add loaders#9
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MikeLippincott wants to merge 2 commits intoWayScience:mainfrom
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Great job - thanks for addressing the changes! I feel this LGTM.
| def _coerce_dataframe_column_names_to_strings( | ||
| dataframe: pandas.DataFrame, | ||
| ) -> pandas.DataFrame: | ||
| """Ensure DataFrame column labels are string-typed before writing.""" |
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For this and other functions consider documenting all parameters and return types.
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| FEATURE_OUTPUT_SCHEMA = pa.DataFrameSchema( | ||
| columns={}, | ||
| strict=False, | ||
| parsers=[pa.Parser(_coerce_dataframe_column_names_to_strings)], | ||
| ) | ||
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| FEATURE_NAME_COMPONENT_SCHEMA = pa.DataFrameSchema( | ||
| columns={ | ||
| "compartment": pa.Column(object, nullable=False, coerce=True), | ||
| "channel": pa.Column(object, nullable=False, coerce=True), | ||
| "feature_type": pa.Column(object, nullable=False, coerce=True), | ||
| "measurement": pa.Column(object, nullable=False, coerce=True), | ||
| }, | ||
| strict=True, | ||
| parsers=[pa.Parser(_coerce_feature_name_components)], | ||
| ) |
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Consider moving all globals to the top of the module.
| return string | ||
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| @beartype |
| numpy.ndarray | ||
| Image returned | ||
| """ | ||
| image = bioio.BioImage(str(image_path)) # selects the first scene found |
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Instead of relying on this thin function could you rely on the bioio method directly where needed? This might save you the strain of needing to maintain this.
| Image returned | ||
| """ | ||
| image = bioio.BioImage(str(image_path)) # selects the first scene found | ||
| return image.get_image_data("ZYX") |
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Should this be configurable in terms of dimensions where applied?
| """Test creating FeatureMetadata instance.""" | ||
| metadata = FeatureMetadata( | ||
| compartment="nucleus", | ||
| @pytest.mark.parametrize( |
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Description
This PR adds the loaders needed for ZedProfiler's featurization process
What kind of change(s) are included?
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