORROWED_REFS - Py_DECREF(key); - #endif - } - } - __Pyx_END_CRITICAL_SECTION(); - assert(PyErr_Occurred()); -} -static int __Pyx_ParseKeywordDict( - PyObject *kwds, - PyObject ** const argnames[], - PyObject *values[], - Py_ssize_t num_pos_args, - Py_ssize_t num_kwargs, - const char* function_name, - int ignore_unknown_kwargs) -{ - PyObject** const *name; - PyObject** const *first_kw_arg = argnames + num_pos_args; - Py_ssize_t extracted = 0; -#if !CYTHON_COMPILING_IN_PYPY || defined(PyArg_ValidateKeywordArguments) - if (unlikely(!PyArg_ValidateKeywordArguments(kwds))) return -1; -#endif - name = first_kw_arg; - while (*name && num_kwargs > extracted) { - PyObject * key = **name; - PyObject *value; - int found = 0; - #if __PYX_LIMITED_VERSION_HEX >= 0x030d0000 - found = PyDict_GetItemRef(kwds, key, &value); - #else - value = PyDict_GetItemWithError(kwds, key); - if (value) { - Py_INCREF(value); - found = 1; - } else { - if (unlikely(PyErr_Occurred())) goto bad; - } - #endif - if (found) { - if (unlikely(found < 0)) goto bad; - values[name-argnames] = value; - extracted++; - } - name++; - } - if (num_kwargs > extracted) { - if (ignore_unknown_kwargs) { - if (unlikely(__Pyx_ValidateDuplicatePosArgs(kwds, argnames, first_kw_arg, function_name) == -1)) - goto bad; - } else { - __Pyx_RejectUnknownKeyword(kwds, argnames, first_kw_arg, function_name); - goto bad; - } - } - return 0; -bad: - return -1; -} -static int __Pyx_ParseKeywordDictToDict( - PyObject *kwds, - PyObject ** const argnames[], - PyObject *kwds2, - PyObject *values[], - Py_ssize_t num_pos_args, - const char* function_name) -{ - PyObject** const *name; - PyObject** const *first_kw_arg = argnames + num_pos_args; - Py_ssize_t len; -#if !CYTHON_COMPILING_IN_PYPY || defined(PyArg_ValidateKeywordArguments) - if (unlikely(!PyArg_ValidateKeywordArguments(kwds))) return -1; -#endif - if (PyDict_Update(kwds2, kwds) < 0) goto bad; - name = first_kw_arg; - while (*name) { - PyObject *key = **name; - PyObject *value; -#if !CYTHON_COMPILING_IN_LIMITED_API && (PY_VERSION_HEX >= 0x030d00A2 || defined(PyDict_Pop)) - int found = PyDict_Pop(kwds2, key, &value); - if (found) { - if (unlikely(found < 0)) goto bad; - values[name-argnames] = value; - } -#elif __PYX_LIMITED_VERSION_HEX >= 0x030d0000 - int found = PyDict_GetItemRef(kwds2, key, &value); - if (found) { - if (unlikely(found < 0)) goto bad; - values[name-argnames] = value; - if (unlikely(PyDict_DelItem(kwds2, key) < 0)) goto bad; - } -#else - #if CYTHON_COMPILING_IN_CPYTHON - value = _PyDict_Pop(kwds2, key, kwds2); - #else - value = __Pyx_CallUnboundCMethod2(&__pyx_mstate_global->__pyx_umethod_PyDict_Type_pop, kwds2, key, kwds2); - #endif - if (value == kwds2) { - Py_DECREF(value); - } else { - if (unlikely(!value)) goto bad; - values[name-argnames] = value; - } -#endif - name++; - } - len = PyDict_Size(kwds2); - if (len > 0) { - return __Pyx_ValidateDuplicatePosArgs(kwds, argnames, first_kw_arg, function_name); - } else if (unlikely(len == -1)) { - goto bad; - } - return 0; -bad: - return -1; -} -static int __Pyx_ParseKeywordsTuple( - PyObject *kwds, - PyObject * const *kwvalues, - PyObject ** const argnames[], - PyObject *kwds2, - PyObject *values[], - Py_ssize_t num_pos_args, - Py_ssize_t num_kwargs, - const char* function_name, - int ignore_unknown_kwargs) -{ - PyObject *key = NULL; - PyObject** const * name; - PyObject** const *first_kw_arg = argnames + num_pos_args; - for (Py_ssize_t pos = 0; pos < num_kwargs; pos++) { -#if CYTHON_AVOID_BORROWED_REFS - key = __Pyx_PySequence_ITEM(kwds, pos); -#else - key = __Pyx_PyTuple_GET_ITEM(kwds, pos); -#endif -#if !CYTHON_ASSUME_SAFE_MACROS - if (unlikely(!key)) goto bad; -#endif - name = first_kw_arg; - while (*name && (**name != key)) name++; - if (*name) { - PyObject *value = kwvalues[pos]; - values[name-argnames] = __Pyx_NewRef(value); - } else { - size_t index_found = 0; - int cmp = __Pyx_MatchKeywordArg(key, argnames, first_kw_arg, &index_found, function_name); - if (cmp == 1) { - PyObject *value = kwvalues[pos]; - values[index_found] = __Pyx_NewRef(value); - } else { - if (unlikely(cmp == -1)) goto bad; - if (kwds2) { - PyObject *value = kwvalues[pos]; - if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; - } else if (!ignore_unknown_kwargs) { - goto invalid_keyword; - } - } - } - #if CYTHON_AVOID_BORROWED_REFS - Py_DECREF(key); - key = NULL; - #endif - } - return 0; -invalid_keyword: - PyErr_Format(PyExc_TypeError, - "%s() got an unexpected keyword argument '%U'", - function_name, key); - goto bad; -bad: - #if CYTHON_AVOID_BORROWED_REFS - Py_XDECREF(key); - #endif - return -1; -} -static int __Pyx_ParseKeywords( - PyObject *kwds, - PyObject * const *kwvalues, - PyObject ** const argnames[], - PyObject *kwds2, - PyObject *values[], - Py_ssize_t num_pos_args, - Py_ssize_t num_kwargs, - const char* function_name, - int ignore_unknown_kwargs) -{ - if (CYTHON_METH_FASTCALL && likely(PyTuple_Check(kwds))) - return __Pyx_ParseKeywordsTuple(kwds, kwvalues, argnames, kwds2, values, num_pos_args, num_kwargs, function_name, ignore_unknown_kwargs); - else if (kwds2) - return __Pyx_ParseKeywordDictToDict(kwds, argnames, kwds2, values, num_pos_args, function_name); - else - return __Pyx_ParseKeywordDict(kwds, argnames, values, num_pos_args, num_kwargs, function_name, ignore_unknown_kwargs); -} - -/* RaiseArgTupleInvalid */ -static void __Pyx_RaiseArgtupleInvalid( - const char* func_name, - int exact, - Py_ssize_t num_min, - Py_ssize_t num_max, - Py_ssize_t num_found) -{ - Py_ssize_t num_expected; - const char *more_or_less; - if (num_found < num_min) { - num_expected = num_min; - more_or_less = "at least"; - } else { - num_expected = num_max; - more_or_less = "at most"; - } - if (exact) { - more_or_less = "exactly"; - } - PyErr_Format(PyExc_TypeError, - "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)", - func_name, more_or_less, num_expected, - (num_expected == 1) ? "" : "s", num_found); -} - -/* ArgTypeTest */ -static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) -{ - __Pyx_TypeName type_name; - __Pyx_TypeName obj_type_name; - PyObject *extra_info = __pyx_mstate_global->__pyx_empty_unicode; - int from_annotation_subclass = 0; - if (unlikely(!type)) { - PyErr_SetString(PyExc_SystemError, "Missing type object"); - return 0; - } - else if (!exact) { - if (likely(__Pyx_TypeCheck(obj, type))) return 1; - } else if (exact == 2) { - if (__Pyx_TypeCheck(obj, type)) { - from_annotation_subclass = 1; - extra_info = __pyx_mstate_global->__pyx_kp_u_Note_that_Cython_is_deliberately; - } - } - type_name = __Pyx_PyType_GetFullyQualifiedName(type); - obj_type_name = __Pyx_PyType_GetFullyQualifiedName(Py_TYPE(obj)); - PyErr_Format(PyExc_TypeError, - "Argument '%.200s' has incorrect type (expected " __Pyx_FMT_TYPENAME - ", got " __Pyx_FMT_TYPENAME ")" -#if __PYX_LIMITED_VERSION_HEX < 0x030C0000 - "%s%U" -#endif - , name, type_name, obj_type_name -#if __PYX_LIMITED_VERSION_HEX < 0x030C0000 - , (from_annotation_subclass ? ". " : ""), extra_info -#endif - ); -#if __PYX_LIMITED_VERSION_HEX >= 0x030C0000 - if (exact == 2 && from_annotation_subclass) { - PyObject *res; - PyObject *vargs[2]; - vargs[0] = PyErr_GetRaisedException(); - vargs[1] = extra_info; - res = PyObject_VectorcallMethod(__pyx_mstate_global->__pyx_kp_u_add_note, vargs, 2, NULL); - Py_XDECREF(res); - PyErr_SetRaisedException(vargs[0]); - } -#endif - __Pyx_DECREF_TypeName(type_name); - __Pyx_DECREF_TypeName(obj_type_name); - return 0; -} - -/* PyDictVersioning */ -#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS -static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { - PyObject *dict = Py_TYPE(obj)->tp_dict; - return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; -} -static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { - PyObject **dictptr = NULL; - Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; - if (offset) { -#if CYTHON_COMPILING_IN_CPYTHON - dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); -#else - dictptr = _PyObject_GetDictPtr(obj); -#endif - } - return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; -} -static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { - PyObject *dict = Py_TYPE(obj)->tp_dict; - if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) - return 0; - return obj_dict_version == __Pyx_get_object_dict_version(obj); -} -#endif - -/* GetModuleGlobalName */ -#if CYTHON_USE_DICT_VERSIONS -static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) -#else -static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) -#endif -{ - PyObject *result; -#if CYTHON_COMPILING_IN_LIMITED_API - if (unlikely(!__pyx_m)) { - if (!PyErr_Occurred()) - PyErr_SetNone(PyExc_NameError); - return NULL; - } - result = PyObject_GetAttr(__pyx_m, name); - if (likely(result)) { - return result; - } - PyErr_Clear(); -#elif CYTHON_AVOID_BORROWED_REFS || CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS - if (unlikely(__Pyx_PyDict_GetItemRef(__pyx_mstate_global->__pyx_d, name, &result) == -1)) PyErr_Clear(); - __PYX_UPDATE_DICT_CACHE(__pyx_mstate_global->__pyx_d, result, *dict_cached_value, *dict_version) - if (likely(result)) { - return result; - } -#else - result = _PyDict_GetItem_KnownHash(__pyx_mstate_global->__pyx_d, name, ((PyASCIIObject *) name)->hash); - __PYX_UPDATE_DICT_CACHE(__pyx_mstate_global->__pyx_d, result, *dict_cached_value, *dict_version) - if (likely(result)) { - return __Pyx_NewRef(result); - } - PyErr_Clear(); -#endif - return __Pyx_GetBuiltinName(name); -} - -/* PyObjectSetAttrStr */ -#if CYTHON_USE_TYPE_SLOTS -static CYTHON_INLINE int __Pyx_PyObject_SetAttrStr(PyObject* obj, PyObject* attr_name, PyObject* value) { - PyTypeObject* tp = Py_TYPE(obj); - if (likely(tp->tp_setattro)) - return tp->tp_setattro(obj, attr_name, value); - return PyObject_SetAttr(obj, attr_name, value); -} -#endif - -/* GetItemInt */ -static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { - PyObject *r; - if (unlikely(!j)) return NULL; - r = PyObject_GetItem(o, j); - Py_DECREF(j); - return r; -} -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, - CYTHON_NCP_UNUSED int wraparound, - CYTHON_NCP_UNUSED int boundscheck) { -#if CYTHON_ASSUME_SAFE_MACROS && CYTHON_ASSUME_SAFE_SIZE && !CYTHON_AVOID_BORROWED_REFS && !CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS - Py_ssize_t wrapped_i = i; - if (wraparound & unlikely(i < 0)) { - wrapped_i += PyList_GET_SIZE(o); - } - if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) { - PyObject *r = PyList_GET_ITEM(o, wrapped_i); - Py_INCREF(r); - return r; - } - return __Pyx_GetItemInt_Generic(o, PyLong_FromSsize_t(i)); -#else - return PySequence_GetItem(o, i); -#endif -} -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, - CYTHON_NCP_UNUSED int wraparound, - CYTHON_NCP_UNUSED int boundscheck) { -#if CYTHON_ASSUME_SAFE_MACROS && CYTHON_ASSUME_SAFE_SIZE && !CYTHON_AVOID_BORROWED_REFS - Py_ssize_t wrapped_i = i; - if (wraparound & unlikely(i < 0)) { - wrapped_i += PyTuple_GET_SIZE(o); - } - if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) { - PyObject *r = PyTuple_GET_ITEM(o, wrapped_i); - Py_INCREF(r); - return r; - } - return __Pyx_GetItemInt_Generic(o, PyLong_FromSsize_t(i)); -#else - return PySequence_GetItem(o, i); -#endif -} -static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, - CYTHON_NCP_UNUSED int wraparound, - CYTHON_NCP_UNUSED int boundscheck) { -#if CYTHON_ASSUME_SAFE_MACROS && CYTHON_ASSUME_SAFE_SIZE && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS - if (is_list || PyList_CheckExact(o)) { - Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); - if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) { - return __Pyx_PyList_GetItemRef(o, n); - } - } - else if (PyTuple_CheckExact(o)) { - Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); - if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) { - PyObject *r = PyTuple_GET_ITEM(o, n); - Py_INCREF(r); - return r; - } - } else { - PyMappingMethods *mm = Py_TYPE(o)->tp_as_mapping; - PySequenceMethods *sm = Py_TYPE(o)->tp_as_sequence; - if (mm && mm->mp_subscript) { - PyObject *r, *key = PyLong_FromSsize_t(i); - if (unlikely(!key)) return NULL; - r = mm->mp_subscript(o, key); - Py_DECREF(key); - return r; - } - if (likely(sm && sm->sq_item)) { - if (wraparound && unlikely(i < 0) && likely(sm->sq_length)) { - Py_ssize_t l = sm->sq_length(o); - if (likely(l >= 0)) { - i += l; - } else { - if (!PyErr_ExceptionMatches(PyExc_OverflowError)) - return NULL; - PyErr_Clear(); - } - } - return sm->sq_item(o, i); - } - } -#else - if (is_list || !PyMapping_Check(o)) { - return PySequence_GetItem(o, i); - } -#endif - return __Pyx_GetItemInt_Generic(o, PyLong_FromSsize_t(i)); -} - -/* PyObjectCallOneArg */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { - PyObject *args[2] = {NULL, arg}; - return __Pyx_PyObject_FastCall(func, args+1, 1 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET); -} - -/* ObjectGetItem */ -#if CYTHON_USE_TYPE_SLOTS -static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject *index) { - PyObject *runerr = NULL; - Py_ssize_t key_value; - key_value = __Pyx_PyIndex_AsSsize_t(index); - if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) { - return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1); - } - if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) { - __Pyx_TypeName index_type_name = __Pyx_PyType_GetFullyQualifiedName(Py_TYPE(index)); - PyErr_Clear(); - PyErr_Format(PyExc_IndexError, - "cannot fit '" __Pyx_FMT_TYPENAME "' into an index-sized integer", index_type_name); - __Pyx_DECREF_TypeName(index_type_name); - } - return NULL; -} -static PyObject *__Pyx_PyObject_GetItem_Slow(PyObject *obj, PyObject *key) { - __Pyx_TypeName obj_type_name; - if (likely(PyType_Check(obj))) { - PyObject *meth = __Pyx_PyObject_GetAttrStrNoError(obj, __pyx_mstate_global->__pyx_n_u_class_getitem); - if (!meth) { - PyErr_Clear(); - } else { - PyObject *result = __Pyx_PyObject_CallOneArg(meth, key); - Py_DECREF(meth); - return result; - } - } - obj_type_name = __Pyx_PyType_GetFullyQualifiedName(Py_TYPE(obj)); - PyErr_Format(PyExc_TypeError, - "'" __Pyx_FMT_TYPENAME "' object is not subscriptable", obj_type_name); - __Pyx_DECREF_TypeName(obj_type_name); - return NULL; -} -static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject *key) { - PyTypeObject *tp = Py_TYPE(obj); - PyMappingMethods *mm = tp->tp_as_mapping; - PySequenceMethods *sm = tp->tp_as_sequence; - if (likely(mm && mm->mp_subscript)) { - return mm->mp_subscript(obj, key); - } - if (likely(sm && sm->sq_item)) { - return __Pyx_PyObject_GetIndex(obj, key); - } - return __Pyx_PyObject_GetItem_Slow(obj, key); -} -#endif - -/* PyObjectFastCallMethod */ -#if !CYTHON_VECTORCALL || PY_VERSION_HEX < 0x03090000 -static PyObject *__Pyx_PyObject_FastCallMethod(PyObject *name, PyObject *const *args, size_t nargsf) { - PyObject *result; - PyObject *attr = PyObject_GetAttr(args[0], name); - if (unlikely(!attr)) - return NULL; - result = __Pyx_PyObject_FastCall(attr, args+1, nargsf - 1); - Py_DECREF(attr); - return result; -} -#endif - -/* HasAttr */ -#if __PYX_LIMITED_VERSION_HEX < 0x030d0000 -static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) { - PyObject *r; - if (unlikely(!PyUnicode_Check(n))) { - PyErr_SetString(PyExc_TypeError, - "hasattr(): attribute name must be string"); - return -1; - } - r = __Pyx_PyObject_GetAttrStrNoError(o, n); - if (!r) { - return (unlikely(PyErr_Occurred())) ? -1 : 0; - } else { - Py_DECREF(r); - return 1; - } -} -#endif - -/* DictGetItem */ -#if !CYTHON_COMPILING_IN_PYPY -static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) { - PyObject *value; - if (unlikely(__Pyx_PyDict_GetItemRef(d, key, &value) == 0)) { // no value, no error - if (unlikely(PyTuple_Check(key))) { - PyObject* args = PyTuple_Pack(1, key); - if (likely(args)) { - PyErr_SetObject(PyExc_KeyError, args); - Py_DECREF(args); - } - } else { - PyErr_SetObject(PyExc_KeyError, key); - } - } - return value; -} -#endif - -/* RaiseTooManyValuesToUnpack */ -static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { - PyErr_Format(PyExc_ValueError, - "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); -} - -/* RaiseNeedMoreValuesToUnpack */ -static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { - PyErr_Format(PyExc_ValueError, - "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", - index, (index == 1) ? "" : "s"); -} - -/* IterFinish */ -static CYTHON_INLINE int __Pyx_IterFinish(void) { - PyObject* exc_type; - __Pyx_PyThreadState_declare - __Pyx_PyThreadState_assign - exc_type = __Pyx_PyErr_CurrentExceptionType(); - if (unlikely(exc_type)) { - if (unlikely(!__Pyx_PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration))) - return -1; - __Pyx_PyErr_Clear(); - return 0; - } - return 0; -} - -/* UnpackItemEndCheck */ -static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected) { - if (unlikely(retval)) { - Py_DECREF(retval); - __Pyx_RaiseTooManyValuesError(expected); - return -1; - } - return __Pyx_IterFinish(); -} - -/* PyObjectCallNoArg */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { - PyObject *arg[2] = {NULL, NULL}; - return __Pyx_PyObject_FastCall(func, arg + 1, 0 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET); -} - -/* PyObjectGetMethod */ -static int __Pyx_PyObject_GetMethod(PyObject *obj, PyObject *name, PyObject **method) { - PyObject *attr; -#if CYTHON_UNPACK_METHODS && CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_PYTYPE_LOOKUP - __Pyx_TypeName type_name; - PyTypeObject *tp = Py_TYPE(obj); - PyObject *descr; - descrgetfunc f = NULL; - PyObject **dictptr, *dict; - int meth_found = 0; - assert (*method == NULL); - if (unlikely(tp->tp_getattro != PyObject_GenericGetAttr)) { - attr = __Pyx_PyObject_GetAttrStr(obj, name); - goto try_unpack; - } - if (unlikely(tp->tp_dict == NULL) && unlikely(PyType_Ready(tp) < 0)) { - return 0; - } - descr = _PyType_Lookup(tp, name); - if (likely(descr != NULL)) { - Py_INCREF(descr); -#if defined(Py_TPFLAGS_METHOD_DESCRIPTOR) && Py_TPFLAGS_METHOD_DESCRIPTOR - if (__Pyx_PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_METHOD_DESCRIPTOR)) -#else - #ifdef __Pyx_CyFunction_USED - if (likely(PyFunction_Check(descr) || __Pyx_IS_TYPE(descr, &PyMethodDescr_Type) || __Pyx_CyFunction_Check(descr))) - #else - if (likely(PyFunction_Check(descr) || __Pyx_IS_TYPE(descr, &PyMethodDescr_Type))) - #endif -#endif - { - meth_found = 1; - } else { - f = Py_TYPE(descr)->tp_descr_get; - if (f != NULL && PyDescr_IsData(descr)) { - attr = f(descr, obj, (PyObject *)Py_TYPE(obj)); - Py_DECREF(descr); - goto try_unpack; - } - } - } - dictptr = _PyObject_GetDictPtr(obj); - if (dictptr != NULL && (dict = *dictptr) != NULL) { - Py_INCREF(dict); - attr = __Pyx_PyDict_GetItemStr(dict, name); - if (attr != NULL) { - Py_INCREF(attr); - Py_DECREF(dict); - Py_XDECREF(descr); - goto try_unpack; - } - Py_DECREF(dict); - } - if (meth_found) { - *method = descr; - return 1; - } - if (f != NULL) { - attr = f(descr, obj, (PyObject *)Py_TYPE(obj)); - Py_DECREF(descr); - goto try_unpack; - } - if (likely(descr != NULL)) { - *method = descr; - return 0; - } - type_name = __Pyx_PyType_GetFullyQualifiedName(tp); - PyErr_Format(PyExc_AttributeError, - "'" __Pyx_FMT_TYPENAME "' object has no attribute '%U'", - type_name, name); - __Pyx_DECREF_TypeName(type_name); - return 0; -#else - attr = __Pyx_PyObject_GetAttrStr(obj, name); - goto try_unpack; -#endif -try_unpack: -#if CYTHON_UNPACK_METHODS - if (likely(attr) && PyMethod_Check(attr) && likely(PyMethod_GET_SELF(attr) == obj)) { - PyObject *function = PyMethod_GET_FUNCTION(attr); - Py_INCREF(function); - Py_DECREF(attr); - *method = function; - return 1; - } -#endif - *method = attr; - return 0; -} - -/* PyObjectCallMethod0 */ -static PyObject* __Pyx_PyObject_CallMethod0(PyObject* obj, PyObject* method_name) { - PyObject *method = NULL, *result = NULL; - int is_method = __Pyx_PyObject_GetMethod(obj, method_name, &method); - if (likely(is_method)) { - result = __Pyx_PyObject_CallOneArg(method, obj); - Py_DECREF(method); - return result; - } - if (unlikely(!method)) goto bad; - result = __Pyx_PyObject_CallNoArg(method); - Py_DECREF(method); -bad: - return result; -} - -/* RaiseNoneIterError */ -static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { - PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); -} - -/* UnpackTupleError */ -static void __Pyx_UnpackTupleError(PyObject *t, Py_ssize_t index) { - if (t == Py_None) { - __Pyx_RaiseNoneNotIterableError(); - } else { - Py_ssize_t size = __Pyx_PyTuple_GET_SIZE(t); - #if !CYTHON_ASSUME_SAFE_SIZE - if (unlikely(size < 0)) return; - #endif - if (size < index) { - __Pyx_RaiseNeedMoreValuesError(size); - } else { - __Pyx_RaiseTooManyValuesError(index); - } - } -} - -/* UnpackTuple2 */ -static CYTHON_INLINE int __Pyx_unpack_tuple2( - PyObject* tuple, PyObject** value1, PyObject** value2, int is_tuple, int has_known_size, int decref_tuple) { - if (likely(is_tuple || PyTuple_Check(tuple))) { - Py_ssize_t size; - if (has_known_size) { - return __Pyx_unpack_tuple2_exact(tuple, value1, value2, decref_tuple); - } - size = __Pyx_PyTuple_GET_SIZE(tuple); - if (likely(size == 2)) { - return __Pyx_unpack_tuple2_exact(tuple, value1, value2, decref_tuple); - } - if (size >= 0) { - __Pyx_UnpackTupleError(tuple, 2); - } - return -1; - } else { - return __Pyx_unpack_tuple2_generic(tuple, value1, value2, has_known_size, decref_tuple); - } -} -static CYTHON_INLINE int __Pyx_unpack_tuple2_exact( - PyObject* tuple, PyObject** pvalue1, PyObject** pvalue2, int decref_tuple) { - PyObject *value1 = NULL, *value2 = NULL; -#if CYTHON_AVOID_BORROWED_REFS || !CYTHON_ASSUME_SAFE_MACROS - value1 = __Pyx_PySequence_ITEM(tuple, 0); if (unlikely(!value1)) goto bad; - value2 = __Pyx_PySequence_ITEM(tuple, 1); if (unlikely(!value2)) goto bad; -#else - value1 = PyTuple_GET_ITEM(tuple, 0); Py_INCREF(value1); - value2 = PyTuple_GET_ITEM(tuple, 1); Py_INCREF(value2); -#endif - if (decref_tuple) { - Py_DECREF(tuple); - } - *pvalue1 = value1; - *pvalue2 = value2; - return 0; -#if CYTHON_AVOID_BORROWED_REFS || !CYTHON_ASSUME_SAFE_MACROS -bad: - Py_XDECREF(value1); - Py_XDECREF(value2); - if (decref_tuple) { Py_XDECREF(tuple); } - return -1; -#endif -} -static int __Pyx_unpack_tuple2_generic(PyObject* tuple, PyObject** pvalue1, PyObject** pvalue2, - int has_known_size, int decref_tuple) { - Py_ssize_t index; - PyObject *value1 = NULL, *value2 = NULL, *iter = NULL; - iternextfunc iternext; - iter = PyObject_GetIter(tuple); - if (unlikely(!iter)) goto bad; - if (decref_tuple) { Py_DECREF(tuple); tuple = NULL; } - iternext = __Pyx_PyObject_GetIterNextFunc(iter); - value1 = iternext(iter); if (unlikely(!value1)) { index = 0; goto unpacking_failed; } - value2 = iternext(iter); if (unlikely(!value2)) { index = 1; goto unpacking_failed; } - if (!has_known_size && unlikely(__Pyx_IternextUnpackEndCheck(iternext(iter), 2))) goto bad; - Py_DECREF(iter); - *pvalue1 = value1; - *pvalue2 = value2; - return 0; -unpacking_failed: - if (!has_known_size && __Pyx_IterFinish() == 0) - __Pyx_RaiseNeedMoreValuesError(index); -bad: - Py_XDECREF(iter); - Py_XDECREF(value1); - Py_XDECREF(value2); - if (decref_tuple) { Py_XDECREF(tuple); } - return -1; -} - -/* dict_iter */ -#if CYTHON_COMPILING_IN_PYPY -#include -#endif -static CYTHON_INLINE PyObject* __Pyx_dict_iterator(PyObject* iterable, int is_dict, PyObject* method_name, - Py_ssize_t* p_orig_length, int* p_source_is_dict) { - is_dict = is_dict || likely(PyDict_CheckExact(iterable)); - *p_source_is_dict = is_dict; - if (is_dict) { -#if !CYTHON_COMPILING_IN_PYPY - *p_orig_length = PyDict_Size(iterable); - Py_INCREF(iterable); - return iterable; -#else - static PyObject *py_items = NULL, *py_keys = NULL, *py_values = NULL; - PyObject **pp = NULL; - if (method_name) { - const char *name = PyUnicode_AsUTF8(method_name); - if (strcmp(name, "iteritems") == 0) pp = &py_items; - else if (strcmp(name, "iterkeys") == 0) pp = &py_keys; - else if (strcmp(name, "itervalues") == 0) pp = &py_values; - if (pp) { - if (!*pp) { - *pp = PyUnicode_FromString(name + 4); - if (!*pp) - return NULL; - } - method_name = *pp; - } - } -#endif - } - *p_orig_length = 0; - if (method_name) { - PyObject* iter; - iterable = __Pyx_PyObject_CallMethod0(iterable, method_name); - if (!iterable) - return NULL; -#if !CYTHON_COMPILING_IN_PYPY - if (PyTuple_CheckExact(iterable) || PyList_CheckExact(iterable)) - return iterable; -#endif - iter = PyObject_GetIter(iterable); - Py_DECREF(iterable); - return iter; - } - return PyObject_GetIter(iterable); -} -#if !CYTHON_COMPILING_IN_PYPY -static CYTHON_INLINE int __Pyx_dict_iter_next_source_is_dict( - PyObject* iter_obj, CYTHON_NCP_UNUSED Py_ssize_t orig_length, CYTHON_NCP_UNUSED Py_ssize_t* ppos, - PyObject** pkey, PyObject** pvalue, PyObject** pitem) { - PyObject *key, *value; - if (unlikely(orig_length != PyDict_Size(iter_obj))) { - PyErr_SetString(PyExc_RuntimeError, "dictionary changed size during iteration"); - return -1; - } - if (unlikely(!PyDict_Next(iter_obj, ppos, &key, &value))) { - return 0; - } - if (pitem) { - PyObject* tuple = PyTuple_New(2); - if (unlikely(!tuple)) { - return -1; - } - Py_INCREF(key); - Py_INCREF(value); - #if CYTHON_ASSUME_SAFE_MACROS - PyTuple_SET_ITEM(tuple, 0, key); - PyTuple_SET_ITEM(tuple, 1, value); - #else - if (unlikely(PyTuple_SetItem(tuple, 0, key) < 0)) { - Py_DECREF(value); - Py_DECREF(tuple); - return -1; - } - if (unlikely(PyTuple_SetItem(tuple, 1, value) < 0)) { - Py_DECREF(tuple); - return -1; - } - #endif - *pitem = tuple; - } else { - if (pkey) { - Py_INCREF(key); - *pkey = key; - } - if (pvalue) { - Py_INCREF(value); - *pvalue = value; - } - } - return 1; -} -#endif -static CYTHON_INLINE int __Pyx_dict_iter_next( - PyObject* iter_obj, CYTHON_NCP_UNUSED Py_ssize_t orig_length, CYTHON_NCP_UNUSED Py_ssize_t* ppos, - PyObject** pkey, PyObject** pvalue, PyObject** pitem, int source_is_dict) { - PyObject* next_item; -#if !CYTHON_COMPILING_IN_PYPY - if (source_is_dict) { - int result; -#if PY_VERSION_HEX >= 0x030d0000 && !CYTHON_COMPILING_IN_LIMITED_API - Py_BEGIN_CRITICAL_SECTION(iter_obj); -#endif - result = __Pyx_dict_iter_next_source_is_dict(iter_obj, orig_length, ppos, pkey, pvalue, pitem); -#if PY_VERSION_HEX >= 0x030d0000 && !CYTHON_COMPILING_IN_LIMITED_API - Py_END_CRITICAL_SECTION(); -#endif - return result; - } else if (PyTuple_CheckExact(iter_obj)) { - Py_ssize_t pos = *ppos; - Py_ssize_t tuple_size = __Pyx_PyTuple_GET_SIZE(iter_obj); - #if !CYTHON_ASSUME_SAFE_SIZE - if (unlikely(tuple_size < 0)) return -1; - #endif - if (unlikely(pos >= tuple_size)) return 0; - *ppos = pos + 1; - #if CYTHON_ASSUME_SAFE_MACROS - next_item = PyTuple_GET_ITEM(iter_obj, pos); - #else - next_item = PyTuple_GetItem(iter_obj, pos); - if (unlikely(!next_item)) return -1; - #endif - Py_INCREF(next_item); - } else if (PyList_CheckExact(iter_obj)) { - Py_ssize_t pos = *ppos; - Py_ssize_t list_size = __Pyx_PyList_GET_SIZE(iter_obj); - #if !CYTHON_ASSUME_SAFE_SIZE - if (unlikely(list_size < 0)) return -1; - #endif - if (unlikely(pos >= list_size)) return 0; - *ppos = pos + 1; - #if CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS - next_item = PyList_GetItemRef(iter_obj, pos); - if (unlikely(!next_item)) return -1; - #elif CYTHON_ASSUME_SAFE_MACROS - next_item = PyList_GET_ITEM(iter_obj, pos); - Py_INCREF(next_item); - #else - next_item = PyList_GetItem(iter_obj, pos); - if (unlikely(!next_item)) return -1; - Py_INCREF(next_item); - #endif - } else -#endif - { - next_item = PyIter_Next(iter_obj); - if (unlikely(!next_item)) { - return __Pyx_IterFinish(); - } - } - if (pitem) { - *pitem = next_item; - } else if (pkey && pvalue) { - if (__Pyx_unpack_tuple2(next_item, pkey, pvalue, source_is_dict, source_is_dict, 1)) - return -1; - } else if (pkey) { - *pkey = next_item; - } else { - *pvalue = next_item; - } - return 1; -} - -/* PyLongBinop */ -#if !CYTHON_COMPILING_IN_PYPY -static PyObject* __Pyx_Fallback___Pyx_PyLong_AddObjC(PyObject *op1, PyObject *op2, int inplace) { - return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); -} -#if CYTHON_USE_PYLONG_INTERNALS -static PyObject* __Pyx_Unpacked___Pyx_PyLong_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check) { - CYTHON_MAYBE_UNUSED_VAR(inplace); - CYTHON_UNUSED_VAR(zerodivision_check); - const long b = intval; - long a, x; -#ifdef HAVE_LONG_LONG - const PY_LONG_LONG llb = intval; - PY_LONG_LONG lla, llx; -#endif - if (unlikely(__Pyx_PyLong_IsZero(op1))) { - return __Pyx_NewRef(op2); - } - if (likely(__Pyx_PyLong_IsCompact(op1))) { - a = __Pyx_PyLong_CompactValue(op1); - } else { - const digit* digits = __Pyx_PyLong_Digits(op1); - const Py_ssize_t size = __Pyx_PyLong_SignedDigitCount(op1); - switch (size) { - case -2: - if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; - #ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { - lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; - #endif - } - CYTHON_FALLTHROUGH; - case 2: - if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; - #ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { - lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; - #endif - } - CYTHON_FALLTHROUGH; - case -3: - if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; - #ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { - lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; - #endif - } - CYTHON_FALLTHROUGH; - case 3: - if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; - #ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { - lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; - #endif - } - CYTHON_FALLTHROUGH; - case -4: - if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; - #ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { - lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; - #endif - } - CYTHON_FALLTHROUGH; - case 4: - if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); - break; - #ifdef HAVE_LONG_LONG - } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { - lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); - goto long_long; - #endif - } - CYTHON_FALLTHROUGH; - default: return PyLong_Type.tp_as_number->nb_add(op1, op2); - } - } - x = a + b; - return PyLong_FromLong(x); -#ifdef HAVE_LONG_LONG - long_long: - llx = lla + llb; - return PyLong_FromLongLong(llx); -#endif - return __Pyx_Fallback___Pyx_PyLong_AddObjC(op1, op2, inplace); - - -} -#endif -static PyObject* __Pyx_Float___Pyx_PyLong_AddObjC(PyObject *float_val, long intval, int zerodivision_check) { - CYTHON_UNUSED_VAR(zerodivision_check); - const long b = intval; - double a = __Pyx_PyFloat_AS_DOUBLE(float_val); - double result; - - result = ((double)a) + (double)b; - return PyFloat_FromDouble(result); -} -static CYTHON_INLINE PyObject* __Pyx_PyLong_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check) { - CYTHON_MAYBE_UNUSED_VAR(intval); - CYTHON_UNUSED_VAR(zerodivision_check); - #if CYTHON_USE_PYLONG_INTERNALS - if (likely(PyLong_CheckExact(op1))) { - return __Pyx_Unpacked___Pyx_PyLong_AddObjC(op1, op2, intval, inplace, zerodivision_check); - } - #endif - if (PyFloat_CheckExact(op1)) { - return __Pyx_Float___Pyx_PyLong_AddObjC(op1, intval, zerodivision_check); - } - return __Pyx_Fallback___Pyx_PyLong_AddObjC(op1, op2, inplace); -} -#endif - -/* PyObjectVectorCallKwBuilder */ -#if CYTHON_VECTORCALL -static int __Pyx_VectorcallBuilder_AddArg(PyObject *key, PyObject *value, PyObject *builder, PyObject **args, int n) { - (void)__Pyx_PyObject_FastCallDict; - if (__Pyx_PyTuple_SET_ITEM(builder, n, key) != (0)) return -1; - Py_INCREF(key); - args[n] = value; - return 0; -} -CYTHON_UNUSED static int __Pyx_VectorcallBuilder_AddArg_Check(PyObject *key, PyObject *value, PyObject *builder, PyObject **args, int n) { - (void)__Pyx_VectorcallBuilder_AddArgStr; - if (unlikely(!PyUnicode_Check(key))) { - PyErr_SetString(PyExc_TypeError, "keywords must be strings"); - return -1; - } - return __Pyx_VectorcallBuilder_AddArg(key, value, builder, args, n); -} -static int __Pyx_VectorcallBuilder_AddArgStr(const char *key, PyObject *value, PyObject *builder, PyObject **args, int n) { - PyObject *pyKey = PyUnicode_FromString(key); - if (!pyKey) return -1; - return __Pyx_VectorcallBuilder_AddArg(pyKey, value, builder, args, n); -} -#else // CYTHON_VECTORCALL -CYTHON_UNUSED static int __Pyx_VectorcallBuilder_AddArg_Check(PyObject *key, PyObject *value, PyObject *builder, CYTHON_UNUSED PyObject **args, CYTHON_UNUSED int n) { - if (unlikely(!PyUnicode_Check(key))) { - PyErr_SetString(PyExc_TypeError, "keywords must be strings"); - return -1; - } - return PyDict_SetItem(builder, key, value); -} -#endif - -/* CIntToDigits */ -static const char DIGIT_PAIRS_10[2*10*10+1] = { - "00010203040506070809" - "10111213141516171819" - "20212223242526272829" - "30313233343536373839" - "40414243444546474849" - "50515253545556575859" - "60616263646566676869" - "70717273747576777879" - "80818283848586878889" - "90919293949596979899" -}; -static const char DIGIT_PAIRS_8[2*8*8+1] = { - "0001020304050607" - "1011121314151617" - "2021222324252627" - "3031323334353637" - "4041424344454647" - "5051525354555657" - "6061626364656667" - "7071727374757677" -}; -static const char DIGITS_HEX[2*16+1] = { - "0123456789abcdef" - "0123456789ABCDEF" -}; - -/* BuildPyUnicode */ -static PyObject* __Pyx_PyUnicode_BuildFromAscii(Py_ssize_t ulength, const char* chars, int clength, - int prepend_sign, char padding_char) { - PyObject *uval; - Py_ssize_t uoffset = ulength - clength; -#if CYTHON_USE_UNICODE_INTERNALS - Py_ssize_t i; - void *udata; - uval = PyUnicode_New(ulength, 127); - if (unlikely(!uval)) return NULL; - udata = PyUnicode_DATA(uval); - if (uoffset > 0) { - i = 0; - if (prepend_sign) { - __Pyx_PyUnicode_WRITE(PyUnicode_1BYTE_KIND, udata, 0, '-'); - i++; - } - for (; i < uoffset; i++) { - __Pyx_PyUnicode_WRITE(PyUnicode_1BYTE_KIND, udata, i, padding_char); - } - } - for (i=0; i < clength; i++) { - __Pyx_PyUnicode_WRITE(PyUnicode_1BYTE_KIND, udata, uoffset+i, chars[i]); - } -#else - { - PyObject *sign = NULL, *padding = NULL; - uval = NULL; - if (uoffset > 0) { - prepend_sign = !!prepend_sign; - if (uoffset > prepend_sign) { - padding = PyUnicode_FromOrdinal(padding_char); - if (likely(padding) && uoffset > prepend_sign + 1) { - PyObject *tmp = PySequence_Repeat(padding, uoffset - prepend_sign); - Py_DECREF(padding); - padding = tmp; - } - if (unlikely(!padding)) goto done_or_error; - } - if (prepend_sign) { - sign = PyUnicode_FromOrdinal('-'); - if (unlikely(!sign)) goto done_or_error; - } - } - uval = PyUnicode_DecodeASCII(chars, clength, NULL); - if (likely(uval) && padding) { - PyObject *tmp = PyUnicode_Concat(padding, uval); - Py_DECREF(uval); - uval = tmp; - } - if (likely(uval) && sign) { - PyObject *tmp = PyUnicode_Concat(sign, uval); - Py_DECREF(uval); - uval = tmp; - } -done_or_error: - Py_XDECREF(padding); - Py_XDECREF(sign); - } -#endif - return uval; -} - -/* COrdinalToPyUnicode */ -static CYTHON_INLINE int __Pyx_CheckUnicodeValue(int value) { - return value <= 1114111; -} -static PyObject* __Pyx_PyUnicode_FromOrdinal_Padded(int value, Py_ssize_t ulength, char padding_char) { - if (likely(ulength <= 250)) { - char chars[256]; - if (value <= 255) { - memset(chars, padding_char, (size_t) (ulength - 1)); - chars[ulength-1] = (char) value; - return PyUnicode_DecodeLatin1(chars, ulength, NULL); - } - char *cpos = chars + sizeof(chars); - if (value < 0x800) { - *--cpos = (char) (0x80 | (value & 0x3f)); - value >>= 6; - *--cpos = (char) (0xc0 | (value & 0x1f)); - } else if (value < 0x10000) { - *--cpos = (char) (0x80 | (value & 0x3f)); - value >>= 6; - *--cpos = (char) (0x80 | (value & 0x3f)); - value >>= 6; - *--cpos = (char) (0xe0 | (value & 0x0f)); - } else { - *--cpos = (char) (0x80 | (value & 0x3f)); - value >>= 6; - *--cpos = (char) (0x80 | (value & 0x3f)); - value >>= 6; - *--cpos = (char) (0x80 | (value & 0x3f)); - value >>= 6; - *--cpos = (char) (0xf0 | (value & 0x07)); - } - cpos -= ulength; - memset(cpos, padding_char, (size_t) (ulength - 1)); - return PyUnicode_DecodeUTF8(cpos, chars + sizeof(chars) - cpos, NULL); - } - if (value <= 127 && CYTHON_USE_UNICODE_INTERNALS) { - const char chars[1] = {(char) value}; - return __Pyx_PyUnicode_BuildFromAscii(ulength, chars, 1, 0, padding_char); - } - { - PyObject *uchar, *padding_uchar, *padding, *result; - padding_uchar = PyUnicode_FromOrdinal(padding_char); - if (unlikely(!padding_uchar)) return NULL; - padding = PySequence_Repeat(padding_uchar, ulength - 1); - Py_DECREF(padding_uchar); - if (unlikely(!padding)) return NULL; - uchar = PyUnicode_FromOrdinal(value); - if (unlikely(!uchar)) { - Py_DECREF(padding); - return NULL; - } - result = PyUnicode_Concat(padding, uchar); - Py_DECREF(padding); - Py_DECREF(uchar); - return result; - } -} - -/* CIntToPyUnicode */ -static CYTHON_INLINE PyObject* __Pyx_PyUnicode_From_Py_ssize_t(Py_ssize_t value, Py_ssize_t width, char padding_char, char format_char) { - char digits[sizeof(Py_ssize_t)*3+2]; - char *dpos, *end = digits + sizeof(Py_ssize_t)*3+2; - const char *hex_digits = DIGITS_HEX; - Py_ssize_t length, ulength; - int prepend_sign, last_one_off; - Py_ssize_t remaining; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const Py_ssize_t neg_one = (Py_ssize_t) -1, const_zero = (Py_ssize_t) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (format_char == 'c') { - if (unlikely(!(is_unsigned || value == 0 || value > 0) || - !(sizeof(value) <= 2 || value & ~ (Py_ssize_t) 0x01fffff || __Pyx_CheckUnicodeValue((int) value)))) { - PyErr_SetString(PyExc_OverflowError, "%c arg not in range(0x110000)"); - return NULL; - } - if (width <= 1) { - return PyUnicode_FromOrdinal((int) value); - } - return __Pyx_PyUnicode_FromOrdinal_Padded((int) value, width, padding_char); - } - if (format_char == 'X') { - hex_digits += 16; - format_char = 'x'; - } - remaining = value; - last_one_off = 0; - dpos = end; - do { - int digit_pos; - switch (format_char) { - case 'o': - digit_pos = abs((int)(remaining % (8*8))); - remaining = (Py_ssize_t) (remaining / (8*8)); - dpos -= 2; - memcpy(dpos, DIGIT_PAIRS_8 + digit_pos * 2, 2); - last_one_off = (digit_pos < 8); - break; - case 'd': - digit_pos = abs((int)(remaining % (10*10))); - remaining = (Py_ssize_t) (remaining / (10*10)); - dpos -= 2; - memcpy(dpos, DIGIT_PAIRS_10 + digit_pos * 2, 2); - last_one_off = (digit_pos < 10); - break; - case 'x': - *(--dpos) = hex_digits[abs((int)(remaining % 16))]; - remaining = (Py_ssize_t) (remaining / 16); - break; - default: - assert(0); - break; - } - } while (unlikely(remaining != 0)); - assert(!last_one_off || *dpos == '0'); - dpos += last_one_off; - length = end - dpos; - ulength = length; - prepend_sign = 0; - if (!is_unsigned && value <= neg_one) { - if (padding_char == ' ' || width <= length + 1) { - *(--dpos) = '-'; - ++length; - } else { - prepend_sign = 1; - } - ++ulength; - } - if (width > ulength) { - ulength = width; - } - if (ulength == 1) { - return PyUnicode_FromOrdinal(*dpos); - } - return __Pyx_PyUnicode_BuildFromAscii(ulength, dpos, (int) length, prepend_sign, padding_char); -} - -/* SliceTupleAndList */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE void __Pyx_crop_slice(Py_ssize_t* _start, Py_ssize_t* _stop, Py_ssize_t* _length) { - Py_ssize_t start = *_start, stop = *_stop, length = *_length; - if (start < 0) { - start += length; - if (start < 0) - start = 0; - } - if (stop < 0) - stop += length; - else if (stop > length) - stop = length; - *_length = stop - start; - *_start = start; - *_stop = stop; -} -static CYTHON_INLINE PyObject* __Pyx_PyTuple_GetSlice( - PyObject* src, Py_ssize_t start, Py_ssize_t stop) { - Py_ssize_t length = PyTuple_GET_SIZE(src); - __Pyx_crop_slice(&start, &stop, &length); - return __Pyx_PyTuple_FromArray(((PyTupleObject*)src)->ob_item + start, length); -} -static CYTHON_INLINE PyObject* __Pyx_PyList_GetSlice_locked( - PyObject* src, Py_ssize_t start, Py_ssize_t stop) { - Py_ssize_t length = PyList_GET_SIZE(src); - __Pyx_crop_slice(&start, &stop, &length); - if (length <= 0) { - return PyList_New(0); - } - return __Pyx_PyList_FromArray(((PyListObject*)src)->ob_item + start, length); -} -static CYTHON_INLINE PyObject* __Pyx_PyList_GetSlice( - PyObject* src, Py_ssize_t start, Py_ssize_t stop) { - PyObject *result; - __Pyx_BEGIN_CRITICAL_SECTION(src); - result = __Pyx_PyList_GetSlice_locked(src, start, stop); - __Pyx_END_CRITICAL_SECTION(); - return result; -} -#endif // CYTHON_COMPILING_IN_CPYTHON - -/* CallUnboundCMethod0 */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_CallUnboundCMethod0(__Pyx_CachedCFunction* cfunc, PyObject* self) { - int was_initialized = __Pyx_CachedCFunction_GetAndSetInitializing(cfunc); - if (likely(was_initialized == 2 && cfunc->func)) { - if (likely(cfunc->flag == METH_NOARGS)) - return __Pyx_CallCFunction(cfunc, self, NULL); - if (likely(cfunc->flag == METH_FASTCALL)) - return __Pyx_CallCFunctionFast(cfunc, self, NULL, 0); - if (cfunc->flag == (METH_FASTCALL | METH_KEYWORDS)) - return __Pyx_CallCFunctionFastWithKeywords(cfunc, self, NULL, 0, NULL); - if (likely(cfunc->flag == (METH_VARARGS | METH_KEYWORDS))) - return __Pyx_CallCFunctionWithKeywords(cfunc, self, __pyx_mstate_global->__pyx_empty_tuple, NULL); - if (cfunc->flag == METH_VARARGS) - return __Pyx_CallCFunction(cfunc, self, __pyx_mstate_global->__pyx_empty_tuple); - return __Pyx__CallUnboundCMethod0(cfunc, self); - } -#if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING - else if (unlikely(was_initialized == 1)) { - __Pyx_CachedCFunction tmp_cfunc = { -#ifndef __cplusplus - 0 -#endif - }; - tmp_cfunc.type = cfunc->type; - tmp_cfunc.method_name = cfunc->method_name; - return __Pyx__CallUnboundCMethod0(&tmp_cfunc, self); - } -#endif - PyObject *result = __Pyx__CallUnboundCMethod0(cfunc, self); - __Pyx_CachedCFunction_SetFinishedInitializing(cfunc); - return result; -} -#endif -static PyObject* __Pyx__CallUnboundCMethod0(__Pyx_CachedCFunction* cfunc, PyObject* self) { - PyObject *result; - if (unlikely(!cfunc->method) && unlikely(__Pyx_TryUnpackUnboundCMethod(cfunc) < 0)) return NULL; - result = __Pyx_PyObject_CallOneArg(cfunc->method, self); - return result; -} - -/* py_dict_keys */ -static CYTHON_INLINE PyObject* __Pyx_PyDict_Keys(PyObject* d) { - return __Pyx_CallUnboundCMethod0(&__pyx_mstate_global->__pyx_umethod_PyDict_Type_keys, d); -} - -/* RaiseUnexpectedTypeError */ -static int -__Pyx_RaiseUnexpectedTypeError(const char *expected, PyObject *obj) -{ - __Pyx_TypeName obj_type_name = __Pyx_PyType_GetFullyQualifiedName(Py_TYPE(obj)); - PyErr_Format(PyExc_TypeError, "Expected %s, got " __Pyx_FMT_TYPENAME, - expected, obj_type_name); - __Pyx_DECREF_TypeName(obj_type_name); - return 0; -} - -/* SliceObject */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_GetSlice(PyObject* obj, - Py_ssize_t cstart, Py_ssize_t cstop, - PyObject** _py_start, PyObject** _py_stop, PyObject** _py_slice, - int has_cstart, int has_cstop, CYTHON_UNUSED int wraparound) { - __Pyx_TypeName obj_type_name; -#if CYTHON_USE_TYPE_SLOTS - PyMappingMethods* mp = Py_TYPE(obj)->tp_as_mapping; - if (likely(mp && mp->mp_subscript)) -#endif - { - PyObject* result; - PyObject *py_slice, *py_start, *py_stop; - if (_py_slice) { - py_slice = *_py_slice; - } else { - PyObject* owned_start = NULL; - PyObject* owned_stop = NULL; - if (_py_start) { - py_start = *_py_start; - } else { - if (has_cstart) { - owned_start = py_start = PyLong_FromSsize_t(cstart); - if (unlikely(!py_start)) goto bad; - } else - py_start = Py_None; - } - if (_py_stop) { - py_stop = *_py_stop; - } else { - if (has_cstop) { - owned_stop = py_stop = PyLong_FromSsize_t(cstop); - if (unlikely(!py_stop)) { - Py_XDECREF(owned_start); - goto bad; - } - } else - py_stop = Py_None; - } - py_slice = PySlice_New(py_start, py_stop, Py_None); - Py_XDECREF(owned_start); - Py_XDECREF(owned_stop); - if (unlikely(!py_slice)) goto bad; - } -#if CYTHON_USE_TYPE_SLOTS - result = mp->mp_subscript(obj, py_slice); -#else - result = PyObject_GetItem(obj, py_slice); -#endif - if (!