base

Total true positive metrics over multiple runs.

class pysatl_cpd.analysis.metrics.multiple_run.classification.base.TotalFP(error_margin)

Bases: TotalSum[TraceT, ProviderT, int], Generic

Configure the total false positive metric with an error margin.

Parameters:

error_margin (tuple[int, int]) – Allowed (left, right) margin around each true change point for matching detections.

__init__(error_margin)

Parameters:

error_margin (tuple[int, int])

Return type:

None

property base_metric: FalsePositiveCount

Per-run false-positive metric.

Return type:

SingleFP

class pysatl_cpd.analysis.metrics.multiple_run.classification.base.TotalFN(error_margin)

Bases: TotalSum[TraceT, ProviderT, int], Generic

Configure the total false negative metric with an error margin.

Parameters:

error_margin (tuple[int, int]) – Allowed (left, right) margin around each true change point for matching detections.

__init__(error_margin)

Parameters:

error_margin (tuple[int, int])

Return type:

None

property base_metric: FalseNegativeCount

Per-run false-negative metric.

Return type:

SingleFN

class pysatl_cpd.analysis.metrics.multiple_run.classification.base.TotalTP(error_margin)

Bases: TotalSum[TraceT, ProviderT, int], Generic

Configure the total true positive metric with an error margin.

Parameters:

error_margin (tuple[int, int]) – Allowed (left, right) margin around each true change point for matching detections.

__init__(error_margin)

Parameters:

error_margin (tuple[int, int])

Return type:

None

property base_metric: TruePositiveCount

Per-run true-positive metric.

Return type:

SingleTP