Feat_categorical_labels #1053
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Feat_categorical_labels #1053
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might approximately work already, but haven't tested much yet basic idea is (1) a CategoricalLabels class which stores lists of integer indices for class labels along with the class list, and provides various "views" such as sparse or dense matrices or dfs, or multihot labels for a single row; (2) convert sparse label dtypes to dense when creating AudioSample objects
…ions' into feat_categorical_labels
these methods replace multihot_clip_labels() and multihot_labels_like(), and support four different output formats: multihot, categorical with integers, categorical with class names, or CategoricalLabels class. Adds CategoricalLabels class, which stores labels as lists of integers and provides methods to "view" or access the labels in various formats including sparse or dense 2d arrays or dataframes. Also provides methods to create from multihot or categorical dataframes. Will be useful for storing labels in a lightweight format when there are many classes and samples. Adds tests for the new BoxedAnnotations methods and removes/updates outdated tests. Still needs tests for the CategoricalLabels class itself.
avoids FutureWarnings when creating Pandas dfs from scipy sparse matrix types, but also seems like unnecessary memory use, consider reverting to bool pending info on this issue: pandas-dev/pandas#59739
this property wont exist when the method is called with Lightning
fixes passing list of classes (rather than pd.Index) in classmethod from_multihot_df adds properties .labels and .class_labels for CategoricalLabels adds missing docstrings for properties and methods of CategoricalLabels
updated labels_df to have categorical rather than int labels, needed to update assertion in test accordingly
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Sep 10, 2024
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these methods replace multihot_clip_labels() and multihot_labels_like(), and support four different output formats: multihot, categorical with integers, categorical with class names, or CategoricalLabels class.
Adds CategoricalLabels class, which stores labels as lists of integers and provides methods to "view" or access the labels in various formats including sparse or dense 2d arrays or dataframes. Also provides methods to create from multihot or categorical dataframes. Will be useful for storing labels in a lightweight format when there are many classes and samples.
Adds tests for the new BoxedAnnotations methods and removes/updates outdated tests. Still needs tests for the CategoricalLabels class itself.