_py_slice) { - Py_DECREF(py_slice); - } - return result; - } - obj_type_name = __Pyx_PyType_GetFullyQualifiedName(Py_TYPE(obj)); - PyErr_Format(PyExc_TypeError, - "'" __Pyx_FMT_TYPENAME "' object is unsliceable", obj_type_name); - __Pyx_DECREF_TypeName(obj_type_name); -bad: - return NULL; -} - -/* ModFloat[double] */ -static CYTHON_INLINE double __Pyx_mod_double(double a, double b, int b_is_constant) { - CYTHON_UNUSED_VAR(b_is_constant); - double r = fmod(a, b); - r += ((r != 0) & ((r < 0) ^ (b < 0))) * b; - return r; -} - -/* SetItemInt */ -static int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v) { - int r; - if (unlikely(!j)) return -1; - r = PyObject_SetItem(o, j, v); - Py_DECREF(j); - return r; -} -static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v, int is_list, - CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { -#if CYTHON_ASSUME_SAFE_MACROS && CYTHON_ASSUME_SAFE_SIZE && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS - if (is_list || PyList_CheckExact(o)) { - Py_ssize_t n = (!wraparound) ? i : ((likely(i >= 0)) ? i : i + PyList_GET_SIZE(o)); - if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o)))) { - Py_INCREF(v); -#if CYTHON_AVOID_THREAD_UNSAFE_BORROWED_REFS - PyList_SetItem(o, n, v); -#else - PyObject* old = PyList_GET_ITEM(o, n); - PyList_SET_ITEM(o, n, v); - Py_DECREF(old); -#endif - return 1; - } - } else { - PyMappingMethods *mm = Py_TYPE(o)->tp_as_mapping; - PySequenceMethods *sm = Py_TYPE(o)->tp_as_sequence; - if (mm && mm->mp_ass_subscript) { - int r; - PyObject *key = PyLong_FromSsize_t(i); - if (unlikely(!key)) return -1; - r = mm->mp_ass_subscript(o, key, v); - Py_DECREF(key); - return r; - } - if (likely(sm && sm->sq_ass_item)) { - if (wraparound && unlikely(i < 0) && likely(sm->sq_length)) { - Py_ssize_t l = sm->sq_length(o); - if (likely(l >= 0)) { - i += l; - } else { - if (!PyErr_ExceptionMatches(PyExc_OverflowError)) - return -1; - PyErr_Clear(); - } - } - return sm->sq_ass_item(o, i, v); - } - } -#else - if (is_list || !PyMapping_Check(o)) - { - return PySequence_SetItem(o, i, v); - } -#endif - return __Pyx_SetItemInt_Generic(o, PyLong_FromSsize_t(i), v); -} - -/* TypeImport */ -#ifndef __PYX_HAVE_RT_ImportType_3_1_2 -#define __PYX_HAVE_RT_ImportType_3_1_2 -static PyTypeObject *__Pyx_ImportType_3_1_2(PyObject *module, const char *module_name, const char *class_name, - size_t size, size_t alignment, enum __Pyx_ImportType_CheckSize_3_1_2 check_size) -{ - PyObject *result = 0; - Py_ssize_t basicsize; - Py_ssize_t itemsize; -#if CYTHON_COMPILING_IN_LIMITED_API - PyObject *py_basicsize; - PyObject *py_itemsize; -#endif - result = PyObject_GetAttrString(module, class_name); - if (!result) - goto bad; - if (!PyType_Check(result)) { - PyErr_Format(PyExc_TypeError, - "%.200s.%.200s is not a type object", - module_name, class_name); - goto bad; - } -#if !CYTHON_COMPILING_IN_LIMITED_API - basicsize = ((PyTypeObject *)result)->tp_basicsize; - itemsize = ((PyTypeObject *)result)->tp_itemsize; -#else - if (size == 0) { - return (PyTypeObject *)result; - } - py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); - if (!py_basicsize) - goto bad; - basicsize = PyLong_AsSsize_t(py_basicsize); - Py_DECREF(py_basicsize); - py_basicsize = 0; - if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) - goto bad; - py_itemsize = PyObject_GetAttrString(result, "__itemsize__"); - if (!py_itemsize) - goto bad; - itemsize = PyLong_AsSsize_t(py_itemsize); - Py_DECREF(py_itemsize); - py_itemsize = 0; - if (itemsize == (Py_ssize_t)-1 && PyErr_Occurred()) - goto bad; -#endif - if (itemsize) { - if (size % alignment) { - alignment = size % alignment; - } - if (itemsize < (Py_ssize_t)alignment) - itemsize = (Py_ssize_t)alignment; - } - if ((size_t)(basicsize + itemsize) < size) { - PyErr_Format(PyExc_ValueError, - "%.200s.%.200s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize+itemsize); - goto bad; - } - if (check_size == __Pyx_ImportType_CheckSize_Error_3_1_2 && - ((size_t)basicsize > size || (size_t)(basicsize + itemsize) < size)) { - PyErr_Format(PyExc_ValueError, - "%.200s.%.200s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd-%zd from PyObject", - module_name, class_name, size, basicsize, basicsize+itemsize); - goto bad; - } - else if (check_size == __Pyx_ImportType_CheckSize_Warn_3_1_2 && (size_t)basicsize > size) { - if (PyErr_WarnFormat(NULL, 0, - "%.200s.%.200s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize) < 0) { - goto bad; - } - } - return (PyTypeObject *)result; -bad: - Py_XDECREF(result); - return NULL; -} -#endif - -/* LimitedApiGetTypeDict */ -#if CYTHON_COMPILING_IN_LIMITED_API -static Py_ssize_t __Pyx_GetTypeDictOffset(void) { - PyObject *tp_dictoffset_o; - Py_ssize_t tp_dictoffset; - tp_dictoffset_o = PyObject_GetAttrString((PyObject*)(&PyType_Type), "__dictoffset__"); - if (unlikely(!tp_dictoffset_o)) return -1; - tp_dictoffset = PyLong_AsSsize_t(tp_dictoffset_o); - Py_DECREF(tp_dictoffset_o); - if (unlikely(tp_dictoffset == 0)) { - PyErr_SetString( - PyExc_TypeError, - "'type' doesn't have a dictoffset"); - return -1; - } else if (unlikely(tp_dictoffset < 0)) { - PyErr_SetString( - PyExc_TypeError, - "'type' has an unexpected negative dictoffset. " - "Please report this as Cython bug"); - return -1; - } - return tp_dictoffset; -} -static PyObject *__Pyx_GetTypeDict(PyTypeObject *tp) { - static Py_ssize_t tp_dictoffset = 0; - if (unlikely(tp_dictoffset == 0)) { - tp_dictoffset = __Pyx_GetTypeDictOffset(); - if (unlikely(tp_dictoffset == -1 && PyErr_Occurred())) { - tp_dictoffset = 0; // try again next time? - return NULL; - } - } - return *(PyObject**)((char*)tp + tp_dictoffset); -} -#endif - -/* SetItemOnTypeDict */ -static int __Pyx__SetItemOnTypeDict(PyTypeObject *tp, PyObject *k, PyObject *v) { - int result; - PyObject *tp_dict; -#if CYTHON_COMPILING_IN_LIMITED_API - tp_dict = __Pyx_GetTypeDict(tp); - if (unlikely(!tp_dict)) return -1; -#else - tp_dict = tp->tp_dict; -#endif - result = PyDict_SetItem(tp_dict, k, v); - if (likely(!result)) { - PyType_Modified(tp); - if (unlikely(PyObject_HasAttr(v, __pyx_mstate_global->__pyx_n_u_set_name))) { - PyObject *setNameResult = PyObject_CallMethodObjArgs(v, __pyx_mstate_global->__pyx_n_u_set_name, (PyObject *) tp, k, NULL); - if (!setNameResult) return -1; - Py_DECREF(setNameResult); - } - } - return result; -} - -/* FixUpExtensionType */ -static int __Pyx_fix_up_extension_type_from_spec(PyType_Spec *spec, PyTypeObject *type) { -#if __PYX_LIMITED_VERSION_HEX > 0x030900B1 - CYTHON_UNUSED_VAR(spec); - CYTHON_UNUSED_VAR(type); - CYTHON_UNUSED_VAR(__Pyx__SetItemOnTypeDict); -#else - const PyType_Slot *slot = spec->slots; - int changed = 0; -#if !CYTHON_COMPILING_IN_LIMITED_API - while (slot && slot->slot && slot->slot != Py_tp_members) - slot++; - if (slot && slot->slot == Py_tp_members) { -#if !CYTHON_COMPILING_IN_CPYTHON - const -#endif // !CYTHON_COMPILING_IN_CPYTHON) - PyMemberDef *memb = (PyMemberDef*) slot->pfunc; - while (memb && memb->name) { - if (memb->name[0] == '_' && memb->name[1] == '_') { - if (strcmp(memb->name, "__weaklistoffset__") == 0) { - assert(memb->type == T_PYSSIZET); - assert(memb->flags == READONLY); - type->tp_weaklistoffset = memb->offset; - changed = 1; - } - else if (strcmp(memb->name, "__dictoffset__") == 0) { - assert(memb->type == T_PYSSIZET); - assert(memb->flags == READONLY); - type->tp_dictoffset = memb->offset; - changed = 1; - } -#if CYTHON_METH_FASTCALL - else if (strcmp(memb->name, "__vectorcalloffset__") == 0) { - assert(memb->type == T_PYSSIZET); - assert(memb->flags == READONLY); -#if PY_VERSION_HEX >= 0x030800b4 - type->tp_vectorcall_offset = memb->offset; -#else - type->tp_print = (printfunc) memb->offset; -#endif - changed = 1; - } -#endif // CYTHON_METH_FASTCALL - else if (strcmp(memb->name, "__module__") == 0) { - PyObject *descr; - assert(memb->type == T_OBJECT); - assert(memb->flags == 0 || memb->flags == READONLY); - descr = PyDescr_NewMember(type, memb); - if (unlikely(!descr)) - return -1; - int set_item_result = PyDict_SetItem(type->tp_dict, PyDescr_NAME(descr), descr); - Py_DECREF(descr); - if (unlikely(set_item_result < 0)) { - return -1; - } - changed = 1; - } - } - memb++; - } - } -#endif // !CYTHON_COMPILING_IN_LIMITED_API - slot = spec->slots; - while (slot && slot->slot && slot->slot != Py_tp_getset) - slot++; - if (slot && slot->slot == Py_tp_getset) { - PyGetSetDef *getset = (PyGetSetDef*) slot->pfunc; - while (getset && getset->name) { - if (getset->name[0] == '_' && getset->name[1] == '_' && strcmp(getset->name, "__module__") == 0) { - PyObject *descr = PyDescr_NewGetSet(type, getset); - if (unlikely(!descr)) - return -1; - #if CYTHON_COMPILING_IN_LIMITED_API - PyObject *pyname = PyUnicode_FromString(getset->name); - if (unlikely(!pyname)) { - Py_DECREF(descr); - return -1; - } - int set_item_result = __Pyx_SetItemOnTypeDict(type, pyname, descr); - Py_DECREF(pyname); - #else - CYTHON_UNUSED_VAR(__Pyx__SetItemOnTypeDict); - int set_item_result = PyDict_SetItem(type->tp_dict, PyDescr_NAME(descr), descr); - #endif - Py_DECREF(descr); - if (unlikely(set_item_result < 0)) { - return -1; - } - changed = 1; - } - ++getset; - } - } - if (changed) - PyType_Modified(type); -#endif // PY_VERSION_HEX > 0x030900B1 - return 0; -} - -/* FetchSharedCythonModule */ -static PyObject *__Pyx_FetchSharedCythonABIModule(void) { - return __Pyx_PyImport_AddModuleRef(__PYX_ABI_MODULE_NAME); -} - -/* dict_setdefault */ -static CYTHON_INLINE PyObject *__Pyx_PyDict_SetDefault(PyObject *d, PyObject *key, PyObject *default_value, - int is_safe_type) { - PyObject* value; - CYTHON_MAYBE_UNUSED_VAR(is_safe_type); -#if CYTHON_COMPILING_IN_LIMITED_API - value = PyObject_CallMethod(d, "setdefault", "OO", key, default_value); -#elif PY_VERSION_HEX >= 0x030d0000 - PyDict_SetDefaultRef(d, key, default_value, &value); -#else - value = PyDict_SetDefault(d, key, default_value); - if (unlikely(!value)) return NULL; - Py_INCREF(value); -#endif - return value; -} - -/* FetchCommonType */ -#if __PYX_LIMITED_VERSION_HEX < 0x030C0000 -static PyObject* __Pyx_PyType_FromMetaclass(PyTypeObject *metaclass, PyObject *module, PyType_Spec *spec, PyObject *bases) { - PyObject *result = __Pyx_PyType_FromModuleAndSpec(module, spec, bases); - if (result && metaclass) { - PyObject *old_tp = (PyObject*)Py_TYPE(result); - Py_INCREF((PyObject*)metaclass); -#if __PYX_LIMITED_VERSION_HEX >= 0x03090000 - Py_SET_TYPE(result, metaclass); -#else - result->ob_type = metaclass; -#endif - Py_DECREF(old_tp); - } - return result; -} -#else -#define __Pyx_PyType_FromMetaclass(me, mo, s, b) PyType_FromMetaclass(me, mo, s, b) -#endif -static int __Pyx_VerifyCachedType(PyObject *cached_type, - const char *name, - Py_ssize_t expected_basicsize) { - Py_ssize_t basicsize; - if (!PyType_Check(cached_type)) { - PyErr_Format(PyExc_TypeError, - "Shared Cython type %.200s is not a type object", name); - return -1; - } - if (expected_basicsize == 0) { - return 0; // size is inherited, nothing useful to check - } -#if CYTHON_COMPILING_IN_LIMITED_API - PyObject *py_basicsize; - py_basicsize = PyObject_GetAttrString(cached_type, "__basicsize__"); - if (unlikely(!py_basicsize)) return -1; - basicsize = PyLong_AsSsize_t(py_basicsize); - Py_DECREF(py_basicsize); - py_basicsize = NULL; - if (unlikely(basicsize == (Py_ssize_t)-1) && PyErr_Occurred()) return -1; -#else - basicsize = ((PyTypeObject*) cached_type)->tp_basicsize; -#endif - if (basicsize != expected_basicsize) { - PyErr_Format(PyExc_TypeError, - "Shared Cython type %.200s has the wrong size, try recompiling", - name); - return -1; - } - return 0; -} -static PyTypeObject *__Pyx_FetchCommonTypeFromSpec(PyTypeObject *metaclass, PyObject *module, PyType_Spec *spec, PyObject *bases) { - PyObject *abi_module = NULL, *cached_type = NULL, *abi_module_dict, *new_cached_type, *py_object_name; - int get_item_ref_result; - const char* object_name = strrchr(spec->name, '.'); - object_name = object_name ? object_name+1 : spec->name; - py_object_name = PyUnicode_FromString(object_name); - if (!py_object_name) return NULL; - abi_module = __Pyx_FetchSharedCythonABIModule(); - if (!abi_module) goto done; - abi_module_dict = PyModule_GetDict(abi_module); - if (!abi_module_dict) goto done; - get_item_ref_result = __Pyx_PyDict_GetItemRef(abi_module_dict, py_object_name, &cached_type); - if (get_item_ref_result == 1) { - if (__Pyx_VerifyCachedType( - cached_type, - object_name, - spec->basicsize) < 0) { - goto bad; - } - goto done; - } else if (unlikely(get_item_ref_result == -1)) { - goto bad; - } - CYTHON_UNUSED_VAR(module); - cached_type = __Pyx_PyType_FromMetaclass(metaclass, abi_module, spec, bases); - if (unlikely(!cached_type)) goto bad; - if (unlikely(__Pyx_fix_up_extension_type_from_spec(spec, (PyTypeObject *) cached_type) < 0)) goto bad; - new_cached_type = __Pyx_PyDict_SetDefault(abi_module_dict, py_object_name, cached_type, 1); - if (unlikely(new_cached_type != cached_type)) { - if (unlikely(!new_cached_type)) goto bad; - Py_DECREF(cached_type); - cached_type = new_cached_type; - if (__Pyx_VerifyCachedType( - cached_type, - object_name, - spec->basicsize) < 0) { - goto bad; - } - goto done; - } else { - Py_DECREF(new_cached_type); - } -done: - Py_XDECREF(abi_module); - Py_DECREF(py_object_name); - assert(cached_type == NULL || PyType_Check(cached_type)); - return (PyTypeObject *) cached_type; -bad: - Py_XDECREF(cached_type); - cached_type = NULL; - goto done; -} - -/* CommonTypesMetaclass */ -PyObject* __pyx_CommonTypesMetaclass_get_module(CYTHON_UNUSED PyObject *self, CYTHON_UNUSED void* context) { - return PyUnicode_FromString(__PYX_ABI_MODULE_NAME); -} -static PyGetSetDef __pyx_CommonTypesMetaclass_getset[] = { - {"__module__", __pyx_CommonTypesMetaclass_get_module, NULL, NULL, NULL}, - {0, 0, 0, 0, 0} -}; -static PyType_Slot __pyx_CommonTypesMetaclass_slots[] = { - {Py_tp_getset, (void *)__pyx_CommonTypesMetaclass_getset}, - {0, 0} -}; -static PyType_Spec __pyx_CommonTypesMetaclass_spec = { - __PYX_TYPE_MODULE_PREFIX "_common_types_metatype", - 0, - 0, -#if PY_VERSION_HEX >= 0x030A0000 - Py_TPFLAGS_IMMUTABLETYPE | - Py_TPFLAGS_DISALLOW_INSTANTIATION | -#endif - Py_TPFLAGS_DEFAULT, - __pyx_CommonTypesMetaclass_slots -}; -static int __pyx_CommonTypesMetaclass_init(PyObject *module) { - __pyx_mstatetype *mstate = __Pyx_PyModule_GetState(module); - PyObject *bases = PyTuple_Pack(1, &PyType_Type); - if (unlikely(!bases)) { - return -1; - } - mstate->__pyx_CommonTypesMetaclassType = __Pyx_FetchCommonTypeFromSpec(NULL, module, &__pyx_CommonTypesMetaclass_spec, bases); - if (unlikely(mstate->__pyx_CommonTypesMetaclassType == NULL)) { - return -1; - } - return 0; -} - -/* CallTypeTraverse */ -#if !CYTHON_USE_TYPE_SPECS || (!CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX < 0x03090000) -#else -static int __Pyx_call_type_traverse(PyObject *o, int always_call, visitproc visit, void *arg) { - #if CYTHON_COMPILING_IN_LIMITED_API && __PYX_LIMITED_VERSION_HEX < 0x03090000 - if (__Pyx_get_runtime_version() < 0x03090000) return 0; - #endif - if (!always_call) { - PyTypeObject *base = __Pyx_PyObject_GetSlot(o, tp_base, PyTypeObject*); - unsigned long flags = PyType_GetFlags(base); - if (flags & Py_TPFLAGS_HEAPTYPE) { - return 0; - } - } - Py_VISIT((PyObject*)Py_TYPE(o)); - return 0; -} -#endif - -/* PyMethodNew */ -#if CYTHON_COMPILING_IN_LIMITED_API -static PyObject *__Pyx_PyMethod_New(PyObject *func, PyObject *self, PyObject *typ) { - PyObject *result; - CYTHON_UNUSED_VAR(typ); - if (!self) - return __Pyx_NewRef(func); - #if __PYX_LIMITED_VERSION_HEX >= 0x030C0000 - { - PyObject *args[] = {func, self}; - result = PyObject_Vectorcall(__pyx_mstate_global->__Pyx_CachedMethodType, args, 2, NULL); - } - #else - result = PyObject_CallFunctionObjArgs(__pyx_mstate_global->__Pyx_CachedMethodType, func, self, NULL); - #endif - return result; -} -#else -static PyObject *__Pyx_PyMethod_New(PyObject *func, PyObject *self, PyObject *typ) { - CYTHON_UNUSED_VAR(typ); - if (!self) - return __Pyx_NewRef(func); - return PyMethod_New(func, self); -} -#endif - -/* PyVectorcallFastCallDict */ -#if CYTHON_METH_FASTCALL && (CYTHON_VECTORCALL || CYTHON_BACKPORT_VECTORCALL) -static PyObject *__Pyx_PyVectorcall_FastCallDict_kw(PyObject *func, __pyx_vectorcallfunc vc, PyObject *const *args, size_t nargs, PyObject *kw) -{ - PyObject *res = NULL; - PyObject *kwnames; - PyObject **newargs; - PyObject **kwvalues; - Py_ssize_t i, pos; - size_t j; - PyObject *key, *value; - unsigned long keys_are_strings; - #if !CYTHON_ASSUME_SAFE_SIZE - Py_ssize_t nkw = PyDict_Size(kw); - if (unlikely(nkw == -1)) return NULL; - #else - Py_ssize_t nkw = PyDict_GET_SIZE(kw); - #endif - newargs = (PyObject **)PyMem_Malloc((nargs + (size_t)nkw) * sizeof(args[0])); - if (unlikely(newargs == NULL)) { - PyErr_NoMemory(); - return NULL; - } - for (j = 0; j < nargs; j++) newargs[j] = args[j]; - kwnames = PyTuple_New(nkw); - if (unlikely(kwnames == NULL)) { - PyMem_Free(newargs); - return NULL; - } - kwvalues = newargs + nargs; - pos = i = 0; - keys_are_strings = Py_TPFLAGS_UNICODE_SUBCLASS; - while (PyDict_Next(kw, &pos, &key, &value)) { - keys_are_strings &= - #if CYTHON_COMPILING_IN_LIMITED_API - PyType_GetFlags(Py_TYPE(key)); - #else - Py_TYPE(key)->tp_flags; - #endif - Py_INCREF(key); - Py_INCREF(value); - #if !CYTHON_ASSUME_SAFE_MACROS - if (unlikely(PyTuple_SetItem(kwnames, i, key) < 0)) goto cleanup; - #else - PyTuple_SET_ITEM(kwnames, i, key); - #endif - kwvalues[i] = value; - i++; - } - if (unlikely(!keys_are_strings)) { - PyErr_SetString(PyExc_TypeError, "keywords must be strings"); - goto cleanup; - } - res = vc(func, newargs, nargs, kwnames); -cleanup: - Py_DECREF(kwnames); - for (i = 0; i < nkw; i++) - Py_DECREF(kwvalues[i]); - PyMem_Free(newargs); - return res; -} -static CYTHON_INLINE PyObject *__Pyx_PyVectorcall_FastCallDict(PyObject *func, __pyx_vectorcallfunc vc, PyObject *const *args, size_t nargs, PyObject *kw) -{ - Py_ssize_t kw_size = - likely(kw == NULL) ? - 0 : -#if !CYTHON_ASSUME_SAFE_SIZE - PyDict_Size(kw); -#else - PyDict_GET_SIZE(kw); -#endif - if (kw_size == 0) { - return vc(func, args, nargs, NULL); - } -#if !CYTHON_ASSUME_SAFE_SIZE - else if (unlikely(kw_size == -1)) { - return NULL; - } -#endif - return __Pyx_PyVectorcall_FastCallDict_kw(func, vc, args, nargs, kw); -} -#endif - -/* CythonFunctionShared */ -#if CYTHON_COMPILING_IN_LIMITED_API -static CYTHON_INLINE int __Pyx__IsSameCyOrCFunctionNoMethod(PyObject *func, void (*cfunc)(void)) { - if (__Pyx_CyFunction_Check(func)) { - return PyCFunction_GetFunction(((__pyx_CyFunctionObject*)func)->func) == (PyCFunction) cfunc; - } else if (PyCFunction_Check(func)) { - return PyCFunction_GetFunction(func) == (PyCFunction) cfunc; - } - return 0; -} -static CYTHON_INLINE int __Pyx__IsSameCyOrCFunction(PyObject *func, void (*cfunc)(void)) { - if ((PyObject*)Py_TYPE(func) == __pyx_mstate_global->__Pyx_CachedMethodType) { - int result; - PyObject *newFunc = PyObject_GetAttr(func, __pyx_mstate_global->__pyx_n_u_func); - if (unlikely(!newFunc)) { - PyErr_Clear(); // It's only an optimization, so don't throw an error - return 0; - } - result = __Pyx__IsSameCyOrCFunctionNoMethod(newFunc, cfunc); - Py_DECREF(newFunc); - return result; - } - return __Pyx__IsSameCyOrCFunctionNoMethod(func, cfunc); -} -#else -static CYTHON_INLINE int __Pyx__IsSameCyOrCFunction(PyObject *func, void (*cfunc)(void)) { - if (PyMethod_Check(func)) { - func = PyMethod_GET_FUNCTION(func); - } - return __Pyx_CyOrPyCFunction_Check(func) && __Pyx_CyOrPyCFunction_GET_FUNCTION(func) == (PyCFunction) cfunc; -} -#endif -static CYTHON_INLINE void __Pyx__CyFunction_SetClassObj(__pyx_CyFunctionObject* f, PyObject* classobj) { -#if PY_VERSION_HEX < 0x030900B1 || CYTHON_COMPILING_IN_LIMITED_API - __Pyx_Py_XDECREF_SET( - __Pyx_CyFunction_GetClassObj(f), - ((classobj) ? __Pyx_NewRef(classobj) : NULL)); -#else - __Pyx_Py_XDECREF_SET( - ((PyCMethodObject *) (f))->mm_class, - (PyTypeObject*)((classobj) ? __Pyx_NewRef(classobj) : NULL)); -#endif -} -static PyObject * -__Pyx_CyFunction_get_doc_locked(__pyx_CyFunctionObject *op) -{ - if (unlikely(op->func_doc == NULL)) { -#if CYTHON_COMPILING_IN_LIMITED_API - op->func_doc = PyObject_GetAttrString(op->func, "__doc__"); - if (unlikely(!op->func_doc)) return NULL; -#else - if (((PyCFunctionObject*)op)->m_ml->ml_doc) { - op->func_doc = PyUnicode_FromString(((PyCFunctionObject*)op)->m_ml->ml_doc); - if (unlikely(op->func_doc == NULL)) - return NULL; - } else { - Py_INCREF(Py_None); - return Py_None; - } -#endif - } - Py_INCREF(op->func_doc); - return op->func_doc; -} -static PyObject * -__Pyx_CyFunction_get_doc(__pyx_CyFunctionObject *op, void *closure) { - PyObject *result; - CYTHON_UNUSED_VAR(closure); - __Pyx_BEGIN_CRITICAL_SECTION(op); - result = __Pyx_CyFunction_get_doc_locked(op); - __Pyx_END_CRITICAL_SECTION(); - return result; -} -static int -__Pyx_CyFunction_set_doc(__pyx_CyFunctionObject *op, PyObject *value, void *context) -{ - CYTHON_UNUSED_VAR(context); - if (value == NULL) { - value = Py_None; - } - Py_INCREF(value); - __Pyx_BEGIN_CRITICAL_SECTION(op); - __Pyx_Py_XDECREF_SET(op->func_doc, value); - __Pyx_END_CRITICAL_SECTION(); - return 0; -} -static PyObject * -__Pyx_CyFunction_get_name_locked(__pyx_CyFunctionObject *op) -{ - if (unlikely(op->func_name == NULL)) { -#if CYTHON_COMPILING_IN_LIMITED_API - op->func_name = PyObject_GetAttrString(op->func, "__name__"); -#else - op->func_name = PyUnicode_InternFromString(((PyCFunctionObject*)op)->m_ml->ml_name); -#endif - if (unlikely(op->func_name == NULL)) - return NULL; - } - Py_INCREF(op->func_name); - return op->func_name; -} -static PyObject * -__Pyx_CyFunction_get_name(__pyx_CyFunctionObject *op, void *context) -{ - PyObject *result = NULL; - CYTHON_UNUSED_VAR(context); - __Pyx_BEGIN_CRITICAL_SECTION(op); - result = __Pyx_CyFunction_get_name_locked(op); - __Pyx_END_CRITICAL_SECTION(); - return result; -} -static int -__Pyx_CyFunction_set_name(__pyx_CyFunctionObject *op, PyObject *value, void *context) -{ - CYTHON_UNUSED_VAR(context); - if (unlikely(value == NULL || !PyUnicode_Check(value))) { - PyErr_SetString(PyExc_TypeError, - "__name__ must be set to a string object"); - return -1; - } - Py_INCREF(value); - __Pyx_BEGIN_CRITICAL_SECTION(op); - __Pyx_Py_XDECREF_SET(op->func_name, value); - __Pyx_END_CRITICAL_SECTION(); - return 0; -} -static PyObject * -__Pyx_CyFunction_get_qualname(__pyx_CyFunctionObject *op, void *context) -{ - CYTHON_UNUSED_VAR(context); - PyObject *result; - __Pyx_BEGIN_CRITICAL_SECTION(op); - Py_INCREF(op->func_qualname); - result = op->func_qualname; - __Pyx_END_CRITICAL_SECTION(); - return result; -} -static int -__Pyx_CyFunction_set_qualname(__pyx_CyFunctionObject *op, PyObject *value, void *context) -{ - CYTHON_UNUSED_VAR(context); - if (unlikely(value == NULL || !PyUnicode_Check(value))) { - PyErr_SetString(PyExc_TypeError, - "__qualname__ must be set to a string object"); - return -1; - } - Py_INCREF(value); - __Pyx_BEGIN_CRITICAL_SECTION(op); - __Pyx_Py_XDECREF_SET(op->func_qualname, value); - __Pyx_END_CRITICAL_SECTION(); - return 0; -} -static PyObject * -__Pyx_CyFunction_get_dict_locked(__pyx_CyFunctionObject *op) -{ - if (unlikely(op->func_dict == NULL)) { - op->func_dict = PyDict_New(); - if (unlikely(op->func_dict == NULL)) - return NULL; - } - Py_INCREF(op->func_dict); - return op->func_dict; -} -static PyObject * -__Pyx_CyFunction_get_dict(__pyx_CyFunctionObject *op, void *context) -{ - CYTHON_UNUSED_VAR(context); - PyObject *result; - __Pyx_BEGIN_CRITICAL_SECTION(op); - result = __Pyx_CyFunction_get_dict_locked(op); - __Pyx_END_CRITICAL_SECTION(); - return result; -} -static int -__Pyx_CyFunction_set_dict(__pyx_CyFunctionObject *op, PyObject *value, void *context) -{ - CYTHON_UNUSED_VAR(context); - if (unlikely(value == NULL)) { - PyErr_SetString(PyExc_TypeError, - "function's dictionary may not be deleted"); - return -1; - } - if (unlikely(!PyDict_Check(value))) { - PyErr_SetString(PyExc_TypeError, - "setting function's dictionary to a non-dict"); - return -1; - } - Py_INCREF(value); - __Pyx_BEGIN_CRITICAL_SECTION(op); - __Pyx_Py_XDECREF_SET(op->func_dict, value); - __Pyx_END_CRITICAL_SECTION(); - return 0; -} -static PyObject * -__Pyx_CyFunction_get_globals(__pyx_CyFunctionObject *op, void *context) -{ - CYTHON_UNUSED_VAR(context); - Py_INCREF(op->func_globals); - return op->func_globals; -} -static PyObject * -__Pyx_CyFunction_get_closure(__pyx_CyFunctionObject *op, void *context) -{ - CYTHON_UNUSED_VAR(op); - CYTHON_UNUSED_VAR(context); - Py_INCREF(Py_None); - return Py_None; -} -static PyObject * -__Pyx_CyFunction_get_code(__pyx_CyFunctionObject *op, void *context) -{ - PyObject* result = (op->func_code) ? op->func_code : Py_None; - CYTHON_UNUSED_VAR(context); - Py_INCREF(result); - return result; -} -static int -__Pyx_CyFunction_init_defaults(__pyx_CyFunctionObject *op) { - int result = 0; - PyObject *res = op->defaults_getter((PyObject *) op); - if (unlikely(!res)) - return -1; - #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS - op->defaults_tuple = PyTuple_GET_ITEM(res, 0); - Py_INCREF(op->defaults_tuple); - op->defaults_kwdict = PyTuple_GET_ITEM(res, 1); - Py_INCREF(op->defaults_kwdict); - #else - op->defaults_tuple = __Pyx_PySequence_ITEM(res, 0); - if (unlikely(!op->defaults_tuple)) result = -1; - else { - op->defaults_kwdict = __Pyx_PySequence_ITEM(res, 1); - if (unlikely(!op->defaults_kwdict)) result = -1; - } - #endif - Py_DECREF(res); - return result; -} -static int -__Pyx_CyFunction_set_defaults(__pyx_CyFunctionObject *op, PyObject* value, void *context) { - CYTHON_UNUSED_VAR(context); - if (!value) { - value = Py_None; - } else if (unlikely(value != Py_None && !PyTuple_Check(value))) { - PyErr_SetString(PyExc_TypeError, - "__defaults__ must be set to a tuple object"); - return -1; - } - PyErr_WarnEx(PyExc_RuntimeWarning, "changes to cyfunction.__defaults__ will not " - "currently affect the values used in function calls", 1); - Py_INCREF(value); - __Pyx_BEGIN_CRITICAL_SECTION(op); - __Pyx_Py_XDECREF_SET(op->defaults_tuple, value); - __Pyx_END_CRITICAL_SECTION(); - return 0; -} -static PyObject * -__Pyx_CyFunction_get_defaults_locked(__pyx_CyFunctionObject *op) { - PyObject* result = op->defaults_tuple; - if (unlikely(!result)) { - if (op->defaults_getter) { - if (unlikely(__Pyx_CyFunction_init_defaults(op) < 0)) return NULL; - result = op->defaults_tuple; - } else { - result = Py_None; - } - } - Py_INCREF(result); - return result; -} -static PyObject * -__Pyx_CyFunction_get_defaults(__pyx_CyFunctionObject *op, void *context) { - PyObject* result = NULL; - CYTHON_UNUSED_VAR(context); - __Pyx_BEGIN_CRITICAL_SECTION(op); - result = __Pyx_CyFunction_get_defaults_locked(op); - __Pyx_END_CRITICAL_SECTION(); - return result; -} -static int -__Pyx_CyFunction_set_kwdefaults(__pyx_CyFunctionObject *op, PyObject* value, void *context) { - CYTHON_UNUSED_VAR(context); - if (!value) { - value = Py_None; - } else if (unlikely(value != Py_None && !PyDict_Check(value))) { - PyErr_SetString(PyExc_TypeError, - "__kwdefaults__ must be set to a dict object"); - return -1; - } - PyErr_WarnEx(PyExc_RuntimeWarning, "changes to cyfunction.__kwdefaults__ will not " - "currently affect the values used in function calls", 1); - Py_INCREF(value); - __Pyx_BEGIN_CRITICAL_SECTION(op); - __Pyx_Py_XDECREF_SET(op->defaults_kwdict, value); - __Pyx_END_CRITICAL_SECTION(); - return 0; -} -static PyObject * -__Pyx_CyFunction_get_kwdefaults_locked(__pyx_CyFunctionObject *op) { - PyObject* result = op->defaults_kwdict; - if (unlikely(!result)) { - if (op->defaults_getter) { - if (unlikely(__Pyx_CyFunction_init_defaults(op) < 0)) return NULL; - result = op->defaults_kwdict; - } else { - result = Py_None; - } - } - Py_INCREF(result); - return result; -} -static PyObject * -__Pyx_CyFunction_get_kwdefaults(__pyx_CyFunctionObject *op, void *context) { - PyObject* result; - CYTHON_UNUSED_VAR(context); - __Pyx_BEGIN_CRITICAL_SECTION(op); - result = __Pyx_CyFunction_get_kwdefaults_locked(op); - __Pyx_END_CRITICAL_SECTION(); - return result; -} -static int -__Pyx_CyFunction_set_annotations(__pyx_CyFunctionObject *op, PyObject* value, void *context) { - CYTHON_UNUSED_VAR(context); - if (!value || value == Py_None) { - value = NULL; - } else if (unlikely(!PyDict_Check(value))) { - PyErr_SetString(PyExc_TypeError, - "__annotations__ must be set to a dict object"); - return -1; - } - Py_XINCREF(value); - __Pyx_BEGIN_CRITICAL_SECTION(op); - __Pyx_Py_XDECREF_SET(op->func_annotations, value); - __Pyx_END_CRITICAL_SECTION(); - return 0; -} -static PyObject * -__Pyx_CyFunction_get_annotations_locked(__pyx_CyFunctionObject *op) { - PyObject* result = op->func_annotations; - if (unlikely(!result)) { - result = PyDict_New(); - if (unlikely(!result)) return NULL; - op->func_annotations = result; - } - Py_INCREF(result); - return result; -} -static PyObject * -__Pyx_CyFunction_get_annotations(__pyx_CyFunctionObject *op, void *context) { - PyObject *result; - CYTHON_UNUSED_VAR(context); - __Pyx_BEGIN_CRITICAL_SECTION(op); - result = __Pyx_CyFunction_get_annotations_locked(op); - __Pyx_END_CRITICAL_SECTION(); - return result; -} -static PyObject * -__Pyx_CyFunction_get_is_coroutine_value(__pyx_CyFunctionObject *op) { - int is_coroutine = op->flags & __Pyx_CYFUNCTION_COROUTINE; 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- nargs -= 1; - break; - case 0: -#if CYTHON_COMPILING_IN_LIMITED_API - self = PyCFunction_GetSelf(((__pyx_CyFunctionObject*)cyfunc)->func); - if (unlikely(!self) && PyErr_Occurred()) return NULL; -#else - self = ((PyCFunctionObject*)cyfunc)->m_self; -#endif - break; - default: - return NULL; - } - if (unlikely(nargs != 1)) { - __Pyx_CyFunction_raise_argument_count_error( - cyfunc, "takes exactly one argument", nargs); - return NULL; - } - return meth(self, args[0]); -} -static PyObject * __Pyx_CyFunction_Vectorcall_FASTCALL_KEYWORDS(PyObject *func, PyObject *const *args, size_t nargsf, PyObject *kwnames) -{ - __pyx_CyFunctionObject *cyfunc = (__pyx_CyFunctionObject *)func; -#if CYTHON_BACKPORT_VECTORCALL - Py_ssize_t nargs = (Py_ssize_t)nargsf; -#else - Py_ssize_t nargs = PyVectorcall_NARGS(nargsf); -#endif - PyObject *self; -#if CYTHON_COMPILING_IN_LIMITED_API - PyCFunction meth = PyCFunction_GetFunction(cyfunc->func); - if (unlikely(!meth)) return NULL; -#else - PyCFunction meth = ((PyCFunctionObject*)cyfunc)->m_ml->ml_meth; -#endif - switch (__Pyx_CyFunction_Vectorcall_CheckArgs(cyfunc, nargs, NULL)) { - case 1: - self = args[0]; - args += 1; - nargs -= 1; - break; - case 0: -#if CYTHON_COMPILING_IN_LIMITED_API - self = PyCFunction_GetSelf(((__pyx_CyFunctionObject*)cyfunc)->func); - if (unlikely(!self) && PyErr_Occurred()) return NULL; -#else - self = ((PyCFunctionObject*)cyfunc)->m_self; -#endif - break; - default: - return NULL; - } - return ((__Pyx_PyCFunctionFastWithKeywords)(void(*)(void))meth)(self, args, nargs, kwnames); -} -static PyObject * __Pyx_CyFunction_Vectorcall_FASTCALL_KEYWORDS_METHOD(PyObject *func, PyObject *const *args, size_t nargsf, PyObject *kwnames) -{ - __pyx_CyFunctionObject *cyfunc = (__pyx_CyFunctionObject *)func; - PyTypeObject *cls = (PyTypeObject *) __Pyx_CyFunction_GetClassObj(cyfunc); -#if CYTHON_BACKPORT_VECTORCALL - Py_ssize_t nargs = (Py_ssize_t)nargsf; -#else - Py_ssize_t nargs = PyVectorcall_NARGS(nargsf); -#endif - PyObject *self; -#if CYTHON_COMPILING_IN_LIMITED_API - PyCFunction meth = PyCFunction_GetFunction(cyfunc->func); - if (unlikely(!meth)) return NULL; -#else - PyCFunction meth = ((PyCFunctionObject*)cyfunc)->m_ml->ml_meth; -#endif - switch (__Pyx_CyFunction_Vectorcall_CheckArgs(cyfunc, nargs, NULL)) { - case 1: - self = args[0]; - args += 1; - nargs -= 1; - break; - case 0: -#if CYTHON_COMPILING_IN_LIMITED_API - self = PyCFunction_GetSelf(((__pyx_CyFunctionObject*)cyfunc)->func); - if (unlikely(!self) && PyErr_Occurred()) return NULL; -#else - self = ((PyCFunctionObject*)cyfunc)->m_self; -#endif - break; - default: - return NULL; - } - return ((__Pyx_PyCMethod)(void(*)(void))meth)(self, cls, args, (size_t)nargs, kwnames); -} -#endif -static PyType_Slot __pyx_CyFunctionType_slots[] = { - {Py_tp_dealloc, (void *)__Pyx_CyFunction_dealloc}, - {Py_tp_repr, (void *)__Pyx_CyFunction_repr}, - {Py_tp_call, (void *)__Pyx_CyFunction_CallAsMethod}, - {Py_tp_traverse, (void *)__Pyx_CyFunction_traverse}, - {Py_tp_clear, (void *)__Pyx_CyFunction_clear}, - {Py_tp_methods, (void *)__pyx_CyFunction_methods}, - {Py_tp_members, (void *)__pyx_CyFunction_members}, - {Py_tp_getset, (void *)__pyx_CyFunction_getsets}, - {Py_tp_descr_get, (void *)__Pyx_PyMethod_New}, - {0, 0}, -}; -static PyType_Spec __pyx_CyFunctionType_spec = { - __PYX_TYPE_MODULE_PREFIX "cython_function_or_method", - sizeof(__pyx_CyFunctionObject), - 0, -#ifdef Py_TPFLAGS_METHOD_DESCRIPTOR - Py_TPFLAGS_METHOD_DESCRIPTOR | -#endif -#if CYTHON_METH_FASTCALL -#if defined(Py_TPFLAGS_HAVE_VECTORCALL) - Py_TPFLAGS_HAVE_VECTORCALL | -#elif defined(_Py_TPFLAGS_HAVE_VECTORCALL) - _Py_TPFLAGS_HAVE_VECTORCALL | -#endif -#endif // CYTHON_METH_FASTCALL -#if PY_VERSION_HEX >= 0x030A0000 - Py_TPFLAGS_IMMUTABLETYPE | -#endif - Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC | Py_TPFLAGS_BASETYPE, - __pyx_CyFunctionType_slots -}; -static int __pyx_CyFunction_init(PyObject *module) { - __pyx_mstatetype *mstate = __Pyx_PyModule_GetState(module); - mstate->__pyx_CyFunctionType = __Pyx_FetchCommonTypeFromSpec( - mstate->__pyx_CommonTypesMetaclassType, module, &__pyx_CyFunctionType_spec, NULL); - if (unlikely(mstate->__pyx_CyFunctionType == NULL)) { - return -1; - } - return 0; -} -static CYTHON_INLINE PyObject *__Pyx_CyFunction_InitDefaults(PyObject *func, PyTypeObject *defaults_type) { - __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; - m->defaults = PyObject_CallObject((PyObject*)defaults_type, NULL); // _PyObject_New(defaults_type); - if (unlikely(!m->defaults)) - return NULL; - return m->defaults; -} -static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsTuple(PyObject *func, PyObject *tuple) { - __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; - m->defaults_tuple = tuple; - Py_INCREF(tuple); -} -static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsKwDict(PyObject *func, PyObject *dict) { - __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; - m->defaults_kwdict = dict; - Py_INCREF(dict); -} -static CYTHON_INLINE void __Pyx_CyFunction_SetAnnotationsDict(PyObject *func, PyObject *dict) { - __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; - m->func_annotations = dict; - Py_INCREF(dict); -} - -/* CythonFunction */ -static PyObject *__Pyx_CyFunction_New(PyMethodDef *ml, int flags, PyObject* qualname, - PyObject *closure, PyObject *module, PyObject* globals, PyObject* code) { - PyObject *op = __Pyx_CyFunction_Init( - PyObject_GC_New(__pyx_CyFunctionObject, __pyx_mstate_global->__pyx_CyFunctionType), - ml, flags, qualname, closure, module, globals, code - ); - if (likely(op)) { - PyObject_GC_Track(op); - } - return op; -} - -/* Py3UpdateBases */ -static PyObject* -__Pyx_PEP560_update_bases(PyObject *bases) -{ - Py_ssize_t i, j, size_bases; - PyObject *base = NULL, *meth, *new_base, *result, *new_bases = NULL; -#if CYTHON_ASSUME_SAFE_SIZE - size_bases = PyTuple_GET_SIZE(bases); -#else - size_bases = PyTuple_Size(bases); - if (size_bases < 0) return NULL; -#endif - for (i = 0; i < size_bases; i++) { -#if CYTHON_AVOID_BORROWED_REFS - Py_CLEAR(base); -#endif -#if CYTHON_ASSUME_SAFE_MACROS - base = PyTuple_GET_ITEM(bases, i); -#else - base = PyTuple_GetItem(bases, i); - if (!base) goto error; -#endif -#if CYTHON_AVOID_BORROWED_REFS - Py_INCREF(base); -#endif - if (PyType_Check(base)) { - if (new_bases) { - if (PyList_Append(new_bases, base) < 0) { - goto error; - } - } - continue; - } - meth = __Pyx_PyObject_GetAttrStrNoError(base, __pyx_mstate_global->__pyx_n_u_mro_entries); - if (!meth && PyErr_Occurred()) { - goto error; - } - if (!meth) { - if (new_bases) { - if (PyList_Append(new_bases, base) < 0) { - goto error; - } - } - continue; - } - new_base = __Pyx_PyObject_CallOneArg(meth, bases); - Py_DECREF(meth); - if (!new_base) { - goto error; - } - if (!PyTuple_Check(new_base)) { - PyErr_SetString(PyExc_TypeError, - "__mro_entries__ must return a tuple"); - Py_DECREF(new_base); - goto error; - } - if (!new_bases) { - if (!(new_bases = PyList_New(i))) { - goto error; - } - for (j = 0; j < i; j++) { - PyObject *base_from_list; -#if CYTHON_ASSUME_SAFE_MACROS - base_from_list = PyTuple_GET_ITEM(bases, j); - PyList_SET_ITEM(new_bases, j, base_from_list); - Py_INCREF(base_from_list); -#else - base_from_list = PyTuple_GetItem(bases, j); - if (!base_from_list) goto error; - Py_INCREF(base_from_list); - if (PyList_SetItem(new_bases, j, base_from_list) < 0) goto error; -#endif - } - } -#if CYTHON_ASSUME_SAFE_SIZE - j = PyList_GET_SIZE(new_bases); -#else - j = PyList_Size(new_bases); - if (j < 0) goto error; -#endif - if (PyList_SetSlice(new_bases, j, j, new_base) < 0) { - goto error; - } - Py_DECREF(new_base); - } - if (!new_bases) { - Py_INCREF(bases); - return bases; - } - result = PyList_AsTuple(new_bases); - Py_DECREF(new_bases); -#if CYTHON_AVOID_BORROWED_REFS - Py_XDECREF(base); -#endif - return result; -error: - Py_XDECREF(new_bases); -#if CYTHON_AVOID_BORROWED_REFS - Py_XDECREF(base); -#endif - return NULL; -} - -/* CalculateMetaclass */ -static PyObject *__Pyx_CalculateMetaclass(PyTypeObject *metaclass, PyObject *bases) { - Py_ssize_t i, nbases; -#if CYTHON_ASSUME_SAFE_SIZE - nbases = PyTuple_GET_SIZE(bases); -#else - nbases = PyTuple_Size(bases); - if (nbases < 0) return NULL; -#endif - for (i=0; i < nbases; i++) { - PyTypeObject *tmptype; -#if CYTHON_ASSUME_SAFE_MACROS - PyObject *tmp = PyTuple_GET_ITEM(bases, i); -#else - PyObject *tmp = PyTuple_GetItem(bases, i); - if (!tmp) return NULL; -#endif - tmptype = Py_TYPE(tmp); - if (!metaclass) { - metaclass = tmptype; - continue; - } - if (PyType_IsSubtype(metaclass, tmptype)) - continue; - if (PyType_IsSubtype(tmptype, metaclass)) { - metaclass = tmptype; - continue; - } - PyErr_SetString(PyExc_TypeError, - "metaclass conflict: " - "the metaclass of a derived class " - "must be a (non-strict) subclass " - "of the metaclasses of all its bases"); - return NULL; - } - if (!metaclass) { - metaclass = &PyType_Type; - } - Py_INCREF((PyObject*) metaclass); - return (PyObject*) metaclass; -} - -/* PyObjectCall2Args */ -static CYTHON_INLINE PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { - PyObject *args[3] = {NULL, arg1, arg2}; - return __Pyx_PyObject_FastCall(function, args+1, 2 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET); -} - -/* PyObjectLookupSpecial */ -#if CYTHON_USE_PYTYPE_LOOKUP && CYTHON_USE_TYPE_SLOTS -static CYTHON_INLINE PyObject* __Pyx__PyObject_LookupSpecial(PyObject* obj, PyObject* attr_name, int with_error) { - PyObject *res; - PyTypeObject *tp = Py_TYPE(obj); - res = _PyType_Lookup(tp, attr_name); - if (likely(res)) { - descrgetfunc f = Py_TYPE(res)->tp_descr_get; - if (!f) { - Py_INCREF(res); - } else { - res = f(res, obj, (PyObject *)tp); - } - } else if (with_error) { - PyErr_SetObject(PyExc_AttributeError, attr_name); - } - return res; -} -#endif - -/* Py3ClassCreate */ -static PyObject *__Pyx_Py3MetaclassPrepare(PyObject *metaclass, PyObject *bases, PyObject *name, - PyObject *qualname, PyObject *mkw, PyObject *modname, PyObject *doc) { - PyObject *ns; - if (metaclass) { - PyObject *prep = __Pyx_PyObject_GetAttrStrNoError(metaclass, __pyx_mstate_global->__pyx_n_u_prepare); - if (prep) { - PyObject *pargs[3] = {NULL, name, bases}; - ns = __Pyx_PyObject_FastCallDict(prep, pargs+1, 2 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET, mkw); - Py_DECREF(prep); - } else { - if (unlikely(PyErr_Occurred())) - return NULL; - ns = PyDict_New(); - } - } else { - ns = PyDict_New(); - } - if (unlikely(!ns)) - return NULL; - if (unlikely(PyObject_SetItem(ns, __pyx_mstate_global->__pyx_n_u_module, modname) < 0)) goto bad; - if (unlikely(PyObject_SetItem(ns, __pyx_mstate_global->__pyx_n_u_qualname, qualname) < 0)) goto bad; - if (unlikely(doc && PyObject_SetItem(ns, __pyx_mstate_global->__pyx_n_u_doc, doc) < 0)) goto bad; - return ns; -bad: - Py_DECREF(ns); - return NULL; -} -static PyObject *__Pyx_Py3ClassCreate(PyObject *metaclass, PyObject *name, PyObject *bases, - PyObject *dict, PyObject *mkw, - int calculate_metaclass, int allow_py2_metaclass) { - PyObject *result; - PyObject *owned_metaclass = NULL; - PyObject *margs[4] = {NULL, name, bases, dict}; - if (allow_py2_metaclass) { - owned_metaclass = PyObject_GetItem(dict, __pyx_mstate_global->__pyx_n_u_metaclass); - if (owned_metaclass) { - metaclass = owned_metaclass; - } else if (likely(PyErr_ExceptionMatches(PyExc_KeyError))) { - PyErr_Clear(); - } else { - return NULL; - } - } - if (calculate_metaclass && (!metaclass || PyType_Check(metaclass))) { - metaclass = __Pyx_CalculateMetaclass((PyTypeObject*) metaclass, bases); - Py_XDECREF(owned_metaclass); - if (unlikely(!metaclass)) - return NULL; - owned_metaclass = metaclass; - } - result = __Pyx_PyObject_FastCallDict(metaclass, margs+1, 3 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET, mkw); - Py_XDECREF(owned_metaclass); - return result; -} - -/* ListPack */ -static PyObject *__Pyx_PyList_Pack(Py_ssize_t n, ...) { - va_list va; - PyObject *l = PyList_New(n); - va_start(va, n); - if (unlikely(!l)) goto end; - for (Py_ssize_t i=0; i__pyx_d, empty_dict, from_list, 1); - if (unlikely(!module)) { - if (unlikely(!PyErr_ExceptionMatches(PyExc_ImportError))) - goto bad; - PyErr_Clear(); - } - } - level = 0; - } - if (!module) { - module = PyImport_ImportModuleLevelObject( - name, __pyx_mstate_global->__pyx_d, empty_dict, from_list, level); - } -bad: - Py_XDECREF(empty_dict); - Py_XDECREF(empty_list); - return module; -} - -/* ImportFrom */ -static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) { - PyObject* value = __Pyx_PyObject_GetAttrStr(module, name); - if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) { - const char* module_name_str = 0; - PyObject* module_name = 0; - PyObject* module_dot = 0; - PyObject* full_name = 0; - PyErr_Clear(); - module_name_str = PyModule_GetName(module); - if (unlikely(!module_name_str)) { goto modbad; } - module_name = PyUnicode_FromString(module_name_str); - if (unlikely(!module_name)) { goto modbad; } - module_dot = PyUnicode_Concat(module_name, __pyx_mstate_global->__pyx_kp_u__14); - if (unlikely(!module_dot)) { goto modbad; } - full_name = PyUnicode_Concat(module_dot, name); - if (unlikely(!full_name)) { goto modbad; } - #if (CYTHON_COMPILING_IN_PYPY && PYPY_VERSION_NUM < 0x07030400) ||\ - CYTHON_COMPILING_IN_GRAAL - { - PyObject *modules = PyImport_GetModuleDict(); - if (unlikely(!modules)) - goto modbad; - value = PyObject_GetItem(modules, full_name); - } - #else - value = PyImport_GetModule(full_name); - #endif - modbad: - Py_XDECREF(full_name); - Py_XDECREF(module_dot); - Py_XDECREF(module_name); - } - if (unlikely(!value)) { - PyErr_Format(PyExc_ImportError, "cannot import name %S", name); - } - return value; -} - -/* ImportDottedModule */ -static PyObject *__Pyx__ImportDottedModule_Error(PyObject *name, PyObject *parts_tuple, Py_ssize_t count) { - PyObject *partial_name = NULL, *slice = NULL, *sep = NULL; - Py_ssize_t size; - if (unlikely(PyErr_Occurred())) { - PyErr_Clear(); - } -#if CYTHON_ASSUME_SAFE_SIZE - size = PyTuple_GET_SIZE(parts_tuple); -#else - size = PyTuple_Size(parts_tuple); - if (size < 0) goto bad; -#endif - if (likely(size == count)) { - partial_name = name; - } else { - slice = PySequence_GetSlice(parts_tuple, 0, count); - if (unlikely(!slice)) - goto bad; - sep = PyUnicode_FromStringAndSize(".", 1); - if (unlikely(!sep)) - goto bad; - partial_name = PyUnicode_Join(sep, slice); - } - PyErr_Format( - PyExc_ModuleNotFoundError, - "No module named '%U'", partial_name); -bad: - Py_XDECREF(sep); - Py_XDECREF(slice); - Py_XDECREF(partial_name); - return NULL; -} -static PyObject *__Pyx__ImportDottedModule_Lookup(PyObject *name) { - PyObject *imported_module; -#if (CYTHON_COMPILING_IN_PYPY && PYPY_VERSION_NUM < 0x07030400) ||\ - CYTHON_COMPILING_IN_GRAAL - PyObject *modules = PyImport_GetModuleDict(); - if (unlikely(!modules)) - return NULL; - imported_module = __Pyx_PyDict_GetItemStr(modules, name); - Py_XINCREF(imported_module); -#else - imported_module = PyImport_GetModule(name); -#endif - return imported_module; -} -static PyObject *__Pyx_ImportDottedModule_WalkParts(PyObject *module, PyObject *name, PyObject *parts_tuple) { - Py_ssize_t i, nparts; -#if CYTHON_ASSUME_SAFE_SIZE - nparts = PyTuple_GET_SIZE(parts_tuple); -#else - nparts = PyTuple_Size(parts_tuple); - if (nparts < 0) return NULL; -#endif - for (i=1; i < nparts && module; i++) { - PyObject *part, *submodule; -#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS - part = PyTuple_GET_ITEM(parts_tuple, i); -#else - part = __Pyx_PySequence_ITEM(parts_tuple, i); - if (!part) return NULL; -#endif - submodule = __Pyx_PyObject_GetAttrStrNoError(module, part); -#if !(CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS) - Py_DECREF(part); -#endif - Py_DECREF(module); - module = submodule; - } - if (unlikely(!module)) { - return __Pyx__ImportDottedModule_Error(name, parts_tuple, i); - } - return module; -} -static PyObject *__Pyx__ImportDottedModule(PyObject *name, PyObject *parts_tuple) { - PyObject *imported_module; - PyObject *module = __Pyx_Import(name, NULL, 0); - if (!parts_tuple || unlikely(!module)) - return module; - imported_module = __Pyx__ImportDottedModule_Lookup(name); - if (likely(imported_module)) { - Py_DECREF(module); - return imported_module; - } - PyErr_Clear(); - return __Pyx_ImportDottedModule_WalkParts(module, name, parts_tuple); -} -static PyObject *__Pyx_ImportDottedModule(PyObject *name, PyObject *parts_tuple) { -#if CYTHON_COMPILING_IN_CPYTHON - PyObject *module = __Pyx__ImportDottedModule_Lookup(name); - if (likely(module)) { - PyObject *spec = __Pyx_PyObject_GetAttrStrNoError(module, __pyx_mstate_global->__pyx_n_u_spec); - if (likely(spec)) { - PyObject *unsafe = __Pyx_PyObject_GetAttrStrNoError(spec, __pyx_mstate_global->__pyx_n_u_initializing); - if (likely(!unsafe || !__Pyx_PyObject_IsTrue(unsafe))) { - Py_DECREF(spec); - spec = NULL; - } - Py_XDECREF(unsafe); - } - if (likely(!spec)) { - PyErr_Clear(); - return module; - } - Py_DECREF(spec); - Py_DECREF(module); - } else if (PyErr_Occurred()) { - PyErr_Clear(); - } -#endif - return __Pyx__ImportDottedModule(name, parts_tuple); -} - -/* ImportDottedModuleRelFirst */ -static PyObject *__Pyx_ImportDottedModuleRelFirst(PyObject *name, PyObject *parts_tuple) { - PyObject *module; - PyObject *from_list = NULL; - module = __Pyx_Import(name, from_list, -1); - Py_XDECREF(from_list); - if (module) { - if (parts_tuple) { - module = __Pyx_ImportDottedModule_WalkParts(module, name, parts_tuple); - } - return module; - } - if (unlikely(!PyErr_ExceptionMatches(PyExc_ImportError))) - return NULL; - PyErr_Clear(); - return __Pyx_ImportDottedModule(name, parts_tuple); -} - -/* PyObjectCallMethod1 */ -#if !(CYTHON_VECTORCALL && __PYX_LIMITED_VERSION_HEX >= 0x030C0000) -static PyObject* __Pyx__PyObject_CallMethod1(PyObject* method, PyObject* arg) { - PyObject *result = __Pyx_PyObject_CallOneArg(method, arg); - Py_DECREF(method); - return result; -} -#endif -static PyObject* __Pyx_PyObject_CallMethod1(PyObject* obj, PyObject* method_name, PyObject* arg) { -#if CYTHON_VECTORCALL && __PYX_LIMITED_VERSION_HEX >= 0x030C0000 - PyObject *args[2] = {obj, arg}; - (void) __Pyx_PyObject_GetMethod; - (void) __Pyx_PyObject_CallOneArg; - (void) __Pyx_PyObject_Call2Args; - return PyObject_VectorcallMethod(method_name, args, 2 | PY_VECTORCALL_ARGUMENTS_OFFSET, NULL); -#else - PyObject *method = NULL, *result; - int is_method = __Pyx_PyObject_GetMethod(obj, method_name, &method); - if (likely(is_method)) { - result = __Pyx_PyObject_Call2Args(method, obj, arg); - Py_DECREF(method); - return result; - } - if (unlikely(!method)) return NULL; - return __Pyx__PyObject_CallMethod1(method, arg); -#endif -} - -/* append */ -static CYTHON_INLINE int __Pyx_PyObject_Append(PyObject* L, PyObject* x) { - if (likely(PyList_CheckExact(L))) { - if (unlikely(__Pyx_PyList_Append(L, x) < 0)) return -1; - } else { - PyObject* retval = __Pyx_PyObject_CallMethod1(L, __pyx_mstate_global->__pyx_n_u_append, x); - if (unlikely(!retval)) - return -1; - Py_DECREF(retval); - } - return 0; -} - -/* CLineInTraceback */ -#if CYTHON_CLINE_IN_TRACEBACK && CYTHON_CLINE_IN_TRACEBACK_RUNTIME -static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line) { - PyObject *use_cline; - PyObject *ptype, *pvalue, *ptraceback; -#if CYTHON_COMPILING_IN_CPYTHON - PyObject **cython_runtime_dict; -#endif - CYTHON_MAYBE_UNUSED_VAR(tstate); - if (unlikely(!__pyx_mstate_global->__pyx_cython_runtime)) { - return c_line; - } - __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); -#if CYTHON_COMPILING_IN_CPYTHON - cython_runtime_dict = _PyObject_GetDictPtr(__pyx_mstate_global->__pyx_cython_runtime); - if (likely(cython_runtime_dict)) { - __Pyx_BEGIN_CRITICAL_SECTION(*cython_runtime_dict); - __PYX_PY_DICT_LOOKUP_IF_MODIFIED( - use_cline, *cython_runtime_dict, - __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_mstate_global->__pyx_n_u_cline_in_traceback)) - Py_XINCREF(use_cline); - __Pyx_END_CRITICAL_SECTION(); - } else -#endif - { - PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStrNoError(__pyx_mstate_global->__pyx_cython_runtime, __pyx_mstate_global->__pyx_n_u_cline_in_traceback); - if (use_cline_obj) { - use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; - Py_INCREF(use_cline); - Py_DECREF(use_cline_obj); - } else { - PyErr_Clear(); - use_cline = NULL; - } - } - if (!use_cline) { - c_line = 0; - (void) PyObject_SetAttr(__pyx_mstate_global->__pyx_cython_runtime, __pyx_mstate_global->__pyx_n_u_cline_in_traceback, Py_False); - } - else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { - c_line = 0; - } - Py_XDECREF(use_cline); - __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); - return c_line; -} -#endif - -/* CodeObjectCache */ -static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { - int start = 0, mid = 0, end = count - 1; - if (end >= 0 && code_line > entries[end].code_line) { - return count; - } - while (start < end) { - mid = start + (end - start) / 2; - if (code_line < entries[mid].code_line) { - end = mid; - } else if (code_line > entries[mid].code_line) { - start = mid + 1; - } else { - return mid; - } - } - if (code_line <= entries[mid].code_line) { - return mid; - } else { - return mid + 1; - } -} -static __Pyx_CachedCodeObjectType *__pyx__find_code_object(struct __Pyx_CodeObjectCache *code_cache, int code_line) { - __Pyx_CachedCodeObjectType* code_object; - int pos; - if (unlikely(!code_line) || unlikely(!code_cache->entries)) { - return NULL; - } - pos = __pyx_bisect_code_objects(code_cache->entries, code_cache->count, code_line); - if (unlikely(pos >= code_cache->count) || unlikely(code_cache->entries[pos].code_line != code_line)) { - return NULL; - } - code_object = code_cache->entries[pos].code_object; - Py_INCREF(code_object); - return code_object; -} -static __Pyx_CachedCodeObjectType *__pyx_find_code_object(int code_line) { -#if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING && !CYTHON_ATOMICS - (void)__pyx__find_code_object; - return NULL; // Most implementation should have atomics. But otherwise, don't make it thread-safe, just miss. -#else - struct __Pyx_CodeObjectCache *code_cache = &__pyx_mstate_global->__pyx_code_cache; -#if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING - __pyx_nonatomic_int_type old_count = __pyx_atomic_incr_acq_rel(&code_cache->accessor_count); - if (old_count < 0) { - __pyx_atomic_decr_acq_rel(&code_cache->accessor_count); - return NULL; - } -#endif - __Pyx_CachedCodeObjectType *result = __pyx__find_code_object(code_cache, code_line); -#if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING - __pyx_atomic_decr_acq_rel(&code_cache->accessor_count); -#endif - return result; -#endif -} -static void __pyx__insert_code_object(struct __Pyx_CodeObjectCache *code_cache, int code_line, __Pyx_CachedCodeObjectType* code_object) -{ - int pos, i; - __Pyx_CodeObjectCacheEntry* entries = code_cache->entries; - if (unlikely(!code_line)) { - return; - } - if (unlikely(!entries)) { - entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); - if (likely(entries)) { - code_cache->entries = entries; - code_cache->max_count = 64; - code_cache->count = 1; - entries[0].code_line = code_line; - entries[0].code_object = code_object; - Py_INCREF(code_object); - } - return; - } - pos = __pyx_bisect_code_objects(code_cache->entries, code_cache->count, code_line); - if ((pos < code_cache->count) && unlikely(code_cache->entries[pos].code_line == code_line)) { - __Pyx_CachedCodeObjectType* tmp = entries[pos].code_object; - entries[pos].code_object = code_object; - Py_INCREF(code_object); - Py_DECREF(tmp); - return; - } - if (code_cache->count == code_cache->max_count) { - int new_max = code_cache->max_count + 64; - entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( - code_cache->entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); - if (unlikely(!entries)) { - return; - } - code_cache->entries = entries; - code_cache->max_count = new_max; - } - for (i=code_cache->count; i>pos; i--) { - entries[i] = entries[i-1]; - } - entries[pos].code_line = code_line; - entries[pos].code_object = code_object; - code_cache->count++; - Py_INCREF(code_object); -} -static void __pyx_insert_code_object(int code_line, __Pyx_CachedCodeObjectType* code_object) { -#if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING && !CYTHON_ATOMICS - (void)__pyx__insert_code_object; - return; // Most implementation should have atomics. But otherwise, don't make it thread-safe, just fail. -#else - struct __Pyx_CodeObjectCache *code_cache = &__pyx_mstate_global->__pyx_code_cache; -#if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING - __pyx_nonatomic_int_type expected = 0; - if (!__pyx_atomic_int_cmp_exchange(&code_cache->accessor_count, &expected, INT_MIN)) { - return; - } -#endif - __pyx__insert_code_object(code_cache, code_line, code_object); -#if CYTHON_COMPILING_IN_CPYTHON_FREETHREADING - __pyx_atomic_sub(&code_cache->accessor_count, INT_MIN); -#endif -#endif -} - -/* AddTraceback */ -#include "compile.h" -#include "frameobject.h" -#include "traceback.h" -#if PY_VERSION_HEX >= 0x030b00a6 && !CYTHON_COMPILING_IN_LIMITED_API && !defined(PYPY_VERSION) - #ifndef Py_BUILD_CORE - #define Py_BUILD_CORE 1 - #endif - #include "internal/pycore_frame.h" -#endif -#if CYTHON_COMPILING_IN_LIMITED_API -static PyObject *__Pyx_PyCode_Replace_For_AddTraceback(PyObject *code, PyObject *scratch_dict, - PyObject *firstlineno, PyObject *name) { - PyObject *replace = NULL; - if (unlikely(PyDict_SetItemString(scratch_dict, "co_firstlineno", firstlineno))) return NULL; - if (unlikely(PyDict_SetItemString(scratch_dict, "co_name", name))) return NULL; - replace = PyObject_GetAttrString(code, "replace"); - if (likely(replace)) { - PyObject *result = PyObject_Call(replace, __pyx_mstate_global->__pyx_empty_tuple, scratch_dict); - Py_DECREF(replace); - return result; - } - PyErr_Clear(); - return NULL; -} -static void __Pyx_AddTraceback(const char *funcname, int c_line, - int py_line, const char *filename) { - PyObject *code_object = NULL, *py_py_line = NULL, *py_funcname = NULL, *dict = NULL; - PyObject *replace = NULL, *getframe = NULL, *frame = NULL; - PyObject *exc_type, *exc_value, *exc_traceback; - int success = 0; - if (c_line) { - (void) __pyx_cfilenm; - (void) __Pyx_CLineForTraceback(__Pyx_PyThreadState_Current, c_line); - } - PyErr_Fetch(&exc_type, &exc_value, &exc_traceback); - code_object = __pyx_find_code_object(c_line ? -c_line : py_line); - if (!code_object) { - code_object = Py_CompileString("_getframe()", filename, Py_eval_input); - if (unlikely(!code_object)) goto bad; - py_py_line = PyLong_FromLong(py_line); - if (unlikely(!py_py_line)) goto bad; - py_funcname = PyUnicode_FromString(funcname); - if (unlikely(!py_funcname)) goto bad; - dict = PyDict_New(); - if (unlikely(!dict)) goto bad; - { - PyObject *old_code_object = code_object; - code_object = __Pyx_PyCode_Replace_For_AddTraceback(code_object, dict, py_py_line, py_funcname); - Py_DECREF(old_code_object); - } - if (unlikely(!code_object)) goto bad; - __pyx_insert_code_object(c_line ? -c_line : py_line, code_object); - } else { - dict = PyDict_New(); - } - getframe = PySys_GetObject("_getframe"); - if (unlikely(!getframe)) goto bad; - if (unlikely(PyDict_SetItemString(dict, "_getframe", getframe))) goto bad; - frame = PyEval_EvalCode(code_object, dict, dict); - if (unlikely(!frame) || frame == Py_None) goto bad; - success = 1; - bad: - PyErr_Restore(exc_type, exc_value, exc_traceback); - Py_XDECREF(code_object); - Py_XDECREF(py_py_line); - Py_XDECREF(py_funcname); - Py_XDECREF(dict); - Py_XDECREF(replace); - if (success) { - PyTraceBack_Here( - (struct _frame*)frame); - } - Py_XDECREF(frame); -} -#else -static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( - const char *funcname, int c_line, - int py_line, const char *filename) { - PyCodeObject *py_code = NULL; - PyObject *py_funcname = NULL; - if (c_line) { - py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); - if (!py_funcname) goto bad; - funcname = PyUnicode_AsUTF8(py_funcname); - if (!funcname) goto bad; - } - py_code = PyCode_NewEmpty(filename, funcname, py_line); - Py_XDECREF(py_funcname); - return py_code; -bad: - Py_XDECREF(py_funcname); - return NULL; -} -static void __Pyx_AddTraceback(const char *funcname, int c_line, - int py_line, const char *filename) { - PyCodeObject *py_code = 0; - PyFrameObject *py_frame = 0; - PyThreadState *tstate = __Pyx_PyThreadState_Current; - PyObject *ptype, *pvalue, *ptraceback; - if (c_line) { - c_line = __Pyx_CLineForTraceback(tstate, c_line); - } - py_code = __pyx_find_code_object(c_line ? -c_line : py_line); - if (!py_code) { - __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); - py_code = __Pyx_CreateCodeObjectForTraceback( - funcname, c_line, py_line, filename); - if (!py_code) { - /* If the code object creation fails, then we should clear the - fetched exception references and propagate the new exception */ - Py_XDECREF(ptype); - Py_XDECREF(pvalue); - Py_XDECREF(ptraceback); - goto bad; - } - __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); - __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); - } - py_frame = PyFrame_New( - tstate, /*PyThreadState *tstate,*/ - py_code, /*PyCodeObject *code,*/ - __pyx_mstate_global->__pyx_d, /*PyObject *globals,*/ - 0 /*PyObject *locals*/ - ); - if (!py_frame) goto bad; - __Pyx_PyFrame_SetLineNumber(py_frame, py_line); - PyTraceBack_Here(py_frame); -bad: - Py_XDECREF(py_code); - Py_XDECREF(py_frame); -} -#endif - -/* CIntFromPyVerify */ -#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ - __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) -#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ - __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) -#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ - {\ - func_type value = func_value;\ - if (sizeof(target_type) < sizeof(func_type)) {\ - if (unlikely(value != (func_type) (target_type) value)) {\ - func_type zero = 0;\ - if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ - return (target_type) -1;\ - if (is_unsigned && unlikely(value < zero))\ - goto raise_neg_overflow;\ - else\ - goto raise_overflow;\ - }\ - }\ - return (target_type) value;\ - } - -/* Declarations */ -#if CYTHON_CCOMPLEX && (1) && (!0 || __cplusplus) - #ifdef __cplusplus - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - return ::std::complex< float >(x, y); - } - #else - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - return x + y*(__pyx_t_float_complex)_Complex_I; - } - #endif -#else - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - __pyx_t_float_complex z; - z.real = x; - z.imag = y; - return z; - } -#endif - -/* Arithmetic */ -#if CYTHON_CCOMPLEX && (1) && (!0 || __cplusplus) -#else - static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - return (a.real == b.real) && (a.imag == b.imag); - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real + b.real; - z.imag = a.imag + b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real - b.real; - z.imag = a.imag - b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real * b.real - a.imag * b.imag; - z.imag = a.real * b.imag + a.imag * b.real; - return z; - } - #if 1 - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - if (b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); - } else if (fabsf(b.real) >= fabsf(b.imag)) { - if (b.real == 0 && b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); - } else { - float r = b.imag / b.real; - float s = (float)(1.0) / (b.real + b.imag * r); - return __pyx_t_float_complex_from_parts( - (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); - } - } else { - float r = b.real / b.imag; - float s = (float)(1.0) / (b.imag + b.real * r); - return __pyx_t_float_complex_from_parts( - (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); - } - } - #else - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - if (b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); - } else { - float denom = b.real * b.real + b.imag * b.imag; - return __pyx_t_float_complex_from_parts( - (a.real * b.real + a.imag * b.imag) / denom, - (a.imag * b.real - a.real * b.imag) / denom); - } - } - #endif - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { - __pyx_t_float_complex z; - z.real = -a.real; - z.imag = -a.imag; - return z; - } - static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { - return (a.real == 0) && (a.imag == 0); - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { - __pyx_t_float_complex z; - z.real = a.real; - z.imag = -a.imag; - return z; - } - #if 1 - static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { - #if !defined(HAVE_HYPOT) || defined(_MSC_VER) - return sqrtf(z.real*z.real + z.imag*z.imag); - #else - return hypotf(z.real, z.imag); - #endif - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - float r, lnr, theta, z_r, z_theta; - if (b.imag == 0 && b.real == (int)b.real) { - if (b.real < 0) { - float denom = a.real * a.real + a.imag * a.imag; - a.real = a.real / denom; - a.imag = -a.imag / denom; - b.real = -b.real; - } - switch ((int)b.real) { - case 0: - z.real = 1; - z.imag = 0; - return z; - case 1: - return a; - case 2: - return __Pyx_c_prod_float(a, a); - case 3: - z = __Pyx_c_prod_float(a, a); - return __Pyx_c_prod_float(z, a); - case 4: - z = __Pyx_c_prod_float(a, a); - return __Pyx_c_prod_float(z, z); - } - } - if (a.imag == 0) { - if (a.real == 0) { - return a; - } else if ((b.imag == 0) && (a.real >= 0)) { - z.real = powf(a.real, b.real); - z.imag = 0; - return z; - } else if (a.real > 0) { - r = a.real; - theta = 0; - } else { - r = -a.real; - theta = atan2f(0.0, -1.0); - } - } else { - r = __Pyx_c_abs_float(a); - theta = atan2f(a.imag, a.real); - } - lnr = logf(r); - z_r = expf(lnr * b.real - theta * b.imag); - z_theta = theta * b.real + lnr * b.imag; - z.real = z_r * cosf(z_theta); - z.imag = z_r * sinf(z_theta); - return z; - } - #endif -#endif - -/* Declarations */ -#if CYTHON_CCOMPLEX && (1) && (!0 || __cplusplus) - #ifdef __cplusplus - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - return ::std::complex< double >(x, y); - } - #else - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - return x + y*(__pyx_t_double_complex)_Complex_I; - } - #endif -#else - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - __pyx_t_double_complex z; - z.real = x; - z.imag = y; - return z; - } -#endif - -/* Arithmetic */ -#if CYTHON_CCOMPLEX && (1) && (!0 || __cplusplus) -#else - static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - return (a.real == b.real) && (a.imag == b.imag); - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real + b.real; - z.imag = a.imag + b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real - b.real; - z.imag = a.imag - b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real * b.real - a.imag * b.imag; - z.imag = a.real * b.imag + a.imag * b.real; - return z; - } - #if 1 - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - if (b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); - } else if (fabs(b.real) >= fabs(b.imag)) { - if (b.real == 0 && b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); - } else { - double r = b.imag / b.real; - double s = (double)(1.0) / (b.real + b.imag * r); - return __pyx_t_double_complex_from_parts( - (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); - } - } else { - double r = b.real / b.imag; - double s = (double)(1.0) / (b.imag + b.real * r); - return __pyx_t_double_complex_from_parts( - (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); - } - } - #else - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - if (b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); - } else { - double denom = b.real * b.real + b.imag * b.imag; - return __pyx_t_double_complex_from_parts( - (a.real * b.real + a.imag * b.imag) / denom, - (a.imag * b.real - a.real * b.imag) / denom); - } - } - #endif - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { - __pyx_t_double_complex z; - z.real = -a.real; - z.imag = -a.imag; - return z; - } - static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { - return (a.real == 0) && (a.imag == 0); - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { - __pyx_t_double_complex z; - z.real = a.real; - z.imag = -a.imag; - return z; - } - #if 1 - static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { - #if !defined(HAVE_HYPOT) || defined(_MSC_VER) - return sqrt(z.real*z.real + z.imag*z.imag); - #else - return hypot(z.real, z.imag); - #endif - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - double r, lnr, theta, z_r, z_theta; - if (b.imag == 0 && b.real == (int)b.real) { - if (b.real < 0) { - double denom = a.real * a.real + a.imag * a.imag; - a.real = a.real / denom; - a.imag = -a.imag / denom; - b.real = -b.real; - } - switch ((int)b.real) { - case 0: - z.real = 1; - z.imag = 0; - return z; - case 1: - return a; - case 2: - return __Pyx_c_prod_double(a, a); - case 3: - z = __Pyx_c_prod_double(a, a); - return __Pyx_c_prod_double(z, a); - case 4: - z = __Pyx_c_prod_double(a, a); - return __Pyx_c_prod_double(z, z); - } - } - if (a.imag == 0) { - if (a.real == 0) { - return a; - } else if ((b.imag == 0) && (a.real >= 0)) { - z.real = pow(a.real, b.real); - z.imag = 0; - return z; - } else if (a.real > 0) { - r = a.real; - theta = 0; - } else { - r = -a.real; - theta = atan2(0.0, -1.0); - } - } else { - r = __Pyx_c_abs_double(a); - theta = atan2(a.imag, a.real); - } - lnr = log(r); - z_r = exp(lnr * b.real - theta * b.imag); - z_theta = theta * b.real + lnr * b.imag; - z.real = z_r * cos(z_theta); - z.imag = z_r * sin(z_theta); - return z; - } - #endif -#endif - -/* Declarations */ -#if CYTHON_CCOMPLEX && (1) && (!0 || __cplusplus) - #ifdef __cplusplus - static CYTHON_INLINE __pyx_t_long_double_complex __pyx_t_long_double_complex_from_parts(long double x, long double y) { - return ::std::complex< long double >(x, y); - } - #else - static CYTHON_INLINE __pyx_t_long_double_complex __pyx_t_long_double_complex_from_parts(long double x, long double y) { - return x + y*(__pyx_t_long_double_complex)_Complex_I; - } - #endif -#else - static CYTHON_INLINE __pyx_t_long_double_complex __pyx_t_long_double_complex_from_parts(long double x, long double y) { - __pyx_t_long_double_complex z; - z.real = x; - z.imag = y; - return z; - } -#endif - -/* Arithmetic */ -#if CYTHON_CCOMPLEX && (1) && (!0 || __cplusplus) -#else - static CYTHON_INLINE int __Pyx_c_eq_long__double(__pyx_t_long_double_complex a, __pyx_t_long_double_complex b) { - return (a.real == b.real) && (a.imag == b.imag); - } - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_sum_long__double(__pyx_t_long_double_complex a, __pyx_t_long_double_complex b) { - __pyx_t_long_double_complex z; - z.real = a.real + b.real; - z.imag = a.imag + b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_diff_long__double(__pyx_t_long_double_complex a, __pyx_t_long_double_complex b) { - __pyx_t_long_double_complex z; - z.real = a.real - b.real; - z.imag = a.imag - b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_prod_long__double(__pyx_t_long_double_complex a, __pyx_t_long_double_complex b) { - __pyx_t_long_double_complex z; - z.real = a.real * b.real - a.imag * b.imag; - z.imag = a.real * b.imag + a.imag * b.real; - return z; - } - #if 1 - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_quot_long__double(__pyx_t_long_double_complex a, __pyx_t_long_double_complex b) { - if (b.imag == 0) { - return __pyx_t_long_double_complex_from_parts(a.real / b.real, a.imag / b.real); - } else if (fabsl(b.real) >= fabsl(b.imag)) { - if (b.real == 0 && b.imag == 0) { - return __pyx_t_long_double_complex_from_parts(a.real / b.real, a.imag / b.imag); - } else { - long double r = b.imag / b.real; - long double s = (long double)(1.0) / (b.real + b.imag * r); - return __pyx_t_long_double_complex_from_parts( - (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); - } - } else { - long double r = b.real / b.imag; - long double s = (long double)(1.0) / (b.imag + b.real * r); - return __pyx_t_long_double_complex_from_parts( - (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); - } - } - #else - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_quot_long__double(__pyx_t_long_double_complex a, __pyx_t_long_double_complex b) { - if (b.imag == 0) { - return __pyx_t_long_double_complex_from_parts(a.real / b.real, a.imag / b.real); - } else { - long double denom = b.real * b.real + b.imag * b.imag; - return __pyx_t_long_double_complex_from_parts( - (a.real * b.real + a.imag * b.imag) / denom, - (a.imag * b.real - a.real * b.imag) / denom); - } - } - #endif - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_neg_long__double(__pyx_t_long_double_complex a) { - __pyx_t_long_double_complex z; - z.real = -a.real; - z.imag = -a.imag; - return z; - } - static CYTHON_INLINE int __Pyx_c_is_zero_long__double(__pyx_t_long_double_complex a) { - return (a.real == 0) && (a.imag == 0); - } - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_conj_long__double(__pyx_t_long_double_complex a) { - __pyx_t_long_double_complex z; - z.real = a.real; - z.imag = -a.imag; - return z; - } - #if 1 - static CYTHON_INLINE long double __Pyx_c_abs_long__double(__pyx_t_long_double_complex z) { - #if !defined(HAVE_HYPOT) || defined(_MSC_VER) - return sqrtl(z.real*z.real + z.imag*z.imag); - #else - return hypotl(z.real, z.imag); - #endif - } - static CYTHON_INLINE __pyx_t_long_double_complex __Pyx_c_pow_long__double(__pyx_t_long_double_complex a, __pyx_t_long_double_complex b) { - __pyx_t_long_double_complex z; - long double r, lnr, theta, z_r, z_theta; - if (b.imag == 0 && b.real == (int)b.real) { - if (b.real < 0) { - long double denom = a.real * a.real + a.imag * a.imag; - a.real = a.real / denom; - a.imag = -a.imag / denom; - b.real = -b.real; - } - switch ((int)b.real) { - case 0: - z.real = 1; - z.imag = 0; - return z; - case 1: - return a; - case 2: - return __Pyx_c_prod_long__double(a, a); - case 3: - z = __Pyx_c_prod_long__double(a, a); - return __Pyx_c_prod_long__double(z, a); - case 4: - z = __Pyx_c_prod_long__double(a, a); - return __Pyx_c_prod_long__double(z, z); - } - } - if (a.imag == 0) { - if (a.real == 0) { - return a; - } else if ((b.imag == 0) && (a.real >= 0)) { - z.real = powl(a.real, b.real); - z.imag = 0; - return z; - } else if (a.real > 0) { - r = a.real; - theta = 0; - } else { - r = -a.real; - theta = atan2l(0.0, -1.0); - } - } else { - r = __Pyx_c_abs_long__double(a); - theta = atan2l(a.imag, a.real); - } - lnr = logl(r); - z_r = expl(lnr * b.real - theta * b.imag); - z_theta = theta * b.real + lnr * b.imag; - z.real = z_r * cosl(z_theta); - z.imag = z_r * sinl(z_theta); - return z; - } - #endif -#endif - -/* CIntFromPy */ -static CYTHON_INLINE TA_RetCode __Pyx_PyLong_As_TA_RetCode(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const TA_RetCode neg_one = (TA_RetCode) -1, const_zero = (TA_RetCode) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (unlikely(!PyLong_Check(x))) { - TA_RetCode val; - PyObject *tmp = __Pyx_PyNumber_Long(x); - if (!tmp) return (TA_RetCode) -1; - val = __Pyx_PyLong_As_TA_RetCode(tmp); - Py_DECREF(tmp); - return val; - } - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - if (unlikely(__Pyx_PyLong_IsNeg(x))) { - goto raise_neg_overflow; - } else if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(TA_RetCode, __Pyx_compact_upylong, __Pyx_PyLong_CompactValueUnsigned(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_DigitCount(x)) { - case 2: - if ((8 * sizeof(TA_RetCode) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RetCode, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RetCode) >= 2 * PyLong_SHIFT)) { - return (TA_RetCode) (((((TA_RetCode)digits[1]) << PyLong_SHIFT) | (TA_RetCode)digits[0])); - } - } - break; - case 3: - if ((8 * sizeof(TA_RetCode) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RetCode, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RetCode) >= 3 * PyLong_SHIFT)) { - return (TA_RetCode) (((((((TA_RetCode)digits[2]) << PyLong_SHIFT) | (TA_RetCode)digits[1]) << PyLong_SHIFT) | (TA_RetCode)digits[0])); - } - } - break; - case 4: - if ((8 * sizeof(TA_RetCode) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RetCode, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RetCode) >= 4 * PyLong_SHIFT)) { - return (TA_RetCode) (((((((((TA_RetCode)digits[3]) << PyLong_SHIFT) | (TA_RetCode)digits[2]) << PyLong_SHIFT) | (TA_RetCode)digits[1]) << PyLong_SHIFT) | (TA_RetCode)digits[0])); - } - } - break; - } - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030C00A7 - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (TA_RetCode) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if ((sizeof(TA_RetCode) <= sizeof(unsigned long))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_RetCode, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(TA_RetCode) <= sizeof(unsigned PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_RetCode, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(TA_RetCode, __Pyx_compact_pylong, __Pyx_PyLong_CompactValue(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_SignedDigitCount(x)) { - case -2: - if ((8 * sizeof(TA_RetCode) - 1 > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RetCode, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RetCode) - 1 > 2 * PyLong_SHIFT)) { - return (TA_RetCode) (((TA_RetCode)-1)*(((((TA_RetCode)digits[1]) << PyLong_SHIFT) | (TA_RetCode)digits[0]))); - } - } - break; - case 2: - if ((8 * sizeof(TA_RetCode) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RetCode, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RetCode) - 1 > 2 * PyLong_SHIFT)) { - return (TA_RetCode) ((((((TA_RetCode)digits[1]) << PyLong_SHIFT) | (TA_RetCode)digits[0]))); - } - } - break; - case -3: - if ((8 * sizeof(TA_RetCode) - 1 > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RetCode, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RetCode) - 1 > 3 * PyLong_SHIFT)) { - return (TA_RetCode) (((TA_RetCode)-1)*(((((((TA_RetCode)digits[2]) << PyLong_SHIFT) | (TA_RetCode)digits[1]) << PyLong_SHIFT) | (TA_RetCode)digits[0]))); - } - } - break; - case 3: - if ((8 * sizeof(TA_RetCode) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RetCode, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RetCode) - 1 > 3 * PyLong_SHIFT)) { - return (TA_RetCode) ((((((((TA_RetCode)digits[2]) << PyLong_SHIFT) | (TA_RetCode)digits[1]) << PyLong_SHIFT) | (TA_RetCode)digits[0]))); - } - } - break; - case -4: - if ((8 * sizeof(TA_RetCode) - 1 > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RetCode, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RetCode) - 1 > 4 * PyLong_SHIFT)) { - return (TA_RetCode) (((TA_RetCode)-1)*(((((((((TA_RetCode)digits[3]) << PyLong_SHIFT) | (TA_RetCode)digits[2]) << PyLong_SHIFT) | (TA_RetCode)digits[1]) << PyLong_SHIFT) | (TA_RetCode)digits[0]))); - } - } - break; - case 4: - if ((8 * sizeof(TA_RetCode) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RetCode, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RetCode) - 1 > 4 * PyLong_SHIFT)) { - return (TA_RetCode) ((((((((((TA_RetCode)digits[3]) << PyLong_SHIFT) | (TA_RetCode)digits[2]) << PyLong_SHIFT) | (TA_RetCode)digits[1]) << PyLong_SHIFT) | (TA_RetCode)digits[0]))); - } - } - break; - } - } -#endif - if ((sizeof(TA_RetCode) <= sizeof(long))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_RetCode, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(TA_RetCode) <= sizeof(PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_RetCode, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { - TA_RetCode val; - int ret = -1; -#if PY_VERSION_HEX >= 0x030d00A6 && !CYTHON_COMPILING_IN_LIMITED_API - Py_ssize_t bytes_copied = PyLong_AsNativeBytes( - x, &val, sizeof(val), Py_ASNATIVEBYTES_NATIVE_ENDIAN | (is_unsigned ? Py_ASNATIVEBYTES_UNSIGNED_BUFFER | Py_ASNATIVEBYTES_REJECT_NEGATIVE : 0)); - if (unlikely(bytes_copied == -1)) { - } else if (unlikely(bytes_copied > (Py_ssize_t) sizeof(val))) { - goto raise_overflow; - } else { - ret = 0; - } -#elif PY_VERSION_HEX < 0x030d0000 && !(CYTHON_COMPILING_IN_PYPY || CYTHON_COMPILING_IN_LIMITED_API) || defined(_PyLong_AsByteArray) - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - ret = _PyLong_AsByteArray((PyLongObject *)x, - bytes, sizeof(val), - is_little, !is_unsigned); -#else - PyObject *v; - PyObject *stepval = NULL, *mask = NULL, *shift = NULL; - int bits, remaining_bits, is_negative = 0; - int chunk_size = (sizeof(long) < 8) ? 30 : 62; - if (likely(PyLong_CheckExact(x))) { - v = __Pyx_NewRef(x); - } else { - v = PyNumber_Long(x); - if (unlikely(!v)) return (TA_RetCode) -1; - assert(PyLong_CheckExact(v)); - } - { - int result = PyObject_RichCompareBool(v, Py_False, Py_LT); - if (unlikely(result < 0)) { - Py_DECREF(v); - return (TA_RetCode) -1; - } - is_negative = result == 1; - } - if (is_unsigned && unlikely(is_negative)) { - Py_DECREF(v); - goto raise_neg_overflow; - } else if (is_negative) { - stepval = PyNumber_Invert(v); - Py_DECREF(v); - if (unlikely(!stepval)) - return (TA_RetCode) -1; - } else { - stepval = v; - } - v = NULL; - val = (TA_RetCode) 0; - mask = PyLong_FromLong((1L << chunk_size) - 1); if (unlikely(!mask)) goto done; - shift = PyLong_FromLong(chunk_size); if (unlikely(!shift)) goto done; - for (bits = 0; bits < (int) sizeof(TA_RetCode) * 8 - chunk_size; bits += chunk_size) { - PyObject *tmp, *digit; - long idigit; - digit = PyNumber_And(stepval, mask); - if (unlikely(!digit)) goto done; - idigit = PyLong_AsLong(digit); - Py_DECREF(digit); - if (unlikely(idigit < 0)) goto done; - val |= ((TA_RetCode) idigit) << bits; - tmp = PyNumber_Rshift(stepval, shift); - if (unlikely(!tmp)) goto done; - Py_DECREF(stepval); stepval = tmp; - } - Py_DECREF(shift); shift = NULL; - Py_DECREF(mask); mask = NULL; - { - long idigit = PyLong_AsLong(stepval); - if (unlikely(idigit < 0)) goto done; - remaining_bits = ((int) sizeof(TA_RetCode) * 8) - bits - (is_unsigned ? 0 : 1); - if (unlikely(idigit >= (1L << remaining_bits))) - goto raise_overflow; - val |= ((TA_RetCode) idigit) << bits; - } - if (!is_unsigned) { - if (unlikely(val & (((TA_RetCode) 1) << (sizeof(TA_RetCode) * 8 - 1)))) - goto raise_overflow; - if (is_negative) - val = ~val; - } - ret = 0; - done: - Py_XDECREF(shift); - Py_XDECREF(mask); - Py_XDECREF(stepval); -#endif - if (unlikely(ret)) - return (TA_RetCode) -1; - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to TA_RetCode"); - return (TA_RetCode) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to TA_RetCode"); - return (TA_RetCode) -1; -} - -/* CIntFromPy */ -static CYTHON_INLINE int __Pyx_PyLong_As_int(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const int neg_one = (int) -1, const_zero = (int) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (unlikely(!PyLong_Check(x))) { - int val; - PyObject *tmp = __Pyx_PyNumber_Long(x); - if (!tmp) return (int) -1; - val = __Pyx_PyLong_As_int(tmp); - Py_DECREF(tmp); - return val; - } - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - if (unlikely(__Pyx_PyLong_IsNeg(x))) { - goto raise_neg_overflow; - } else if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(int, __Pyx_compact_upylong, __Pyx_PyLong_CompactValueUnsigned(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_DigitCount(x)) { - case 2: - if ((8 * sizeof(int) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(int) >= 2 * PyLong_SHIFT)) { - return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - case 3: - if ((8 * sizeof(int) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(int) >= 3 * PyLong_SHIFT)) { - return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - case 4: - if ((8 * sizeof(int) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(int) >= 4 * PyLong_SHIFT)) { - return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - } - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030C00A7 - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (int) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if ((sizeof(int) <= sizeof(unsigned long))) { - __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(int) <= sizeof(unsigned PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(int, __Pyx_compact_pylong, __Pyx_PyLong_CompactValue(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_SignedDigitCount(x)) { - case -2: - if ((8 * sizeof(int) - 1 > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(int) - 1 > 2 * PyLong_SHIFT)) { - return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 2: - if ((8 * sizeof(int) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(int) - 1 > 2 * PyLong_SHIFT)) { - return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case -3: - if ((8 * sizeof(int) - 1 > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(int) - 1 > 3 * PyLong_SHIFT)) { - return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 3: - if ((8 * sizeof(int) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(int) - 1 > 3 * PyLong_SHIFT)) { - return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case -4: - if ((8 * sizeof(int) - 1 > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(int) - 1 > 4 * PyLong_SHIFT)) { - return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 4: - if ((8 * sizeof(int) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(int) - 1 > 4 * PyLong_SHIFT)) { - return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - } - } -#endif - if ((sizeof(int) <= sizeof(long))) { - __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(int) <= sizeof(PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { - int val; - int ret = -1; -#if PY_VERSION_HEX >= 0x030d00A6 && !CYTHON_COMPILING_IN_LIMITED_API - Py_ssize_t bytes_copied = PyLong_AsNativeBytes( - x, &val, sizeof(val), Py_ASNATIVEBYTES_NATIVE_ENDIAN | (is_unsigned ? Py_ASNATIVEBYTES_UNSIGNED_BUFFER | Py_ASNATIVEBYTES_REJECT_NEGATIVE : 0)); - if (unlikely(bytes_copied == -1)) { - } else if (unlikely(bytes_copied > (Py_ssize_t) sizeof(val))) { - goto raise_overflow; - } else { - ret = 0; - } -#elif PY_VERSION_HEX < 0x030d0000 && !(CYTHON_COMPILING_IN_PYPY || CYTHON_COMPILING_IN_LIMITED_API) || defined(_PyLong_AsByteArray) - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - ret = _PyLong_AsByteArray((PyLongObject *)x, - bytes, sizeof(val), - is_little, !is_unsigned); -#else - PyObject *v; - PyObject *stepval = NULL, *mask = NULL, *shift = NULL; - int bits, remaining_bits, is_negative = 0; - int chunk_size = (sizeof(long) < 8) ? 30 : 62; - if (likely(PyLong_CheckExact(x))) { - v = __Pyx_NewRef(x); - } else { - v = PyNumber_Long(x); - if (unlikely(!v)) return (int) -1; - assert(PyLong_CheckExact(v)); - } - { - int result = PyObject_RichCompareBool(v, Py_False, Py_LT); - if (unlikely(result < 0)) { - Py_DECREF(v); - return (int) -1; - } - is_negative = result == 1; - } - if (is_unsigned && unlikely(is_negative)) { - Py_DECREF(v); - goto raise_neg_overflow; - } else if (is_negative) { - stepval = PyNumber_Invert(v); - Py_DECREF(v); - if (unlikely(!stepval)) - return (int) -1; - } else { - stepval = v; - } - v = NULL; - val = (int) 0; - mask = PyLong_FromLong((1L << chunk_size) - 1); if (unlikely(!mask)) goto done; - shift = PyLong_FromLong(chunk_size); if (unlikely(!shift)) goto done; - for (bits = 0; bits < (int) sizeof(int) * 8 - chunk_size; bits += chunk_size) { - PyObject *tmp, *digit; - long idigit; - digit = PyNumber_And(stepval, mask); - if (unlikely(!digit)) goto done; - idigit = PyLong_AsLong(digit); - Py_DECREF(digit); - if (unlikely(idigit < 0)) goto done; - val |= ((int) idigit) << bits; - tmp = PyNumber_Rshift(stepval, shift); - if (unlikely(!tmp)) goto done; - Py_DECREF(stepval); stepval = tmp; - } - Py_DECREF(shift); shift = NULL; - Py_DECREF(mask); mask = NULL; - { - long idigit = PyLong_AsLong(stepval); - if (unlikely(idigit < 0)) goto done; - remaining_bits = ((int) sizeof(int) * 8) - bits - (is_unsigned ? 0 : 1); - if (unlikely(idigit >= (1L << remaining_bits))) - goto raise_overflow; - val |= ((int) idigit) << bits; - } - if (!is_unsigned) { - if (unlikely(val & (((int) 1) << (sizeof(int) * 8 - 1)))) - goto raise_overflow; - if (is_negative) - val = ~val; - } - ret = 0; - done: - Py_XDECREF(shift); - Py_XDECREF(mask); - Py_XDECREF(stepval); -#endif - if (unlikely(ret)) - return (int) -1; - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to int"); - return (int) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to int"); - return (int) -1; -} - -/* CIntToPy */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_int(int value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const int neg_one = (int) -1, const_zero = (int) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(int) < sizeof(long)) { - return PyLong_FromLong((long) value); - } else if (sizeof(int) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#if defined(HAVE_LONG_LONG) && !CYTHON_COMPILING_IN_PYPY - } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(int) <= sizeof(long)) { - return PyLong_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - unsigned char *bytes = (unsigned char *)&value; -#if !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX >= 0x030d00A4 - if (is_unsigned) { - return PyLong_FromUnsignedNativeBytes(bytes, sizeof(value), -1); - } else { - return PyLong_FromNativeBytes(bytes, sizeof(value), -1); - } -#elif !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX < 0x030d0000 - int one = 1; int little = (int)*(unsigned char *)&one; - return _PyLong_FromByteArray(bytes, sizeof(int), - little, !is_unsigned); -#else - int one = 1; int little = (int)*(unsigned char *)&one; - PyObject *from_bytes, *result = NULL, *kwds = NULL; - PyObject *py_bytes = NULL, *order_str = NULL; - from_bytes = PyObject_GetAttrString((PyObject*)&PyLong_Type, "from_bytes"); - if (!from_bytes) return NULL; - py_bytes = PyBytes_FromStringAndSize((char*)bytes, sizeof(int)); - if (!py_bytes) goto limited_bad; - order_str = PyUnicode_FromString(little ? "little" : "big"); - if (!order_str) goto limited_bad; - { - PyObject *args[3+(CYTHON_VECTORCALL ? 1 : 0)] = { NULL, py_bytes, order_str }; - if (!is_unsigned) { - kwds = __Pyx_MakeVectorcallBuilderKwds(1); - if (!kwds) goto limited_bad; - if (__Pyx_VectorcallBuilder_AddArgStr("signed", __Pyx_NewRef(Py_True), kwds, args+3, 0) < 0) goto limited_bad; - } - result = __Pyx_Object_Vectorcall_CallFromBuilder(from_bytes, args+1, 2 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET, kwds); - } - limited_bad: - Py_XDECREF(kwds); - Py_XDECREF(order_str); - Py_XDECREF(py_bytes); - Py_XDECREF(from_bytes); - return result; -#endif - } -} - -/* CIntToPy */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_TA_RetCode(TA_RetCode value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const TA_RetCode neg_one = (TA_RetCode) -1, const_zero = (TA_RetCode) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(TA_RetCode) < sizeof(long)) { - return PyLong_FromLong((long) value); - } else if (sizeof(TA_RetCode) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#if defined(HAVE_LONG_LONG) && !CYTHON_COMPILING_IN_PYPY - } else if (sizeof(TA_RetCode) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(TA_RetCode) <= sizeof(long)) { - return PyLong_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(TA_RetCode) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - unsigned char *bytes = (unsigned char *)&value; -#if !