dice-group · alkidbaci · Nov 16, 2024 · Nov 11, 2024 · Nov 12, 2024 · Nov 12, 2024
diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml
@@ -4,7 +4,7 @@ on:
   push:
     branches:
      - master
-     - develop
+     - documentation # only for quick updates or testing purposes
   pull_request:
 
 jobs:

diff --git a/.gitignore b/.gitignore
@@ -157,6 +157,7 @@ pre_trained_agents.zip
 embeddings.zip
 KGs.zip
 /Fuseki/
+/checkpoints/
 /KGs/
 **/NCESData*
 **/CLIPData*

diff --git a/README.md b/README.md
@@ -1,6 +1,6 @@
 [![Coverage](https://img.shields.io/badge/coverage-86%25-green)](https://ontolearn-docs-dice-group.netlify.app/usage/09_further_resources#code-coverage)
-[![Pypi](https://img.shields.io/badge/pypi-0.8.0-blue)](https://pypi.org/project/ontolearn/0.8.0/)
-[![Docs](https://img.shields.io/badge/documentation-0.8.0-yellow)](https://ontolearn-docs-dice-group.netlify.app/usage/01_introduction)
+[![Pypi](https://img.shields.io/badge/pypi-0.8.1-blue)](https://pypi.org/project/ontolearn/0.8.1/)
+[![Docs](https://img.shields.io/badge/documentation-0.8.1-yellow)](https://ontolearn-docs-dice-group.netlify.app/usage/01_introduction)
 [![Python](https://img.shields.io/badge/python-3.10.13+-4584b6)](https://www.python.org/downloads/release/python-31013/)
 &nbsp;
 

diff --git a/docs/usage/01_introduction.md b/docs/usage/01_introduction.md
@@ -1,6 +1,6 @@
 # About Ontolearn
 
-**Version:** ontolearn 0.8.0
+**Version:** ontolearn 0.8.1
 
 **GitHub repository:** [https://github.com/dice-group/Ontolearn](https://github.com/dice-group/Ontolearn)
 

diff --git a/examples/retrieval_eval.py b/examples/retrieval_eval.py
@@ -86,9 +86,9 @@ def execute(args):
     object_properties = sorted({i for i in symbolic_kb.get_object_properties()})
 
     # (3.1) Subsample if required.
-    if args.ratio_sample_object_prop:
+    if args.ratio_sample_object_prob:
         object_properties = {i for i in random.sample(population=list(object_properties),
-                                                      k=max(1, int(len(object_properties) * args.ratio_sample_object_prop)))}
+                                                      k=max(1, int(len(object_properties) * args.ratio_sample_object_prob)))}
 
     object_properties = set(object_properties)    
 
@@ -261,6 +261,7 @@ def concept_retrieval(retriever_func, c) -> Tuple[Set[str], float]:
     print(df_g["Type"].count())
     mean_df = df_g[numerical_df.columns].mean()
     print(mean_df)
+    return jaccard_sim, f1_sim
 
 
 def get_default_arguments():
@@ -271,7 +272,7 @@ def get_default_arguments():
     parser.add_argument("--gamma", type=float, default=0.9)
     parser.add_argument("--seed", type=int, default=1)
     parser.add_argument("--ratio_sample_nc", type=float, default=0.2, help="To sample OWL Classes.")
-    parser.add_argument("--ratio_sample_object_prop", type=float, default=0.1, help="To sample OWL Object Properties.")
+    parser.add_argument("--ratio_sample_object_prob", type=float, default=0.1, help="To sample OWL Object Properties.")
     parser.add_argument("--min_jaccard_similarity", type=float, default=0.0, help="Minimum Jaccard similarity to be achieve by the reasoner")
     parser.add_argument("--num_nominals", type=int, default=10, help="Number of OWL named individuals to be sampled.")
 

diff --git a/examples/retrieval_eval_under_incomplete.py b/examples/retrieval_eval_under_incomplete.py
@@ -226,6 +226,7 @@ def execute(args):
     print(final_df.head())
     print(f"Results have been saved to {final_csv_path}")
     stopJVM()
+    return avg_jaccard_reasoners
 
 
 

diff --git a/ontolearn/__init__.py b/ontolearn/__init__.py
@@ -22,4 +22,4 @@
 # SOFTWARE.
 # -----------------------------------------------------------------------------
 
-__version__ = '0.8.0'
+__version__ = '0.8.1'
diff --git a/setup.py b/setup.py
@@ -47,7 +47,7 @@
     "tqdm>=4.64.0",
     "transformers>=4.38.1",
     "pytest>=7.2.2",
-    "owlapy==1.3.2",
+    "owlapy==1.3.3",
     "dicee==0.1.4",
     "ontosample>=0.2.2",
     "sphinx>=7.2.6",
@@ -95,7 +95,7 @@ def deps_list(*pkgs):
 setup(
     name="ontolearn",
     description="Ontolearn is an open-source software library for structured machine learning in Python. Ontolearn includes modules for processing knowledge bases, inductive logic programming and ontology engineering.",
-    version="0.8.0",
+    version="0.8.1",
     packages=find_packages(),
     install_requires=extras["min"],
     extras_require=extras,

diff --git a/tests/test_retrieval_eval_examples.py b/tests/test_retrieval_eval_examples.py
@@ -0,0 +1,52 @@
+import os
+import unittest
+from examples.retrieval_eval import execute
+from examples.retrieval_eval_under_incomplete import execute as execute2
+import shutil
+
+class RetrievalTests(unittest.TestCase):
+
+    def test_retrieval_eval(self):
+        class ARGS:
+            def __init__(self):
+                self.path_kg = "KGs/Family/father.owl"
+                self.path_kge_model = None
+                self.endpoint_triple_store = None
+                self.gamma = 0.9
+                self.seed = 1
+                self.min_jaccard_similarity = 0.0
+                self.ratio_sample_nc = 0.2
+                self.ratio_sample_object_prob = 0.1
+                self.num_nominals = 10
+                self.path_report = "incomplete_father_0_1/ALCQHI_Retrieval_Results.csv"
+        args = ARGS()
+        os.mkdir("incomplete_father_0_1")
+        js, f1 = execute(args)
+
+        self.assertEqual(js, 1.0)
+        self.assertEqual(f1, 1.0)
+
+    def test_retrieval_eval_under_incomplete(self):
+        class ARGS:
+            def __init__(self):
+                self.path_kg = "KGs/Family/father.owl"
+                self.seed = 1
+                self.ratio_sample_nc = None
+                self.ratio_sample_object_prob = None
+                self.path_report = "ALCQHI_Retrieval_Results.csv"
+                self.number_of_subgraphs = 1
+                self.ratio = 0.1
+                self.operation = "incomplete"
+                self.sample = "No"
+
+        args = ARGS()
+        results = execute2(args)
+        for r, v in results.items():
+            self.assertGreaterEqual(v, 0.9)
+        if os.path.exists("incomplete_father_0_1"):
+            shutil.rmtree("incomplete_father_0_1")
+        if os.path.exists("KGs_Family_father_owl"):
+            shutil.rmtree("KGs_Family_father_owl")
+        if os.path.exists("checkpoints"):
+            shutil.rmtree("checkpoints")
+
-Original file line number
+Diff line change
@@ Expand Up / @@ -4,7 +4,7 @@ on: @@
       push:
         branches:
          - master
-         - develop
+         - documentation # only for quick updates or testing purposes
       pull_request:
     jobs:
@@ Expand Down @@