phenonaut.integration.integrators package

Submodules

phenonaut.integration.integrators.base module

class phenonaut.integration.integrators.base.ViewIntegrator(name: str, has_fit: bool, has_transform: bool, has_fit_transform: bool)

Bases: object

fit(datasets: list[Dataset]) → None

fit_train_test_transform_test(datasets_train: list[list[Dataset]], datasets_test: list[list[Dataset]]) → Dataset

Fit transform for MVMDS

Parameters:

datasets (list[list[phenonaut.data.Dataset]]) –

M length list of N length lists of datasets, where M is of length 2 for train+test sets, and 3 for train, val, test sets and N is the number of views for each.

[[View1_train, View1_val, View1_test], [[View1_train, View1_val, View1_test]]]

Returns:

_description_

Return type:

phenonaut.data.Dataset

fit_transform(datasets: list[Dataset]) → Dataset

static merge_splits_to_single_views(datasets: list[list[Dataset]] | list[Dataset]) → list[Dataset]

_summary_

Parameters:

datasets (list[list[phenonaut.data.Dataset]] | list[phenonaut.data.Dataset]) –

M length list of N length lists of datasets, where M is of length 2 for train+test sets, and 3 for train, val, test sets and N is the number of views for each.

[[View1_train, View1_val, View1_test], [[View1_train, View1_val, View1_test]]]

Returns:

_description_

Return type:

list[phenonaut.data.Dataset]

static multiplex_df(datasets: list[Dataset], how: str = 'left', random_state: int | Generator = 7, drop_non_critical_data: bool = True, shuffle_joined_dataset: bool = True) → tuple[DataFrame, list[list[str]]]

static multiplex_df_merge_single_samples(datasets: list[Dataset], how: str = 'left', random_state: int | Generator = 7, keep_metadata_columns: bool = True) → tuple[DataFrame, list[list[str]]]

transform(datasets: list[Dataset]) → Dataset

phenonaut.integration.integrators.classic module

class phenonaut.integration.integrators.classic.Concatenate_ViewIntegrator(name: str = 'ConcatenateVieswIntegrator', **kwargs)

Bases: ViewIntegrator

__call__(datasets: list[Dataset]) → Dataset

Call self as a function.

class phenonaut.integration.integrators.classic.MVMDS_ViewIntegrator(name: str = 'MVMDSViewIntegrator', **kwargs)

Bases: ViewIntegrator

__call__(datasets: list[Dataset]) → Dataset

Call self as a function.

class phenonaut.integration.integrators.classic.SplitAutoencoder_ViewIntegrator(name: str = 'SplitAutoEncoderViewIntegrator', **kwargs)

Bases: ViewIntegrator

__call__(datasets_train: list[Dataset], datasets_test: list[Dataset]) → Dataset

Call self as a function.

Module contents

class phenonaut.integration.integrators.Concatenate_ViewIntegrator(name: str = 'ConcatenateVieswIntegrator', **kwargs)

Bases: ViewIntegrator

__call__(datasets: list[Dataset]) → Dataset

Call self as a function.

class phenonaut.integration.integrators.MVMDS_ViewIntegrator(name: str = 'MVMDSViewIntegrator', **kwargs)

Bases: ViewIntegrator

__call__(datasets: list[Dataset]) → Dataset

Call self as a function.

class phenonaut.integration.integrators.SplitAutoencoder_ViewIntegrator(name: str = 'SplitAutoEncoderViewIntegrator', **kwargs)

Bases: ViewIntegrator

__call__(datasets_train: list[Dataset], datasets_test: list[Dataset]) → Dataset

Call self as a function.