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX >= 0x030d00A4 - if (is_unsigned) { - return PyLong_FromUnsignedNativeBytes(bytes, sizeof(value), -1); - } else { - return PyLong_FromNativeBytes(bytes, sizeof(value), -1); - } -#elif !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX < 0x030d0000 - int one = 1; int little = (int)*(unsigned char *)&one; - return _PyLong_FromByteArray(bytes, sizeof(TA_RetCode), - little, !is_unsigned); -#else - int one = 1; int little = (int)*(unsigned char *)&one; - PyObject *from_bytes, *result = NULL, *kwds = NULL; - PyObject *py_bytes = NULL, *order_str = NULL; - from_bytes = PyObject_GetAttrString((PyObject*)&PyLong_Type, "from_bytes"); - if (!from_bytes) return NULL; - py_bytes = PyBytes_FromStringAndSize((char*)bytes, sizeof(TA_RetCode)); - if (!py_bytes) goto limited_bad; - order_str = PyUnicode_FromString(little ? "little" : "big"); - if (!order_str) goto limited_bad; - { - PyObject *args[3+(CYTHON_VECTORCALL ? 1 : 0)] = { NULL, py_bytes, order_str }; - if (!is_unsigned) { - kwds = __Pyx_MakeVectorcallBuilderKwds(1); - if (!kwds) goto limited_bad; - if (__Pyx_VectorcallBuilder_AddArgStr("signed", __Pyx_NewRef(Py_True), kwds, args+3, 0) < 0) goto limited_bad; - } - result = __Pyx_Object_Vectorcall_CallFromBuilder(from_bytes, args+1, 2 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET, kwds); - } - limited_bad: - Py_XDECREF(kwds); - Py_XDECREF(order_str); - Py_XDECREF(py_bytes); - Py_XDECREF(from_bytes); - return result; -#endif - } -} - -/* CIntFromPy */ -static CYTHON_INLINE TA_FuncUnstId __Pyx_PyLong_As_TA_FuncUnstId(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const TA_FuncUnstId neg_one = (TA_FuncUnstId) -1, const_zero = (TA_FuncUnstId) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (unlikely(!PyLong_Check(x))) { - TA_FuncUnstId val; - PyObject *tmp = __Pyx_PyNumber_Long(x); - if (!tmp) return (TA_FuncUnstId) -1; - val = __Pyx_PyLong_As_TA_FuncUnstId(tmp); - Py_DECREF(tmp); - return val; - } - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - if (unlikely(__Pyx_PyLong_IsNeg(x))) { - goto raise_neg_overflow; - } else if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(TA_FuncUnstId, __Pyx_compact_upylong, __Pyx_PyLong_CompactValueUnsigned(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_DigitCount(x)) { - case 2: - if ((8 * sizeof(TA_FuncUnstId) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_FuncUnstId, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_FuncUnstId) >= 2 * PyLong_SHIFT)) { - return (TA_FuncUnstId) (((((TA_FuncUnstId)digits[1]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[0])); - } - } - break; - case 3: - if ((8 * sizeof(TA_FuncUnstId) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_FuncUnstId, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_FuncUnstId) >= 3 * PyLong_SHIFT)) { - return (TA_FuncUnstId) (((((((TA_FuncUnstId)digits[2]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[1]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[0])); - } - } - break; - case 4: - if ((8 * sizeof(TA_FuncUnstId) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_FuncUnstId, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_FuncUnstId) >= 4 * PyLong_SHIFT)) { - return (TA_FuncUnstId) (((((((((TA_FuncUnstId)digits[3]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[2]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[1]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[0])); - } - } - break; - } - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030C00A7 - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (TA_FuncUnstId) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if ((sizeof(TA_FuncUnstId) <= sizeof(unsigned long))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_FuncUnstId, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(TA_FuncUnstId) <= sizeof(unsigned PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_FuncUnstId, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(TA_FuncUnstId, __Pyx_compact_pylong, __Pyx_PyLong_CompactValue(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_SignedDigitCount(x)) { - case -2: - if ((8 * sizeof(TA_FuncUnstId) - 1 > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_FuncUnstId, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_FuncUnstId) - 1 > 2 * PyLong_SHIFT)) { - return (TA_FuncUnstId) (((TA_FuncUnstId)-1)*(((((TA_FuncUnstId)digits[1]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[0]))); - } - } - break; - case 2: - if ((8 * sizeof(TA_FuncUnstId) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_FuncUnstId, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_FuncUnstId) - 1 > 2 * PyLong_SHIFT)) { - return (TA_FuncUnstId) ((((((TA_FuncUnstId)digits[1]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[0]))); - } - } - break; - case -3: - if ((8 * sizeof(TA_FuncUnstId) - 1 > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_FuncUnstId, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_FuncUnstId) - 1 > 3 * PyLong_SHIFT)) { - return (TA_FuncUnstId) (((TA_FuncUnstId)-1)*(((((((TA_FuncUnstId)digits[2]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[1]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[0]))); - } - } - break; - case 3: - if ((8 * sizeof(TA_FuncUnstId) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_FuncUnstId, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_FuncUnstId) - 1 > 3 * PyLong_SHIFT)) { - return (TA_FuncUnstId) ((((((((TA_FuncUnstId)digits[2]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[1]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[0]))); - } - } - break; - case -4: - if ((8 * sizeof(TA_FuncUnstId) - 1 > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_FuncUnstId, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_FuncUnstId) - 1 > 4 * PyLong_SHIFT)) { - return (TA_FuncUnstId) (((TA_FuncUnstId)-1)*(((((((((TA_FuncUnstId)digits[3]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[2]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[1]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[0]))); - } - } - break; - case 4: - if ((8 * sizeof(TA_FuncUnstId) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_FuncUnstId, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_FuncUnstId) - 1 > 4 * PyLong_SHIFT)) { - return (TA_FuncUnstId) ((((((((((TA_FuncUnstId)digits[3]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[2]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[1]) << PyLong_SHIFT) | (TA_FuncUnstId)digits[0]))); - } - } - break; - } - } -#endif - if ((sizeof(TA_FuncUnstId) <= sizeof(long))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_FuncUnstId, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(TA_FuncUnstId) <= sizeof(PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_FuncUnstId, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { - TA_FuncUnstId val; - int ret = -1; -#if PY_VERSION_HEX >= 0x030d00A6 && !CYTHON_COMPILING_IN_LIMITED_API - Py_ssize_t bytes_copied = PyLong_AsNativeBytes( - x, &val, sizeof(val), Py_ASNATIVEBYTES_NATIVE_ENDIAN | (is_unsigned ? Py_ASNATIVEBYTES_UNSIGNED_BUFFER | Py_ASNATIVEBYTES_REJECT_NEGATIVE : 0)); - if (unlikely(bytes_copied == -1)) { - } else if (unlikely(bytes_copied > (Py_ssize_t) sizeof(val))) { - goto raise_overflow; - } else { - ret = 0; - } -#elif PY_VERSION_HEX < 0x030d0000 && !(CYTHON_COMPILING_IN_PYPY || CYTHON_COMPILING_IN_LIMITED_API) || defined(_PyLong_AsByteArray) - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - ret = _PyLong_AsByteArray((PyLongObject *)x, - bytes, sizeof(val), - is_little, !is_unsigned); -#else - PyObject *v; - PyObject *stepval = NULL, *mask = NULL, *shift = NULL; - int bits, remaining_bits, is_negative = 0; - int chunk_size = (sizeof(long) < 8) ? 30 : 62; - if (likely(PyLong_CheckExact(x))) { - v = __Pyx_NewRef(x); - } else { - v = PyNumber_Long(x); - if (unlikely(!v)) return (TA_FuncUnstId) -1; - assert(PyLong_CheckExact(v)); - } - { - int result = PyObject_RichCompareBool(v, Py_False, Py_LT); - if (unlikely(result < 0)) { - Py_DECREF(v); - return (TA_FuncUnstId) -1; - } - is_negative = result == 1; - } - if (is_unsigned && unlikely(is_negative)) { - Py_DECREF(v); - goto raise_neg_overflow; - } else if (is_negative) { - stepval = PyNumber_Invert(v); - Py_DECREF(v); - if (unlikely(!stepval)) - return (TA_FuncUnstId) -1; - } else { - stepval = v; - } - v = NULL; - val = (TA_FuncUnstId) 0; - mask = PyLong_FromLong((1L << chunk_size) - 1); if (unlikely(!mask)) goto done; - shift = PyLong_FromLong(chunk_size); if (unlikely(!shift)) goto done; - for (bits = 0; bits < (int) sizeof(TA_FuncUnstId) * 8 - chunk_size; bits += chunk_size) { - PyObject *tmp, *digit; - long idigit; - digit = PyNumber_And(stepval, mask); - if (unlikely(!digit)) goto done; - idigit = PyLong_AsLong(digit); - Py_DECREF(digit); - if (unlikely(idigit < 0)) goto done; - val |= ((TA_FuncUnstId) idigit) << bits; - tmp = PyNumber_Rshift(stepval, shift); - if (unlikely(!tmp)) goto done; - Py_DECREF(stepval); stepval = tmp; - } - Py_DECREF(shift); shift = NULL; - Py_DECREF(mask); mask = NULL; - { - long idigit = PyLong_AsLong(stepval); - if (unlikely(idigit < 0)) goto done; - remaining_bits = ((int) sizeof(TA_FuncUnstId) * 8) - bits - (is_unsigned ? 0 : 1); - if (unlikely(idigit >= (1L << remaining_bits))) - goto raise_overflow; - val |= ((TA_FuncUnstId) idigit) << bits; - } - if (!is_unsigned) { - if (unlikely(val & (((TA_FuncUnstId) 1) << (sizeof(TA_FuncUnstId) * 8 - 1)))) - goto raise_overflow; - if (is_negative) - val = ~val; - } - ret = 0; - done: - Py_XDECREF(shift); - Py_XDECREF(mask); - Py_XDECREF(stepval); -#endif - if (unlikely(ret)) - return (TA_FuncUnstId) -1; - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to TA_FuncUnstId"); - return (TA_FuncUnstId) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to TA_FuncUnstId"); - return (TA_FuncUnstId) -1; -} - -/* CIntFromPy */ -static CYTHON_INLINE unsigned int __Pyx_PyLong_As_unsigned_int(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const unsigned int neg_one = (unsigned int) -1, const_zero = (unsigned int) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (unlikely(!PyLong_Check(x))) { - unsigned int val; - PyObject *tmp = __Pyx_PyNumber_Long(x); - if (!tmp) return (unsigned int) -1; - val = __Pyx_PyLong_As_unsigned_int(tmp); - Py_DECREF(tmp); - return val; - } - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - if (unlikely(__Pyx_PyLong_IsNeg(x))) { - goto raise_neg_overflow; - } else if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(unsigned int, __Pyx_compact_upylong, __Pyx_PyLong_CompactValueUnsigned(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_DigitCount(x)) { - case 2: - if ((8 * sizeof(unsigned int) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(unsigned int) >= 2 * PyLong_SHIFT)) { - return (unsigned int) (((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])); - } - } - break; - case 3: - if ((8 * sizeof(unsigned int) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(unsigned int) >= 3 * PyLong_SHIFT)) { - return (unsigned int) (((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])); - } - } - break; - case 4: - if ((8 * sizeof(unsigned int) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(unsigned int) >= 4 * PyLong_SHIFT)) { - return (unsigned int) (((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])); - } - } - break; - } - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030C00A7 - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (unsigned int) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if ((sizeof(unsigned int) <= sizeof(unsigned long))) { - __PYX_VERIFY_RETURN_INT_EXC(unsigned int, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(unsigned int) <= sizeof(unsigned PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(unsigned int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(unsigned int, __Pyx_compact_pylong, __Pyx_PyLong_CompactValue(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_SignedDigitCount(x)) { - case -2: - if ((8 * sizeof(unsigned int) - 1 > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT)) { - return (unsigned int) (((unsigned int)-1)*(((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); - } - } - break; - case 2: - if ((8 * sizeof(unsigned int) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT)) { - return (unsigned int) ((((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); - } - } - break; - case -3: - if ((8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT)) { - return (unsigned int) (((unsigned int)-1)*(((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); - } - } - break; - case 3: - if ((8 * sizeof(unsigned int) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT)) { - return (unsigned int) ((((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); - } - } - break; - case -4: - if ((8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(unsigned int) - 1 > 4 * PyLong_SHIFT)) { - return (unsigned int) (((unsigned int)-1)*(((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); - } - } - break; - case 4: - if ((8 * sizeof(unsigned int) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(unsigned int) - 1 > 4 * PyLong_SHIFT)) { - return (unsigned int) ((((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); - } - } - break; - } - } -#endif - if ((sizeof(unsigned int) <= sizeof(long))) { - __PYX_VERIFY_RETURN_INT_EXC(unsigned int, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(unsigned int) <= sizeof(PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(unsigned int, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { - unsigned int val; - int ret = -1; -#if PY_VERSION_HEX >= 0x030d00A6 && !CYTHON_COMPILING_IN_LIMITED_API - Py_ssize_t bytes_copied = PyLong_AsNativeBytes( - x, &val, sizeof(val), Py_ASNATIVEBYTES_NATIVE_ENDIAN | (is_unsigned ? Py_ASNATIVEBYTES_UNSIGNED_BUFFER | Py_ASNATIVEBYTES_REJECT_NEGATIVE : 0)); - if (unlikely(bytes_copied == -1)) { - } else if (unlikely(bytes_copied > (Py_ssize_t) sizeof(val))) { - goto raise_overflow; - } else { - ret = 0; - } -#elif PY_VERSION_HEX < 0x030d0000 && !(CYTHON_COMPILING_IN_PYPY || CYTHON_COMPILING_IN_LIMITED_API) || defined(_PyLong_AsByteArray) - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - ret = _PyLong_AsByteArray((PyLongObject *)x, - bytes, sizeof(val), - is_little, !is_unsigned); -#else - PyObject *v; - PyObject *stepval = NULL, *mask = NULL, *shift = NULL; - int bits, remaining_bits, is_negative = 0; - int chunk_size = (sizeof(long) < 8) ? 30 : 62; - if (likely(PyLong_CheckExact(x))) { - v = __Pyx_NewRef(x); - } else { - v = PyNumber_Long(x); - if (unlikely(!v)) return (unsigned int) -1; - assert(PyLong_CheckExact(v)); - } - { - int result = PyObject_RichCompareBool(v, Py_False, Py_LT); - if (unlikely(result < 0)) { - Py_DECREF(v); - return (unsigned int) -1; - } - is_negative = result == 1; - } - if (is_unsigned && unlikely(is_negative)) { - Py_DECREF(v); - goto raise_neg_overflow; - } else if (is_negative) { - stepval = PyNumber_Invert(v); - Py_DECREF(v); - if (unlikely(!stepval)) - return (unsigned int) -1; - } else { - stepval = v; - } - v = NULL; - val = (unsigned int) 0; - mask = PyLong_FromLong((1L << chunk_size) - 1); if (unlikely(!mask)) goto done; - shift = PyLong_FromLong(chunk_size); if (unlikely(!shift)) goto done; - for (bits = 0; bits < (int) sizeof(unsigned int) * 8 - chunk_size; bits += chunk_size) { - PyObject *tmp, *digit; - long idigit; - digit = PyNumber_And(stepval, mask); - if (unlikely(!digit)) goto done; - idigit = PyLong_AsLong(digit); - Py_DECREF(digit); - if (unlikely(idigit < 0)) goto done; - val |= ((unsigned int) idigit) << bits; - tmp = PyNumber_Rshift(stepval, shift); - if (unlikely(!tmp)) goto done; - Py_DECREF(stepval); stepval = tmp; - } - Py_DECREF(shift); shift = NULL; - Py_DECREF(mask); mask = NULL; - { - long idigit = PyLong_AsLong(stepval); - if (unlikely(idigit < 0)) goto done; - remaining_bits = ((int) sizeof(unsigned int) * 8) - bits - (is_unsigned ? 0 : 1); - if (unlikely(idigit >= (1L << remaining_bits))) - goto raise_overflow; - val |= ((unsigned int) idigit) << bits; - } - if (!is_unsigned) { - if (unlikely(val & (((unsigned int) 1) << (sizeof(unsigned int) * 8 - 1)))) - goto raise_overflow; - if (is_negative) - val = ~val; - } - ret = 0; - done: - Py_XDECREF(shift); - Py_XDECREF(mask); - Py_XDECREF(stepval); -#endif - if (unlikely(ret)) - return (unsigned int) -1; - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to unsigned int"); - return (unsigned int) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to unsigned int"); - return (unsigned int) -1; -} - -/* CIntToPy */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_unsigned_int(unsigned int value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const unsigned int neg_one = (unsigned int) -1, const_zero = (unsigned int) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(unsigned int) < sizeof(long)) { - return PyLong_FromLong((long) value); - } else if (sizeof(unsigned int) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#if defined(HAVE_LONG_LONG) && !CYTHON_COMPILING_IN_PYPY - } else if (sizeof(unsigned int) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(unsigned int) <= sizeof(long)) { - return PyLong_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(unsigned int) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - unsigned char *bytes = (unsigned char *)&value; -#if !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX >= 0x030d00A4 - if (is_unsigned) { - return PyLong_FromUnsignedNativeBytes(bytes, sizeof(value), -1); - } else { - return PyLong_FromNativeBytes(bytes, sizeof(value), -1); - } -#elif !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX < 0x030d0000 - int one = 1; int little = (int)*(unsigned char *)&one; - return _PyLong_FromByteArray(bytes, sizeof(unsigned int), - little, !is_unsigned); -#else - int one = 1; int little = (int)*(unsigned char *)&one; - PyObject *from_bytes, *result = NULL, *kwds = NULL; - PyObject *py_bytes = NULL, *order_str = NULL; - from_bytes = PyObject_GetAttrString((PyObject*)&PyLong_Type, "from_bytes"); - if (!from_bytes) return NULL; - py_bytes = PyBytes_FromStringAndSize((char*)bytes, sizeof(unsigned int)); - if (!py_bytes) goto limited_bad; - order_str = PyUnicode_FromString(little ? "little" : "big"); - if (!order_str) goto limited_bad; - { - PyObject *args[3+(CYTHON_VECTORCALL ? 1 : 0)] = { NULL, py_bytes, order_str }; - if (!is_unsigned) { - kwds = __Pyx_MakeVectorcallBuilderKwds(1); - if (!kwds) goto limited_bad; - if (__Pyx_VectorcallBuilder_AddArgStr("signed", __Pyx_NewRef(Py_True), kwds, args+3, 0) < 0) goto limited_bad; - } - result = __Pyx_Object_Vectorcall_CallFromBuilder(from_bytes, args+1, 2 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET, kwds); - } - limited_bad: - Py_XDECREF(kwds); - Py_XDECREF(order_str); - Py_XDECREF(py_bytes); - Py_XDECREF(from_bytes); - return result; -#endif - } -} - -/* CIntFromPy */ -static CYTHON_INLINE TA_Compatibility __Pyx_PyLong_As_TA_Compatibility(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const TA_Compatibility neg_one = (TA_Compatibility) -1, const_zero = (TA_Compatibility) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (unlikely(!PyLong_Check(x))) { - TA_Compatibility val; - PyObject *tmp = __Pyx_PyNumber_Long(x); - if (!tmp) return (TA_Compatibility) -1; - val = __Pyx_PyLong_As_TA_Compatibility(tmp); - Py_DECREF(tmp); - return val; - } - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - if (unlikely(__Pyx_PyLong_IsNeg(x))) { - goto raise_neg_overflow; - } else if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(TA_Compatibility, __Pyx_compact_upylong, __Pyx_PyLong_CompactValueUnsigned(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_DigitCount(x)) { - case 2: - if ((8 * sizeof(TA_Compatibility) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_Compatibility, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_Compatibility) >= 2 * PyLong_SHIFT)) { - return (TA_Compatibility) (((((TA_Compatibility)digits[1]) << PyLong_SHIFT) | (TA_Compatibility)digits[0])); - } - } - break; - case 3: - if ((8 * sizeof(TA_Compatibility) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_Compatibility, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_Compatibility) >= 3 * PyLong_SHIFT)) { - return (TA_Compatibility) (((((((TA_Compatibility)digits[2]) << PyLong_SHIFT) | (TA_Compatibility)digits[1]) << PyLong_SHIFT) | (TA_Compatibility)digits[0])); - } - } - break; - case 4: - if ((8 * sizeof(TA_Compatibility) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_Compatibility, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_Compatibility) >= 4 * PyLong_SHIFT)) { - return (TA_Compatibility) (((((((((TA_Compatibility)digits[3]) << PyLong_SHIFT) | (TA_Compatibility)digits[2]) << PyLong_SHIFT) | (TA_Compatibility)digits[1]) << PyLong_SHIFT) | (TA_Compatibility)digits[0])); - } - } - break; - } - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030C00A7 - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (TA_Compatibility) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if ((sizeof(TA_Compatibility) <= sizeof(unsigned long))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_Compatibility, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(TA_Compatibility) <= sizeof(unsigned PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_Compatibility, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(TA_Compatibility, __Pyx_compact_pylong, __Pyx_PyLong_CompactValue(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_SignedDigitCount(x)) { - case -2: - if ((8 * sizeof(TA_Compatibility) - 1 > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_Compatibility, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_Compatibility) - 1 > 2 * PyLong_SHIFT)) { - return (TA_Compatibility) (((TA_Compatibility)-1)*(((((TA_Compatibility)digits[1]) << PyLong_SHIFT) | (TA_Compatibility)digits[0]))); - } - } - break; - case 2: - if ((8 * sizeof(TA_Compatibility) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_Compatibility, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_Compatibility) - 1 > 2 * PyLong_SHIFT)) { - return (TA_Compatibility) ((((((TA_Compatibility)digits[1]) << PyLong_SHIFT) | (TA_Compatibility)digits[0]))); - } - } - break; - case -3: - if ((8 * sizeof(TA_Compatibility) - 1 > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_Compatibility, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_Compatibility) - 1 > 3 * PyLong_SHIFT)) { - return (TA_Compatibility) (((TA_Compatibility)-1)*(((((((TA_Compatibility)digits[2]) << PyLong_SHIFT) | (TA_Compatibility)digits[1]) << PyLong_SHIFT) | (TA_Compatibility)digits[0]))); - } - } - break; - case 3: - if ((8 * sizeof(TA_Compatibility) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_Compatibility, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_Compatibility) - 1 > 3 * PyLong_SHIFT)) { - return (TA_Compatibility) ((((((((TA_Compatibility)digits[2]) << PyLong_SHIFT) | (TA_Compatibility)digits[1]) << PyLong_SHIFT) | (TA_Compatibility)digits[0]))); - } - } - break; - case -4: - if ((8 * sizeof(TA_Compatibility) - 1 > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_Compatibility, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_Compatibility) - 1 > 4 * PyLong_SHIFT)) { - return (TA_Compatibility) (((TA_Compatibility)-1)*(((((((((TA_Compatibility)digits[3]) << PyLong_SHIFT) | (TA_Compatibility)digits[2]) << PyLong_SHIFT) | (TA_Compatibility)digits[1]) << PyLong_SHIFT) | (TA_Compatibility)digits[0]))); - } - } - break; - case 4: - if ((8 * sizeof(TA_Compatibility) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_Compatibility, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_Compatibility) - 1 > 4 * PyLong_SHIFT)) { - return (TA_Compatibility) ((((((((((TA_Compatibility)digits[3]) << PyLong_SHIFT) | (TA_Compatibility)digits[2]) << PyLong_SHIFT) | (TA_Compatibility)digits[1]) << PyLong_SHIFT) | (TA_Compatibility)digits[0]))); - } - } - break; - } - } -#endif - if ((sizeof(TA_Compatibility) <= sizeof(long))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_Compatibility, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(TA_Compatibility) <= sizeof(PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_Compatibility, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { - TA_Compatibility val; - int ret = -1; -#if PY_VERSION_HEX >= 0x030d00A6 && !CYTHON_COMPILING_IN_LIMITED_API - Py_ssize_t bytes_copied = PyLong_AsNativeBytes( - x, &val, sizeof(val), Py_ASNATIVEBYTES_NATIVE_ENDIAN | (is_unsigned ? Py_ASNATIVEBYTES_UNSIGNED_BUFFER | Py_ASNATIVEBYTES_REJECT_NEGATIVE : 0)); - if (unlikely(bytes_copied == -1)) { - } else if (unlikely(bytes_copied > (Py_ssize_t) sizeof(val))) { - goto raise_overflow; - } else { - ret = 0; - } -#elif PY_VERSION_HEX < 0x030d0000 && !(CYTHON_COMPILING_IN_PYPY || CYTHON_COMPILING_IN_LIMITED_API) || defined(_PyLong_AsByteArray) - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - ret = _PyLong_AsByteArray((PyLongObject *)x, - bytes, sizeof(val), - is_little, !is_unsigned); -#else - PyObject *v; - PyObject *stepval = NULL, *mask = NULL, *shift = NULL; - int bits, remaining_bits, is_negative = 0; - int chunk_size = (sizeof(long) < 8) ? 30 : 62; - if (likely(PyLong_CheckExact(x))) { - v = __Pyx_NewRef(x); - } else { - v = PyNumber_Long(x); - if (unlikely(!v)) return (TA_Compatibility) -1; - assert(PyLong_CheckExact(v)); - } - { - int result = PyObject_RichCompareBool(v, Py_False, Py_LT); - if (unlikely(result < 0)) { - Py_DECREF(v); - return (TA_Compatibility) -1; - } - is_negative = result == 1; - } - if (is_unsigned && unlikely(is_negative)) { - Py_DECREF(v); - goto raise_neg_overflow; - } else if (is_negative) { - stepval = PyNumber_Invert(v); - Py_DECREF(v); - if (unlikely(!stepval)) - return (TA_Compatibility) -1; - } else { - stepval = v; - } - v = NULL; - val = (TA_Compatibility) 0; - mask = PyLong_FromLong((1L << chunk_size) - 1); if (unlikely(!mask)) goto done; - shift = PyLong_FromLong(chunk_size); if (unlikely(!shift)) goto done; - for (bits = 0; bits < (int) sizeof(TA_Compatibility) * 8 - chunk_size; bits += chunk_size) { - PyObject *tmp, *digit; - long idigit; - digit = PyNumber_And(stepval, mask); - if (unlikely(!digit)) goto done; - idigit = PyLong_AsLong(digit); - Py_DECREF(digit); - if (unlikely(idigit < 0)) goto done; - val |= ((TA_Compatibility) idigit) << bits; - tmp = PyNumber_Rshift(stepval, shift); - if (unlikely(!tmp)) goto done; - Py_DECREF(stepval); stepval = tmp; - } - Py_DECREF(shift); shift = NULL; - Py_DECREF(mask); mask = NULL; - { - long idigit = PyLong_AsLong(stepval); - if (unlikely(idigit < 0)) goto done; - remaining_bits = ((int) sizeof(TA_Compatibility) * 8) - bits - (is_unsigned ? 0 : 1); - if (unlikely(idigit >= (1L << remaining_bits))) - goto raise_overflow; - val |= ((TA_Compatibility) idigit) << bits; - } - if (!is_unsigned) { - if (unlikely(val & (((TA_Compatibility) 1) << (sizeof(TA_Compatibility) * 8 - 1)))) - goto raise_overflow; - if (is_negative) - val = ~val; - } - ret = 0; - done: - Py_XDECREF(shift); - Py_XDECREF(mask); - Py_XDECREF(stepval); -#endif - if (unlikely(ret)) - return (TA_Compatibility) -1; - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to TA_Compatibility"); - return (TA_Compatibility) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to TA_Compatibility"); - return (TA_Compatibility) -1; -} - -/* CIntFromPy */ -static CYTHON_INLINE TA_CandleSettingType __Pyx_PyLong_As_TA_CandleSettingType(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const TA_CandleSettingType neg_one = (TA_CandleSettingType) -1, const_zero = (TA_CandleSettingType) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (unlikely(!PyLong_Check(x))) { - TA_CandleSettingType val; - PyObject *tmp = __Pyx_PyNumber_Long(x); - if (!tmp) return (TA_CandleSettingType) -1; - val = __Pyx_PyLong_As_TA_CandleSettingType(tmp); - Py_DECREF(tmp); - return val; - } - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - if (unlikely(__Pyx_PyLong_IsNeg(x))) { - goto raise_neg_overflow; - } else if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(TA_CandleSettingType, __Pyx_compact_upylong, __Pyx_PyLong_CompactValueUnsigned(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_DigitCount(x)) { - case 2: - if ((8 * sizeof(TA_CandleSettingType) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_CandleSettingType, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_CandleSettingType) >= 2 * PyLong_SHIFT)) { - return (TA_CandleSettingType) (((((TA_CandleSettingType)digits[1]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[0])); - } - } - break; - case 3: - if ((8 * sizeof(TA_CandleSettingType) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_CandleSettingType, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_CandleSettingType) >= 3 * PyLong_SHIFT)) { - return (TA_CandleSettingType) (((((((TA_CandleSettingType)digits[2]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[1]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[0])); - } - } - break; - case 4: - if ((8 * sizeof(TA_CandleSettingType) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_CandleSettingType, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_CandleSettingType) >= 4 * PyLong_SHIFT)) { - return (TA_CandleSettingType) (((((((((TA_CandleSettingType)digits[3]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[2]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[1]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[0])); - } - } - break; - } - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030C00A7 - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (TA_CandleSettingType) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if ((sizeof(TA_CandleSettingType) <= sizeof(unsigned long))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_CandleSettingType, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(TA_CandleSettingType) <= sizeof(unsigned PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_CandleSettingType, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(TA_CandleSettingType, __Pyx_compact_pylong, __Pyx_PyLong_CompactValue(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_SignedDigitCount(x)) { - case -2: - if ((8 * sizeof(TA_CandleSettingType) - 1 > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_CandleSettingType, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_CandleSettingType) - 1 > 2 * PyLong_SHIFT)) { - return (TA_CandleSettingType) (((TA_CandleSettingType)-1)*(((((TA_CandleSettingType)digits[1]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[0]))); - } - } - break; - case 2: - if ((8 * sizeof(TA_CandleSettingType) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_CandleSettingType, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_CandleSettingType) - 1 > 2 * PyLong_SHIFT)) { - return (TA_CandleSettingType) ((((((TA_CandleSettingType)digits[1]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[0]))); - } - } - break; - case -3: - if ((8 * sizeof(TA_CandleSettingType) - 1 > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_CandleSettingType, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_CandleSettingType) - 1 > 3 * PyLong_SHIFT)) { - return (TA_CandleSettingType) (((TA_CandleSettingType)-1)*(((((((TA_CandleSettingType)digits[2]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[1]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[0]))); - } - } - break; - case 3: - if ((8 * sizeof(TA_CandleSettingType) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_CandleSettingType, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_CandleSettingType) - 1 > 3 * PyLong_SHIFT)) { - return (TA_CandleSettingType) ((((((((TA_CandleSettingType)digits[2]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[1]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[0]))); - } - } - break; - case -4: - if ((8 * sizeof(TA_CandleSettingType) - 1 > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_CandleSettingType, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_CandleSettingType) - 1 > 4 * PyLong_SHIFT)) { - return (TA_CandleSettingType) (((TA_CandleSettingType)-1)*(((((((((TA_CandleSettingType)digits[3]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[2]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[1]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[0]))); - } - } - break; - case 4: - if ((8 * sizeof(TA_CandleSettingType) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_CandleSettingType, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_CandleSettingType) - 1 > 4 * PyLong_SHIFT)) { - return (TA_CandleSettingType) ((((((((((TA_CandleSettingType)digits[3]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[2]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[1]) << PyLong_SHIFT) | (TA_CandleSettingType)digits[0]))); - } - } - break; - } - } -#endif - if ((sizeof(TA_CandleSettingType) <= sizeof(long))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_CandleSettingType, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(TA_CandleSettingType) <= sizeof(PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_CandleSettingType, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { - TA_CandleSettingType val; - int ret = -1; -#if PY_VERSION_HEX >= 0x030d00A6 && !CYTHON_COMPILING_IN_LIMITED_API - Py_ssize_t bytes_copied = PyLong_AsNativeBytes( - x, &val, sizeof(val), Py_ASNATIVEBYTES_NATIVE_ENDIAN | (is_unsigned ? Py_ASNATIVEBYTES_UNSIGNED_BUFFER | Py_ASNATIVEBYTES_REJECT_NEGATIVE : 0)); - if (unlikely(bytes_copied == -1)) { - } else if (unlikely(bytes_copied > (Py_ssize_t) sizeof(val))) { - goto raise_overflow; - } else { - ret = 0; - } -#elif PY_VERSION_HEX < 0x030d0000 && !(CYTHON_COMPILING_IN_PYPY || CYTHON_COMPILING_IN_LIMITED_API) || defined(_PyLong_AsByteArray) - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - ret = _PyLong_AsByteArray((PyLongObject *)x, - bytes, sizeof(val), - is_little, !is_unsigned); -#else - PyObject *v; - PyObject *stepval = NULL, *mask = NULL, *shift = NULL; - int bits, remaining_bits, is_negative = 0; - int chunk_size = (sizeof(long) < 8) ? 30 : 62; - if (likely(PyLong_CheckExact(x))) { - v = __Pyx_NewRef(x); - } else { - v = PyNumber_Long(x); - if (unlikely(!v)) return (TA_CandleSettingType) -1; - assert(PyLong_CheckExact(v)); - } - { - int result = PyObject_RichCompareBool(v, Py_False, Py_LT); - if (unlikely(result < 0)) { - Py_DECREF(v); - return (TA_CandleSettingType) -1; - } - is_negative = result == 1; - } - if (is_unsigned && unlikely(is_negative)) { - Py_DECREF(v); - goto raise_neg_overflow; - } else if (is_negative) { - stepval = PyNumber_Invert(v); - Py_DECREF(v); - if (unlikely(!stepval)) - return (TA_CandleSettingType) -1; - } else { - stepval = v; - } - v = NULL; - val = (TA_CandleSettingType) 0; - mask = PyLong_FromLong((1L << chunk_size) - 1); if (unlikely(!mask)) goto done; - shift = PyLong_FromLong(chunk_size); if (unlikely(!shift)) goto done; - for (bits = 0; bits < (int) sizeof(TA_CandleSettingType) * 8 - chunk_size; bits += chunk_size) { - PyObject *tmp, *digit; - long idigit; - digit = PyNumber_And(stepval, mask); - if (unlikely(!digit)) goto done; - idigit = PyLong_AsLong(digit); - Py_DECREF(digit); - if (unlikely(idigit < 0)) goto done; - val |= ((TA_CandleSettingType) idigit) << bits; - tmp = PyNumber_Rshift(stepval, shift); - if (unlikely(!tmp)) goto done; - Py_DECREF(stepval); stepval = tmp; - } - Py_DECREF(shift); shift = NULL; - Py_DECREF(mask); mask = NULL; - { - long idigit = PyLong_AsLong(stepval); - if (unlikely(idigit < 0)) goto done; - remaining_bits = ((int) sizeof(TA_CandleSettingType) * 8) - bits - (is_unsigned ? 0 : 1); - if (unlikely(idigit >= (1L << remaining_bits))) - goto raise_overflow; - val |= ((TA_CandleSettingType) idigit) << bits; - } - if (!is_unsigned) { - if (unlikely(val & (((TA_CandleSettingType) 1) << (sizeof(TA_CandleSettingType) * 8 - 1)))) - goto raise_overflow; - if (is_negative) - val = ~val; - } - ret = 0; - done: - Py_XDECREF(shift); - Py_XDECREF(mask); - Py_XDECREF(stepval); -#endif - if (unlikely(ret)) - return (TA_CandleSettingType) -1; - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to TA_CandleSettingType"); - return (TA_CandleSettingType) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to TA_CandleSettingType"); - return (TA_CandleSettingType) -1; -} - -/* CIntFromPy */ -static CYTHON_INLINE TA_RangeType __Pyx_PyLong_As_TA_RangeType(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const TA_RangeType neg_one = (TA_RangeType) -1, const_zero = (TA_RangeType) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (unlikely(!PyLong_Check(x))) { - TA_RangeType val; - PyObject *tmp = __Pyx_PyNumber_Long(x); - if (!tmp) return (TA_RangeType) -1; - val = __Pyx_PyLong_As_TA_RangeType(tmp); - Py_DECREF(tmp); - return val; - } - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - if (unlikely(__Pyx_PyLong_IsNeg(x))) { - goto raise_neg_overflow; - } else if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(TA_RangeType, __Pyx_compact_upylong, __Pyx_PyLong_CompactValueUnsigned(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_DigitCount(x)) { - case 2: - if ((8 * sizeof(TA_RangeType) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RangeType, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RangeType) >= 2 * PyLong_SHIFT)) { - return (TA_RangeType) (((((TA_RangeType)digits[1]) << PyLong_SHIFT) | (TA_RangeType)digits[0])); - } - } - break; - case 3: - if ((8 * sizeof(TA_RangeType) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RangeType, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RangeType) >= 3 * PyLong_SHIFT)) { - return (TA_RangeType) (((((((TA_RangeType)digits[2]) << PyLong_SHIFT) | (TA_RangeType)digits[1]) << PyLong_SHIFT) | (TA_RangeType)digits[0])); - } - } - break; - case 4: - if ((8 * sizeof(TA_RangeType) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RangeType, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RangeType) >= 4 * PyLong_SHIFT)) { - return (TA_RangeType) (((((((((TA_RangeType)digits[3]) << PyLong_SHIFT) | (TA_RangeType)digits[2]) << PyLong_SHIFT) | (TA_RangeType)digits[1]) << PyLong_SHIFT) | (TA_RangeType)digits[0])); - } - } - break; - } - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030C00A7 - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (TA_RangeType) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if ((sizeof(TA_RangeType) <= sizeof(unsigned long))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_RangeType, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(TA_RangeType) <= sizeof(unsigned PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_RangeType, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(TA_RangeType, __Pyx_compact_pylong, __Pyx_PyLong_CompactValue(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_SignedDigitCount(x)) { - case -2: - if ((8 * sizeof(TA_RangeType) - 1 > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RangeType, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RangeType) - 1 > 2 * PyLong_SHIFT)) { - return (TA_RangeType) (((TA_RangeType)-1)*(((((TA_RangeType)digits[1]) << PyLong_SHIFT) | (TA_RangeType)digits[0]))); - } - } - break; - case 2: - if ((8 * sizeof(TA_RangeType) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RangeType, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RangeType) - 1 > 2 * PyLong_SHIFT)) { - return (TA_RangeType) ((((((TA_RangeType)digits[1]) << PyLong_SHIFT) | (TA_RangeType)digits[0]))); - } - } - break; - case -3: - if ((8 * sizeof(TA_RangeType) - 1 > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RangeType, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RangeType) - 1 > 3 * PyLong_SHIFT)) { - return (TA_RangeType) (((TA_RangeType)-1)*(((((((TA_RangeType)digits[2]) << PyLong_SHIFT) | (TA_RangeType)digits[1]) << PyLong_SHIFT) | (TA_RangeType)digits[0]))); - } - } - break; - case 3: - if ((8 * sizeof(TA_RangeType) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RangeType, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RangeType) - 1 > 3 * PyLong_SHIFT)) { - return (TA_RangeType) ((((((((TA_RangeType)digits[2]) << PyLong_SHIFT) | (TA_RangeType)digits[1]) << PyLong_SHIFT) | (TA_RangeType)digits[0]))); - } - } - break; - case -4: - if ((8 * sizeof(TA_RangeType) - 1 > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RangeType, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RangeType) - 1 > 4 * PyLong_SHIFT)) { - return (TA_RangeType) (((TA_RangeType)-1)*(((((((((TA_RangeType)digits[3]) << PyLong_SHIFT) | (TA_RangeType)digits[2]) << PyLong_SHIFT) | (TA_RangeType)digits[1]) << PyLong_SHIFT) | (TA_RangeType)digits[0]))); - } - } - break; - case 4: - if ((8 * sizeof(TA_RangeType) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(TA_RangeType, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(TA_RangeType) - 1 > 4 * PyLong_SHIFT)) { - return (TA_RangeType) ((((((((((TA_RangeType)digits[3]) << PyLong_SHIFT) | (TA_RangeType)digits[2]) << PyLong_SHIFT) | (TA_RangeType)digits[1]) << PyLong_SHIFT) | (TA_RangeType)digits[0]))); - } - } - break; - } - } -#endif - if ((sizeof(TA_RangeType) <= sizeof(long))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_RangeType, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(TA_RangeType) <= sizeof(PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(TA_RangeType, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { - TA_RangeType val; - int ret = -1; -#if PY_VERSION_HEX >= 0x030d00A6 && !CYTHON_COMPILING_IN_LIMITED_API - Py_ssize_t bytes_copied = PyLong_AsNativeBytes( - x, &val, sizeof(val), Py_ASNATIVEBYTES_NATIVE_ENDIAN | (is_unsigned ? Py_ASNATIVEBYTES_UNSIGNED_BUFFER | Py_ASNATIVEBYTES_REJECT_NEGATIVE : 0)); - if (unlikely(bytes_copied == -1)) { - } else if (unlikely(bytes_copied > (Py_ssize_t) sizeof(val))) { - goto raise_overflow; - } else { - ret = 0; - } -#elif PY_VERSION_HEX < 0x030d0000 && !(CYTHON_COMPILING_IN_PYPY || CYTHON_COMPILING_IN_LIMITED_API) || defined(_PyLong_AsByteArray) - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - ret = _PyLong_AsByteArray((PyLongObject *)x, - bytes, sizeof(val), - is_little, !is_unsigned); -#else - PyObject *v; - PyObject *stepval = NULL, *mask = NULL, *shift = NULL; - int bits, remaining_bits, is_negative = 0; - int chunk_size = (sizeof(long) < 8) ? 30 : 62; - if (likely(PyLong_CheckExact(x))) { - v = __Pyx_NewRef(x); - } else { - v = PyNumber_Long(x); - if (unlikely(!v)) return (TA_RangeType) -1; - assert(PyLong_CheckExact(v)); - } - { - int result = PyObject_RichCompareBool(v, Py_False, Py_LT); - if (unlikely(result < 0)) { - Py_DECREF(v); - return (TA_RangeType) -1; - } - is_negative = result == 1; - } - if (is_unsigned && unlikely(is_negative)) { - Py_DECREF(v); - goto raise_neg_overflow; - } else if (is_negative) { - stepval = PyNumber_Invert(v); - Py_DECREF(v); - if (unlikely(!stepval)) - return (TA_RangeType) -1; - } else { - stepval = v; - } - v = NULL; - val = (TA_RangeType) 0; - mask = PyLong_FromLong((1L << chunk_size) - 1); if (unlikely(!mask)) goto done; - shift = PyLong_FromLong(chunk_size); if (unlikely(!shift)) goto done; - for (bits = 0; bits < (int) sizeof(TA_RangeType) * 8 - chunk_size; bits += chunk_size) { - PyObject *tmp, *digit; - long idigit; - digit = PyNumber_And(stepval, mask); - if (unlikely(!digit)) goto done; - idigit = PyLong_AsLong(digit); - Py_DECREF(digit); - if (unlikely(idigit < 0)) goto done; - val |= ((TA_RangeType) idigit) << bits; - tmp = PyNumber_Rshift(stepval, shift); - if (unlikely(!tmp)) goto done; - Py_DECREF(stepval); stepval = tmp; - } - Py_DECREF(shift); shift = NULL; - Py_DECREF(mask); mask = NULL; - { - long idigit = PyLong_AsLong(stepval); - if (unlikely(idigit < 0)) goto done; - remaining_bits = ((int) sizeof(TA_RangeType) * 8) - bits - (is_unsigned ? 