Fix to_functional_df function - #677
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Code changes looks good. Though I am not fully sold on breaking backwards compatibility.
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This PR makes 2 major changes:
to_functional_dfto matchto_classification_df: functional profiles (so, samples) are the rows whereas function ids (or function ids x taxa names for stratified results) are the columns. For stratified results, the function ids x taxa names is a MultiIndex on the columns.taxa_stratified=Trueis handled properly in that data frame: each contributing taxon gets its own column in the dataframe.As part of this PR some benchmarks were run on sparse representation of the data frame - the verdict is: not worth it since the wide format introduces a lot of columns so huge overhead in pandas. The sparse format actually uses more memory due to that even at values at ~25% full. We'd need ~1k samples for sparse to become useful.
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