dacapo.blockwise.argmax_worker

Attributes

`logger`
`read_write_conflict`
`fit`
`path`

Functions

`cli`(log_level)	CLI for running the threshold worker.
`start_worker`(input_container, input_dataset, ...[, ...])
`start_worker_fn`(input_container, input_dataset, ...[, ...])	Start the threshold worker.
`spawn_worker`(input_array_identifier, ...)	Spawn a worker to predict on a given dataset.

Module Contents

dacapo.blockwise.argmax_worker.logger

dacapo.blockwise.argmax_worker.read_write_conflict: bool = False

dacapo.blockwise.argmax_worker.fit: str = 'valid'

dacapo.blockwise.argmax_worker.path

dacapo.blockwise.argmax_worker.cli(log_level)

CLI for running the threshold worker.

Parameters:: log_level (str) – The log level to use.

dacapo.blockwise.argmax_worker.start_worker(input_container: upath.UPath | str, input_dataset: str, output_container: upath.UPath | str, output_dataset: str, return_io_loop: bool = False)

dacapo.blockwise.argmax_worker.start_worker_fn(input_container: upath.UPath | str, input_dataset: str, output_container: upath.UPath | str, output_dataset: str, 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.

dacapo.blockwise.argmax_worker.spawn_worker(input_array_identifier: dacapo.store.array_store.LocalArrayIdentifier, output_array_identifier: dacapo.store.array_store.LocalArrayIdentifier)

Spawn a worker to predict on a given dataset.

Parameters:

model (Model) – The model to use for prediction.
raw_array (Array) – The raw data to predict on.
prediction_array_identifier (LocalArrayIdentifier) – The identifier of the prediction array.

Returns:

The function to run the worker.

Return type:

Callable