0 : 1); - if (unlikely(idigit >= (1L << remaining_bits))) - goto raise_overflow; - val |= ((TA_RangeType) idigit) << bits; - } - if (!is_unsigned) { - if (unlikely(val & (((TA_RangeType) 1) << (sizeof(TA_RangeType) * 8 - 1)))) - goto raise_overflow; - if (is_negative) - val = ~val; - } - ret = 0; - done: - Py_XDECREF(shift); - Py_XDECREF(mask); - Py_XDECREF(stepval); -#endif - if (unlikely(ret)) - return (TA_RangeType) -1; - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to TA_RangeType"); - return (TA_RangeType) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to TA_RangeType"); - return (TA_RangeType) -1; -} - -/* CIntToPy */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_long(long value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const long neg_one = (long) -1, const_zero = (long) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(long) < sizeof(long)) { - return PyLong_FromLong((long) value); - } else if (sizeof(long) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#if defined(HAVE_LONG_LONG) && !CYTHON_COMPILING_IN_PYPY - } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(long) <= sizeof(long)) { - return PyLong_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - unsigned char *bytes = (unsigned char *)&value; -#if !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX >= 0x030d00A4 - if (is_unsigned) { - return PyLong_FromUnsignedNativeBytes(bytes, sizeof(value), -1); - } else { - return PyLong_FromNativeBytes(bytes, sizeof(value), -1); - } -#elif !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX < 0x030d0000 - int one = 1; int little = (int)*(unsigned char *)&one; - return _PyLong_FromByteArray(bytes, sizeof(long), - little, !is_unsigned); -#else - int one = 1; int little = (int)*(unsigned char *)&one; - PyObject *from_bytes, *result = NULL, *kwds = NULL; - PyObject *py_bytes = NULL, *order_str = NULL; - from_bytes = PyObject_GetAttrString((PyObject*)&PyLong_Type, "from_bytes"); - if (!from_bytes) return NULL; - py_bytes = PyBytes_FromStringAndSize((char*)bytes, sizeof(long)); - if (!py_bytes) goto limited_bad; - order_str = PyUnicode_FromString(little ? "little" : "big"); - if (!order_str) goto limited_bad; - { - PyObject *args[3+(CYTHON_VECTORCALL ? 1 : 0)] = { NULL, py_bytes, order_str }; - if (!is_unsigned) { - kwds = __Pyx_MakeVectorcallBuilderKwds(1); - if (!kwds) goto limited_bad; - if (__Pyx_VectorcallBuilder_AddArgStr("signed", __Pyx_NewRef(Py_True), kwds, args+3, 0) < 0) goto limited_bad; - } - result = __Pyx_Object_Vectorcall_CallFromBuilder(from_bytes, args+1, 2 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET, kwds); - } - limited_bad: - Py_XDECREF(kwds); - Py_XDECREF(order_str); - Py_XDECREF(py_bytes); - Py_XDECREF(from_bytes); - return result; -#endif - } -} - -/* CIntToPy */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_TA_OptInputParameterType(TA_OptInputParameterType value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const TA_OptInputParameterType neg_one = (TA_OptInputParameterType) -1, const_zero = (TA_OptInputParameterType) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(TA_OptInputParameterType) < sizeof(long)) { - return PyLong_FromLong((long) value); - } else if (sizeof(TA_OptInputParameterType) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#if defined(HAVE_LONG_LONG) && !CYTHON_COMPILING_IN_PYPY - } else if (sizeof(TA_OptInputParameterType) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(TA_OptInputParameterType) <= sizeof(long)) { - return PyLong_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(TA_OptInputParameterType) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - unsigned char *bytes = (unsigned char *)&value; -#if !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX >= 0x030d00A4 - if (is_unsigned) { - return PyLong_FromUnsignedNativeBytes(bytes, sizeof(value), -1); - } else { - return PyLong_FromNativeBytes(bytes, sizeof(value), -1); - } -#elif !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX < 0x030d0000 - int one = 1; int little = (int)*(unsigned char *)&one; - return _PyLong_FromByteArray(bytes, sizeof(TA_OptInputParameterType), - little, !is_unsigned); -#else - int one = 1; int little = (int)*(unsigned char *)&one; - PyObject *from_bytes, *result = NULL, *kwds = NULL; - PyObject *py_bytes = NULL, *order_str = NULL; - from_bytes = PyObject_GetAttrString((PyObject*)&PyLong_Type, "from_bytes"); - if (!from_bytes) return NULL; - py_bytes = PyBytes_FromStringAndSize((char*)bytes, sizeof(TA_OptInputParameterType)); - if (!py_bytes) goto limited_bad; - order_str = PyUnicode_FromString(little ? "little" : "big"); - if (!order_str) goto limited_bad; - { - PyObject *args[3+(CYTHON_VECTORCALL ? 1 : 0)] = { NULL, py_bytes, order_str }; - if (!is_unsigned) { - kwds = __Pyx_MakeVectorcallBuilderKwds(1); - if (!kwds) goto limited_bad; - if (__Pyx_VectorcallBuilder_AddArgStr("signed", __Pyx_NewRef(Py_True), kwds, args+3, 0) < 0) goto limited_bad; - } - result = __Pyx_Object_Vectorcall_CallFromBuilder(from_bytes, args+1, 2 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET, kwds); - } - limited_bad: - Py_XDECREF(kwds); - Py_XDECREF(order_str); - Py_XDECREF(py_bytes); - Py_XDECREF(from_bytes); - return result; -#endif - } -} - -/* CIntToPy */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_TA_FuncFlags(TA_FuncFlags value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const TA_FuncFlags neg_one = (TA_FuncFlags) -1, const_zero = (TA_FuncFlags) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(TA_FuncFlags) < sizeof(long)) { - return PyLong_FromLong((long) value); - } else if (sizeof(TA_FuncFlags) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#if defined(HAVE_LONG_LONG) && !CYTHON_COMPILING_IN_PYPY - } else if (sizeof(TA_FuncFlags) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(TA_FuncFlags) <= sizeof(long)) { - return PyLong_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(TA_FuncFlags) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - unsigned char *bytes = (unsigned char *)&value; -#if !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX >= 0x030d00A4 - if (is_unsigned) { - return PyLong_FromUnsignedNativeBytes(bytes, sizeof(value), -1); - } else { - return PyLong_FromNativeBytes(bytes, sizeof(value), -1); - } -#elif !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX < 0x030d0000 - int one = 1; int little = (int)*(unsigned char *)&one; - return _PyLong_FromByteArray(bytes, sizeof(TA_FuncFlags), - little, !is_unsigned); -#else - int one = 1; int little = (int)*(unsigned char *)&one; - PyObject *from_bytes, *result = NULL, *kwds = NULL; - PyObject *py_bytes = NULL, *order_str = NULL; - from_bytes = PyObject_GetAttrString((PyObject*)&PyLong_Type, "from_bytes"); - if (!from_bytes) return NULL; - py_bytes = PyBytes_FromStringAndSize((char*)bytes, sizeof(TA_FuncFlags)); - if (!py_bytes) goto limited_bad; - order_str = PyUnicode_FromString(little ? "little" : "big"); - if (!order_str) goto limited_bad; - { - PyObject *args[3+(CYTHON_VECTORCALL ? 1 : 0)] = { NULL, py_bytes, order_str }; - if (!is_unsigned) { - kwds = __Pyx_MakeVectorcallBuilderKwds(1); - if (!kwds) goto limited_bad; - if (__Pyx_VectorcallBuilder_AddArgStr("signed", __Pyx_NewRef(Py_True), kwds, args+3, 0) < 0) goto limited_bad; - } - result = __Pyx_Object_Vectorcall_CallFromBuilder(from_bytes, args+1, 2 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET, kwds); - } - limited_bad: - Py_XDECREF(kwds); - Py_XDECREF(order_str); - Py_XDECREF(py_bytes); - Py_XDECREF(from_bytes); - return result; -#endif - } -} - -/* CIntToPy */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_TA_InputFlags(TA_InputFlags value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const TA_InputFlags neg_one = (TA_InputFlags) -1, const_zero = (TA_InputFlags) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(TA_InputFlags) < sizeof(long)) { - return PyLong_FromLong((long) value); - } else if (sizeof(TA_InputFlags) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#if defined(HAVE_LONG_LONG) && !CYTHON_COMPILING_IN_PYPY - } else if (sizeof(TA_InputFlags) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(TA_InputFlags) <= sizeof(long)) { - return PyLong_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(TA_InputFlags) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - unsigned char *bytes = (unsigned char *)&value; -#if !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX >= 0x030d00A4 - if (is_unsigned) { - return PyLong_FromUnsignedNativeBytes(bytes, sizeof(value), -1); - } else { - return PyLong_FromNativeBytes(bytes, sizeof(value), -1); - } -#elif !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX < 0x030d0000 - int one = 1; int little = (int)*(unsigned char *)&one; - return _PyLong_FromByteArray(bytes, sizeof(TA_InputFlags), - little, !is_unsigned); -#else - int one = 1; int little = (int)*(unsigned char *)&one; - PyObject *from_bytes, *result = NULL, *kwds = NULL; - PyObject *py_bytes = NULL, *order_str = NULL; - from_bytes = PyObject_GetAttrString((PyObject*)&PyLong_Type, "from_bytes"); - if (!from_bytes) return NULL; - py_bytes = PyBytes_FromStringAndSize((char*)bytes, sizeof(TA_InputFlags)); - if (!py_bytes) goto limited_bad; - order_str = PyUnicode_FromString(little ? "little" : "big"); - if (!order_str) goto limited_bad; - { - PyObject *args[3+(CYTHON_VECTORCALL ? 1 : 0)] = { NULL, py_bytes, order_str }; - if (!is_unsigned) { - kwds = __Pyx_MakeVectorcallBuilderKwds(1); - if (!kwds) goto limited_bad; - if (__Pyx_VectorcallBuilder_AddArgStr("signed", __Pyx_NewRef(Py_True), kwds, args+3, 0) < 0) goto limited_bad; - } - result = __Pyx_Object_Vectorcall_CallFromBuilder(from_bytes, args+1, 2 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET, kwds); - } - limited_bad: - Py_XDECREF(kwds); - Py_XDECREF(order_str); - Py_XDECREF(py_bytes); - Py_XDECREF(from_bytes); - return result; -#endif - } -} - -/* CIntToPy */ -static CYTHON_INLINE PyObject* __Pyx_PyLong_From_TA_OutputFlags(TA_OutputFlags value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const TA_OutputFlags neg_one = (TA_OutputFlags) -1, const_zero = (TA_OutputFlags) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(TA_OutputFlags) < sizeof(long)) { - return PyLong_FromLong((long) value); - } else if (sizeof(TA_OutputFlags) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#if defined(HAVE_LONG_LONG) && !CYTHON_COMPILING_IN_PYPY - } else if (sizeof(TA_OutputFlags) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(TA_OutputFlags) <= sizeof(long)) { - return PyLong_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(TA_OutputFlags) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - unsigned char *bytes = (unsigned char *)&value; -#if !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX >= 0x030d00A4 - if (is_unsigned) { - return PyLong_FromUnsignedNativeBytes(bytes, sizeof(value), -1); - } else { - return PyLong_FromNativeBytes(bytes, sizeof(value), -1); - } -#elif !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX < 0x030d0000 - int one = 1; int little = (int)*(unsigned char *)&one; - return _PyLong_FromByteArray(bytes, sizeof(TA_OutputFlags), - little, !is_unsigned); -#else - int one = 1; int little = (int)*(unsigned char *)&one; - PyObject *from_bytes, *result = NULL, *kwds = NULL; - PyObject *py_bytes = NULL, *order_str = NULL; - from_bytes = PyObject_GetAttrString((PyObject*)&PyLong_Type, "from_bytes"); - if (!from_bytes) return NULL; - py_bytes = PyBytes_FromStringAndSize((char*)bytes, sizeof(TA_OutputFlags)); - if (!py_bytes) goto limited_bad; - order_str = PyUnicode_FromString(little ? "little" : "big"); - if (!order_str) goto limited_bad; - { - PyObject *args[3+(CYTHON_VECTORCALL ? 1 : 0)] = { NULL, py_bytes, order_str }; - if (!is_unsigned) { - kwds = __Pyx_MakeVectorcallBuilderKwds(1); - if (!kwds) goto limited_bad; - if (__Pyx_VectorcallBuilder_AddArgStr("signed", __Pyx_NewRef(Py_True), kwds, args+3, 0) < 0) goto limited_bad; - } - result = __Pyx_Object_Vectorcall_CallFromBuilder(from_bytes, args+1, 2 | __Pyx_PY_VECTORCALL_ARGUMENTS_OFFSET, kwds); - } - limited_bad: - Py_XDECREF(kwds); - Py_XDECREF(order_str); - Py_XDECREF(py_bytes); - Py_XDECREF(from_bytes); - return result; -#endif - } -} - -/* FormatTypeName */ -#if CYTHON_COMPILING_IN_LIMITED_API && __PYX_LIMITED_VERSION_HEX < 0x030d0000 -static __Pyx_TypeName -__Pyx_PyType_GetFullyQualifiedName(PyTypeObject* tp) -{ - PyObject *module = NULL, *name = NULL, *result = NULL; - #if __PYX_LIMITED_VERSION_HEX < 0x030b0000 - name = __Pyx_PyObject_GetAttrStr((PyObject *)tp, - __pyx_mstate_global->__pyx_n_u_qualname); - #else - name = PyType_GetQualName(tp); - #endif - if (unlikely(name == NULL) || unlikely(!PyUnicode_Check(name))) goto bad; - module = __Pyx_PyObject_GetAttrStr((PyObject *)tp, - __pyx_mstate_global->__pyx_n_u_module); - if (unlikely(module == NULL) || unlikely(!PyUnicode_Check(module))) goto bad; - if (PyUnicode_CompareWithASCIIString(module, "builtins") == 0) { - result = name; - name = NULL; - goto done; - } - result = PyUnicode_FromFormat("%U.%U", module, name); - if (unlikely(result == NULL)) goto bad; - done: - Py_XDECREF(name); - Py_XDECREF(module); - return result; - bad: - PyErr_Clear(); - if (name) { - result = name; - name = NULL; - } else { - result = __Pyx_NewRef(__pyx_mstate_global->__pyx_kp_u__15); - } - goto done; -} -#endif - -/* CIntFromPy */ -static CYTHON_INLINE long __Pyx_PyLong_As_long(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const long neg_one = (long) -1, const_zero = (long) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (unlikely(!PyLong_Check(x))) { - long val; - PyObject *tmp = __Pyx_PyNumber_Long(x); - if (!tmp) return (long) -1; - val = __Pyx_PyLong_As_long(tmp); - Py_DECREF(tmp); - return val; - } - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - if (unlikely(__Pyx_PyLong_IsNeg(x))) { - goto raise_neg_overflow; - } else if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(long, __Pyx_compact_upylong, __Pyx_PyLong_CompactValueUnsigned(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_DigitCount(x)) { - case 2: - if ((8 * sizeof(long) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(long) >= 2 * PyLong_SHIFT)) { - return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - case 3: - if ((8 * sizeof(long) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(long) >= 3 * PyLong_SHIFT)) { - return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - case 4: - if ((8 * sizeof(long) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(long) >= 4 * PyLong_SHIFT)) { - return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - } - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030C00A7 - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (long) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if ((sizeof(long) <= sizeof(unsigned long))) { - __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(long) <= sizeof(unsigned PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - if (__Pyx_PyLong_IsCompact(x)) { - __PYX_VERIFY_RETURN_INT(long, __Pyx_compact_pylong, __Pyx_PyLong_CompactValue(x)) - } else { - const digit* digits = __Pyx_PyLong_Digits(x); - assert(__Pyx_PyLong_DigitCount(x) > 1); - switch (__Pyx_PyLong_SignedDigitCount(x)) { - case -2: - if ((8 * sizeof(long) - 1 > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(long) - 1 > 2 * PyLong_SHIFT)) { - return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 2: - if ((8 * sizeof(long) > 1 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 2 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(long) - 1 > 2 * PyLong_SHIFT)) { - return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case -3: - if ((8 * sizeof(long) - 1 > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(long) - 1 > 3 * PyLong_SHIFT)) { - return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 3: - if ((8 * sizeof(long) > 2 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 3 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(long) - 1 > 3 * PyLong_SHIFT)) { - return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case -4: - if ((8 * sizeof(long) - 1 > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(long) - 1 > 4 * PyLong_SHIFT)) { - return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 4: - if ((8 * sizeof(long) > 3 * PyLong_SHIFT)) { - if ((8 * sizeof(unsigned long) > 4 * PyLong_SHIFT)) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if ((8 * sizeof(long) - 1 > 4 * PyLong_SHIFT)) { - return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - } - } -#endif - if ((sizeof(long) <= sizeof(long))) { - __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if ((sizeof(long) <= sizeof(PY_LONG_LONG))) { - __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { - long val; - int ret = -1; -#if PY_VERSION_HEX >= 0x030d00A6 && !CYTHON_COMPILING_IN_LIMITED_API - Py_ssize_t bytes_copied = PyLong_AsNativeBytes( - x, &val, sizeof(val), Py_ASNATIVEBYTES_NATIVE_ENDIAN | (is_unsigned ? Py_ASNATIVEBYTES_UNSIGNED_BUFFER | Py_ASNATIVEBYTES_REJECT_NEGATIVE : 0)); - if (unlikely(bytes_copied == -1)) { - } else if (unlikely(bytes_copied > (Py_ssize_t) sizeof(val))) { - goto raise_overflow; - } else { - ret = 0; - } -#elif PY_VERSION_HEX < 0x030d0000 && !(CYTHON_COMPILING_IN_PYPY || CYTHON_COMPILING_IN_LIMITED_API) || defined(_PyLong_AsByteArray) - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - ret = _PyLong_AsByteArray((PyLongObject *)x, - bytes, sizeof(val), - is_little, !is_unsigned); -#else - PyObject *v; - PyObject *stepval = NULL, *mask = NULL, *shift = NULL; - int bits, remaining_bits, is_negative = 0; - int chunk_size = (sizeof(long) < 8) ? 30 : 62; - if (likely(PyLong_CheckExact(x))) { - v = __Pyx_NewRef(x); - } else { - v = PyNumber_Long(x); - if (unlikely(!v)) return (long) -1; - assert(PyLong_CheckExact(v)); - } - { - int result = PyObject_RichCompareBool(v, Py_False, Py_LT); - if (unlikely(result < 0)) { - Py_DECREF(v); - return (long) -1; - } - is_negative = result == 1; - } - if (is_unsigned && unlikely(is_negative)) { - Py_DECREF(v); - goto raise_neg_overflow; - } else if (is_negative) { - stepval = PyNumber_Invert(v); - Py_DECREF(v); - if (unlikely(!stepval)) - return (long) -1; - } else { - stepval = v; - } - v = NULL; - val = (long) 0; - mask = PyLong_FromLong((1L << chunk_size) - 1); if (unlikely(!mask)) goto done; - shift = PyLong_FromLong(chunk_size); if (unlikely(!shift)) goto done; - for (bits = 0; bits < (int) sizeof(long) * 8 - chunk_size; bits += chunk_size) { - PyObject *tmp, *digit; - long idigit; - digit = PyNumber_And(stepval, mask); - if (unlikely(!digit)) goto done; - idigit = PyLong_AsLong(digit); - Py_DECREF(digit); - if (unlikely(idigit < 0)) goto done; - val |= ((long) idigit) << bits; - tmp = PyNumber_Rshift(stepval, shift); - if (unlikely(!tmp)) goto done; - Py_DECREF(stepval); stepval = tmp; - } - Py_DECREF(shift); shift = NULL; - Py_DECREF(mask); mask = NULL; - { - long idigit = PyLong_AsLong(stepval); - if (unlikely(idigit < 0)) goto done; - remaining_bits = ((int) sizeof(long) * 8) - bits - (is_unsigned ? 0 : 1); - if (unlikely(idigit >= (1L << remaining_bits))) - goto raise_overflow; - val |= ((long) idigit) << bits; - } - if (!is_unsigned) { - if (unlikely(val & (((long) 1) << (sizeof(long) * 8 - 1)))) - goto raise_overflow; - if (is_negative) - val = ~val; - } - ret = 0; - done: - Py_XDECREF(shift); - Py_XDECREF(mask); - Py_XDECREF(stepval); -#endif - if (unlikely(ret)) - return (long) -1; - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to long"); - return (long) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to long"); - return (long) -1; -} - -/* FastTypeChecks */ -#if CYTHON_COMPILING_IN_CPYTHON -static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { - while (a) { - a = __Pyx_PyType_GetSlot(a, tp_base, PyTypeObject*); - if (a == b) - return 1; - } - return b == &PyBaseObject_Type; -} -static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { - PyObject *mro; - if (a == b) return 1; - mro = a->tp_mro; - if (likely(mro)) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(mro); - for (i = 0; i < n; i++) { - if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) - return 1; - } - return 0; - } - return __Pyx_InBases(a, b); -} -static CYTHON_INLINE int __Pyx_IsAnySubtype2(PyTypeObject *cls, PyTypeObject *a, PyTypeObject *b) { - PyObject *mro; - if (cls == a || cls == b) return 1; - mro = cls->tp_mro; - if (likely(mro)) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(mro); - for (i = 0; i < n; i++) { - PyObject *base = PyTuple_GET_ITEM(mro, i); - if (base == (PyObject *)a || base == (PyObject *)b) - return 1; - } - return 0; - } - return __Pyx_InBases(cls, a) || __Pyx_InBases(cls, b); -} -static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { - if (exc_type1) { - return __Pyx_IsAnySubtype2((PyTypeObject*)err, (PyTypeObject*)exc_type1, (PyTypeObject*)exc_type2); - } else { - return __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); - } -} -static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { - Py_ssize_t i, n; - assert(PyExceptionClass_Check(exc_type)); - n = PyTuple_GET_SIZE(tuple); - for (i=0; i= 0x030b0000 - return Py_Version & ~0xFFUL; -#else - static unsigned long __Pyx_cached_runtime_version = 0; - if (__Pyx_cached_runtime_version == 0) { - const char* rt_version = Py_GetVersion(); - unsigned long version = 0; - unsigned long factor = 0x01000000UL; - unsigned int digit = 0; - int i = 0; - while (factor) { - while ('0' <= rt_version[i] && rt_version[i] <= '9') { - digit = digit * 10 + (unsigned int) (rt_version[i] - '0'); - ++i; - } - version += factor * digit; - if (rt_version[i] != '.') - break; - digit = 0; - factor >>= 8; - ++i; - } - __Pyx_cached_runtime_version = version; - } - return __Pyx_cached_runtime_version; -#endif -} - -/* CheckBinaryVersion */ -static int __Pyx_check_binary_version(unsigned long ct_version, unsigned long rt_version, int allow_newer) { - const unsigned long MAJOR_MINOR = 0xFFFF0000UL; - if ((rt_version & MAJOR_MINOR) == (ct_version & MAJOR_MINOR)) - return 0; - if (likely(allow_newer && (rt_version & MAJOR_MINOR) > (ct_version & MAJOR_MINOR))) - return 1; - { - char message[200]; - PyOS_snprintf(message, sizeof(message), - "compile time Python version %d.%d " - "of module '%.100s' " - "%s " - "runtime version %d.%d", - (int) (ct_version >> 24), (int) ((ct_version >> 16) & 0xFF), - __Pyx_MODULE_NAME, - (allow_newer) ? "was newer than" : "does not match", - (int) (rt_version >> 24), (int) ((rt_version >> 16) & 0xFF) - ); - return PyErr_WarnEx(NULL, message, 1); - } -} - -/* NewCodeObj */ -#if CYTHON_COMPILING_IN_LIMITED_API - static PyObject* __Pyx__PyCode_New(int a, int p, int k, int l, int s, int f, - PyObject *code, PyObject *c, PyObject* n, PyObject *v, - PyObject *fv, PyObject *cell, PyObject* fn, - PyObject *name, int fline, PyObject *lnos) { - PyObject *exception_table = NULL; - PyObject *types_module=NULL, *code_type=NULL, *result=NULL; - #if __PYX_LIMITED_VERSION_HEX < 0x030b0000 - PyObject *version_info; - PyObject *py_minor_version = NULL; - #endif - long minor_version = 0; - PyObject *type, *value, *traceback; - PyErr_Fetch(&type, &value, &traceback); - #if __PYX_LIMITED_VERSION_HEX >= 0x030b0000 - minor_version = 11; - #else - if (!(version_info = PySys_GetObject("version_info"))) goto end; - if (!(py_minor_version = PySequence_GetItem(version_info, 1))) goto end; - minor_version = PyLong_AsLong(py_minor_version); - Py_DECREF(py_minor_version); - if (minor_version == -1 && PyErr_Occurred()) goto end; - #endif - if (!(types_module = PyImport_ImportModule("types"))) goto end; - if (!(code_type = PyObject_GetAttrString(types_module, "CodeType"))) goto end; - if (minor_version <= 7) { - (void)p; - result = PyObject_CallFunction(code_type, "iiiiiOOOOOOiOOO", a, k, l, s, f, code, - c, n, v, fn, name, fline, lnos, fv, cell); - } else if (minor_version <= 10) { - result = PyObject_CallFunction(code_type, "iiiiiiOOOOOOiOOO", a,p, k, l, s, f, code, - c, n, v, fn, name, fline, lnos, fv, cell); - } else { - if (!(exception_table = PyBytes_FromStringAndSize(NULL, 0))) goto end; - result = PyObject_CallFunction(code_type, "iiiiiiOOOOOOOiOOOO", a,p, k, l, s, f, code, - c, n, v, fn, name, name, fline, lnos, exception_table, fv, cell); - } - end: - Py_XDECREF(code_type); - Py_XDECREF(exception_table); - Py_XDECREF(types_module); - if (type) { - PyErr_Restore(type, value, traceback); - } - return result; - } -#elif PY_VERSION_HEX >= 0x030B0000 - static PyCodeObject* __Pyx__PyCode_New(int a, int p, int k, int l, int s, int f, - PyObject *code, PyObject *c, PyObject* n, PyObject *v, - PyObject *fv, PyObject *cell, PyObject* fn, - PyObject *name, int fline, PyObject *lnos) { - PyCodeObject *result; - result = - #if PY_VERSION_HEX >= 0x030C0000 - PyUnstable_Code_NewWithPosOnlyArgs - #else - PyCode_NewWithPosOnlyArgs - #endif - (a, p, k, l, s, f, code, c, n, v, fv, cell, fn, name, name, fline, lnos, __pyx_mstate_global->__pyx_empty_bytes); - return result; - } -#elif PY_VERSION_HEX >= 0x030800B2 && !CYTHON_COMPILING_IN_PYPY - #define __Pyx__PyCode_New(a, p, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ - PyCode_NewWithPosOnlyArgs(a, p, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) -#else - #define __Pyx__PyCode_New(a, p, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ - PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) -#endif -static PyObject* __Pyx_PyCode_New( - const __Pyx_PyCode_New_function_description descr, - PyObject * const *varnames, - PyObject *filename, - PyObject *funcname, - const char *line_table, - PyObject *tuple_dedup_map -) { - PyObject *code_obj = NULL, *varnames_tuple_dedup = NULL, *code_bytes = NULL, *line_table_bytes = NULL; - Py_ssize_t var_count = (Py_ssize_t) descr.nlocals; - PyObject *varnames_tuple = PyTuple_New(var_count); - if (unlikely(!varnames_tuple)) return NULL; - for (Py_ssize_t i=0; i < var_count; i++) { - Py_INCREF(varnames[i]); - if (__Pyx_PyTuple_SET_ITEM(varnames_tuple, i, varnames[i]) != (0)) goto done; - } - #if CYTHON_COMPILING_IN_LIMITED_API - varnames_tuple_dedup = PyDict_GetItem(tuple_dedup_map, varnames_tuple); - if (!varnames_tuple_dedup) { - if (unlikely(PyDict_SetItem(tuple_dedup_map, varnames_tuple, varnames_tuple) < 0)) goto done; - varnames_tuple_dedup = varnames_tuple; - } - #else - varnames_tuple_dedup = PyDict_SetDefault(tuple_dedup_map, varnames_tuple, varnames_tuple); - if (unlikely(!varnames_tuple_dedup)) goto done; - #endif - #if CYTHON_AVOID_BORROWED_REFS - Py_INCREF(varnames_tuple_dedup); - #endif - if (__PYX_LIMITED_VERSION_HEX >= (0x030b0000) && line_table != NULL - && !CYTHON_COMPILING_IN_GRAAL) { - line_table_bytes = PyBytes_FromStringAndSize(line_table, descr.line_table_length); - if (unlikely(!line_table_bytes)) goto done; - Py_ssize_t code_len = (descr.line_table_length * 2 + 4) & ~3; - code_bytes = PyBytes_FromStringAndSize(NULL, code_len); - if (unlikely(!code_bytes)) goto done; - char* c_code_bytes = PyBytes_AsString(code_bytes); - if (unlikely(!c_code_bytes)) goto done; - memset(c_code_bytes, 0, (size_t) code_len); - } - code_obj = (PyObject*) __Pyx__PyCode_New( - (int) descr.argcount, - (int) descr.num_posonly_args, - (int) descr.num_kwonly_args, - (int) descr.nlocals, - 0, - (int) descr.flags, - code_bytes ? code_bytes : __pyx_mstate_global->__pyx_empty_bytes, - __pyx_mstate_global->__pyx_empty_tuple, - __pyx_mstate_global->__pyx_empty_tuple, - varnames_tuple_dedup, - __pyx_mstate_global->__pyx_empty_tuple, - __pyx_mstate_global->__pyx_empty_tuple, - filename, - funcname, - (int) descr.first_line, - (__PYX_LIMITED_VERSION_HEX >= (0x030b0000) && line_table_bytes) ? line_table_bytes : __pyx_mstate_global->__pyx_empty_bytes - ); -done: - Py_XDECREF(code_bytes); - Py_XDECREF(line_table_bytes); - #if CYTHON_AVOID_BORROWED_REFS - Py_XDECREF(varnames_tuple_dedup); - #endif - Py_DECREF(varnames_tuple); - return code_obj; -} - -/* InitStrings */ -static int __Pyx_InitStrings(__Pyx_StringTabEntry const *t, PyObject **target, const char* const* encoding_names) { - while (t->s) { - PyObject *str; - if (t->is_unicode) { - if (t->intern) { - str = PyUnicode_InternFromString(t->s); - } else if (t->encoding) { - str = PyUnicode_Decode(t->s, t->n - 1, encoding_names[t->encoding], NULL); - } else { - str = PyUnicode_FromStringAndSize(t->s, t->n - 1); - } - } else { - str = PyBytes_FromStringAndSize(t->s, t->n - 1); - } - if (!str) - return -1; - *target = str; - if (PyObject_Hash(str) == -1) - return -1; - ++t; - ++target; - } - return 0; -} - -#include -static CYTHON_INLINE Py_ssize_t __Pyx_ssize_strlen(const char *s) { - size_t len = strlen(s); - if (unlikely(len > (size_t) PY_SSIZE_T_MAX)) { - PyErr_SetString(PyExc_OverflowError, "byte string is too long"); - return -1; - } - return (Py_ssize_t) len; -} -static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { - Py_ssize_t len = __Pyx_ssize_strlen(c_str); - if (unlikely(len < 0)) return NULL; - return __Pyx_PyUnicode_FromStringAndSize(c_str, len); -} -static CYTHON_INLINE PyObject* __Pyx_PyByteArray_FromString(const char* c_str) { - Py_ssize_t len = __Pyx_ssize_strlen(c_str); - if (unlikely(len < 0)) return NULL; - return PyByteArray_FromStringAndSize(c_str, len); -} -static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { - Py_ssize_t ignore; - return __Pyx_PyObject_AsStringAndSize(o, &ignore); -} -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 -static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { - if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; -#if CYTHON_COMPILING_IN_LIMITED_API - { - const char* result; - Py_ssize_t unicode_length; - CYTHON_MAYBE_UNUSED_VAR(unicode_length); // only for __PYX_DEFAULT_STRING_ENCODING_IS_ASCII - #if __PYX_LIMITED_VERSION_HEX < 0x030A0000 - if (unlikely(PyArg_Parse(o, "s#", &result, length) < 0)) return NULL; - #else - result = PyUnicode_AsUTF8AndSize(o, length); - #endif - #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII - unicode_length = PyUnicode_GetLength(o); - if (unlikely(unicode_length < 0)) return NULL; - if (unlikely(unicode_length != *length)) { - PyUnicode_AsASCIIString(o); - return NULL; - } - #endif - return result; - } -#else -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII - if (likely(PyUnicode_IS_ASCII(o))) { - *length = PyUnicode_GET_LENGTH(o); - return PyUnicode_AsUTF8(o); - } else { - PyUnicode_AsASCIIString(o); - return NULL; - } -#else - return PyUnicode_AsUTF8AndSize(o, length); -#endif -#endif -} -#endif -static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { -#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 - if (PyUnicode_Check(o)) { - return __Pyx_PyUnicode_AsStringAndSize(o, length); - } else -#endif - if (PyByteArray_Check(o)) { -#if (CYTHON_ASSUME_SAFE_SIZE && CYTHON_ASSUME_SAFE_MACROS) || (CYTHON_COMPILING_IN_PYPY && (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE))) - *length = PyByteArray_GET_SIZE(o); - return PyByteArray_AS_STRING(o); -#else - *length = PyByteArray_Size(o); - if (*length == -1) return NULL; - return PyByteArray_AsString(o); -#endif - } else - { - char* result; - int r = PyBytes_AsStringAndSize(o, &result, length); - if (unlikely(r < 0)) { - return NULL; - } else { - return result; - } - } -} -static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { - int is_true = x == Py_True; - if (is_true | (x == Py_False) | (x == Py_None)) return is_true; - else return PyObject_IsTrue(x); -} -static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) { - int retval; - if (unlikely(!x)) return -1; - retval = __Pyx_PyObject_IsTrue(x); - Py_DECREF(x); - return retval; -} -static PyObject* __Pyx_PyNumber_LongWrongResultType(PyObject* result) { - __Pyx_TypeName result_type_name = __Pyx_PyType_GetFullyQualifiedName(Py_TYPE(result)); - if (PyLong_Check(result)) { - if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1, - "__int__ returned non-int (type " __Pyx_FMT_TYPENAME "). " - "The ability to return an instance of a strict subclass of int is deprecated, " - "and may be removed in a future version of Python.", - result_type_name)) { - __Pyx_DECREF_TypeName(result_type_name); - Py_DECREF(result); - return NULL; - } - __Pyx_DECREF_TypeName(result_type_name); - return result; - } - PyErr_Format(PyExc_TypeError, - "__int__ returned non-int (type " __Pyx_FMT_TYPENAME ")", - result_type_name); - __Pyx_DECREF_TypeName(result_type_name); - Py_DECREF(result); - return NULL; -} -static CYTHON_INLINE PyObject* __Pyx_PyNumber_Long(PyObject* x) { -#if CYTHON_USE_TYPE_SLOTS - PyNumberMethods *m; -#endif - PyObject *res = NULL; - if (likely(PyLong_Check(x))) - return __Pyx_NewRef(x); -#if CYTHON_USE_TYPE_SLOTS - m = Py_TYPE(x)->tp_as_number; - if (likely(m && m->nb_int)) { - res = m->nb_int(x); - } -#else - if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) { - res = PyNumber_Long(x); - } -#endif - if (likely(res)) { - if (unlikely(!PyLong_CheckExact(res))) { - return __Pyx_PyNumber_LongWrongResultType(res); - } - } - else if (!PyErr_Occurred()) { - PyErr_SetString(PyExc_TypeError, - "an integer is required"); - } - return res; -} -static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { - Py_ssize_t ival; - PyObject *x; - if (likely(PyLong_CheckExact(b))) { - #if CYTHON_USE_PYLONG_INTERNALS - if (likely(__Pyx_PyLong_IsCompact(b))) { - return __Pyx_PyLong_CompactValue(b); - } else { - const digit* digits = __Pyx_PyLong_Digits(b); - const Py_ssize_t size = __Pyx_PyLong_SignedDigitCount(b); - switch (size) { - case 2: - if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { - return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); - } - break; - case -2: - if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { - return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); - } - break; - case 3: - if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { - return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); - } - break; - case -3: - if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { - return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); - } - break; - case 4: - if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { - return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); - } - break; - case -4: - if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { - return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); - } - break; - } - } - #endif - return PyLong_AsSsize_t(b); - } - x = PyNumber_Index(b); - if (!x) return -1; - ival = PyLong_AsSsize_t(x); - Py_DECREF(x); - return ival; -} -static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject* o) { - if (sizeof(Py_hash_t) == sizeof(Py_ssize_t)) { - return (Py_hash_t) __Pyx_PyIndex_AsSsize_t(o); - } else { - Py_ssize_t ival; - PyObject *x; - x = PyNumber_Index(o); - if (!x) return -1; - ival = PyLong_AsLong(x); - Py_DECREF(x); - return ival; - } -} -static CYTHON_INLINE PyObject *__Pyx_Owned_Py_None(int b) { - CYTHON_UNUSED_VAR(b); - return __Pyx_NewRef(Py_None); -} -static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) { - return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False); -} -static CYTHON_INLINE PyObject * __Pyx_PyLong_FromSize_t(size_t ival) { - return PyLong_FromSize_t(ival); -} - - -/* MultiPhaseInitModuleState */ -#if CYTHON_PEP489_MULTI_PHASE_INIT && CYTHON_USE_MODULE_STATE -#ifndef CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE -#if (CYTHON_COMPILING_IN_LIMITED_API || PY_VERSION_HEX >= 0x030C0000) - #define CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE 1 -#else - #define CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE 0 -#endif -#endif -#if CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE && !CYTHON_ATOMICS -#error "Module state with PEP489 requires atomics. Currently that's one of\ - C11, C++11, gcc atomic intrinsics or MSVC atomic intrinsics" -#endif -#if !CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE -#define __Pyx_ModuleStateLookup_Lock() -#define __Pyx_ModuleStateLookup_Unlock() -#elif !CYTHON_COMPILING_IN_LIMITED_API && PY_VERSION_HEX >= 0x030d0000 -static PyMutex __Pyx_ModuleStateLookup_mutex = {0}; -#define __Pyx_ModuleStateLookup_Lock() PyMutex_Lock(&__Pyx_ModuleStateLookup_mutex) -#define __Pyx_ModuleStateLookup_Unlock() PyMutex_Unlock(&__Pyx_ModuleStateLookup_mutex) -#elif defined(__cplusplus) && __cplusplus >= 201103L -#include -static std::mutex __Pyx_ModuleStateLookup_mutex; -#define __Pyx_ModuleStateLookup_Lock() __Pyx_ModuleStateLookup_mutex.lock() -#define __Pyx_ModuleStateLookup_Unlock() __Pyx_ModuleStateLookup_mutex.unlock() -#elif defined(__STDC_VERSION__) && (__STDC_VERSION__ > 201112L) && !defined(__STDC_NO_THREADS__) -#include -static mtx_t __Pyx_ModuleStateLookup_mutex; -static once_flag __Pyx_ModuleStateLookup_mutex_once_flag = ONCE_FLAG_INIT; -static void __Pyx_ModuleStateLookup_initialize_mutex(void) { - mtx_init(&__Pyx_ModuleStateLookup_mutex, mtx_plain); -} -#define __Pyx_ModuleStateLookup_Lock()\ - call_once(&__Pyx_ModuleStateLookup_mutex_once_flag, __Pyx_ModuleStateLookup_initialize_mutex);\ - mtx_lock(&__Pyx_ModuleStateLookup_mutex) -#define __Pyx_ModuleStateLookup_Unlock() mtx_unlock(&__Pyx_ModuleStateLookup_mutex) -#elif defined(HAVE_PTHREAD_H) -#include -static pthread_mutex_t __Pyx_ModuleStateLookup_mutex = PTHREAD_MUTEX_INITIALIZER; -#define __Pyx_ModuleStateLookup_Lock() pthread_mutex_lock(&__Pyx_ModuleStateLookup_mutex) -#define __Pyx_ModuleStateLookup_Unlock() pthread_mutex_unlock(&__Pyx_ModuleStateLookup_mutex) -#elif defined(_WIN32) -#include // synchapi.h on its own doesn't work -static SRWLOCK __Pyx_ModuleStateLookup_mutex = SRWLOCK_INIT; -#define __Pyx_ModuleStateLookup_Lock() AcquireSRWLockExclusive(&__Pyx_ModuleStateLookup_mutex) -#define __Pyx_ModuleStateLookup_Unlock() ReleaseSRWLockExclusive(&__Pyx_ModuleStateLookup_mutex) -#else -#error "No suitable lock available for CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE.\ - Requires C standard >= C11, or C++ standard >= C++11,\ - or pthreads, or the Windows 32 API, or Python >= 3.13." -#endif -typedef struct { - int64_t id; - PyObject *module; -} __Pyx_InterpreterIdAndModule; -typedef struct { - char interpreter_id_as_index; - Py_ssize_t count; - Py_ssize_t allocated; - __Pyx_InterpreterIdAndModule table[1]; -} __Pyx_ModuleStateLookupData; -#define __PYX_MODULE_STATE_LOOKUP_SMALL_SIZE 32 -#if CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE -static __pyx_atomic_int_type __Pyx_ModuleStateLookup_read_counter = 0; -#endif -#if CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE -static __pyx_atomic_ptr_type __Pyx_ModuleStateLookup_data = 0; -#else -static __Pyx_ModuleStateLookupData* __Pyx_ModuleStateLookup_data = NULL; -#endif -static __Pyx_InterpreterIdAndModule* __Pyx_State_FindModuleStateLookupTableLowerBound( - __Pyx_InterpreterIdAndModule* table, - Py_ssize_t count, - int64_t interpreterId) { - __Pyx_InterpreterIdAndModule* begin = table; - __Pyx_InterpreterIdAndModule* end = begin + count; - if (begin->id == interpreterId) { - return begin; - } - while ((end - begin) > __PYX_MODULE_STATE_LOOKUP_SMALL_SIZE) { - __Pyx_InterpreterIdAndModule* halfway = begin + (end - begin)/2; - if (halfway->id == interpreterId) { - return halfway; - } - if (halfway->id < interpreterId) { - begin = halfway; - } else { - end = halfway; - } - } - for (; begin < end; ++begin) { - if (begin->id >= interpreterId) return begin; - } - return begin; -} -static PyObject *__Pyx_State_FindModule(CYTHON_UNUSED void* dummy) { - int64_t interpreter_id = PyInterpreterState_GetID(__Pyx_PyInterpreterState_Get()); - if (interpreter_id == -1) return NULL; -#if CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE - __Pyx_ModuleStateLookupData* data = (__Pyx_ModuleStateLookupData*)__pyx_atomic_pointer_load_relaxed(&__Pyx_ModuleStateLookup_data); - { - __pyx_atomic_incr_acq_rel(&__Pyx_ModuleStateLookup_read_counter); - if (likely(data)) { - __Pyx_ModuleStateLookupData* new_data = (__Pyx_ModuleStateLookupData*)__pyx_atomic_pointer_load_acquire(&__Pyx_ModuleStateLookup_data); - if (likely(data == new_data)) { - goto read_finished; - } - } - __pyx_atomic_decr_acq_rel(&__Pyx_ModuleStateLookup_read_counter); - __Pyx_ModuleStateLookup_Lock(); - __pyx_atomic_incr_relaxed(&__Pyx_ModuleStateLookup_read_counter); - data = (__Pyx_ModuleStateLookupData*)__pyx_atomic_pointer_load_relaxed(&__Pyx_ModuleStateLookup_data); - __Pyx_ModuleStateLookup_Unlock(); - } - read_finished:; -#else - __Pyx_ModuleStateLookupData* data = __Pyx_ModuleStateLookup_data; -#endif - __Pyx_InterpreterIdAndModule* found = NULL; - if (unlikely(!data)) goto end; - if (data->interpreter_id_as_index) { - if (interpreter_id < data->count) { - found = data->table+interpreter_id; - } - } else { - found = __Pyx_State_FindModuleStateLookupTableLowerBound( - data->table, data->count, interpreter_id); - } - end: - { - PyObject *result=NULL; - if (found && found->id == interpreter_id) { - result = found->module; - } -#if CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE - __pyx_atomic_decr_acq_rel(&__Pyx_ModuleStateLookup_read_counter); -#endif - return result; - } -} -#if CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE -static void __Pyx_ModuleStateLookup_wait_until_no_readers(void) { - while (__pyx_atomic_load(&__Pyx_ModuleStateLookup_read_counter) != 0); -} -#else -#define __Pyx_ModuleStateLookup_wait_until_no_readers() -#endif -static int __Pyx_State_AddModuleInterpIdAsIndex(__Pyx_ModuleStateLookupData **old_data, PyObject* module, int64_t interpreter_id) { - Py_ssize_t to_allocate = (*old_data)->allocated; - while (to_allocate <= interpreter_id) { - if (to_allocate == 0) to_allocate = 1; - else to_allocate *= 2; - } - __Pyx_ModuleStateLookupData *new_data = *old_data; - if (to_allocate != (*old_data)->allocated) { - new_data = (__Pyx_ModuleStateLookupData *)realloc( - *old_data, - sizeof(__Pyx_ModuleStateLookupData)+(to_allocate-1)*sizeof(__Pyx_InterpreterIdAndModule)); - if (!new_data) { - PyErr_NoMemory(); - return -1; - } - for (Py_ssize_t i = new_data->allocated; i < to_allocate; ++i) { - new_data->table[i].id = i; - new_data->table[i].module = NULL; - } - new_data->allocated = to_allocate; - } - new_data->table[interpreter_id].module = module; - if (new_data->count < interpreter_id+1) { - new_data->count = interpreter_id+1; - } - *old_data = new_data; - return 0; -} -static void __Pyx_State_ConvertFromInterpIdAsIndex(__Pyx_ModuleStateLookupData *data) { - __Pyx_InterpreterIdAndModule *read = data->table; - __Pyx_InterpreterIdAndModule *write = data->table; - __Pyx_InterpreterIdAndModule *end = read + data->count; - for (; readmodule) { - write->id = read->id; - write->module = read->module; - ++write; - } - } - data->count = write - data->table; - for (; writeid = 0; - write->module = NULL; - } - data->interpreter_id_as_index = 0; -} -static int __Pyx_State_AddModule(PyObject* module, CYTHON_UNUSED void* dummy) { - int64_t interpreter_id = PyInterpreterState_GetID(__Pyx_PyInterpreterState_Get()); - if (interpreter_id == -1) return -1; - int result = 0; - __Pyx_ModuleStateLookup_Lock(); -#if CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE - __Pyx_ModuleStateLookupData *old_data = (__Pyx_ModuleStateLookupData *) - __pyx_atomic_pointer_exchange(&__Pyx_ModuleStateLookup_data, 0); -#else - __Pyx_ModuleStateLookupData *old_data = __Pyx_ModuleStateLookup_data; -#endif - __Pyx_ModuleStateLookupData *new_data = old_data; - if (!new_data) { - new_data = (__Pyx_ModuleStateLookupData *)calloc(1, sizeof(__Pyx_ModuleStateLookupData)); - if (!new_data) { - result = -1; - PyErr_NoMemory(); - goto end; - } - new_data->allocated = 1; - new_data->interpreter_id_as_index = 1; - } - __Pyx_ModuleStateLookup_wait_until_no_readers(); - if (new_data->interpreter_id_as_index) { - if (interpreter_id < __PYX_MODULE_STATE_LOOKUP_SMALL_SIZE) { - result = __Pyx_State_AddModuleInterpIdAsIndex(&new_data, module, interpreter_id); - goto end; - } - __Pyx_State_ConvertFromInterpIdAsIndex(new_data); - } - { - Py_ssize_t insert_at = 0; - { - __Pyx_InterpreterIdAndModule* lower_bound = __Pyx_State_FindModuleStateLookupTableLowerBound( - new_data->table, new_data->count, interpreter_id); - assert(lower_bound); - insert_at = lower_bound - new_data->table; - if (unlikely(insert_at < new_data->count && lower_bound->id == interpreter_id)) { - lower_bound->module = module; - goto end; // already in table, nothing more to do - } - } - if (new_data->count+1 >= new_data->allocated) { - Py_ssize_t to_allocate = (new_data->count+1)*2; - new_data = - (__Pyx_ModuleStateLookupData*)realloc( - new_data, - sizeof(__Pyx_ModuleStateLookupData) + - (to_allocate-1)*sizeof(__Pyx_InterpreterIdAndModule)); - if (!new_data) { - result = -1; - new_data = old_data; - PyErr_NoMemory(); - goto end; - } - new_data->allocated = to_allocate; - } - ++new_data->count; - int64_t last_id = interpreter_id; - PyObject *last_module = module; - for (Py_ssize_t i=insert_at; icount; ++i) { - int64_t current_id = new_data->table[i].id; - new_data->table[i].id = last_id; - last_id = current_id; - PyObject *current_module = new_data->table[i].module; - new_data->table[i].module = last_module; - last_module = current_module; - } - } - end: -#if CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE - __pyx_atomic_pointer_exchange(&__Pyx_ModuleStateLookup_data, new_data); -#else - __Pyx_ModuleStateLookup_data = new_data; -#endif - __Pyx_ModuleStateLookup_Unlock(); - return result; -} -static int __Pyx_State_RemoveModule(CYTHON_UNUSED void* dummy) { - int64_t interpreter_id = PyInterpreterState_GetID(__Pyx_PyInterpreterState_Get()); - if (interpreter_id == -1) return -1; - __Pyx_ModuleStateLookup_Lock(); -#if CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE - __Pyx_ModuleStateLookupData *data = (__Pyx_ModuleStateLookupData *) - __pyx_atomic_pointer_exchange(&__Pyx_ModuleStateLookup_data, 0); -#else - __Pyx_ModuleStateLookupData *data = __Pyx_ModuleStateLookup_data; -#endif - if (data->interpreter_id_as_index) { - if (interpreter_id < data->count) { - data->table[interpreter_id].module = NULL; - } - goto done; - } - { - __Pyx_ModuleStateLookup_wait_until_no_readers(); - __Pyx_InterpreterIdAndModule* lower_bound = __Pyx_State_FindModuleStateLookupTableLowerBound( - data->table, data->count, interpreter_id); - if (!lower_bound) goto done; - if (lower_bound->id != interpreter_id) goto done; - __Pyx_InterpreterIdAndModule *end = data->table+data->count; - for (;lower_boundid = (lower_bound+1)->id; - lower_bound->module = (lower_bound+1)->module; - } - } - --data->count; - if (data->count == 0) { - free(data); - data = NULL; - } - done: -#if CYTHON_MODULE_STATE_LOOKUP_THREAD_SAFE - __pyx_atomic_pointer_exchange(&__Pyx_ModuleStateLookup_data, data); -#else - __Pyx_ModuleStateLookup_data = data; -#endif - __Pyx_ModuleStateLookup_Unlock(); - return 0; -} -#endif - -/* #### Code section: utility_code_pragmas_end ### */ -#ifdef _MSC_VER -#pragma warning( pop ) -#endif - - - -/* #### Code section: end ### */ -#endif /* Py_PYTHON_H */ diff --git a/talib/_ta_lib.pxd b/talib/_ta_lib.pxd deleted file mode 100644 index 65b712177..000000000 --- a/talib/_ta_lib.pxd +++ /dev/null @@ -1,529 +0,0 @@ -#cython: language_level=2 - -cdef extern from "ta-lib/ta_defs.h": - - ctypedef int TA_RetCode - TA_RetCode TA_SUCCESS = 0 - TA_RetCode TA_LIB_NOT_INITIALIZE = 1 - TA_RetCode TA_BAD_PARAM = 2 - TA_RetCode TA_ALLOC_ERR = 3 - TA_RetCode TA_GROUP_NOT_FOUND = 4 - TA_RetCode TA_FUNC_NOT_FOUND = 5 - TA_RetCode TA_INVALID_HANDLE = 6 - TA_RetCode TA_INVALID_PARAM_HOLDER = 7 - TA_RetCode TA_INVALID_PARAM_HOLDER_TYPE = 8 - TA_RetCode TA_INVALID_PARAM_FUNCTION = 9 - TA_RetCode TA_INPUT_NOT_ALL_INITIALIZE = 10 - TA_RetCode TA_OUTPUT_NOT_ALL_INITIALIZE = 11 - TA_RetCode TA_OUT_OF_RANGE_START_INDEX = 12 - TA_RetCode TA_OUT_OF_RANGE_END_INDEX = 13 - TA_RetCode TA_INVALID_LIST_TYPE = 14 - TA_RetCode TA_BAD_OBJECT = 15 - TA_RetCode TA_NOT_SUPPORTED = 16 - TA_RetCode TA_INTERNAL_ERROR = 5000 - TA_RetCode TA_UNKNOWN_ERR = 0xffff - - ctypedef int TA_Compatibility - TA_Compatibility TA_COMPATIBILITY_DEFAULT = 0 - TA_Compatibility TA_COMPATIBILITY_METASTOCK = 1 - - ctypedef int TA_MAType - TA_MAType TA_MAType_SMA = 0 - TA_MAType TA_MAType_EMA = 1 - TA_MAType TA_MAType_WMA = 2 - TA_MAType TA_MAType_DEMA = 3 - TA_MAType TA_MAType_TEMA = 4 - TA_MAType TA_MAType_TRIMA = 5 - TA_MAType TA_MAType_KAMA = 6 - TA_MAType TA_MAType_MAMA = 7 - TA_MAType TA_MAType_T3 = 8 - - ctypedef int TA_FuncUnstId - TA_FuncUnstId TA_FUNC_UNST_ADX = 0 - TA_FuncUnstId TA_FUNC_UNST_ADXR = 1 - TA_FuncUnstId TA_FUNC_UNST_ATR = 2 - TA_FuncUnstId TA_FUNC_UNST_CMO = 3 - TA_FuncUnstId TA_FUNC_UNST_DX = 4 - TA_FuncUnstId TA_FUNC_UNST_EMA = 5 - TA_FuncUnstId TA_FUNC_UNST_HT_DCPERIOD = 6 - TA_FuncUnstId TA_FUNC_UNST_HT_DCPHASE = 7 - TA_FuncUnstId TA_FUNC_UNST_HD_PHASOR = 8 - TA_FuncUnstId TA_FUNC_UNST_HT_SINE = 9 - TA_FuncUnstId TA_FUNC_UNST_HT_TRENDLINE = 10 - TA_FuncUnstId TA_FUNC_UNST_HT_TRENDMODE = 11 - TA_FuncUnstId TA_FUNC_UNST_KAMA = 12 - TA_FuncUnstId TA_FUNC_UNST_MAMA = 13 - TA_FuncUnstId TA_FUNC_UNST_MFI = 14 - TA_FuncUnstId TA_FUNC_UNST_MINUS_DI = 15 - TA_FuncUnstId TA_FUNC_UNST_MINUS_DM = 16 - TA_FuncUnstId TA_FUNC_UNST_NATR = 17 - TA_FuncUnstId TA_FUNC_UNST_PLUS_DI = 18 - TA_FuncUnstId TA_FUNC_UNST_PLUS_DM = 19 - TA_FuncUnstId TA_FUNC_UNST_RSI = 20 - TA_FuncUnstId TA_FUNC_UNST_STOCHRSI = 21 - TA_FuncUnstId TA_FUNC_UNST_T3 = 21 - TA_FuncUnstId TA_FUNC_UNST_ALL = 22 - TA_FuncUnstId TA_FUNC_UNST_NONE = -1 - - ctypedef int TA_RangeType - TA_RangeType TA_RangeType_RealBody = 0 - TA_RangeType TA_RangeType_HighLow = 1 - TA_RangeType TA_RangeType_Shadows = 2 - - ctypedef int TA_CandleSettingType - TA_CandleSettingType TA_BodyLong = 0 - TA_CandleSettingType TA_BodyVeryLong = 1 - TA_CandleSettingType TA_BodyShort = 2 - TA_CandleSettingType TA_BodyDoji = 3 - TA_CandleSettingType TA_ShadowLong = 4 - TA_CandleSettingType TA_ShadowVeryLong = 5 - TA_CandleSettingType TA_ShadowShort = 6 - TA_CandleSettingType TA_ShadowVeryShort = 7 - TA_CandleSettingType TA_Near = 8 - TA_CandleSettingType TA_Far = 9 - TA_CandleSettingType TA_Equal = 10 - TA_CandleSettingType TA_AllCandleSettings = 11 - -cdef extern from "ta-lib/ta_common.h": - const char *TA_GetVersionString() - const char *TA_GetVersionMajor() - const char *TA_GetVersionMinor() - const char *TA_GetVersionBuild() - const char *TA_GetVersionDate() - const char *TA_GetVersionTime() - - ctypedef double TA_Real - ctypedef int TA_Integer - - ctypedef struct TA_StringTable: - unsigned int size - const char **string - void *hiddenData - - ctypedef struct TA_RetCodeInfo: - const char* enumStr - const char* infoStr - - void TA_SetRetCodeInfo(TA_RetCode theRetCode, TA_RetCodeInfo *retCodeInfo) - - TA_RetCode TA_Initialize() - TA_RetCode TA_Shutdown() - -cdef extern from "ta-lib/ta_abstract.h": - - TA_RetCode TA_GroupTableAlloc(TA_StringTable **table) - TA_RetCode TA_GroupTableFree(TA_StringTable *table) - - TA_RetCode TA_FuncTableAlloc(const char *group, TA_StringTable **table) - TA_RetCode TA_FuncTableFree(TA_StringTable *table) - - ctypedef unsigned int TA_FuncHandle - TA_RetCode TA_GetFuncHandle(const char *name, const TA_FuncHandle **handle) - - ctypedef int TA_FuncFlags - ctypedef struct TA_FuncInfo: - const char *name - const char *group - const char *hint - const char *camelCaseName - TA_FuncFlags flags - unsigned int nbInput - unsigned int nbOptInput - unsigned int nbOutput - const TA_FuncHandle *handle - - TA_RetCode TA_GetFuncInfo(const TA_FuncHandle *handle, const TA_FuncInfo **funcInfo) - - ctypedef int TA_InputParameterType - TA_InputParameterType TA_Input_Price = 0 - TA_InputParameterType TA_Input_Real = 1 - TA_InputParameterType TA_Input_Integer = 2 - - ctypedef int TA_OptInputParameterType - TA_OptInputParameterType TA_OptInput_RealRange = 0 - TA_OptInputParameterType TA_OptInput_RealList = 1 - TA_OptInputParameterType TA_OptInput_IntegerRange = 2 - TA_OptInputParameterType TA_OptInput_IntegerList = 3 - - ctypedef int TA_OutputParameterType - TA_OutputParameterType TA_Output_Real = 0 - TA_OutputParameterType TA_Output_Integer = 1 - - ctypedef int TA_InputFlags - ctypedef int TA_OptInputFlags - ctypedef int TA_OutputFlags - - ctypedef struct TA_InputParameterInfo: - TA_InputParameterType type - const char *paramName - TA_InputFlags flags - - ctypedef struct TA_OptInputParameterInfo: - TA_OptInputParameterType type - const char *paramName - TA_OptInputFlags flags - const char *displayName - const void *dataSet - TA_Real defaultValue - const char *hint - const char *helpFile - - ctypedef struct TA_OutputParameterInfo: - TA_OutputParameterType type - const char *paramName - TA_OutputFlags flags - - TA_RetCode TA_GetInputParameterInfo(const TA_FuncHandle *handle, unsigned int paramIndex, const TA_InputParameterInfo **info) - TA_RetCode TA_GetOptInputParameterInfo(const TA_FuncHandle *handle, unsigned int paramIndex, const TA_OptInputParameterInfo **info) - TA_RetCode TA_GetOutputParameterInfo(const TA_FuncHandle *handle, unsigned int paramIndex, const TA_OutputParameterInfo **info) - - ctypedef struct TA_ParamHolder: - void *hiddenData - - TA_RetCode TA_ParamHolderAlloc(const TA_FuncHandle *handle, TA_ParamHolder **allocatedParams) # get_lookback() - TA_RetCode TA_ParamHolderFree(TA_ParamHolder *params) - - TA_RetCode TA_SetOptInputParamInteger(TA_ParamHolder *params, unsigned int paramIndex, TA_Integer optInValue) - TA_RetCode TA_SetOptInputParamReal(TA_ParamHolder *params, unsigned int paramIndex, TA_Real optInValue) - - TA_RetCode TA_GetLookback(const TA_ParamHolder *params, TA_Integer *lookback) - - TA_RetCode TA_CallFunc(const TA_ParamHolder *params, TA_Integer startIdx, TA_Integer endIdx, TA_Integer *outBegIdx, TA_Integer *outNbElement) - - char* TA_FunctionDescriptionXML() - -cdef extern from "ta-lib/ta_func.h": - TA_RetCode TA_ACCBANDS(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outRealUpperBand[], double outRealMiddleBand[], double outRealLowerBand[]) - int TA_ACCBANDS_Lookback(int optInTimePeriod) - TA_RetCode TA_ACOS(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_ACOS_Lookback() - TA_RetCode TA_AD(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], const double inVolume[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_AD_Lookback() - TA_RetCode TA_ADD(int startIdx, int endIdx, const double inReal0[], const double inReal1[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_ADD_Lookback() - TA_RetCode TA_ADOSC(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], const double inVolume[], int optInFastPeriod, int optInSlowPeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_ADOSC_Lookback(int optInFastPeriod, int optInSlowPeriod) - TA_RetCode TA_ADX(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_ADX_Lookback(int optInTimePeriod) - TA_RetCode TA_ADXR(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_ADXR_Lookback(int optInTimePeriod) - TA_RetCode TA_APO(int startIdx, int endIdx, const double inReal[], int optInFastPeriod, int optInSlowPeriod, TA_MAType optInMAType, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_APO_Lookback(int optInFastPeriod, int optInSlowPeriod, TA_MAType optInMAType) - TA_RetCode TA_AROON(int startIdx, int endIdx, const double inHigh[], const double inLow[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outAroonDown[], double outAroonUp[]) - int TA_AROON_Lookback(int optInTimePeriod) - TA_RetCode TA_AROONOSC(int startIdx, int endIdx, const double inHigh[], const double inLow[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_AROONOSC_Lookback(int optInTimePeriod) - TA_RetCode TA_ASIN(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_ASIN_Lookback() - TA_RetCode TA_ATAN(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_ATAN_Lookback() - TA_RetCode TA_ATR(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_ATR_Lookback(int optInTimePeriod) - TA_RetCode TA_AVGPRICE(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_AVGPRICE_Lookback() - TA_RetCode TA_AVGDEV(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_AVGDEV_Lookback(int optInTimePeriod) - TA_RetCode TA_BBANDS(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, double optInNbDevUp, double optInNbDevDn, TA_MAType optInMAType, int *outBegIdx, int *outNBElement, double outRealUpperBand[], double outRealMiddleBand[], double outRealLowerBand[]) - int TA_BBANDS_Lookback(int optInTimePeriod, double optInNbDevUp, double optInNbDevDn, TA_MAType optInMAType) - TA_RetCode TA_BETA(int startIdx, int endIdx, const double inReal0[], const double inReal1[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_BETA_Lookback(int optInTimePeriod) - TA_RetCode TA_BOP(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_BOP_Lookback() - TA_RetCode TA_CCI(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_CCI_Lookback(int optInTimePeriod) - TA_RetCode TA_CDL2CROWS(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDL2CROWS_Lookback() - TA_RetCode TA_CDL3BLACKCROWS(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDL3BLACKCROWS_Lookback() - TA_RetCode TA_CDL3INSIDE(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDL3INSIDE_Lookback() - TA_RetCode TA_CDL3LINESTRIKE(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDL3LINESTRIKE_Lookback() - TA_RetCode TA_CDL3OUTSIDE(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDL3OUTSIDE_Lookback() - TA_RetCode TA_CDL3STARSINSOUTH(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDL3STARSINSOUTH_Lookback() - TA_RetCode TA_CDL3WHITESOLDIERS(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDL3WHITESOLDIERS_Lookback() - TA_RetCode TA_CDLABANDONEDBABY(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], double optInPenetration, int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLABANDONEDBABY_Lookback(double optInPenetration) - TA_RetCode TA_CDLADVANCEBLOCK(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLADVANCEBLOCK_Lookback() - TA_RetCode TA_CDLBELTHOLD(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLBELTHOLD_Lookback() - TA_RetCode TA_CDLBREAKAWAY(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLBREAKAWAY_Lookback() - TA_RetCode TA_CDLCLOSINGMARUBOZU(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLCLOSINGMARUBOZU_Lookback() - TA_RetCode TA_CDLCONCEALBABYSWALL(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLCONCEALBABYSWALL_Lookback() - TA_RetCode TA_CDLCOUNTERATTACK(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLCOUNTERATTACK_Lookback() - TA_RetCode TA_CDLDARKCLOUDCOVER(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], double optInPenetration, int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLDARKCLOUDCOVER_Lookback(double optInPenetration) - TA_RetCode TA_CDLDOJI(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLDOJI_Lookback() - TA_RetCode TA_CDLDOJISTAR(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLDOJISTAR_Lookback() - TA_RetCode TA_CDLDRAGONFLYDOJI(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLDRAGONFLYDOJI_Lookback() - TA_RetCode TA_CDLENGULFING(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLENGULFING_Lookback() - TA_RetCode TA_CDLEVENINGDOJISTAR(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], double optInPenetration, int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLEVENINGDOJISTAR_Lookback(double optInPenetration) - TA_RetCode TA_CDLEVENINGSTAR(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], double optInPenetration, int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLEVENINGSTAR_Lookback(double optInPenetration) - TA_RetCode TA_CDLGAPSIDESIDEWHITE(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLGAPSIDESIDEWHITE_Lookback() - TA_RetCode TA_CDLGRAVESTONEDOJI(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLGRAVESTONEDOJI_Lookback() - TA_RetCode TA_CDLHAMMER(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLHAMMER_Lookback() - TA_RetCode TA_CDLHANGINGMAN(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLHANGINGMAN_Lookback() - TA_RetCode TA_CDLHARAMI(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLHARAMI_Lookback() - TA_RetCode TA_CDLHARAMICROSS(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLHARAMICROSS_Lookback() - TA_RetCode TA_CDLHIGHWAVE(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLHIGHWAVE_Lookback() - TA_RetCode TA_CDLHIKKAKE(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLHIKKAKE_Lookback() - TA_RetCode TA_CDLHIKKAKEMOD(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLHIKKAKEMOD_Lookback() - TA_RetCode TA_CDLHOMINGPIGEON(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLHOMINGPIGEON_Lookback() - TA_RetCode TA_CDLIDENTICAL3CROWS(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLIDENTICAL3CROWS_Lookback() - TA_RetCode TA_CDLINNECK(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLINNECK_Lookback() - TA_RetCode TA_CDLINVERTEDHAMMER(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLINVERTEDHAMMER_Lookback() - TA_RetCode TA_CDLKICKING(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLKICKING_Lookback() - TA_RetCode TA_CDLKICKINGBYLENGTH(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLKICKINGBYLENGTH_Lookback() - TA_RetCode TA_CDLLADDERBOTTOM(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLLADDERBOTTOM_Lookback() - TA_RetCode TA_CDLLONGLEGGEDDOJI(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLLONGLEGGEDDOJI_Lookback() - TA_RetCode TA_CDLLONGLINE(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLLONGLINE_Lookback() - TA_RetCode TA_CDLMARUBOZU(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLMARUBOZU_Lookback() - TA_RetCode TA_CDLMATCHINGLOW(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLMATCHINGLOW_Lookback() - TA_RetCode TA_CDLMATHOLD(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], double optInPenetration, int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLMATHOLD_Lookback(double optInPenetration) - TA_RetCode TA_CDLMORNINGDOJISTAR(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], double optInPenetration, int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLMORNINGDOJISTAR_Lookback(double optInPenetration) - TA_RetCode TA_CDLMORNINGSTAR(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], double optInPenetration, int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLMORNINGSTAR_Lookback(double optInPenetration) - TA_RetCode TA_CDLONNECK(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLONNECK_Lookback() - TA_RetCode TA_CDLPIERCING(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLPIERCING_Lookback() - TA_RetCode TA_CDLRICKSHAWMAN(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLRICKSHAWMAN_Lookback() - TA_RetCode TA_CDLRISEFALL3METHODS(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLRISEFALL3METHODS_Lookback() - TA_RetCode TA_CDLSEPARATINGLINES(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLSEPARATINGLINES_Lookback() - TA_RetCode TA_CDLSHOOTINGSTAR(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLSHOOTINGSTAR_Lookback() - TA_RetCode TA_CDLSHORTLINE(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLSHORTLINE_Lookback() - TA_RetCode TA_CDLSPINNINGTOP(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLSPINNINGTOP_Lookback() - TA_RetCode TA_CDLSTALLEDPATTERN(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLSTALLEDPATTERN_Lookback() - TA_RetCode TA_CDLSTICKSANDWICH(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLSTICKSANDWICH_Lookback() - TA_RetCode TA_CDLTAKURI(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLTAKURI_Lookback() - TA_RetCode TA_CDLTASUKIGAP(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLTASUKIGAP_Lookback() - TA_RetCode TA_CDLTHRUSTING(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLTHRUSTING_Lookback() - TA_RetCode TA_CDLTRISTAR(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLTRISTAR_Lookback() - TA_RetCode TA_CDLUNIQUE3RIVER(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLUNIQUE3RIVER_Lookback() - TA_RetCode TA_CDLUPSIDEGAP2CROWS(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLUPSIDEGAP2CROWS_Lookback() - TA_RetCode TA_CDLXSIDEGAP3METHODS(int startIdx, int endIdx, const double inOpen[], const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_CDLXSIDEGAP3METHODS_Lookback() - TA_RetCode TA_CEIL(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_CEIL_Lookback() - TA_RetCode TA_CMO(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_CMO_Lookback(int optInTimePeriod) - TA_RetCode TA_CORREL(int startIdx, int endIdx, const double inReal0[], const double inReal1[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_CORREL_Lookback(int optInTimePeriod) - TA_RetCode TA_COS(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_COS_Lookback() - TA_RetCode TA_COSH(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_COSH_Lookback() - TA_RetCode TA_DEMA(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_DEMA_Lookback(int optInTimePeriod) - TA_RetCode TA_DIV(int startIdx, int endIdx, const double inReal0[], const double inReal1[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_DIV_Lookback() - TA_RetCode TA_DX(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_DX_Lookback(int optInTimePeriod) - TA_RetCode TA_EMA(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_EMA_Lookback(int optInTimePeriod) - TA_RetCode TA_EXP(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_EXP_Lookback() - TA_RetCode TA_FLOOR(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_FLOOR_Lookback() - TA_RetCode TA_HT_DCPERIOD(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_HT_DCPERIOD_Lookback() - TA_RetCode TA_HT_DCPHASE(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_HT_DCPHASE_Lookback() - TA_RetCode TA_HT_PHASOR(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outInPhase[], double outQuadrature[]) - int TA_HT_PHASOR_Lookback() - TA_RetCode TA_HT_SINE(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outSine[], double outLeadSine[]) - int TA_HT_SINE_Lookback() - TA_RetCode TA_HT_TRENDLINE(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_HT_TRENDLINE_Lookback() - TA_RetCode TA_HT_TRENDMODE(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_HT_TRENDMODE_Lookback() - TA_RetCode TA_IMI(int startIdx, int endIdx, const double inOpen[], const double inClose[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_IMI_Lookback(int optInTimePeriod) - TA_RetCode TA_KAMA(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_KAMA_Lookback(int optInTimePeriod) - TA_RetCode TA_LINEARREG(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_LINEARREG_Lookback(int optInTimePeriod) - TA_RetCode TA_LINEARREG_ANGLE(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_LINEARREG_ANGLE_Lookback(int optInTimePeriod) - TA_RetCode TA_LINEARREG_INTERCEPT(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_LINEARREG_INTERCEPT_Lookback(int optInTimePeriod) - TA_RetCode TA_LINEARREG_SLOPE(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_LINEARREG_SLOPE_Lookback(int optInTimePeriod) - TA_RetCode TA_LN(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_LN_Lookback() - TA_RetCode TA_LOG10(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_LOG10_Lookback() - TA_RetCode TA_MA(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, TA_MAType optInMAType, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_MA_Lookback(int optInTimePeriod, TA_MAType optInMAType) - TA_RetCode TA_MACD(int startIdx, int endIdx, const double inReal[], int optInFastPeriod, int optInSlowPeriod, int optInSignalPeriod, int *outBegIdx, int *outNBElement, double outMACD[], double outMACDSignal[], double outMACDHist[]) - int TA_MACD_Lookback(int optInFastPeriod, int optInSlowPeriod, int optInSignalPeriod) - TA_RetCode TA_MACDEXT(int startIdx, int endIdx, const double inReal[], int optInFastPeriod, TA_MAType optInFastMAType, int optInSlowPeriod, TA_MAType optInSlowMAType, int optInSignalPeriod, TA_MAType optInSignalMAType, int *outBegIdx, int *outNBElement, double outMACD[], double outMACDSignal[], double outMACDHist[]) - int TA_MACDEXT_Lookback(int optInFastPeriod, TA_MAType optInFastMAType, int optInSlowPeriod, TA_MAType optInSlowMAType, int optInSignalPeriod, TA_MAType optInSignalMAType) - TA_RetCode TA_MACDFIX(int startIdx, int endIdx, const double inReal[], int optInSignalPeriod, int *outBegIdx, int *outNBElement, double outMACD[], double outMACDSignal[], double outMACDHist[]) - int TA_MACDFIX_Lookback(int optInSignalPeriod) - TA_RetCode TA_MAMA(int startIdx, int endIdx, const double inReal[], double optInFastLimit, double optInSlowLimit, int *outBegIdx, int *outNBElement, double outMAMA[], double outFAMA[]) - int TA_MAMA_Lookback(double optInFastLimit, double optInSlowLimit) - TA_RetCode TA_MAVP(int startIdx, int endIdx, const double inReal[], const double inPeriods[], int optInMinPeriod, int optInMaxPeriod, TA_MAType optInMAType, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_MAVP_Lookback(int optInMinPeriod, int optInMaxPeriod, TA_MAType optInMAType) - TA_RetCode TA_MAX(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_MAX_Lookback(int optInTimePeriod) - TA_RetCode TA_MAXINDEX(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_MAXINDEX_Lookback(int optInTimePeriod) - TA_RetCode TA_MEDPRICE(int startIdx, int endIdx, const double inHigh[], const double inLow[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_MEDPRICE_Lookback() - TA_RetCode TA_MFI(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], const double inVolume[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_MFI_Lookback(int optInTimePeriod) - TA_RetCode TA_MIDPOINT(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_MIDPOINT_Lookback(int optInTimePeriod) - TA_RetCode TA_MIDPRICE(int startIdx, int endIdx, const double inHigh[], const double inLow[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_MIDPRICE_Lookback(int optInTimePeriod) - TA_RetCode TA_MIN(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_MIN_Lookback(int optInTimePeriod) - TA_RetCode TA_MININDEX(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, int outInteger[]) - int TA_MININDEX_Lookback(int optInTimePeriod) - TA_RetCode TA_MINMAX(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outMin[], double outMax[]) - int TA_MINMAX_Lookback(int optInTimePeriod) - TA_RetCode TA_MINMAXINDEX(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, int outMinIdx[], int outMaxIdx[]) - int TA_MINMAXINDEX_Lookback(int optInTimePeriod) - TA_RetCode TA_MINUS_DI(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_MINUS_DI_Lookback(int optInTimePeriod) - TA_RetCode TA_MINUS_DM(int startIdx, int endIdx, const double inHigh[], const double inLow[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_MINUS_DM_Lookback(int optInTimePeriod) - TA_RetCode TA_MOM(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_MOM_Lookback(int optInTimePeriod) - TA_RetCode TA_MULT(int startIdx, int endIdx, const double inReal0[], const double inReal1[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_MULT_Lookback() - TA_RetCode TA_NATR(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_NATR_Lookback(int optInTimePeriod) - TA_RetCode TA_OBV(int startIdx, int endIdx, const double inReal[], const double inVolume[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_OBV_Lookback() - TA_RetCode TA_PLUS_DI(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_PLUS_DI_Lookback(int optInTimePeriod) - TA_RetCode TA_PLUS_DM(int startIdx, int endIdx, const double inHigh[], const double inLow[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_PLUS_DM_Lookback(int optInTimePeriod) - TA_RetCode TA_PPO(int startIdx, int endIdx, const double inReal[], int optInFastPeriod, int optInSlowPeriod, TA_MAType optInMAType, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_PPO_Lookback(int optInFastPeriod, int optInSlowPeriod, TA_MAType optInMAType) - TA_RetCode TA_ROC(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_ROC_Lookback(int optInTimePeriod) - TA_RetCode TA_ROCP(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_ROCP_Lookback(int optInTimePeriod) - TA_RetCode TA_ROCR(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_ROCR_Lookback(int optInTimePeriod) - TA_RetCode TA_ROCR100(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_ROCR100_Lookback(int optInTimePeriod) - TA_RetCode TA_RSI(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) nogil - int TA_RSI_Lookback(int optInTimePeriod) nogil - TA_RetCode TA_SAR(int startIdx, int endIdx, const double inHigh[], const double inLow[], double optInAcceleration, double optInMaximum, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_SAR_Lookback(double optInAcceleration, double optInMaximum) - TA_RetCode TA_SAREXT(int startIdx, int endIdx, const double inHigh[], const double inLow[], double optInStartValue, double optInOffsetOnReverse, double optInAccelerationInitLong, double optInAccelerationLong, double optInAccelerationMaxLong, double optInAccelerationInitShort, double optInAccelerationShort, double optInAccelerationMaxShort, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_SAREXT_Lookback(double optInStartValue, double optInOffsetOnReverse, double optInAccelerationInitLong, double optInAccelerationLong, double optInAccelerationMaxLong, double optInAccelerationInitShort, double optInAccelerationShort, double optInAccelerationMaxShort) - TA_RetCode TA_SIN(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_SIN_Lookback() - TA_RetCode TA_SINH(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_SINH_Lookback() - TA_RetCode TA_SMA(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_SMA_Lookback(int optInTimePeriod) - TA_RetCode TA_SQRT(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_SQRT_Lookback() - TA_RetCode TA_STDDEV(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, double optInNbDev, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_STDDEV_Lookback(int optInTimePeriod, double optInNbDev) - TA_RetCode TA_STOCH(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int optInFastK_Period, int optInSlowK_Period, TA_MAType optInSlowK_MAType, int optInSlowD_Period, TA_MAType optInSlowD_MAType, int *outBegIdx, int *outNBElement, double outSlowK[], double outSlowD[]) - int TA_STOCH_Lookback(int optInFastK_Period, int optInSlowK_Period, TA_MAType optInSlowK_MAType, int optInSlowD_Period, TA_MAType optInSlowD_MAType) - TA_RetCode TA_STOCHF(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int optInFastK_Period, int optInFastD_Period, TA_MAType optInFastD_MAType, int *outBegIdx, int *outNBElement, double outFastK[], double outFastD[]) - int TA_STOCHF_Lookback(int optInFastK_Period, int optInFastD_Period, TA_MAType optInFastD_MAType) - TA_RetCode TA_STOCHRSI(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int optInFastK_Period, int optInFastD_Period, TA_MAType optInFastD_MAType, int *outBegIdx, int *outNBElement, double outFastK[], double outFastD[]) - int TA_STOCHRSI_Lookback(int optInTimePeriod, int optInFastK_Period, int optInFastD_Period, TA_MAType optInFastD_MAType) - TA_RetCode TA_SUB(int startIdx, int endIdx, const double inReal0[], const double inReal1[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_SUB_Lookback() - TA_RetCode TA_SUM(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_SUM_Lookback(int optInTimePeriod) - TA_RetCode TA_T3(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, double optInVFactor, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_T3_Lookback(int optInTimePeriod, double optInVFactor) - TA_RetCode TA_TAN(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_TAN_Lookback() - TA_RetCode TA_TANH(int startIdx, int endIdx, const double inReal[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_TANH_Lookback() - TA_RetCode TA_TEMA(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_TEMA_Lookback(int optInTimePeriod) - TA_RetCode TA_TRANGE(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_TRANGE_Lookback() - TA_RetCode TA_TRIMA(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_TRIMA_Lookback(int optInTimePeriod) - TA_RetCode TA_TRIX(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_TRIX_Lookback(int optInTimePeriod) - TA_RetCode TA_TSF(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_TSF_Lookback(int optInTimePeriod) - TA_RetCode TA_TYPPRICE(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_TYPPRICE_Lookback() - TA_RetCode TA_ULTOSC(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int optInTimePeriod1, int optInTimePeriod2, int optInTimePeriod3, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_ULTOSC_Lookback(int optInTimePeriod1, int optInTimePeriod2, int optInTimePeriod3) - TA_RetCode TA_VAR(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, double optInNbDev, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_VAR_Lookback(int optInTimePeriod, double optInNbDev) - TA_RetCode TA_WCLPRICE(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int *outBegIdx, int *outNBElement, double outReal[]) - int TA_WCLPRICE_Lookback() - TA_RetCode TA_WILLR(int startIdx, int endIdx, const double inHigh[], const double inLow[], const double inClose[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_WILLR_Lookback(int optInTimePeriod) - TA_RetCode TA_WMA(int startIdx, int endIdx, const double inReal[], int optInTimePeriod, int *outBegIdx, int *outNBElement, double outReal[]) - int TA_WMA_Lookback(int optInTimePeriod) - - # TALIB functions for TA_SetUnstablePeriod - TA_RetCode TA_SetUnstablePeriod(TA_FuncUnstId id, unsigned int unstablePeriod) - unsigned int TA_GetUnstablePeriod(TA_FuncUnstId id) - - # TALIB functions for TA_SetCompatibility - TA_RetCode TA_SetCompatibility(TA_Compatibility value) - TA_Compatibility TA_GetCompatibility() - - # TALIB functions for TA_SetCandleSettings - TA_RetCode TA_SetCandleSettings(TA_CandleSettingType settingType, TA_RangeType rangeType, int avgPeriod, double factor) - TA_RetCode TA_RestoreCandleDefaultSettings(TA_CandleSettingType) diff --git a/talib/_ta_lib.pyi b/talib/_ta_lib.pyi deleted file mode 100644 index 4356269ff..000000000 --- a/talib/_ta_lib.pyi +++ /dev/null @@ -1,1983 +0,0 @@ -import numpy as np -from enum import Enum -from typing import Tuple -from numpy.typing import NDArray - -class MA_Type(Enum): - SMA = 0 - EMA = 1 - WMA = 2 - DEMA = 3 - TEMA = 4 - TRIMA = 5 - KAMA = 6 - MAMA = 7 - T3 = 8 - -#Overlap Studies Functions - -def BBANDS( - real: NDArray[np.float64], - timeperiod: int= 5, - nbdevup: float= 2, - nbdevdn: float= 2, - matype: MA_Type = MA_Type.SMA - )-> Tuple[NDArray[np.float64], NDArray[np.float64], NDArray[np.float64]]: ... - -def DEMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def EMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def HT_TRENDLINE(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def KAMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def MA( - real: NDArray[np.float64], - timeperiod: int= 30, - matype: MA_Type = MA_Type.SMA - )-> NDArray[np.float64]: ... - -def MAMA( - real: NDArray[np.float64], - fastlimit: float= 0, - slowlimit: float= 0 - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def MAVP( - real: NDArray[np.float64], - periods: float, - minperiod: int= 2, - maxperiod: int= 30, - matype: MA_Type = MA_Type.SMA - )-> NDArray[np.float64]: ... - -def MIDPOINT( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def MIDPRICE( - high: NDArray[np.float64], - low: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def SAR( - high: NDArray[np.float64], - low: NDArray[np.float64], - acceleration: float= 0, - maximum: float= 0 - )-> NDArray[np.float64]: ... - -def SAREXT( - high: NDArray[np.float64], - low: NDArray[np.float64], - startvalue: float= 0, - offsetonreverse: float= 0, - accelerationinitlong: float= 0, - accelerationlong: float= 0, - accelerationmaxlong: float= 0, - accelerationinitshort: float= 0, - accelerationshort: float= 0, - accelerationmaxshort: float= 0 - )-> NDArray[np.float64]: ... - -def SMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def T3( - real: NDArray[np.float64], - timeperiod: int= 5, - vfactor: float= 0 - )-> NDArray[np.float64]: ... - -def TEMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def TRIMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def WMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -#Momentum Indicator Functions - -def ADX( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def ADXR( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def APO( - real: NDArray[np.float64], - fastperiod: int= 12, - slowperiod: int= 26, - matype: MA_Type = MA_Type.SMA - )-> NDArray[np.float64]: ... - -def AROON( - high: NDArray[np.float64], - low: NDArray[np.float64], - timeperiod: int= 14 - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def AROONOSC( - high: NDArray[np.float64], - low: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def BOP( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def CCI( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def CMO( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def DX( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def MACD( - real: NDArray[np.float64], - fastperiod: int= 12, - slowperiod: int= 26, - signalperiod: int= 9 - )-> Tuple[NDArray[np.float64], NDArray[np.float64], NDArray[np.float64]]: ... - -def MACDEXT( - real: NDArray[np.float64], - fastperiod: int= 12, - fastmatype: MA_Type = MA_Type.SMA, - slowperiod: int= 26, - slowmatype: MA_Type = MA_Type.SMA, - signalperiod: int= 9, - signalmatype: MA_Type = MA_Type.SMA - )-> Tuple[NDArray[np.float64], NDArray[np.float64], NDArray[np.float64]]: ... - -def MACDFIX( - real: NDArray[np.float64], - signalperiod: int= 9 - )-> Tuple[NDArray[np.float64], NDArray[np.float64], NDArray[np.float64]]: ... - -def MFI( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - volume: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def MINUS_DI( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def MINUS_DM( - high: NDArray[np.float64], - low: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def MOM( - real: NDArray[np.float64], - timeperiod: int= 10 - )-> NDArray[np.float64]: ... - -def PLUS_DI( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def PLUS_DM( - high: NDArray[np.float64], - low: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def PPO( - real: NDArray[np.float64], - fastperiod: int= 12, - slowperiod: int= 26, - matype: MA_Type = MA_Type.SMA - )-> NDArray[np.float64]: ... - -def ROC( - real: NDArray[np.float64], - timeperiod: int= 10 - )-> NDArray[np.float64]: ... - -def ROCP( - real: NDArray[np.float64], - timeperiod: int= 10 - )-> NDArray[np.float64]: ... - -def ROCR( - real: NDArray[np.float64], - timeperiod: int= 10 - )-> NDArray[np.float64]: ... - -def ROCR100( - real: NDArray[np.float64], - timeperiod: int= 10 - )-> NDArray[np.float64]: ... - -def RSI( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def STOCH( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - fastk_period: int= 5, - slowk_period: int= 3, - slowk_matype: MA_Type = MA_Type.SMA, - slowd_period: int= 3, - slowd_matype: MA_Type = MA_Type.SMA - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def STOCHF( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - fastk_period: int= 5, - fastd_period: int= 3, - fastd_matype: MA_Type = MA_Type.SMA - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def STOCHRSI( - real: NDArray[np.float64], - timeperiod: int= 14, - fastk_period: int= 5, - fastd_period: int= 3, - fastd_matype: MA_Type = MA_Type.SMA - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def TRIX( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def ULTOSC( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod1: int= 7, - timeperiod2: int= 14, - timeperiod3: int= 28 - )-> NDArray[np.float64]: ... - -def WILLR( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -#Volume Indicator Functions - -def AD( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - volume: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def ADOSC( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - volume: NDArray[np.float64], - fastperiod: int= 3, - slowperiod: int= 10 - )-> NDArray[np.float64]: ... - -def OBV( - close: NDArray[np.float64], - volume: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -#Volatility Indicator Functions - -def ATR( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def NATR( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def TRANGE( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -# Price Transform Functions - -def AVGPRICE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def MEDPRICE( - high: NDArray[np.float64], - low: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def TYPPRICE( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def WCLPRICE( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -# Cycle Indicator Functions - -def HT_DCPERIOD(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def HT_DCPHASE(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def HT_PHASOR(real: NDArray[np.float64])-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def HT_SINE(real: NDArray[np.float64])-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def HT_TRENDMODE(real: NDArray[np.float64])-> Tuple[NDArray[np.float64], NDArray[np.int32]]: ... - -#Pattern Recognition Functions - -def CDL2CROWS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDL3BLACKCROWS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDL3INSIDE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDL3LINESTRIKE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDL3OUTSIDE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDL3STARSINSOUTH( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDL3WHITESOLDIERS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLABANDONEDBABY( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def CDLADVANCEBLOCK( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLBELTHOLD( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLBREAKAWAY( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLCLOSINGMARUBOZU( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLCONCEALBABYSWALL( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLCOUNTERATTACK( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLDARKCLOUDCOVER( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def CDLDOJI( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLDOJISTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLDRAGONFLYDOJI( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLENGULFING( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLEVENINGDOJISTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def CDLEVENINGSTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def CDLGAPSIDESIDEWHITE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLGRAVESTONEDOJI( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLHAMMER( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLHANGINGMAN( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLHARAMI( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLHARAMICROSS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLHIGHWAVE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLHIKKAKE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLHIKKAKEMOD( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLHOMINGPIGEON( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLIDENTICAL3CROWS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLINNECK( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLINVERTEDHAMMER( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLKICKING( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLKICKINGBYLENGTH( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLLADDERBOTTOM( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLLONGLEGGEDDOJI( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLLONGLINE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLMARUBOZU( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLMATCHINGLOW( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLMATHOLD( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def CDLMORNINGDOJISTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def CDLMORNINGSTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def CDLONNECK( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLPIERCING( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLRICKSHAWMAN( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLRISEFALL3METHODS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLSEPARATINGLINES( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLSHOOTINGSTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLSHORTLINE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLSPINNINGTOP( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLSTALLEDPATTERN( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLSTICKSANDWICH( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLTAKURI( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLTASUKIGAP( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLTHRUSTING( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLTRISTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLUNIQUE3RIVER( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLUPSIDEGAP2CROWS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def