dacapo.blockwise.threshold_worker

Attributes

logger

read_write_conflict

fit

path

Functions

cli(log_level)

start_worker(input_container, input_dataset, ...[, ...])

start_worker_fn(input_container, input_dataset, ...[, ...])

Start the threshold worker.

spawn_worker(input_array_identifier, ...[, threshold])

Spawn a worker to predict on a given dataset.

Module Contents

dacapo.blockwise.threshold_worker.logger
dacapo.blockwise.threshold_worker.read_write_conflict: bool = False
dacapo.blockwise.threshold_worker.fit: str = 'valid'
dacapo.blockwise.threshold_worker.path
dacapo.blockwise.threshold_worker.cli(log_level)
dacapo.blockwise.threshold_worker.start_worker(input_container: upath.UPath | str, input_dataset: str, output_container: upath.UPath | str, output_dataset: str, threshold: float = 0.0, return_io_loop: bool = False)
dacapo.blockwise.threshold_worker.start_worker_fn(input_container: upath.UPath | str, input_dataset: str, output_container: upath.UPath | str, output_dataset: str, threshold: float = 0.0, return_io_loop: bool = False)

Start the threshold worker.

Parameters:

  • input_container (Path | str) – The input container.

  • input_dataset (str) – The input dataset.

  • output_container (Path | str) – The output container.

  • output_dataset (str) – The output dataset.

  • threshold (float) – The threshold.

dacapo.blockwise.threshold_worker.spawn_worker(input_array_identifier: dacapo.store.array_store.LocalArrayIdentifier, output_array_identifier: dacapo.store.array_store.LocalArrayIdentifier, threshold: float = 0.0)

Spawn a worker to predict on a given dataset.

Parameters:

  • input_array_identifier (LocalArrayIdentifier) – The raw data to predict on.

  • output_array_identifier (LocalArrayIdentifier) – The identifier of the prediction array.

  • threshold (float) – The threshold.

Returns:

The function to run the worker.

Return type:

Callable