dacapo.experiments.validation_scores

Module Contents

Classes

ValidationScores

class dacapo.experiments.validation_scores.ValidationScores

property criteria: List[str]

property parameter_names: List[str]

parameters: List[dacapo.experiments.tasks.post_processors.PostProcessorParameters]

datasets: List[dacapo.experiments.datasplits.datasets.Dataset]

evaluation_scores: dacapo.experiments.tasks.evaluators.EvaluationScores

scores: List[dacapo.experiments.validation_iteration_scores.ValidationIterationScores]

subscores(iteration_scores: List[dacapo.experiments.validation_iteration_scores.ValidationIterationScores]) → ValidationScores

add_iteration_scores(iteration_scores: dacapo.experiments.validation_iteration_scores.ValidationIterationScores) → None

delete_after(iteration: int) → None

validated_until() → int

The number of iterations validated for (the maximum iteration plus one).

compare(existing_iteration_scores: List[dacapo.experiments.validation_iteration_scores.ValidationIterationScores]) → Tuple[bool, int]

Compares iteration stats provided from elsewhere to scores we have saved locally. Local scores take priority. If local scores are at a lower iteration than the existing ones, delete the existing ones and replace with local. If local iteration > existing iteration, just update existing scores with the last overhanging local scores.

to_xarray() → xarray.DataArray

get_best(data: xarray.DataArray, dim: str) → Tuple[xarray.DataArray, xarray.DataArray]

Compute the Best scores along dimension “dim” per criterion. Returns both the index associated with the best value, and the best value in two seperate arrays.