CDLXSIDEGAP3METHODS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -# Statistic Functions - -def BETA( - real0: NDArray[np.float64], - real1: NDArray[np.float64], - timeperiod: int= 5 - )-> NDArray[np.float64]: ... - -def CORREL( - real0: NDArray[np.float64], - real1: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def LINEARREG( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def LINEARREG_ANGLE( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def LINEARREG_INTERCEPT( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def LINEARREG_SLOPE( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def STDDEV( - real: NDArray[np.float64], - timeperiod: int= 5, - nbdev: float= 1 - )-> NDArray[np.float64]: ... - -def TSF( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def VAR( - real: NDArray[np.float64], - timeperiod: int= 5, - nbdev: float= 1 - )-> NDArray[np.float64]: ... - -# Math Transform Functions - -def ACOS(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def ASIN(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def ATAN(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def CEIL(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def COS(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def COSH(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def EXP(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def FLOOR(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def LN(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def LOG10(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def SIN(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def SINH(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def SQRT(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def TAN(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def TANH(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -#Math Operator Functions - -def ADD( - real0: NDArray[np.float64], - real1: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def DIV( - real0: NDArray[np.float64], - real1: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def MAX( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def MAXINDEX( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.int32]: ... - -def MIN( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def MININDEX( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.int32]: ... - -def MINMAX( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def MINMAXINDEX( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def MULT( - real0: NDArray[np.float64], - real1: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def SUB( - real0: NDArray[np.float64], - real1: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def SUM( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def ACCBANDS( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 20 - )-> NDArray[np.float64]: ... - -def AVGDEV( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def IMI( - open: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -#Overlap Studies Functions - -def stream_BBANDS( - real: NDArray[np.float64], - timeperiod: int= 5, - nbdevup: float= 2, - nbdevdn: float= 2, - matype: MA_Type = MA_Type.SMA - )-> Tuple[NDArray[np.float64], NDArray[np.float64], NDArray[np.float64]]: ... - -def stream_DEMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def stream_EMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def stream_HT_TRENDLINE(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_KAMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def stream_MA( - real: NDArray[np.float64], - timeperiod: int= 30, - matype: MA_Type = MA_Type.SMA - )-> NDArray[np.float64]: ... - -def stream_MAMA( - real: NDArray[np.float64], - fastlimit: float= 0, - slowlimit: float= 0 - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def stream_MAVP( - real: NDArray[np.float64], - periods: float, - minperiod: int= 2, - maxperiod: int= 30, - matype: MA_Type = MA_Type.SMA - )-> NDArray[np.float64]: ... - -def stream_MIDPOINT( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_MIDPRICE( - high: NDArray[np.float64], - low: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_SAR( - high: NDArray[np.float64], - low: NDArray[np.float64], - acceleration: float= 0, - maximum: float= 0 - )-> NDArray[np.float64]: ... - -def stream_SAREXT( - high: NDArray[np.float64], - low: NDArray[np.float64], - startvalue: float= 0, - offsetonreverse: float= 0, - accelerationinitlong: float= 0, - accelerationlong: float= 0, - accelerationmaxlong: float= 0, - accelerationinitshort: float= 0, - accelerationshort: float= 0, - accelerationmaxshort: float= 0 - )-> NDArray[np.float64]: ... - -def stream_SMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def stream_T3( - real: NDArray[np.float64], - timeperiod: int= 5, - vfactor: float= 0 - )-> NDArray[np.float64]: ... - -def stream_TEMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def stream_TRIMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def stream_WMA( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -#Momentum Indicator Functions - -def stream_ADX( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_ADXR( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_APO( - real: NDArray[np.float64], - fastperiod: int= 12, - slowperiod: int= 26, - matype: MA_Type = MA_Type.SMA - )-> NDArray[np.float64]: ... - -def stream_AROON( - high: NDArray[np.float64], - low: NDArray[np.float64], - timeperiod: int= 14 - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def stream_AROONOSC( - high: NDArray[np.float64], - low: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_BOP( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def stream_CCI( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_CMO( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_DX( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_MACD( - real: NDArray[np.float64], - fastperiod: int= 12, - slowperiod: int= 26, - signalperiod: int= 9 - )-> Tuple[NDArray[np.float64], NDArray[np.float64], NDArray[np.float64]]: ... - -def stream_MACDEXT( - real: NDArray[np.float64], - fastperiod: int= 12, - fastmatype: MA_Type = MA_Type.SMA, - slowperiod: int= 26, - slowmatype: MA_Type = MA_Type.SMA, - signalperiod: int= 9, - signalmatype: MA_Type = MA_Type.SMA - )-> Tuple[NDArray[np.float64], NDArray[np.float64], NDArray[np.float64]]: ... - -def stream_MACDFIX( - real: NDArray[np.float64], - signalperiod: int= 9 - )-> Tuple[NDArray[np.float64], NDArray[np.float64], NDArray[np.float64]]: ... - -def stream_MFI( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - volume: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_MINUS_DI( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_MINUS_DM( - high: NDArray[np.float64], - low: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_MOM( - real: NDArray[np.float64], - timeperiod: int= 10 - )-> NDArray[np.float64]: ... - -def stream_PLUS_DI( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_PLUS_DM( - high: NDArray[np.float64], - low: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_PPO( - real: NDArray[np.float64], - fastperiod: int= 12, - slowperiod: int= 26, - matype: MA_Type = MA_Type.SMA - )-> NDArray[np.float64]: ... - -def stream_ROC( - real: NDArray[np.float64], - timeperiod: int= 10 - )-> NDArray[np.float64]: ... - -def stream_ROCP( - real: NDArray[np.float64], - timeperiod: int= 10 - )-> NDArray[np.float64]: ... - -def stream_ROCR( - real: NDArray[np.float64], - timeperiod: int= 10 - )-> NDArray[np.float64]: ... - -def stream_ROCR100( - real: NDArray[np.float64], - timeperiod: int= 10 - )-> NDArray[np.float64]: ... - -def stream_RSI( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_STOCH( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - fastk_period: int= 5, - slowk_period: int= 3, - slowk_matype: MA_Type = MA_Type.SMA, - slowd_period: int= 3, - slowd_matype: MA_Type = MA_Type.SMA - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def stream_STOCHF( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - fastk_period: int= 5, - fastd_period: int= 3, - fastd_matype: MA_Type = MA_Type.SMA - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def stream_STOCHRSI( - real: NDArray[np.float64], - timeperiod: int= 14, - fastk_period: int= 5, - fastd_period: int= 3, - fastd_matype: MA_Type = MA_Type.SMA - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def stream_TRIX( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def stream_ULTOSC( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod1: int= 7, - timeperiod2: int= 14, - timeperiod3: int= 28 - )-> NDArray[np.float64]: ... - -def stream_WILLR( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -#Volume Indicator Functions - -def stream_AD( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - volume: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def stream_ADOSC( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - volume: NDArray[np.float64], - fastperiod: int= 3, - slowperiod: int= 10 - )-> NDArray[np.float64]: ... - -def stream_OBV( - close: NDArray[np.float64], - volume: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -#Volatility Indicator Functions - -def stream_ATR( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_NATR( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_TRANGE( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -# Price Transform Functions - -def stream_AVGPRICE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def stream_MEDPRICE( - high: NDArray[np.float64], - low: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def stream_TYPPRICE( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def stream_WCLPRICE( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -# Cycle Indicator Functions - -def stream_HT_DCPERIOD(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_HT_DCPHASE(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_HT_PHASOR(real: NDArray[np.float64])-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def stream_HT_SINE(real: NDArray[np.float64])-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def stream_HT_TRENDMODE(real: NDArray[np.float64])-> Tuple[NDArray[np.float64], NDArray[np.int32]]: ... - -#Pattern Recognition Functions - -def stream_CDL2CROWS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDL3BLACKCROWS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDL3INSIDE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDL3LINESTRIKE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDL3OUTSIDE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDL3STARSINSOUTH( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDL3WHITESOLDIERS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLABANDONEDBABY( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def stream_CDLADVANCEBLOCK( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLBELTHOLD( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLBREAKAWAY( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLCLOSINGMARUBOZU( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLCONCEALBABYSWALL( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLCOUNTERATTACK( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLDARKCLOUDCOVER( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def stream_CDLDOJI( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLDOJISTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLDRAGONFLYDOJI( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLENGULFING( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLEVENINGDOJISTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def stream_CDLEVENINGSTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def stream_CDLGAPSIDESIDEWHITE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLGRAVESTONEDOJI( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLHAMMER( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLHANGINGMAN( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLHARAMI( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLHARAMICROSS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLHIGHWAVE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLHIKKAKE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLHIKKAKEMOD( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLHOMINGPIGEON( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLIDENTICAL3CROWS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLINNECK( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLINVERTEDHAMMER( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLKICKING( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLKICKINGBYLENGTH( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLLADDERBOTTOM( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLLONGLEGGEDDOJI( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLLONGLINE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLMARUBOZU( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLMATCHINGLOW( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLMATHOLD( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def stream_CDLMORNINGDOJISTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def stream_CDLMORNINGSTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - penetration: float= 0 - )-> NDArray[np.int32]: ... - -def stream_CDLONNECK( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLPIERCING( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLRICKSHAWMAN( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLRISEFALL3METHODS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLSEPARATINGLINES( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLSHOOTINGSTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLSHORTLINE( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLSPINNINGTOP( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLSTALLEDPATTERN( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLSTICKSANDWICH( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLTAKURI( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLTASUKIGAP( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLTHRUSTING( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLTRISTAR( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLUNIQUE3RIVER( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLUPSIDEGAP2CROWS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -def stream_CDLXSIDEGAP3METHODS( - open: NDArray[np.float64], - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64] - )-> NDArray[np.int32]: ... - -# Statistic Functions - -def stream_BETA( - real0: NDArray[np.float64], - real1: NDArray[np.float64], - timeperiod: int= 5 - )-> NDArray[np.float64]: ... - -def stream_CORREL( - real0: NDArray[np.float64], - real1: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def stream_LINEARREG( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_LINEARREG_ANGLE( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_LINEARREG_INTERCEPT( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_LINEARREG_SLOPE( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_STDDEV( - real: NDArray[np.float64], - timeperiod: int= 5, - nbdev: float= 1 - )-> NDArray[np.float64]: ... - -def stream_TSF( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_VAR( - real: NDArray[np.float64], - timeperiod: int= 5, - nbdev: float= 1 - )-> NDArray[np.float64]: ... - -# Math Transform Functions - -def stream_ACOS(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_ASIN(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_ATAN(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_CEIL(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_COS(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_COSH(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_EXP(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_FLOOR(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_LN(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_LOG10(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_SIN(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_SINH(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_SQRT(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_TAN(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -def stream_TANH(real: NDArray[np.float64])-> NDArray[np.float64]: ... - -#Math Operator Functions - -def stream_ADD( - real0: NDArray[np.float64], - real1: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def stream_DIV( - real0: NDArray[np.float64], - real1: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def stream_MAX( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def stream_MAXINDEX( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.int32]: ... - -def stream_MIN( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def stream_MININDEX( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.int32]: ... - -def stream_MINMAX( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def stream_MINMAXINDEX( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> Tuple[NDArray[np.float64], NDArray[np.float64]]: ... - -def stream_MULT( - real0: NDArray[np.float64], - real1: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def stream_SUB( - real0: NDArray[np.float64], - real1: NDArray[np.float64] - )-> NDArray[np.float64]: ... - -def stream_SUM( - real: NDArray[np.float64], - timeperiod: int= 30 - )-> NDArray[np.float64]: ... - -def stream_ACCBANDS( - high: NDArray[np.float64], - low: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 20 - )-> NDArray[np.float64]: ... - -def stream_AVGDEV( - real: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... - -def stream_IMI( - open: NDArray[np.float64], - close: NDArray[np.float64], - timeperiod: int= 14 - )-> NDArray[np.float64]: ... diff --git a/talib/_ta_lib.pyx b/talib/_ta_lib.pyx deleted file mode 100644 index 2b8aec2b6..000000000 --- a/talib/_ta_lib.pyx +++ /dev/null @@ -1,8 +0,0 @@ -#cython: embedsignature=True, emit_code_comments=False - -include "_common.pxi" -include "_func.pxi" -include "_abstract.pxi" -include "_stream.pxi" - -__all__ = __TA_FUNCTION_NAMES__ + ["stream_%s" % name for name in __TA_FUNCTION_NAMES__] diff --git a/talib/abstract.py b/talib/abstract.py deleted file mode 100644 index a224cb6e5..000000000 --- a/talib/abstract.py +++ /dev/null @@ -1,26 +0,0 @@ -import talib._ta_lib as _ta_lib -from ._ta_lib import Function as _Function, __TA_FUNCTION_NAMES__, _get_defaults_and_docs - -# add some backwards compat for backtrader - -_func_obj_mapping = { - func_name: getattr(_ta_lib, func_name) - for func_name in __TA_FUNCTION_NAMES__ -} - - -def Function(function_name, *args, **kwargs): - func_name = function_name.upper() - if func_name not in _func_obj_mapping: - raise Exception('%s not supported by TA-LIB.' % func_name) - - return _Function( - func_name, _func_obj_mapping[func_name], *args, **kwargs - ) - - -for func_name in __TA_FUNCTION_NAMES__: - globals()[func_name] = Function(func_name) - - -__all__ = ["Function", "_get_defaults_and_docs"] + __TA_FUNCTION_NAMES__ diff --git a/talib/common.pxd b/talib/common.pxd deleted file mode 100644 index a1357543b..000000000 --- a/talib/common.pxd +++ /dev/null @@ -1,2 +0,0 @@ -from _ta_lib cimport TA_RetCode -cpdef _ta_check_success(str function_name, TA_RetCode ret_code) diff --git a/talib/deprecated.py b/talib/deprecated.py deleted file mode 100644 index 264fc46ce..000000000 --- a/talib/deprecated.py +++ /dev/null @@ -1,2 +0,0 @@ -# TA_MAType enums -MA_SMA, MA_EMA, MA_WMA, MA_DEMA, MA_TEMA, MA_TRIMA, MA_KAMA, MA_MAMA, MA_T3 = range(9) diff --git a/talib/py.typed b/talib/py.typed deleted file mode 100644 index e69de29bb..000000000 diff --git a/talib/stream.py b/talib/stream.py deleted file mode 100644 index ee2cc85e9..000000000 --- a/talib/stream.py +++ /dev/null @@ -1,6 +0,0 @@ -import talib._ta_lib as _ta_lib -from ._ta_lib import __TA_FUNCTION_NAMES__ - - -for func_name in __TA_FUNCTION_NAMES__: - globals()[func_name] = getattr(_ta_lib, "stream_%s" % func_name) diff --git a/tests/conftest.py b/tests/conftest.py deleted file mode 100644 index 9756ae7dd..000000000 --- a/tests/conftest.py +++ /dev/null @@ -1,244 +0,0 @@ -from __future__ import print_function - -import pytest -import numpy as np - - -@pytest.fixture(scope='session') -def ford_2012_dates(): - return np.asarray([ - 20120103, 20120104, 20120105, 20120106, 20120109, - 20120110, 20120111, 20120112, 20120113, 20120117, 20120118, 20120119, - 20120120, 20120123, 20120124, 20120125, 20120126, 20120127, 20120130, - 20120131, 20120201, 20120202, 20120203, 20120206, 20120207, 20120208, - 20120209, 20120210, 20120213, 20120214, 20120215, 20120216, 20120217, - 20120221, 20120222, 20120223, 20120224, 20120227, 20120228, 20120229, - 20120301, 20120302, 20120305, 20120306, 20120307, 20120308, 20120309, - 20120312, 20120313, 20120314, 20120315, 20120316, 20120319, 20120320, - 20120321, 20120322, 20120323, 20120326, 20120327, 20120328, 20120329, - 20120330, 20120402, 20120403, 20120404, 20120405, 20120409, 20120410, - 20120411, 20120412, 20120413, 20120416, 20120417, 20120418, 20120419, - 20120420, 20120423, 20120424, 20120425, 20120426, 20120427, 20120430, - 20120501, 20120502, 20120503, 20120504, 20120507, 20120508, 20120509, - 20120510, 20120511, 20120514, 20120515, 20120516, 20120517, 20120518, - 20120521, 20120522, 20120523, 20120524, 20120525, 20120529, 20120530, - 20120531, 20120601, 20120604, 20120605, 20120606, 20120607, 20120608, - 20120611, 20120612, 20120613, 20120614, 20120615, 20120618, 20120619, - 20120620, 20120621, 20120622, 20120625, 20120626, 20120627, 20120628, - 20120629, 20120702, 20120703, 20120705, 20120706, 20120709, 20120710, - 20120711, 20120712, 20120713, 20120716, 20120717, 20120718, 20120719, - 20120720, 20120723, 20120724, 20120725, 20120726, 20120727, 20120730, - 20120731, 20120801, 20120802, 20120803, 20120806, 20120807, 20120808, - 20120809, 20120810, 20120813, 20120814, 20120815, 20120816, 20120817, - 20120820, 20120821, 20120822, 20120823, 20120824, 20120827, 20120828, - 20120829, 20120830, 20120831, 20120904, 20120905, 20120906, 20120907, - 20120910, 20120911, 20120912, 20120913, 20120914, 20120917, 20120918, - 20120919, 20120920, 20120921, 20120924, 20120925, 20120926, 20120927, - 20120928, 20121001, 20121002, 20121003, 20121004, 20121005, 20121008, - 20121009, 20121010, 20121011, 20121012, 20121015, 20121016, 20121017, - 20121018, 20121019, 20121022, 20121023, 20121024, 20121025, 20121026, - 20121031, 20121101, 20121102, 20121105, 20121106, 20121107, 20121108, - 20121109, 20121112, 20121113, 20121114, 20121115, 20121116, 20121119, - 20121120, 20121121, 20121123, 20121126, 20121127, 20121128, 20121129, - 20121130, 20121203, 20121204, 20121205, 20121206, 20121207, 20121210, - 20121211, 20121212, 20121213, 20121214, 20121217, 20121218, 20121219, - 20121220, 20121221, 20121224, 20121226, 20121227, 20121228, 20121231 - ]) - - -@pytest.fixture(scope='session') -def ford_2012(): - return { - 'open': np.asarray([ - 11.00, 11.15, 11.33, 11.74, 11.83, 12.00, 11.74, 12.16, 12.01, - 12.20, 12.03, 12.48, 12.55, 12.69, 12.56, 12.80, 13.03, 11.96, - 12.06, 12.47, 12.73, 12.40, 12.47, 12.85, 12.93, 12.91, 12.89, - 12.52, 12.74, 12.46, 12.47, 12.38, 12.84, 12.74, 12.49, 12.27, - 12.43, 12.11, 12.34, 12.28, 12.48, 12.74, 12.67, 12.23, 12.21, - 12.41, 12.53, 12.57, 12.48, 12.64, 12.90, 12.86, 12.52, 12.48, - 12.59, 12.48, 12.31, 12.45, 12.51, 12.35, 12.33, 12.55, 12.50, - 12.71, 12.46, 12.38, 12.26, 12.19, 11.99, 11.94, 11.98, 12.01, - 11.98, 11.81, 11.81, 11.71, 11.15, 11.61, 11.51, 11.71, 12.03, - 11.42, 11.25, 11.16, 11.13, 10.84, 10.53, 10.60, 10.48, 10.83, - 10.61, 10.41, 10.34, 10.23, 10.16, 10.08, 10.02, 10.25, 10.32, - 10.50, 10.61, 10.69, 10.73, 10.62, 10.33, 10.15, 10.01, 10.29, - 10.73, 10.48, 10.77, 10.47, 10.39, 10.27, 10.40, 10.35, 10.37, - 10.58, 10.65, 10.35, 10.13, 10.06, 10.05, 9.93, 9.95, 9.50, 9.53, - 9.67, 9.47, 9.46, 9.50, 9.33, 9.26, 9.16, 9.22, 9.28, 9.38, 9.45, - 9.28, 9.08, 9.17, 9.17, 9.05, 8.99, 9.04, 9.13, 9.29, 8.99, 9.02, - 9.13, 9.18, 9.25, 9.31, 9.30, 9.35, 9.45, 9.44, 9.50, 9.65, 9.58, - 9.65, 9.50, 9.45, 9.42, 9.51, 9.37, 9.33, 9.30, 9.39, 9.37, 9.45, - 9.66, 9.95, 10.08, 10.18, 10.25, 10.20, 10.41, 10.27, 10.30, 10.49, - 10.48, 10.53, 10.30, 10.35, 9.98, 10.13, 9.99, 9.89, 10.01, 9.82, - 10.06, 10.17, 10.06, 10.21, 10.12, 10.06, 10.14, 10.11, 10.26, - 10.31, 10.36, 10.42, 10.14, 10.02, 10.08, 10.42, 10.35, 10.70, - 11.19, 11.31, 11.15, 11.33, 11.25, 11.07, 10.76, 11.03, 10.89, - 11.02, 10.57, 10.58, 10.65, 10.85, 10.84, 10.98, 11.05, 11.10, - 11.05, 11.32, 11.52, 11.56, 11.40, 11.32, 11.26, 11.27, 11.41, - 11.51, 11.52, 11.46, 11.27, 11.16, 11.48, 11.79, 11.74, 11.55, - 11.67, 12.31, 12.79, 12.55, 12.88 - ]), - 'high': np.asarray([ - 11.25, 11.53, 11.63, 11.80, 11.95, 12.05, 12.18, 12.18, 12.08, - 12.26, 12.37, 12.72, 12.64, 12.84, 12.86, 12.98, 13.05, 12.53, - 12.44, 12.51, 12.75, 12.43, 12.84, 13.00, 12.97, 12.96, 12.90, - 12.66, 12.74, 12.58, 12.57, 12.77, 12.88, 12.76, 12.51, 12.44, - 12.46, 12.36, 12.35, 12.55, 12.77, 12.94, 12.68, 12.25, 12.30, - 12.55, 12.73, 12.59, 12.72, 12.90, 13.04, 12.90, 12.68, 12.61, - 12.67, 12.54, 12.37, 12.50, 12.61, 12.36, 12.52, 12.58, 12.65, - 12.95, 12.52, 12.58, 12.29, 12.28, 12.02, 12.13, 12.03, 12.05, - 12.00, 11.85, 11.88, 11.72, 11.40, 11.61, 11.75, 11.93, 12.04, - 11.47, 11.34, 11.17, 11.15, 10.87, 10.79, 10.64, 10.81, 10.86, - 10.83, 10.53, 10.34, 10.43, 10.25, 10.18, 10.23, 10.40, 10.45, - 10.62, 10.68, 10.88, 10.75, 10.68, 10.37, 10.18, 10.24, 10.58, - 10.78, 10.68, 10.80, 10.55, 10.49, 10.45, 10.42, 10.40, 10.64, - 10.74, 10.68, 10.40, 10.18, 10.08, 10.10, 10.09, 9.98, 9.60, 9.79, - 9.74, 9.52, 9.47, 9.55, 9.38, 9.28, 9.32, 9.32, 9.35, 9.52, 9.50, - 9.35, 9.21, 9.24, 9.20, 9.11, 9.10, 9.18, 9.28, 9.42, 9.03, 9.15, - 9.21, 9.39, 9.38, 9.46, 9.36, 9.42, 9.66, 9.54, 9.67, 9.66, 9.64, - 9.70, 9.56, 9.54, 9.52, 9.52, 9.44, 9.40, 9.34, 9.43, 9.47, 9.62, - 9.96, 10.23, 10.28, 10.25, 10.30, 10.38, 10.57, 10.42, 10.45, 10.66, - 10.52, 10.54, 10.40, 10.37, 10.12, 10.18, 10.00, 10.08, 10.05, - 10.02, 10.15, 10.28, 10.12, 10.25, 10.12, 10.26, 10.25, 10.25, - 10.32, 10.41, 10.57, 10.43, 10.24, 10.11, 10.29, 10.49, 10.42, - 11.17, 11.30, 11.38, 11.35, 11.59, 11.34, 11.23, 11.10, 11.16, - 11.10, 11.05, 10.80, 10.64, 10.90, 11.02, 11.00, 11.10, 11.14, - 11.27, 11.26, 11.53, 11.60, 11.70, 11.44, 11.40, 11.31, 11.50, - 11.53, 11.58, 11.56, 11.50, 11.27, 11.41, 11.68, 11.85, 11.80, - 11.86, 12.40, 12.79, 12.81, 12.88, 13.08 - ]), - 'low': np.asarray([ - 10.99, 11.07, 11.24, 11.52, 11.70, 11.63, 11.65, 11.89, 11.84, - 11.96, 12.00, 12.43, 12.45, 12.55, 12.46, 12.70, 12.66, 11.79, - 12.00, 12.20, 12.29, 12.20, 12.39, 12.71, 12.83, 12.80, 12.67, - 12.37, 12.51, 12.34, 12.33, 12.38, 12.71, 12.46, 12.22, 12.16, - 12.19, 11.99, 12.20, 12.25, 12.45, 12.68, 12.41, 12.00, 12.15, - 12.32, 12.48, 12.37, 12.40, 12.63, 12.83, 12.51, 12.48, 12.39, - 12.55, 12.24, 12.18, 12.39, 12.30, 12.18, 12.24, 12.40, 12.44, - 12.46, 12.32, 12.38, 12.11, 11.65, 11.88, 11.86, 11.84, 11.83, - 11.88, 11.72, 11.58, 11.39, 11.15, 11.36, 11.43, 11.67, 11.52, - 11.15, 11.11, 11.00, 10.85, 10.63, 10.52, 10.40, 10.41, 10.66, - 10.56, 10.30, 10.10, 10.15, 10.01, 9.96, 10.00, 10.15, 10.22, 10.38, - 10.51, 10.68, 10.52, 10.40, 10.06, 9.91, 9.97, 10.27, 10.52, 10.38, - 10.45, 10.31, 10.22, 10.21, 10.26, 10.26, 10.35, 10.52, 10.25, - 10.18, 9.95, 9.96, 9.97, 9.93, 9.46, 9.30, 9.49, 9.53, 9.40, 9.31, - 9.28, 9.26, 9.12, 9.14, 9.15, 9.12, 9.34, 9.33, 9.18, 9.05, 8.95, - 8.91, 8.83, 8.88, 9.01, 9.12, 8.99, 8.82, 8.96, 9.09, 9.18, 9.24, - 9.30, 9.23, 9.25, 9.42, 9.41, 9.49, 9.60, 9.51, 9.52, 9.40, 9.42, - 9.41, 9.38, 9.31, 9.29, 9.25, 9.31, 9.35, 9.39, 9.66, 9.93, 10.06, - 10.13, 10.17, 10.12, 10.39, 10.26, 10.28, 10.45, 10.35, 10.36, - 10.26, 10.06, 9.86, 10.02, 9.81, 9.88, 9.71, 9.76, 9.96, 10.13, - 9.99, 10.02, 9.95, 10.05, 10.09, 10.09, 10.22, 10.26, 10.33, 10.13, - 10.03, 9.97, 10.01, 10.28, 10.22, 10.60, 10.88, 11.15, 11.13, 11.26, - 11.04, 10.89, 10.71, 10.96, 10.86, 10.62, 10.46, 10.38, 10.65, - 10.76, 10.80, 10.96, 10.97, 11.10, 10.98, 11.32, 11.33, 11.40, - 11.23, 11.18, 11.19, 11.26, 11.41, 11.40, 11.43, 11.21, 11.03, - 11.14, 11.40, 11.62, 11.58, 11.47, 11.67, 12.31, 12.36, 12.52, 12.76 - ]), - 'close': np.asarray([ - 11.13, 11.30, 11.59, 11.71, 11.80, 11.80, 12.07, 12.14, 12.04, - 12.02, 12.34, 12.61, 12.59, 12.66, 12.82, 12.93, 12.79, 12.21, - 12.29, 12.42, 12.33, 12.26, 12.79, 12.96, 12.88, 12.84, 12.69, - 12.44, 12.54, 12.48, 12.38, 12.74, 12.75, 12.53, 12.28, 12.40, - 12.23, 12.30, 12.25, 12.38, 12.66, 12.72, 12.46, 12.09, 12.24, - 12.46, 12.58, 12.43, 12.70, 12.88, 12.90, 12.51, 12.63, 12.54, - 12.57, 12.32, 12.32, 12.48, 12.32, 12.32, 12.50, 12.48, 12.62, - 12.64, 12.51, 12.47, 12.22, 11.79, 11.91, 12.07, 11.92, 11.88, - 11.91, 11.79, 11.66, 11.41, 11.35, 11.39, 11.73, 11.87, 11.60, - 11.28, 11.23, 11.10, 10.92, 10.67, 10.66, 10.61, 10.69, 10.71, - 10.58, 10.32, 10.15, 10.16, 10.01, 10.01, 10.20, 10.19, 10.41, - 10.59, 10.60, 10.84, 10.66, 10.56, 10.12, 10.04, 10.19, 10.57, - 10.55, 10.66, 10.45, 10.50, 10.30, 10.41, 10.35, 10.34, 10.56, - 10.65, 10.27, 10.19, 10.01, 10.01, 10.02, 10.09, 9.59, 9.39, 9.60, - 9.57, 9.50, 9.45, 9.35, 9.33, 9.13, 9.27, 9.26, 9.34, 9.38, 9.35, - 9.21, 9.17, 9.06, 8.97, 8.96, 9.00, 9.10, 9.24, 9.04, 8.92, 9.09, - 9.15, 9.31, 9.35, 9.34, 9.35, 9.40, 9.44, 9.49, 9.59, 9.63, 9.63, - 9.53, 9.49, 9.45, 9.49, 9.39, 9.34, 9.32, 9.31, 9.34, 9.41, 9.57, - 9.92, 10.14, 10.11, 10.15, 10.21, 10.34, 10.53, 10.39, 10.42, 10.59, - 10.44, 10.40, 10.32, 10.09, 10.01, 10.02, 9.86, 9.93, 9.79, 9.94, - 10.11, 10.16, 10.05, 10.10, 9.98, 10.14, 10.12, 10.22, 10.30, 10.41, - 10.43, 10.18, 10.17, 10.00, 10.17, 10.39, 10.36, 11.16, 11.25, - 11.17, 11.25, 11.42, 11.06, 10.90, 10.93, 10.97, 11.00, 10.67, - 10.57, 10.50, 10.83, 10.85, 10.92, 11.10, 11.11, 11.10, 11.25, - 11.53, 11.45, 11.41, 11.31, 11.31, 11.24, 11.48, 11.47, 11.49, - 11.47, 11.27, 11.10, 11.39, 11.67, 11.73, 11.77, 11.86, 12.40, - 12.79, 12.76, 12.87, 12.95 - ]), - 'volume': np.asarray([ - 45709900, 79725200, 67877500, 59840700, 53981500, 121750600, - 63806000, 48687700, 46366700, 44398400, 47102700, 70894200, - 43705700, 49379700, 45768400, 54021600, 75470700, 142155300, - 57752600, 46412100, 71669000, 48347600, 78851200, 46363300, - 39413500, 35352500, 52290500, 52505500, 34474400, 39627900, - 38174800, 49164400, 30778000, 38409800, 43326000, 36747600, - 31399300, 38703400, 30789000, 62093700, 68262000, 49063500, - 28433700, 57374500, 28440900, 37099100, 36159300, 30275700, - 42783600, 47578500, 55286600, 77119600, 52445700, 40214400, - 27521400, 50117100, 44755000, 26692200, 35070700, 41051700, - 51039700, 36381000, 43966900, 97034200, 51505000, 37939500, - 42515300, 77370300, 34724400, 26988800, 39675000, 31903500, - 35981200, 32314000, 48169200, 52631000, 31269200, 38615200, - 45185400, 40889300, 83070300, 46156300, 43959200, 48572900, - 40238400, 53268400, 33235200, 46174500, 54501200, 42526100, - 36561300, 50225200, 41886500, 44321300, 49648900, 50572000, - 38134900, 44295700, 75647800, 45334100, 30430800, 43760600, - 44592100, 54297000, 68237000, 57305600, 38326200, 50458000, - 33846100, 30811600, 35811400, 35130800, 53471900, 37531800, - 39442000, 27361000, 37155900, 40810100, 40062800, 56427300, - 44297600, 31871900, 33278900, 38648400, 138138600, 63388600, - 49629300, 31783900, 30355400, 37441600, 33516600, 32028700, - 55111000, 30248300, 28838200, 29510000, 31010000, 33615000, - 27968300, 33773800, 53519200, 44338200, 51798900, 67986800, - 40958300, 41360900, 65973000, 45326500, 38631400, 23819100, - 43574500, 22630300, 30909800, 19618800, 21122000, 21129500, - 21308300, 34323700, 34533900, 38923800, 26281100, 26965500, - 23537700, 19574600, 22754200, 23084400, 26115700, 16459400, - 28029200, 37965000, 40608800, 67996400, 60617000, 43381300, - 28165300, 28046500, 50920200, 55934300, 31922200, 34937000, - 42403000, 28755100, 35459800, 28557900, 36866300, 44362600, - 25740900, 44586300, 33445600, 63630000, 51023800, 46855500, - 40693900, 25473900, 38235700, 33951600, 39328700, 24108500, - 26466500, 32788400, 29346300, 44041700, 40493000, 39149700, - 32476500, 49339800, 59290900, 43485500, 137960900, 88770100, - 53399000, 37995000, 51232200, 56674900, 45948800, 40703600, - 25723100, 33342900, 45664700, 48879800, 45346200, 39359100, - 34739800, 21181700, 16032200, 26831700, 37610000, 38496900, - 57289300, 41329600, 47746300, 37760200, 33152400, 31065800, - 38404500, 26025200, 36326900, 31099900, 35443200, 36933500, - 46983300, 61810400, 54884700, 47750100, 94489300, 91734900, - 140331900, 108315100, 95668600, 106908900 - ]) - } - - -@pytest.fixture(scope='session') -def series(): - return np.array([ - 91.50, 94.81, 94.38, 95.09, 93.78, 94.62, 92.53, 92.75, 90.31, 92.47, - 96.12, 97.25, 98.50, 89.88, 91.00, 92.81, 89.16, 89.34, 91.62, 89.88, - 88.38, 87.62, 84.78, 83.00, 83.50, 81.38, 84.44, 89.25, 86.38, 86.25, - 85.25, 87.12, 85.81, 88.97, 88.47, 86.88, 86.81, 84.88, 84.19, 83.88, - 83.38, 85.50, 89.19, 89.44, 91.09, 90.75, 91.44, 89.00, 91.00, 90.50, - 89.03, 88.81, 84.28, 83.50, 82.69, 84.75, 85.66, 86.19, 88.94, 89.28, - 88.62, 88.50, 91.97, 91.50, 93.25, 93.50, 93.16, 91.72, 90.00, 89.69, - 88.88, 85.19, 83.38, 84.88, 85.94, 97.25, 99.88, 104.94, 106.00, 102.50, - 102.41, 104.59, 106.12, 106.00, 106.06, 104.62, 108.62, 109.31, 110.50, - 112.75, 123.00, 119.62, 118.75, 119.25, 117.94, 116.44, 115.19, 111.88, - 110.59, 118.12, 116.00, 116.00, 112.00, 113.75, 112.94, 116.00, 120.50, - 116.62, 117.00, 115.25, 114.31, 115.50, 115.87, 120.69, 120.19, 120.75, - 124.75, 123.37, 122.94, 122.56, 123.12, 122.56, 124.62, 129.25, 131.00, - 132.25, 131.00, 132.81, 134.00, 137.38, 137.81, 137.88, 137.25, 136.31, - 136.25, 134.63, 128.25, 129.00, 123.87, 124.81, 123.00, 126.25, 128.38, - 125.37, 125.69, 122.25, 119.37, 118.50, 123.19, 123.50, 122.19, 119.31, - 123.31, 121.12, 123.37, 127.37, 128.50, 123.87, 122.94, 121.75, 124.44, - 122.00, 122.37, 122.94, 124.00, 123.19, 124.56, 127.25, 125.87, 128.86, - 132.00, 130.75, 134.75, 135.00, 132.38, 133.31, 131.94, 130.00, 125.37, - 130.13, 127.12, 125.19, 122.00, 125.00, 123.00, 123.50, 120.06, 121.00, - 117.75, 119.87, 122.00, 119.19, 116.37, 113.50, 114.25, 110.00, 105.06, - 107.00, 107.87, 107.00, 107.12, 107.00, 91.00, 93.94, 93.87, 95.50, - 93.00, 94.94, 98.25, 96.75, 94.81, 94.37, 91.56, 90.25, 93.94, 93.62, - 97.00, 95.00, 95.87, 94.06, 94.62, 93.75, 98.00, 103.94, 107.87, 106.06, - 104.50, 105.00, 104.19, 103.06, 103.42, 105.27, 111.87, 116.00, 116.62, - 118.28, 113.37, 109.00, 109.70, 109.25, 107.00, 109.19, 110.00, 109.20, - 110.12, 108.00, 108.62, 109.75, 109.81, 109.00, 108.75, 107.87 - ]) \ No newline at end of file diff --git a/tests/test_abstract.py b/tests/test_abstract.py deleted file mode 100644 index 338518608..000000000 --- a/tests/test_abstract.py +++ /dev/null @@ -1,369 +0,0 @@ -import copy -import re -import threading -import time - -import numpy as np -import pytest -from numpy.testing import assert_array_equal, assert_raises - -try: - from collections import OrderedDict -except ImportError: # handle python 2.6 and earlier - from ordereddict import OrderedDict - -import talib -from talib import abstract, func - - -def assert_array_not_equal(x, y): - assert_raises(AssertionError, assert_array_equal, x, y) - - -def test_pandas(ford_2012): - import pandas - input_df = pandas.DataFrame(ford_2012) - input_dict = dict((k, pandas.Series(v)) for k, v in ford_2012.items()) - - expected_k, expected_d = func.STOCH(ford_2012['high'], ford_2012['low'], ford_2012['close']) # 5, 3, 0, 3, 0 - output = abstract.Function('stoch', input_df).outputs - assert isinstance(output, pandas.DataFrame) - assert_array_equal(expected_k, output['slowk']) - assert_array_equal(expected_d, output['slowd']) - output = abstract.Function('stoch', input_dict).outputs - assert isinstance(output, list) - assert_array_equal(expected_k, output[0]) - assert_array_equal(expected_d, output[1]) - - expected = func.SMA(ford_2012['close'], 10) - output = abstract.Function('sma', input_df, 10).outputs - assert isinstance(output, pandas.Series) - assert_array_equal(expected, output) - output = abstract.Function('sma', input_dict, 10).outputs - assert isinstance(output, np.ndarray) - assert_array_equal(expected, output) - - -def test_pandas_series(ford_2012): - import pandas - input_df = pandas.DataFrame(ford_2012) - output = talib.SMA(input_df['close'], 10) - expected = pandas.Series(func.SMA(ford_2012['close'], 10), - index=input_df.index) - pandas.testing.assert_series_equal(output, expected) - - # Test kwargs - output = talib.SMA(real=input_df['close'], timeperiod=10) - pandas.testing.assert_series_equal(output, expected) - - # Test talib.func API - output = func.SMA(input_df['close'], timeperiod=10) - pandas.testing.assert_series_equal(output, expected) - - # Test multiple outputs such as from BBANDS - _, output, _ = talib.BBANDS(input_df['close'], 10) - expected = pandas.Series(func.BBANDS(ford_2012['close'], 10)[1], - index=input_df.index) - pandas.testing.assert_series_equal(output, expected) - - -def test_SMA(ford_2012): - expected = func.SMA(ford_2012['close'], 10) - assert_array_equal(expected, abstract.Function('sma', ford_2012, 10).outputs) - assert_array_equal(expected, abstract.Function('sma')(ford_2012, 10, price='close')) - assert_array_equal(expected, abstract.Function('sma')(ford_2012, timeperiod=10)) - expected = func.SMA(ford_2012['open'], 10) - assert_array_equal(expected, abstract.Function('sma', ford_2012, 10, price='open').outputs) - assert_array_equal(expected, abstract.Function('sma', price='low')(ford_2012, 10, price='open')) - assert_array_not_equal(expected, abstract.Function('sma', ford_2012, 10, price='open')(timeperiod=20)) - assert_array_not_equal(expected, abstract.Function('sma', ford_2012)(10, price='close')) - assert_array_not_equal(expected, abstract.Function('sma', 10)(ford_2012, price='high')) - assert_array_not_equal(expected, abstract.Function('sma', price='low')(ford_2012, 10)) - input_arrays = {'foobarbaz': ford_2012['open']} - assert_array_equal(expected, abstract.SMA(input_arrays, 10, price='foobarbaz')) - - -def test_STOCH(ford_2012): - # check defaults match - expected_k, expected_d = func.STOCH(ford_2012['high'], ford_2012['low'], ford_2012['close']) # 5, 3, 0, 3, 0 - got_k, got_d = abstract.Function('stoch', ford_2012).outputs - assert_array_equal(expected_k, got_k) - assert_array_equal(expected_d, got_d) - - expected_k, expected_d = func.STOCH(ford_2012['high'], ford_2012['low'], ford_2012['close']) - got_k, got_d = abstract.Function('stoch', ford_2012)(5, 3, 0, 3, 0) - assert_array_equal(expected_k, got_k) - assert_array_equal(expected_d, got_d) - - expected_k, expected_d = func.STOCH(ford_2012['high'], ford_2012['low'], ford_2012['close'], 15) - got_k, got_d = abstract.Function('stoch', ford_2012)(15, 5, 0, 5, 0) - assert_array_not_equal(expected_k, got_k) - assert_array_not_equal(expected_d, got_d) - - expected_k, expected_d = func.STOCH(ford_2012['high'], ford_2012['low'], ford_2012['close'], 15, 5, 1, 5, 1) - got_k, got_d = abstract.Function('stoch', ford_2012)(15, 5, 1, 5, 1) - assert_array_equal(expected_k, got_k) - assert_array_equal(expected_d, got_d) - - -def test_doji_candle(ford_2012): - expected = func.CDLDOJI(ford_2012['open'], ford_2012['high'], ford_2012['low'], ford_2012['close']) - got = abstract.Function('CDLDOJI').run(ford_2012) - assert_array_equal(got, expected) - - -def test_MAVP(ford_2012): - mavp = abstract.MAVP - with pytest.raises(Exception): - mavp.set_input_arrays(ford_2012) - input_d = {} - input_d['close'] = ford_2012['close'] - input_d['periods'] = np.arange(30) - assert mavp.set_input_arrays(input_d) - assert mavp.input_arrays == input_d - - -def test_info(): - stochrsi = abstract.Function('STOCHRSI') - stochrsi.input_names = {'price': 'open'} - stochrsi.parameters = {'fastd_matype': talib.MA_Type.EMA} - expected = { - 'display_name': 'Stochastic Relative Strength Index', - 'function_flags': ['Function has an unstable period'], - 'group': 'Momentum Indicators', - 'input_names': OrderedDict([('price', 'open')]), - 'name': 'STOCHRSI', - 'output_flags': OrderedDict([ - ('fastk', ['Line']), - ('fastd', ['Line']), - ]), - 'output_names': ['fastk', 'fastd'], - 'parameters': OrderedDict([ - ('timeperiod', 14), - ('fastk_period', 5), - ('fastd_period', 3), - ('fastd_matype', 1), - ]), - } - assert expected == stochrsi.info - - expected = { - 'display_name': 'Bollinger Bands', - 'function_flags': ['Output scale same as input'], - 'group': 'Overlap Studies', - 'input_names': OrderedDict([('price', 'close')]), - 'name': 'BBANDS', - 'output_flags': OrderedDict([ - ('upperband', ['Values represent an upper limit']), - ('middleband', ['Line']), - ('lowerband', ['Values represent a lower limit']), - ]), - 'output_names': ['upperband', 'middleband', 'lowerband'], - 'parameters': OrderedDict([ - ('timeperiod', 5), - ('nbdevup', 2), - ('nbdevdn', 2), - ('matype', 0), - ]), - } - assert expected == abstract.Function('BBANDS').info - - -def test_input_names(): - expected = OrderedDict([('price', 'close')]) - assert expected == abstract.Function('MAMA').input_names - - # test setting input_names - obv = abstract.Function('OBV') - expected = OrderedDict([ - ('price', 'open'), - ('prices', ['volume']), - ]) - obv.input_names = expected - assert obv.input_names == expected - - obv.input_names = { - 'price': 'open', - 'prices': ['volume'], - } - assert obv.input_names == expected - - -def test_input_arrays(ford_2012): - mama = abstract.Function('MAMA') - - # test default setting - assert mama.get_input_arrays() == {} - - # test setting/getting input_arrays - assert mama.set_input_arrays(ford_2012) - assert mama.get_input_arrays() == ford_2012 - with pytest.raises(Exception): - mama.set_input_arrays({'hello': 'fail', 'world': 'bye'}) - - # test only required keys are needed - willr = abstract.Function('WILLR') - reqd = willr.input_names['prices'] - input_d = dict([(key, ford_2012[key]) for key in reqd]) - assert willr.set_input_arrays(input_d) - assert willr.input_arrays == input_d - - # test extraneous keys are ignored - input_d['extra_stuffs'] = 'you should never see me' - input_d['date'] = np.random.rand(100) - assert willr.set_input_arrays(input_d) - - # test missing keys get detected - input_d['open'] = ford_2012['open'] - input_d.pop('close') - with pytest.raises(Exception): - willr.set_input_arrays(input_d) - - # test changing input_names on the Function - willr.input_names = {'prices': ['high', 'low', 'open']} - assert willr.set_input_arrays(input_d) - - -def test_parameters(): - stoch = abstract.Function('STOCH') - expected = OrderedDict([ - ('fastk_period', 5), - ('slowk_period', 3), - ('slowk_matype', 0), - ('slowd_period', 3), - ('slowd_matype', 0), - ]) - assert expected == stoch.parameters - - stoch.parameters = {'fastk_period': 10} - expected['fastk_period'] = 10 - assert expected == stoch.parameters - - stoch.parameters = {'slowk_period': 8, 'slowd_period': 5} - expected['slowk_period'] = 8 - expected['slowd_period'] = 5 - assert expected == stoch.parameters - - stoch.parameters = {'slowd_matype': talib.MA_Type.T3} - expected['slowd_matype'] = 8 - assert expected == stoch.parameters - - stoch.parameters = { - 'slowk_matype': talib.MA_Type.WMA, - 'slowd_matype': talib.MA_Type.EMA, - } - expected['slowk_matype'] = 2 - expected['slowd_matype'] = 1 - assert expected == stoch.parameters - - -def test_lookback(): - assert abstract.Function('SMA', 10).lookback == 9 - - stochrsi = abstract.Function('stochrsi', 20, 5, 3) - assert stochrsi.lookback == 26 - - -def test_call_supports_same_signature_as_func_module(ford_2012): - adx = abstract.Function('ADX') - - expected = func.ADX(ford_2012['open'], ford_2012['high'], ford_2012['low']) - output = adx(ford_2012['open'], ford_2012['high'], ford_2012['low']) - assert_array_equal(expected, output) - - expected_error = re.escape('Too many price arguments: expected 3 (high, low, close)') - - with pytest.raises(TypeError, match=expected_error): - adx(ford_2012['open'], ford_2012['high'], ford_2012['low'], ford_2012['close']) - - expected_error = re.escape('Not enough price arguments: expected 3 (high, low, close)') - - with pytest.raises(TypeError, match=expected_error): - adx(ford_2012['open'], ford_2012['high']) - - -def test_parameter_type_checking(ford_2012): - sma = abstract.Function('SMA', timeperiod=10) - - expected_error = re.escape('Invalid parameter value for timeperiod (expected int, got float)') - - with pytest.raises(TypeError, match=expected_error): - sma(ford_2012['close'], 35.5) - - with pytest.raises(TypeError, match=expected_error): - abstract.Function('SMA', timeperiod=35.5) - - with pytest.raises(TypeError, match=expected_error): - sma.parameters = {'timeperiod': 35.5} - - with pytest.raises(TypeError, match=expected_error): - sma.set_parameters(timeperiod=35.5) - - -def test_call_doesnt_cache_parameters(ford_2012): - sma = abstract.Function('SMA', timeperiod=10) - - expected = func.SMA(ford_2012['open'], 20) - output = sma(ford_2012, timeperiod=20, price='open') - assert_array_equal(expected, output) - - expected = func.SMA(ford_2012['close'], 20) - output = sma(ford_2012, timeperiod=20) - assert_array_equal(expected, output) - - expected = func.SMA(ford_2012['close'], 10) - output = sma(ford_2012) - assert_array_equal(expected, output) - - -def test_call_without_arguments(): - with pytest.raises(TypeError, match='Not enough price arguments'): - abstract.Function('SMA')() - - with pytest.raises(TypeError, match='Not enough price arguments'): - abstract.Function('SMA')(10) - - -def test_threading(): - import pandas as pd - TEST_LEN_SHORT = 999 - TEST_LEN_LONG = 4005 - LOOPS = 1000 - THREADS = 4 - - data_short = np.random.rand(TEST_LEN_SHORT, 5) - data_long = np.random.rand(TEST_LEN_LONG, 5) - - df_short = pd.DataFrame(data_short, columns=['open', 'high', 'low', 'close', 'volume']) - df_long = pd.DataFrame(data_long, columns=['open', 'high', 'low', 'close', 'volume']) - - total = 0 - - def loop(i): - nonlocal total - if i % 2 == 0: - df = copy.deepcopy(df_short) - else: - df = copy.deepcopy(df_long) - - for _ in range(LOOPS): - total += 1 - df['RSI'] = abstract.RSI(df) - - t0 = time.time() - - threads = [] - for i in range(THREADS): - t = threading.Thread(target=lambda: loop(i)) - threads.append(t) - t.start() - - for t in threads: - t.join() - - t1 = time.time() - print('test_len: %d, loops: %d' % (TEST_LEN_LONG, LOOPS)) - print('%.6f' % (t1 - t0)) - print('%.6f' % ((t1 - t0) / LOOPS)) - - assert total == THREADS * LOOPS diff --git a/tests/test_func.py b/tests/test_func.py deleted file mode 100644 index de45f824a..000000000 --- a/tests/test_func.py +++ /dev/null @@ -1,197 +0,0 @@ -import numpy as np -from numpy.testing import assert_array_equal, assert_array_almost_equal -import pytest - -import talib -from talib import func - - -def test_talib_version(): - assert talib.