czbenchmarks.tasks.integration

Attributes

logger

Classes

BatchIntegrationTaskInput

Pydantic model for BatchIntegrationTask inputs.

BatchIntegrationOutput

Output for batch integration task.

BatchIntegrationTask

Task for evaluating batch integration quality.

Module Contents

czbenchmarks.tasks.integration.logger
class czbenchmarks.tasks.integration.BatchIntegrationTaskInput(/, **data: Any)[source]

Bases: czbenchmarks.tasks.task.TaskInput

Pydantic model for BatchIntegrationTask inputs.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

batch_labels: czbenchmarks.types.ListLike
labels: czbenchmarks.types.ListLike
class czbenchmarks.tasks.integration.BatchIntegrationOutput(/, **data: Any)[source]

Bases: czbenchmarks.tasks.task.TaskOutput

Output for batch integration task.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

cell_representation: czbenchmarks.tasks.types.CellRepresentation
class czbenchmarks.tasks.integration.BatchIntegrationTask(*, random_seed: int = RANDOM_SEED)[source]

Bases: czbenchmarks.tasks.task.Task

Task for evaluating batch integration quality.

This task computes metrics to assess how well different batches are integrated in the embedding space while preserving biological signals.

Parameters:

random_seed (int) – Random seed for reproducibility

display_name = 'Batch Integration'
description = 'Evaluate batch integration quality using various integration metrics.'
input_model