Util

Miscellaneous utility functions

pycytominer.cyto_utils.util.check_aggregate_operation(operation: str) str

Confirm that the input operation for aggregation is currently supported.

Parameters:

operation (str) – Aggregation operation to provide.

Returns:

Correctly formatted operation method.

Return type:

str

pycytominer.cyto_utils.util.check_compartments(compartments: str | list[str])

Checks if the input compartments are noncanonical compartments.

Parameters:

compartments (list of str) – Input compartments.

Returns:

Nothing is returned.

Return type:

None

pycytominer.cyto_utils.util.check_consensus_operation(operation: str) str

Confirm that the input operation for consensus is currently supported.

Parameters:

operation (str) – Consensus operation to provide.

Returns:

Correctly formatted operation method.

Return type:

str

pycytominer.cyto_utils.util.check_correlation_method(method: str) Literal['pearson', 'kendall', 'spearman']

Confirm that the input method is currently supported.

Parameters:

method (str) – The correlation metric to use.

Returns:

Correctly formatted correlation method.

Return type:

str

pycytominer.cyto_utils.util.check_fields_of_view(data_fields_of_view: list[int], input_fields_of_view: list[int])

Confirm that the input list of fields of view is a subset of the list of fields of view in the image table.

Parameters:
  • data_fields_of_view (list of int) – Fields of view in the image table.

  • input_fields_of_view (list of int) – Input fields of view.

Returns:

Nothing is returned.

Return type:

None

pycytominer.cyto_utils.util.check_fields_of_view_format(fields_of_view: str | list[int]) str | list[int]

Confirm that the input fields of view is valid.

Parameters:

fields_of_view (list of int) – List of integer fields of view.

Returns:

Correctly formatted fields_of_view variable.

Return type:

str or list of int

pycytominer.cyto_utils.util.check_image_features(image_features: list[str], image_columns: list[str])

Confirm that the input list of image features are present in the image table

Parameters:
  • image_features (list of str) – Input image features to extract from the image table.

  • image_columns (list of str) – Columns in the image table

Returns:

Nothing is returned.

Return type:

None

pycytominer.cyto_utils.util.extract_image_features(image_feature_categories: list[str], image_df: DataFrame, image_cols: list[str], strata: list[str]) DataFrame

Confirm that the input list of image features categories are present in the image table and then extract those features.

Parameters:
  • image_feature_categories (list of str) – Input image feature groups to extract from the image table.

  • image_df (pd.DataFrame) – Image dataframe.

  • image_cols (list of str) – Columns to select from the image table.

  • strata (list of str) – The columns to groupby and aggregate single cells.

Returns:

image_features_df – Dataframe with extracted image features.

Return type:

pd.DataFrame

pycytominer.cyto_utils.util.get_default_compartments() list[str]

Returns default compartments.

Returns:

Default compartments.

Return type:

list of str

pycytominer.cyto_utils.util.get_pairwise_correlation(population_df: DataFrame, method: str = 'pearson') tuple[DataFrame, DataFrame]

Given a population dataframe, calculate all pairwise correlations.

Parameters:
  • population_df (pd.DataFrame) – Includes metadata and observation features.

  • method (str, default "pearson") – Which correlation matrix to use to test cutoff.

Returns:

A tuple of two DataFrames. The first is a symmetrical correlation matrix. The second is a long format DataFrame of pairwise correlations.

Return type:

tuple of (pd.DataFrame, pd.DataFrame)

pycytominer.cyto_utils.util.load_known_metadata_dictionary(metadata_file: str = '/home/docs/checkouts/readthedocs.org/user_builds/pycytominer/checkouts/stable/pycytominer/cyto_utils/../data/metadata_feature_dictionary.txt') dict[str, list[str]]

From a tab separated text file (two columns: [“compartment”, “feature”]), load previously known metadata columns per compartment.

Parameters:

metadata_file (str) – File location of the metadata text file. Uses a default dictionary if you do not specify.

Returns:

Compartment (keys) mappings to previously known metadata (values).

Return type:

dict

pycytominer.cyto_utils.util.write_to_file_if_user_specifies_output_details(func: Callable[[...], DataFrame | str]) Callable[[...], DataFrame | str]

Decorate a function to optionally write its output to disk.

The decorator intercepts common output-related keyword arguments (output_file, output_type, compression_options, float_format) from the decorated function call. The wrapped function should return a pandas.DataFrame when output_file is provided; the DataFrame is written using pycytominer.cyto_utils.output() and the resulting path is returned instead.