__ta_version__[:5] == b'0.6.4' - - -def test_num_functions(): - assert len(talib.get_functions()) == 158 - - -def test_input_wrong_type(): - a1 = np.arange(10, dtype=int) - with pytest.raises(Exception): - func.MOM(a1) - - -def test_input_lengths(): - a1 = np.arange(10, dtype=float) - a2 = np.arange(11, dtype=float) - with pytest.raises(Exception): - func.BOP(a2, a1, a1, a1) - with pytest.raises(Exception): - func.BOP(a1, a2, a1, a1) - with pytest.raises(Exception): - func.BOP(a1, a1, a2, a1) - with pytest.raises(Exception): - func.BOP(a1, a1, a1, a2) - - -def test_input_allnans(): - a = np.arange(20, dtype=float) - a[:] = np.nan - r = func.RSI(a) - assert np.all(np.isnan(r)) - - -def test_input_nans(): - a1 = np.arange(10, dtype=float) - a2 = np.arange(10, dtype=float) - a2[0] = np.nan - a2[1] = np.nan - r1, r2 = func.AROON(a1, a2, 2) - assert_array_equal(r1, [np.nan, np.nan, np.nan, np.nan, 0, 0, 0, 0, 0, 0]) - assert_array_equal(r2, [np.nan, np.nan, np.nan, np.nan, 100, 100, 100, 100, 100, 100]) - r1, r2 = func.AROON(a2, a1, 2) - assert_array_equal(r1, [np.nan, np.nan, np.nan, np.nan, 0, 0, 0, 0, 0, 0]) - assert_array_equal(r2, [np.nan, np.nan, np.nan, np.nan, 100, 100, 100, 100, 100, 100]) - - -def test_unstable_period(): - a = np.arange(10, dtype=float) - r = func.EMA(a, 3) - assert_array_equal(r, [np.nan, np.nan, 1, 2, 3, 4, 5, 6, 7, 8]) - talib.set_unstable_period('EMA', 5) - r = func.EMA(a, 3) - assert_array_equal(r, [np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, 6, 7, 8]) - talib.set_unstable_period('EMA', 0) - - -def test_compatibility(): - a = np.arange(10, dtype=float) - talib.set_compatibility(0) - r = func.EMA(a, 3) - assert_array_equal(r, [np.nan, np.nan, 1, 2, 3, 4, 5, 6, 7, 8]) - talib.set_compatibility(1) - r = func.EMA(a, 3) - assert_array_equal(r, [np.nan, np.nan,1.25,2.125,3.0625,4.03125,5.015625,6.0078125,7.00390625,8.001953125]) - talib.set_compatibility(0) - - -def test_MIN(series): - result = func.MIN(series, timeperiod=4) - i = np.where(~np.isnan(result))[0][0] - assert len(series) == len(result) - assert result[i + 1] == 93.780 - assert result[i + 2] == 93.780 - assert result[i + 3] == 92.530 - assert result[i + 4] == 92.530 - values = np.array([np.nan, 5., 4., 3., 5., 7.]) - result = func.MIN(values, timeperiod=2) - assert_array_equal(result, [np.nan, np.nan, 4, 3, 3, 5]) - - -def test_MAX(series): - result = func.MAX(series, timeperiod=4) - i = np.where(~np.isnan(result))[0][0] - assert len(series) == len(result) - assert result[i + 2] == 95.090 - assert result[i + 3] == 95.090 - assert result[i + 4] == 94.620 - assert result[i + 5] == 94.620 - - -def test_MOM(): - values = np.array([90.0,88.0,89.0]) - result = func.MOM(values, timeperiod=1) - assert_array_equal(result, [np.nan, -2, 1]) - result = func.MOM(values, timeperiod=2) - assert_array_equal(result, [np.nan, np.nan, -1]) - result = func.MOM(values, timeperiod=3) - assert_array_equal(result, [np.nan, np.nan, np.nan]) - result = func.MOM(values, timeperiod=4) - assert_array_equal(result, [np.nan, np.nan, np.nan]) - - -def test_BBANDS(series): - upper, middle, lower = func.BBANDS( - series, - timeperiod=20, - nbdevup=2.0, - nbdevdn=2.0, - matype=talib.MA_Type.EMA - ) - i = np.where(~np.isnan(upper))[0][0] - assert len(upper) == len(middle) == len(lower) == len(series) - # assert abs(upper[i + 0] - 98.0734) < 1e-3 - assert abs(middle[i + 0] - 92.8910) < 1e-3 - assert abs(lower[i + 0] - 87.7086) < 1e-3 - # assert abs(upper[i + 13] - 93.674) < 1e-3 - assert abs(middle[i + 13] - 87.679) < 1e-3 - assert abs(lower[i + 13] - 81.685) < 1e-3 - - -def test_DEMA(series): - result = func.DEMA(series) - i = np.where(~np.isnan(result))[0][0] - assert len(series) == len(result) - assert abs(result[i + 1] - 86.765) < 1e-3 - assert abs(result[i + 2] - 86.942) < 1e-3 - assert abs(result[i + 3] - 87.089) < 1e-3 - assert abs(result[i + 4] - 87.656) < 1e-3 - - -def test_EMAEMA(series): - result = func.EMA(series, timeperiod=2) - result = func.EMA(result, timeperiod=2) - i = np.where(~np.isnan(result))[0][0] - assert len(series) == len(result) - assert i == 2 - - -def test_CDL3BLACKCROWS(): - o = np.array([39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 40.32, 40.51, 38.09, 35.00, 27.66, 30.80]) - h = np.array([40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 41.69, 40.84, 38.12, 35.50, 31.74, 32.51]) - l = np.array([35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 39.26, 36.73, 33.37, 30.03, 27.03, 28.31]) - c = np.array([40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.46, 37.08, 33.37, 30.03, 31.46, 28.31]) - - result = func.CDL3BLACKCROWS(o, h, l, c) - assert_array_equal(result, [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -100, 0, 0]) - - -def test_RSI(): - a = np.array([0.00000024, 0.00000024, 0.00000024, - 0.00000024, 0.00000024, 0.00000023, - 0.00000024, 0.00000024, 0.00000024, - 0.00000024, 0.00000023, 0.00000024, - 0.00000023, 0.00000024, 0.00000023, - 0.00000024, 0.00000024, 0.00000023, - 0.00000023, 0.00000023], dtype='float64') - result = func.RSI(a, 10) - assert_array_almost_equal(result, [np.nan,np.nan,np.nan,np.nan,np.nan,np.nan,np.nan,np.nan,np.nan,np.nan,33.333333333333329,51.351351351351347,39.491916859122398,51.84807024709005,42.25953803191981,52.101824405061215,52.101824405061215,43.043664867691085,43.043664867691085,43.043664867691085]) - result = func.RSI(a * 100000, 10) - assert_array_almost_equal(result, [np.nan,np.nan,np.nan,np.nan,np.nan,np.nan,np.nan,np.nan,np.nan,np.nan,33.333333333333329,51.351351351351347,39.491916859122398,51.84807024709005,42.25953803191981,52.101824405061215,52.101824405061215,43.043664867691085,43.043664867691085,43.043664867691085]) - - -def test_MAVP(): - a = np.array([1,5,3,4,7,3,8,1,4,6], dtype=float) - b = np.array([2,4,2,4,2,4,2,4,2,4], dtype=float) - result = func.MAVP(a, b, minperiod=2, maxperiod=4) - assert_array_equal(result, [np.nan,np.nan,np.nan,3.25,5.5,4.25,5.5,4.75,2.5,4.75]) - sma2 = func.SMA(a, 2) - assert_array_equal(result[4::2], sma2[4::2]) - sma4 = func.SMA(a, 4) - assert_array_equal(result[3::2], sma4[3::2]) - result = func.MAVP(a, b, minperiod=2, maxperiod=3) - assert_array_equal(result, [np.nan,np.nan,4,4,5.5,4.666666666666667,5.5,4,2.5,3.6666666666666665]) - sma3 = func.SMA(a, 3) - assert_array_equal(result[2::2], sma2[2::2]) - assert_array_equal(result[3::2], sma3[3::2]) - - -def test_MAXINDEX(): - import talib as func - import numpy as np - a = np.array([1., 2, 3, 4, 5, 6, 7, 8, 7, 7, 3, 4, 5, 6, 7, 8, 9, 2, 3, 4, 5, 15]) - b = func.MA(a, 10) - c = func.MAXINDEX(b, 10) - assert_array_equal(c, [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,16,16,16,21]) - d = np.array([1., 2, 3]) - e = func.MAXINDEX(d, 10) - assert_array_equal(e, [0,0,0]) diff --git a/tests/test_pandas.py b/tests/test_pandas.py deleted file mode 100644 index 78f1a1236..000000000 --- a/tests/test_pandas.py +++ /dev/null @@ -1,51 +0,0 @@ -import numpy as np -from numpy.testing import assert_array_equal -import pandas as pd - -import talib - - -def test_MOM(): - values = pd.Series([90.0,88.0,89.0], index=[10, 20, 30]) - result = talib.MOM(values, timeperiod=1) - assert isinstance(result, pd.Series) - assert_array_equal(result.values, [np.nan, -2, 1]) - assert_array_equal(result.index, [10, 20, 30]) - result = talib.MOM(values, timeperiod=2) - assert isinstance(result, pd.Series) - assert_array_equal(result.values, [np.nan, np.nan, -1]) - assert_array_equal(result.index, [10, 20, 30]) - result = talib.MOM(values, timeperiod=3) - assert isinstance(result, pd.Series) - assert_array_equal(result.values, [np.nan, np.nan, np.nan]) - assert_array_equal(result.index, [10, 20, 30]) - result = talib.MOM(values, timeperiod=4) - assert isinstance(result, pd.Series) - assert_array_equal(result.values, [np.nan, np.nan, np.nan]) - assert_array_equal(result.index, [10, 20, 30]) - - -def test_MAVP(): - a = pd.Series([1,5,3,4,7,3,8,1,4,6], index=range(10, 20), dtype=float) - b = pd.Series([2,4,2,4,2,4,2,4,2,4], index=range(20, 30), dtype=float) - result = talib.MAVP(a, b, minperiod=2, maxperiod=4) - assert isinstance(result, pd.Series) - assert_array_equal(result.values, [np.nan,np.nan,np.nan,3.25,5.5,4.25,5.5,4.75,2.5,4.75]) - assert_array_equal(result.index, range(10, 20)) - sma2 = talib.SMA(a, 2) - assert isinstance(sma2, pd.Series) - assert_array_equal(sma2.index, range(10, 20)) - assert_array_equal(result.values[4::2], sma2.values[4::2]) - sma4 = talib.SMA(a, 4) - assert isinstance(sma4, pd.Series) - assert_array_equal(sma4.index, range(10, 20)) - assert_array_equal(result.values[3::2], sma4.values[3::2]) - result = talib.MAVP(a, b, minperiod=2, maxperiod=3) - assert isinstance(result, pd.Series) - assert_array_equal(result.values, [np.nan,np.nan,4,4,5.5,4.666666666666667,5.5,4,2.5,3.6666666666666665]) - assert_array_equal(result.index, range(10, 20)) - sma3 = talib.SMA(a, 3) - assert isinstance(sma3, pd.Series) - assert_array_equal(sma3.index, range(10, 20)) - assert_array_equal(result.values[2::2], sma2.values[2::2]) - assert_array_equal(result.values[3::2], sma3.values[3::2]) diff --git a/tests/test_polars.py b/tests/test_polars.py deleted file mode 100644 index f83e594d9..000000000 --- a/tests/test_polars.py +++ /dev/null @@ -1,88 +0,0 @@ -import numpy as np -from numpy.testing import assert_array_equal -import polars as pl - -import talib -from talib import abstract - -def test_MOM(): - values = pl.Series([90.0,88.0,89.0]) - result = talib.MOM(values, timeperiod=1) - assert isinstance(result, pl.Series) - assert_array_equal(result.to_numpy(), [np.nan, -2, 1]) - result = talib.MOM(values, timeperiod=2) - assert isinstance(result, pl.Series) - assert_array_equal(result.to_numpy(), [np.nan, np.nan, -1]) - result = talib.MOM(values, timeperiod=3) - assert isinstance(result, pl.Series) - assert_array_equal(result.to_numpy(), [np.nan, np.nan, np.nan]) - result = talib.MOM(values, timeperiod=4) - assert isinstance(result, pl.Series) - assert_array_equal(result.to_numpy(), [np.nan, np.nan, np.nan]) - - -def test_MAVP(): - a = pl.Series([1,5,3,4,7,3,8,1,4,6], dtype=pl.Float64) - b = pl.Series([2,4,2,4,2,4,2,4,2,4], dtype=pl.Float64) - result = talib.MAVP(a, b, minperiod=2, maxperiod=4) - assert isinstance(result, pl.Series) - assert_array_equal(result.to_numpy(), [np.nan,np.nan,np.nan,3.25,5.5,4.25,5.5,4.75,2.5,4.75]) - sma2 = talib.SMA(a, 2) - assert isinstance(sma2, pl.Series) - assert_array_equal(result.to_numpy()[4::2], sma2.to_numpy()[4::2]) - sma4 = talib.SMA(a, 4) - assert isinstance(sma4, pl.Series) - assert_array_equal(result.to_numpy()[3::2], sma4.to_numpy()[3::2]) - result = talib.MAVP(a, b, minperiod=2, maxperiod=3) - assert isinstance(result, pl.Series) - assert_array_equal(result.to_numpy(), [np.nan,np.nan,4,4,5.5,4.666666666666667,5.5,4,2.5,3.6666666666666665]) - sma3 = talib.SMA(a, 3) - assert isinstance(sma3, pl.Series) - assert_array_equal(result.to_numpy()[2::2], sma2.to_numpy()[2::2]) - assert_array_equal(result.to_numpy()[3::2], sma3.to_numpy()[3::2]) - - -def test_TEVA(): - size = 50 - df = pl.DataFrame( - { - "open": np.random.uniform(low=0.0, high=100.0, size=size).astype("float32"), - "high": np.random.uniform(low=0.0, high=100.0, size=size).astype("float32"), - "low": np.random.uniform(low=0.0, high=100.0, size=size).astype("float32"), - "close": np.random.uniform(low=0.0, high=100.0, size=size).astype("float32"), - "volume": np.random.uniform(low=0.0, high=100.0, size=size).astype("float32") - } - ) - tema1 = abstract.TEMA(df, timeperiod=9) - assert isinstance(tema1, pl.Series) - assert len(tema1) == 50 - inputs = abstract.TEMA.get_input_arrays() - assert inputs.columns == df.columns - for column in df.columns: - assert_array_equal(inputs[column].to_numpy(), df[column].to_numpy()) - - tema2 = abstract.TEMA(df, timeperiod=9) - assert isinstance(tema2, pl.Series) - assert len(tema2) == 50 - inputs = abstract.TEMA.get_input_arrays() - assert inputs.columns == df.columns - for column in df.columns: - assert_array_equal(inputs[column].to_numpy(), df[column].to_numpy()) - - assert_array_equal(tema1.to_numpy(), tema2.to_numpy()) - -def test_AVR(): - size = 50 - df = pl.DataFrame( - { - "open": np.random.uniform(low=0.0, high=100.0, size=size).astype("float32"), - "high": np.random.uniform(low=0.0, high=100.0, size=size).astype("float32"), - "low": np.random.uniform(low=0.0, high=100.0, size=size).astype("float32"), - "close": np.random.uniform(low=0.0, high=100.0, size=size).astype("float32"), - "volume": np.random.uniform(low=0.0, high=100.0, size=size).astype("float32") - } - ) - high = df['high'] - low = df['low'] - close = df['close'] - atr = talib.ATR(high, low, close, timeperiod=14) diff --git a/tests/test_stream.py b/tests/test_stream.py deleted file mode 100644 index afb99edcf..000000000 --- a/tests/test_stream.py +++ /dev/null @@ -1,66 +0,0 @@ -import numpy as np -import pandas as pd - -from talib import stream - - -def test_streaming(): - a = np.array([1,1,2,3,5,8,13], dtype=float) - r = stream.MOM(a, timeperiod=1) - assert r == 5 - r = stream.MOM(a, timeperiod=2) - assert r == 8 - r = stream.MOM(a, timeperiod=3) - assert r == 10 - r = stream.MOM(a, timeperiod=4) - assert r == 11 - r = stream.MOM(a, timeperiod=5) - assert r == 12 - r = stream.MOM(a, timeperiod=6) - assert r == 12 - r = stream.MOM(a, timeperiod=7) - assert np.isnan(r) - - -def test_streaming_pandas(): - a = pd.Series([1,1,2,3,5,8,13]) - r = stream.MOM(a, timeperiod=1) - assert r == 5 - r = stream.MOM(a, timeperiod=2) - assert r == 8 - r = stream.MOM(a, timeperiod=3) - assert r == 10 - r = stream.MOM(a, timeperiod=4) - assert r == 11 - r = stream.MOM(a, timeperiod=5) - assert r == 12 - r = stream.MOM(a, timeperiod=6) - assert r == 12 - r = stream.MOM(a, timeperiod=7) - assert np.isnan(r) - - -def test_CDL3BLACKCROWS(): - o = np.array([39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 40.32, 40.51, 38.09, 35.00]) - h = np.array([40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 41.69, 40.84, 38.12, 35.50]) - l = np.array([35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 39.26, 36.73, 33.37, 30.03]) - c = np.array([40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.46, 37.08, 33.37, 30.03]) - - r = stream.CDL3BLACKCROWS(o, h, l, c) - assert r == -100 - - -def test_CDL3BLACKCROWS_pandas(): - o = pd.Series([39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 39.00, 40.32, 40.51, 38.09, 35.00]) - h = pd.Series([40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 40.84, 41.69, 40.84, 38.12, 35.50]) - l = pd.Series([35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 35.80, 39.26, 36.73, 33.37, 30.03]) - c = pd.Series([40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.29, 40.46, 37.08, 33.37, 30.03]) - - r = stream.CDL3BLACKCROWS(o, h, l, c) - assert r == -100 - - -def test_MAXINDEX(): - a = np.array([1., 2, 3, 4, 5, 6, 7, 8, 7, 7, 3, 4, 5, 6, 7, 8, 9, 2, 3, 4, 5, 15]) - r = stream.MAXINDEX(a, 10) - assert r == 21 diff --git a/tools/build_talib_linux.sh b/tools/build_talib_linux.sh deleted file mode 100644 index cc57df507..000000000 --- a/tools/build_talib_linux.sh +++ /dev/null @@ -1,53 +0,0 @@ -#!/bin/bash - -TALIB_C_VER="${TALIB_C_VER:=0.6.4}" -CMAKE_GENERATOR="Unix Makefiles" -CMAKE_BUILD_TYPE=Release -CMAKE_CONFIGURATION_TYPES=Release - -# Download TA-Lib C Library -curl -L -o talib-${TALIB_C_VER}.zip https://github.com/TA-Lib/ta-lib/archive/refs/tags/v${TALIB_C_VER}.zip -if [ $? -ne 0 ]; then - echo "Failed to download TA-Lib C library" - exit 1 -fi - -# Unzip TA-Lib C -unzip -q talib-${TALIB_C_VER}.zip -if [ $? -ne 0 ]; then - echo "Failed to extract TA-Lib C library" - exit 1 -fi - -# cd to TA-Lib C -cd ta-lib-${TALIB_C_VER} - -# Copy TA-Lib C headers to TA-Lib Python -mkdir -p include/ta-lib/ -cp include/*.h include/ta-lib/ - -# Create build directory -mkdir -p _build -cd _build - -# Use CMake to configure the build -cmake -G "$CMAKE_GENERATOR" -DCMAKE_BUILD_TYPE=$CMAKE_BUILD_TYPE -DCMAKE_INSTALL_PREFIX=../../ta-lib-install .. -if [ $? -ne 0 ]; then - echo "CMake configuration failed" - exit 1 -fi - -# Compile TA-Lib -make -if [ $? -ne 0 ]; then - echo "Build failed" - exit 1 -fi - -make install -if [ $? -ne 0 ]; then - echo "Install failed" - exit 1 -fi - -echo "TA-Lib build completed successfully!" diff --git a/tools/build_talib_macos.sh b/tools/build_talib_macos.sh deleted file mode 100644 index cc57df507..000000000 --- a/tools/build_talib_macos.sh +++ /dev/null @@ -1,53 +0,0 @@ -#!/bin/bash - -TALIB_C_VER="${TALIB_C_VER:=0.6.4}" -CMAKE_GENERATOR="Unix Makefiles" -CMAKE_BUILD_TYPE=Release -CMAKE_CONFIGURATION_TYPES=Release - -# Download TA-Lib C Library -curl -L -o talib-${TALIB_C_VER}.zip https://github.com/TA-Lib/ta-lib/archive/refs/tags/v${TALIB_C_VER}.zip -if [ $? -ne 0 ]; then - echo "Failed to download TA-Lib C library" - exit 1 -fi - -# Unzip TA-Lib C -unzip -q talib-${TALIB_C_VER}.zip -if [ $? -ne 0 ]; then - echo "Failed to extract TA-Lib C library" - exit 1 -fi - -# cd to TA-Lib C -cd ta-lib-${TALIB_C_VER} - -# Copy TA-Lib C headers to TA-Lib Python -mkdir -p include/ta-lib/ -cp include/*.h include/ta-lib/ - -# Create build directory -mkdir -p _build -cd _build - -# Use CMake to configure the build -cmake -G "$CMAKE_GENERATOR" -DCMAKE_BUILD_TYPE=$CMAKE_BUILD_TYPE -DCMAKE_INSTALL_PREFIX=../../ta-lib-install .. -if [ $? -ne 0 ]; then - echo "CMake configuration failed" - exit 1 -fi - -# Compile TA-Lib -make -if [ $? -ne 0 ]; then - echo "Build failed" - exit 1 -fi - -make install -if [ $? -ne 0 ]; then - echo "Install failed" - exit 1 -fi - -echo "TA-Lib build completed successfully!" diff --git a/tools/build_talib_windows.cmd b/tools/build_talib_windows.cmd deleted file mode 100644 index ad994d948..000000000 --- a/tools/build_talib_windows.cmd +++ /dev/null @@ -1,38 +0,0 @@ -:: Download and build TA-Lib -@echo on - -if not defined TALIB_C_VER set TALIB_C_VER=0.6.4 - -set CMAKE_GENERATOR=NMake Makefiles -set CMAKE_BUILD_TYPE=Release -set CMAKE_CONFIGURATION_TYPES=Release - -curl -L -o talib-%TALIB_C_VER%.zip https://github.com/TA-Lib/ta-lib/archive/refs/tags/v%TALIB_C_VER%.zip -if errorlevel 1 exit /B 1 - -tar -xzvf talib-%TALIB_C_VER%.zip -if errorlevel 1 exit /B 1 - -:: git apply --verbose --binary talib.diff -:: if errorlevel 1 exit /B 1 - -:: set MSBUILDTREATHIGHERTOOLSVERSIONASCURRENT - -setlocal -cd ta-lib-%TALIB_C_VER% - -mkdir include\ta-lib -copy /Y include\*.* include\ta-lib - -md _build -cd _build - -cmake.exe .. -if errorlevel 1 exit /B 1 - -nmake.exe /nologo all -if errorlevel 1 exit /B 1 - -copy /Y /B ta-lib-static.lib ta-lib.lib - -endlocal diff --git a/tools/example.py b/tools/example.py deleted file mode 100644 index 87c35b522..000000000 --- a/tools/example.py +++ /dev/null @@ -1,60 +0,0 @@ -from __future__ import print_function - -import sys -import numpy as np -import pylab - -import talib -from talib.abstract import Function - -TEST_LEN = int(sys.argv[1]) if len(sys.argv) > 1 else 100 -r = np.arange(TEST_LEN) -idata = np.random.random(TEST_LEN) - -def func_example(): - odata = talib.MA(idata) - upper, middle, lower = talib.BBANDS(idata) - kama = talib.KAMA(idata) - plot(odata, upper, middle, lower, kama) - -def abstract_example(): - sma = Function('sma') - input_arrays = sma.get_input_arrays() - for key in input_arrays.keys(): - input_arrays[key] = idata - sma.set_input_arrays(input_arrays) - odata = sma(30) # timePeriod=30, specified as an arg - - bbands = Function('bbands', input_arrays) - bbands.parameters = { - 'timeperiod': 20, - 'nbdevup': 2, - 'nbdevdn': 2 - } - upper, middle, lower = bbands() # multiple output values unpacked (these will always have the correct order) - - kama = Function('kama').run(input_arrays) # alternative run() calling method. - plot(odata, upper, middle, lower, kama) - -def plot(odata, upper, middle, lower, kama): - pylab.plot(r, idata, 'b-', label="original") - pylab.plot(r, odata, 'g-', label="MA") - pylab.plot(r, upper, 'r-', label="Upper") - pylab.plot(r, middle, 'r-', label="Middle") - pylab.plot(r, lower, 'r-', label="Lower") - pylab.plot(r, kama, 'g', label="KAMA") - pylab.legend() - pylab.show() - -if __name__ == '__main__': - print('All functions (sorted by group):') - groups = talib.get_function_groups() - for group, functions in sorted(groups.items()): - print('%s functions: %s' % (group, functions)) - - if len(sys.argv) == 1 or sys.argv[1] == 'func': - print('Using talib.func') - func_example() - else: - print('Using talib.abstract') - abstract_example() diff --git a/tools/generate_func.py b/tools/generate_func.py deleted file mode 100644 index 185909083..000000000 --- a/tools/generate_func.py +++ /dev/null @@ -1,438 +0,0 @@ -from __future__ import print_function - -import os -import re -import sys - -from talib import abstract - -# FIXME: initialize once, then shutdown at the end, rather than each call? -# FIXME: should we pass startIdx and endIdx into function? -# FIXME: don't return number of elements since it always equals allocation? - -functions = [] -if sys.platform == 'win32': - include_dirs = [ - r"c:\ta-lib\c\include", - r"c:\Program Files\TA-Lib\include", - r"c:\Program Files (x86)\TA-Lib\include", - ] -else: - include_dirs = [ - '/usr/include', - '/usr/local/include', - '/opt/include', - '/opt/local/include', - '/opt/homebrew/include', - '/opt/homebrew/opt/ta-lib/include', - ] - -if 'TA_INCLUDE_PATH' in os.environ: - include_dirs = os.environ['TA_INCLUDE_PATH'].split(os.pathsep) - -header_found = False -for path in include_dirs: - ta_func_header = os.path.join(path, 'ta-lib', 'ta_func.h') - if os.path.exists(ta_func_header): - header_found = True - break -if not header_found: - print('Error: ta-lib/ta_func.h not found', file=sys.stderr) - sys.exit(1) -with open(ta_func_header) as f: - tmp = [] - for line in f: - if line.startswith('TA_LIB_API'): - line = line[10:] - line = line.strip() - if tmp or \ - line.startswith('TA_RetCode TA_') or \ - line.startswith('int TA_'): - line = re.sub(r'/\*[^\*]+\*/', '', line) # strip comments - tmp.append(line) - if not line: - s = ' '.join(tmp) - s = re.sub(r'\s+', ' ', s) - functions.append(s) - tmp = [] - -# strip "float" functions -functions = [s for s in functions if not s.startswith('TA_RetCode TA_S_')] - -# strip non-indicators -functions = [s for s in functions if not s.startswith('TA_RetCode TA_Set')] -functions = [s for s in functions if not s.startswith('TA_RetCode TA_Restore')] - -# print headers -print("""\ -cimport numpy as np -from numpy import nan -from cython import boundscheck, wraparound - -# _ta_check_success: defined in _common.pxi - -cdef double NaN = nan - -cdef extern from "numpy/arrayobject.h": - int PyArray_TYPE(np.ndarray) - np.ndarray PyArray_EMPTY(int, np.npy_intp*, int, int) - int PyArray_FLAGS(np.ndarray) - np.ndarray PyArray_GETCONTIGUOUS(np.ndarray) - -np.import_array() # Initialize the NumPy C API - -cimport _ta_lib as lib -from _ta_lib cimport TA_RetCode - -cdef np.ndarray check_array(np.ndarray real): - if PyArray_TYPE(real) != np.NPY_DOUBLE: - raise Exception("input array type is not double") - if real.ndim != 1: - raise Exception("input array has wrong dimensions") - if not (PyArray_FLAGS(real) & np.NPY_ARRAY_C_CONTIGUOUS): - real = PyArray_GETCONTIGUOUS(real) - return real - -cdef np.npy_intp check_length2(np.ndarray a1, np.ndarray a2) except -1: - cdef: - np.npy_intp length - length = a1.shape[0] - if length != a2.shape[0]: - raise Exception("input array lengths are different") - return length - -cdef np.npy_intp check_length3(np.ndarray a1, np.ndarray a2, np.ndarray a3) except -1: - cdef: - np.npy_intp length - length = a1.shape[0] - if length != a2.shape[0]: - raise Exception("input array lengths are different") - if length != a3.shape[0]: - raise Exception("input array lengths are different") - return length - -cdef np.npy_intp check_length4(np.ndarray a1, np.ndarray a2, np.ndarray a3, np.ndarray a4) except -1: - cdef: - np.npy_intp length - length = a1.shape[0] - if length != a2.shape[0]: - raise Exception("input array lengths are different") - if length != a3.shape[0]: - raise Exception("input array lengths are different") - if length != a4.shape[0]: - raise Exception("input array lengths are different") - return length - -cdef np.npy_int check_begidx1(np.npy_intp length, double* a1): - cdef: - double val - for i from 0 <= i < length: - val = a1[i] - if val != val: - continue - return i - else: - return length - 1 - -cdef np.npy_int check_begidx2(np.npy_intp length, double* a1, double* a2): - cdef: - double val - for i from 0 <= i < length: - val = a1[i] - if val != val: - continue - val = a2[i] - if val != val: - continue - return i - else: - return length - 1 - -cdef np.npy_int check_begidx3(np.npy_intp length, double* a1, double* a2, double* a3): - cdef: - double val - for i from 0 <= i < length: - val = a1[i] - if val != val: - continue - val = a2[i] - if val != val: - continue - val = a3[i] - if val != val: - continue - return i - else: - return length - 1 - -cdef np.npy_int check_begidx4(np.npy_intp length, double* a1, double* a2, double* a3, double* a4): - cdef: - double val - for i from 0 <= i < length: - val = a1[i] - if val != val: - continue - val = a2[i] - if val != val: - continue - val = a3[i] - if val != val: - continue - val = a4[i] - if val != val: - continue - return i - else: - return length - 1 - -cdef np.ndarray make_double_array(np.npy_intp length, int lookback): - cdef: - np.ndarray outreal - double* outreal_data - outreal = PyArray_EMPTY(1, &length, np.NPY_DOUBLE, np.NPY_ARRAY_DEFAULT) - outreal_data = outreal.data - for i from 0 <= i < min(lookback, length): - outreal_data[i] = NaN - return outreal - -cdef np.ndarray make_int_array(np.npy_intp length, int lookback): - cdef: - np.ndarray outinteger - int* outinteger_data - outinteger = PyArray_EMPTY(1, &length, np.NPY_INT32, np.NPY_ARRAY_DEFAULT) - outinteger_data = outinteger.data - for i from 0 <= i < min(lookback, length): - outinteger_data[i] = 0 - return outinteger - -""") - -# cleanup variable names to make them more pythonic -def cleanup(name): - if name.startswith('in'): - return name[2:].lower() - elif name.startswith('optIn'): - return name[5:].lower() - else: - return name.lower() - -# print functions -names = [] -for f in functions: - if 'Lookback' in f: # skip lookback functions - continue - - i = f.index('(') - name = f[:i].split()[1] - args = f[i:].split(',') - args = [re.sub(r'[\(\);]', '', s).strip() for s in args] - - shortname = name[3:] - names.append(shortname) - try: - func_info = abstract.Function(shortname).info - defaults, documentation = abstract._get_defaults_and_docs(func_info) - except: - print("cannot find defaults and docs for", shortname, file=sys.stderr) - defaults, documentation = {}, "" - - print('@wraparound(False) # turn off relative indexing from end of lists') - print('@boundscheck(False) # turn off bounds-checking for entire function') - print('def %s(' % shortname, end=' ') - docs = [' %s(' % shortname] - i = 0 - for arg in args: - var = arg.split()[-1] - - if var in ('startIdx', 'endIdx'): - continue - - elif 'out' in var: - break - - if i > 0: - print(',', end=' ') - i += 1 - - if var.endswith('[]'): - var = cleanup(var[:-2]) - assert arg.startswith('const double'), arg - print('np.ndarray %s not None' % var, end=' ') - docs.append(var) - docs.append(', ') - - elif var.startswith('opt'): - var = cleanup(var) - default_arg = arg.split()[-1][len('optIn'):] # chop off typedef and 'optIn' - default_arg = default_arg[0].lower() + default_arg[1:] # lowercase first letter - - if arg.startswith('double'): - if default_arg in defaults: - print('double %s=%s' % (var, defaults[default_arg]), end=' ') - else: - print('double %s=-4e37' % var, end=' ') # TA_REAL_DEFAULT - elif arg.startswith('int'): - if default_arg in defaults: - print('int %s=%s' % (var, defaults[default_arg]), end=' ') - else: - print('int %s=-2**31' % var, end=' ') # TA_INTEGER_DEFAULT - elif arg.startswith('TA_MAType'): - print('int %s=%s' % (var, defaults.get('matype', 0)), end=' ') # TA_MAType_SMA - else: - assert False, arg - if '[, ' not in docs: - docs[-1] = ('[, ') - docs.append('%s=?' % var) - docs.append(', ') - - docs[-1] = '])' if '[, ' in docs else ')' - if documentation: - tmp_docs = [] - lower_case = False - documentation = documentation.split('\n')[2:] # discard abstract calling definition - for line in documentation: - line = line.replace('Substraction', 'Subtraction') - if 'prices' not in line and 'price' in line: - line = line.replace('price', 'real') - if not line or line.isspace(): - tmp_docs.append('') - else: - tmp_docs.append(' %s' % line) # add an indent of 4 spaces - docs.append('\n\n') - docs.append('\n'.join(tmp_docs)) - docs.append('\n ') - print('):') - print(' """%s"""' % ''.join(docs)) - print(' cdef:') - print(' np.npy_intp length') - print(' int begidx, endidx, lookback') - print(' TA_RetCode retCode') - - for arg in args: - var = arg.split()[-1] - if 'out' not in var: - continue - if var.endswith('[]'): - var = cleanup(var[:-2]) - print(' np.ndarray %s' % var) - elif var.startswith('*'): - var = cleanup(var[1:]) - print(' int %s' % var) - else: - assert False, arg - - for arg in args: - var = arg.split()[-1] - if 'out' in var: - break - if var.endswith('[]'): - var = cleanup(var[:-2]) - if 'double' in arg: - cast = '' - else: - assert False, arg - print(' %s = check_array(%s)' % (var, var)) - - # check all input array lengths are the same - inputs = [] - for arg in args: - var = arg.split()[-1] - if 'out' in var: - break - if var.endswith('[]'): - var = cleanup(var[:-2]) - inputs.append(var) - if len(inputs) == 1: - print(' length = %s.shape[0]' % inputs[0]) - else: - print(' length = check_length%s(%s)' % (len(inputs), ', '.join(inputs))) - - # check for all input values are non-NaN - print(' begidx = check_begidx%s(length, %s)' % (len(inputs), ', '.join('(%s.data)' % s for s in inputs))) - - print(' endidx = length - begidx - 1') - print(' lookback = begidx + lib.%s_Lookback(' % name, end=' ') - opts = [arg for arg in args if 'opt' in arg] - for i, opt in enumerate(opts): - if i > 0: - print(',', end=' ') - print(cleanup(opt.split()[-1]), end=' ') - print(')') - - for arg in args: - var = arg.split()[-1] - - if 'out' not in var: - continue - - if var.endswith('[]'): - var = cleanup(var[:-2]) - if 'double' in arg: - print(' %s = make_double_array(length, lookback)' % var) - elif 'int' in arg: - print(' %s = make_int_array(length, lookback)' % var) - else: - assert False, args - - print(' retCode = lib.%s(' % name, end=' ') - - for i, arg in enumerate(args): - if i > 0: - print(',', end=' ') - var = arg.split()[-1] - - if var.endswith('[]'): - var = cleanup(var[:-2]) - if 'out' in var: - data = '(%s.data)+lookback' % var - else: - data = '(%s.data)+begidx' % var - if 'double' in arg: - print('%s' % data, end=' ') - elif 'int' in arg: - print('%s' % data, end=' ') - else: - assert False, arg - - elif var.startswith('*'): - var = cleanup(var[1:]) - print('&%s' % var, end=' ') - - else: - cleaned = cleanup(var) if var != 'startIdx' else '0' - print(cleaned, end=' ') - - print(')') - print(' _ta_check_success("%s", retCode)' % name) - if 'INDEX' in f: - for arg in args: - var = arg.split()[-1] - - if 'out' not in var: - continue - - if var.endswith('[]'): - var = cleanup(var[:-2]) - print(' %s_data = %s.data' % (var, var)) - print(' for i from lookback <= i < length:') - print(' %s_data[i] += begidx' % var) - print(' return ', end='') - i = 0 - for arg in args: - var = arg.split()[-1] - if var.endswith('[]'): - var = var[:-2] - elif var.startswith('*'): - var = var[1:] - if var.startswith('out'): - if var not in ("outNBElement", "outBegIdx"): - if i > 0: - print(',', end=' ') - i += 1 - print(cleanup(var), end=' ') - else: - assert re.match('.*(void|startIdx|endIdx|opt|in)/*', arg), arg - print('') - print('') - -print('__TA_FUNCTION_NAMES__ = [%s]' % ','.join(['\"%s\"' % name for name in names])) diff --git a/tools/generate_stream.py b/tools/generate_stream.py deleted file mode 100644 index 7029c989d..000000000 --- a/tools/generate_stream.py +++ /dev/null @@ -1,295 +0,0 @@ -from __future__ import print_function - -import os -import re -import sys - -from talib import abstract - -# FIXME: initialize once, then shutdown at the end, rather than each call? -# FIXME: should we pass startIdx and endIdx into function? -# FIXME: don't return number of elements since it always equals allocation? - -functions = [] -if sys.platform == 'win32': - include_dirs = [ - r"c:\ta-lib\c\include", - r"c:\Program Files\TA-Lib\include", - r"c:\Program Files (x86)\TA-Lib\include", - ] -else: - include_dirs = [ - '/usr/include', - '/usr/local/include', - '/opt/include', - '/opt/local/include', - '/opt/homebrew/include', - '/opt/homebrew/opt/ta-lib/include', - ] - -if 'TA_INCLUDE_PATH' in os.environ: - include_dirs = os.environ['TA_INCLUDE_PATH'].split(os.pathsep) - -header_found = False -for path in include_dirs: - ta_func_header = os.path.join(path, 'ta-lib', 'ta_func.h') - if os.path.exists(ta_func_header): - header_found = True - break -if not header_found: - print('Error: ta-lib/ta_func.h not found', file=sys.stderr) - sys.exit(1) -with open(ta_func_header) as f: - tmp = [] - for line in f: - if line.startswith('TA_LIB_API'): - line = line[10:] - line = line.strip() - if tmp or \ - line.startswith('TA_RetCode TA_') or \ - line.startswith('int TA_'): - line = re.sub(r'/\*[^\*]+\*/', '', line) # strip comments - tmp.append(line) - if not line: - s = ' '.join(tmp) - s = re.sub(r'\s+', ' ', s) - functions.append(s) - tmp = [] - -# strip "float" functions -functions = [s for s in functions if not s.startswith('TA_RetCode TA_S_')] - -# strip non-indicators -functions = [s for s in functions if not s.startswith('TA_RetCode TA_Set')] -functions = [s for s in functions if not s.startswith('TA_RetCode TA_Restore')] - -# print headers -print("""\ -cimport numpy as np -from cython import boundscheck, wraparound -cimport _ta_lib as lib -from _ta_lib cimport TA_RetCode -# NOTE: _ta_check_success, NaN are defined in common.pxi - -np.import_array() # Initialize the NumPy C API -""") - -# cleanup variable names to make them more pythonic -def cleanup(name): - if name.startswith('in'): - return name[2:].lower() - elif name.startswith('optIn'): - return name[5:].lower() - else: - return name.lower() - -# print functions -names = [] -for f in functions: - if 'Lookback' in f: # skip lookback functions - continue - - i = f.index('(') - name = f[:i].split()[1] - args = f[i:].split(',') - args = [re.sub(r'[\(\);]', '', s).strip() for s in args] - - shortname = name[3:] - names.append(shortname) - try: - func_info = abstract.Function(shortname).info - defaults, documentation = abstract._get_defaults_and_docs(func_info) - except: - print("cannot find defaults and docs for", shortname, file=sys.stderr) - defaults, documentation = {}, "" - - print('@wraparound(False) # turn off relative indexing from end of lists') - print('@boundscheck(False) # turn off bounds-checking for entire function') - print('def stream_%s(' % shortname, end=' ') - docs = [' %s(' % shortname] - i = 0 - for arg in args: - var = arg.split()[-1] - - if var in ('startIdx', 'endIdx'): - continue - - elif 'out' in var: - break - - if i > 0: - print(',', end=' ') - i += 1 - - if var.endswith('[]'): - var = cleanup(var[:-2]) - assert arg.startswith('const double'), arg - print('np.ndarray %s not None' % var, end=' ') - docs.append(var) - docs.append(', ') - - elif var.startswith('opt'): - var = cleanup(var) - default_arg = arg.split()[-1][len('optIn'):] # chop off typedef and 'optIn' - default_arg = default_arg[0].lower() + default_arg[1:] # lowercase first letter - - if arg.startswith('double'): - if default_arg in defaults: - print('double %s=%s' % (var, defaults[default_arg]), end=' ') - else: - print('double %s=-4e37' % var, end=' ') # TA_REAL_DEFAULT - elif arg.startswith('int'): - if default_arg in defaults: - print('int %s=%s' % (var, defaults[default_arg]), end=' ') - else: - print('int %s=-2**31' % var, end=' ') # TA_INTEGER_DEFAULT - elif arg.startswith('TA_MAType'): - print('int %s=%s' % (var, defaults.get('matype', 0)), end=' ') # TA_MAType_SMA - else: - assert False, arg - if '[, ' not in docs: - docs[-1] = ('[, ') - docs.append('%s=?' % var) - docs.append(', ') - - docs[-1] = '])' if '[, ' in docs else ')' - if documentation: - tmp_docs = [] - lower_case = False - documentation = documentation.split('\n')[2:] # discard abstract calling definition - for line in documentation: - line = line.replace('Substraction', 'Subtraction') - if 'prices' not in line and 'price' in line: - line = line.replace('price', 'real') - if not line or line.isspace(): - tmp_docs.append('') - else: - tmp_docs.append(' %s' % line) # add an indent of 4 spaces - docs.append('\n\n') - docs.append('\n'.join(tmp_docs)) - docs.append('\n ') - print('):') - print(' """%s"""' % ''.join(docs)) - print(' cdef:') - print(' np.npy_intp length') - print(' TA_RetCode retCode') - for arg in args: - var = arg.split()[-1] - if 'out' in var: - break - if var.endswith('[]'): - var = cleanup(var[:-2]) - if 'double' in arg: - print(' double* %s_data' % var) - elif 'int' in arg: - print(' int* %s_data' % var) - else: - assert False, args - - for arg in args: - var = arg.split()[-1] - if 'out' not in var: - continue - if var.endswith('[]'): - var = cleanup(var[:-2]) - if 'double' in arg: - print(' double %s' % var) - elif 'int' in arg: - print(' int %s' % var) - else: - assert False, args - elif var.startswith('*'): - var = cleanup(var[1:]) - print(' int %s' % var) - else: - assert False, arg - - for arg in args: - var = arg.split()[-1] - if 'out' in var: - break - if var.endswith('[]'): - var = cleanup(var[:-2]) - if 'double' in arg: - cast = '' - else: - assert False, arg - print(' %s = check_array(%s)' % (var, var)) - print(' %s_data = %s%s.data' % (var, cast, var)) - - # check all input array lengths are the same - inputs = [] - for arg in args: - var = arg.split()[-1] - if 'out' in var: - break - if var.endswith('[]'): - var = cleanup(var[:-2]) - inputs.append(var) - - if len(inputs) == 1: - print(' length = %s.shape[0]' % inputs[0]) - else: - print(' length = check_length%s(%s)' % (len(inputs), ', '.join(inputs))) - - for arg in args: - var = arg.split()[-1] - - if 'out' not in var: - continue - - if var.endswith('[]'): - var = cleanup(var[:-2]) - if 'double' in arg: - print(' %s = NaN' % var) - elif 'int' in arg: - print(' %s = 0' % var) - else: - assert False, args - - print(' retCode = lib.%s(' % name, end=' ') - - for i, arg in enumerate(args): - if i > 0: - print(',', end=' ') - var = arg.split()[-1] - - if var.endswith('[]'): - var = cleanup(var[:-2]) - if 'out' in var: - print('&%s' % var, end=' ') - else: - print('%s_data' % var, end=' ') - - elif var.startswith('*'): - var = cleanup(var[1:]) - print('&%s' % var, end=' ') - - elif var in ('startIdx', 'endIdx'): - print('(length) - 1', end= ' ') - - else: - cleaned = cleanup(var) - print(cleaned, end=' ') - - print(')') - print(' _ta_check_success("%s", retCode)' % name) - print(' return ', end='') - i = 0 - for arg in args: - var = arg.split()[-1] - if var.endswith('[]'): - var = var[:-2] - elif var.startswith('*'): - var = var[1:] - if var.startswith('out'): - if var not in ("outNBElement", "outBegIdx"): - if i > 0: - print(',', end=' ') - i += 1 - print(cleanup(var), end=' ') - else: - assert re.match('.*(void|startIdx|endIdx|opt|in)/*', arg), arg - print('') - print('') - diff --git a/tools/perf_talib.py b/tools/perf_talib.py deleted file mode 100644 index 6bc1910d6..000000000 --- a/tools/perf_talib.py +++ /dev/null @@ -1,25 +0,0 @@ -from __future__ import print_function - -import numpy -import talib -import time -import sys - -TEST_LEN = int(sys.argv[1]) if len(sys.argv) > 1 else 10000 -LOOPS = int(sys.argv[2]) if len(sys.argv) > 2 else 1000 - -data = numpy.random.random(TEST_LEN) - -if False: # fill array with nans - data[:-1] = numpy.nan - -t0 = time.time() -for _ in range(LOOPS): - talib.MA(data) - talib.BBANDS(data) - talib.KAMA(data) - talib.CDLMORNINGDOJISTAR(data, data, data, data) -t1 = time.time() -print('test_len: %d, loops: %d' % (TEST_LEN, LOOPS)) -print('%.6f' % (t1 - t0)) -print('%.6f' % ((t1 - t0) / LOOPS)) diff --git a/tools/threads_talib.py b/tools/threads_talib.py deleted file mode 100644 index 12e922b17..000000000 --- a/tools/threads_talib.py +++ /dev/null @@ -1,54 +0,0 @@ -from __future__ import print_function -import time -import threading - -import numpy -import copy -from talib.abstract import RSI -import sys -import pandas as pd - -TEST_LEN_SHORT = int(sys.argv[1]) if len(sys.argv) > 1 else 999 -TEST_LEN_LONG = int(sys.argv[1]) if len(sys.argv) > 1 else 4005 -LOOPS = int(sys.argv[2]) if len(sys.argv) > 2 else 1000 - -data_short = numpy.random.rand(TEST_LEN_SHORT, 5) -data_long = numpy.random.rand(TEST_LEN_LONG, 5) - -df_short = pd.DataFrame(data_short, columns={ - 'open', 'high', 'low', 'close', 'volume'}) -df_long = pd.DataFrame(data_long, columns={ - 'open', 'high', 'low', 'close', 'volume'}) - -total = 0 - - -def loop(): - global total - if threading.get_native_id() % 2 == 0: - df = copy.deepcopy(df_short) - else: - df = copy.deepcopy(df_long) - - while total < LOOPS: - total += 1 - try: - df['RSI'] = RSI(df) - except ValueError as msg: - raise ValueError(msg) - - -t0 = time.time() - -threads = [] -for i in range(4): - t = threading.Thread(target=loop) - threads.append(t) - t.start() - -for t in threads: - t.join() -t1 = time.time() -print('test_len: %d, loops: %d' % (TEST_LEN_LONG, LOOPS)) -print('%.6f' % (t1 - t0)) -print('%.6f' % ((t1 - t0) / LOOPS))