czbenchmarks.tasks.integration
Attributes
Classes
Pydantic model for BatchIntegrationTask inputs. |
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Output for batch integration task. |
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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