Prediction Outputs

Module containing functions to convert prediction outputs to desired form.

`combine_batches(predictions, tiled)`

combine_batches(predictions: list[Any], tiled: Literal[True]) -> tuple[list[NDArray], list[TileInformation]]

combine_batches(predictions: list[Any], tiled: Literal[False]) -> list[NDArray]

combine_batches(predictions: list[Any], tiled: Union[bool, Literal[True], Literal[False]]) -> Union[list[NDArray], tuple[list[NDArray], list[TileInformation]]]

If predictions are in batches, they will be combined.

TODO improve description!

Parameters:

Name	Type	Description	Default
`predictions`	`list`	Predictions that are output from `Trainer.predict`.	required
`tiled`	`bool`	Whether the predictions are tiled.	required

Returns:

Type	Description
`(list of numpy.ndarray) or tuple of (list of numpy.ndarray, list of TileInformation)`	Combined batches.

`convert_outputs(predictions, tiled)`

Convert the Lightning trainer outputs to the desired form.

This method allows stitching back together tiled predictions.

Parameters:

Name	Type	Description	Default
`predictions`	`list`	Predictions that are output from `Trainer.predict`.	required
`tiled`	`bool`	Whether the predictions are tiled.	required

Returns:

Type	Description
`list of numpy.ndarray or numpy.ndarray`	list of arrays with the axes SC(Z)YX. If there is only 1 output it will not be in a list.

`convert_outputs_microsplit(predictions, dataset)`

Convert microsplit Lightning trainer outputs using eval_utils stitching functions.

This function processes microsplit predictions that return (tile_prediction, tile_std) tuples and stitches them back together using the same logic as get_single_file_mmse.

Parameters:

Name	Type	Description	Default
`predictions`	`list of tuple[NDArray, NDArray]`	Predictions from Lightning trainer for microsplit. Each element is a tuple of (tile_prediction, tile_std) where both are numpy arrays from predict_step.	required
`dataset`	`Dataset`	The dataset object used for prediction, needed for stitching function selection and stitching process.	required

Returns:

Type	Description
`tuple[NDArray, NDArray]`	A tuple of (stitched_predictions, stitched_stds) representing the full stitched predictions and standard deviations.

`convert_outputs_pn2v(predictions, tiled)`

Convert the Lightning trainer outputs to the desired form.

This method allows stitching back together tiled predictions.

Parameters:

Name	Type	Description	Default
`predictions`	`list`	Predictions that are output from `Trainer.predict`. Length of list the total number of tiles divided by the batch size. Each element consists of a tuple of ((prediction, mse), tile_info_list). 1st dimension of each tensor is the bs. Length of tile info list is the batch size.	required
`tiled`	`bool`	Whether the predictions are tiled.	required

Returns:

Type	Description
`tuple[list[NDArray], list[NDArray]]`	Tuple of (predictions, mmse) where each is a list of arrays with axes SC(Z)YX.