traccuracy.track_errors._basic

Module Contents

Functions

classify_basic_errors(→ None)

Classify basic node and edge errors in the matched graphs.

Attributes

logger

VALID_MATCHING_TYPES

traccuracy.track_errors._basic.logger
traccuracy.track_errors._basic.VALID_MATCHING_TYPES = ['one-to-one']
traccuracy.track_errors._basic.classify_basic_errors(matched: traccuracy.matchers._matched.Matched, relax_skips_gt: bool = False, relax_skips_pred: bool = False) → None[source]

Classify basic node and edge errors in the matched graphs.

A pair of GT/pred nodes is classified as true positive if the matching is one-to-one. False positive nodes are all those remaining in the pred graph. False negative nodes are all those remaining in the GT graph.

A pair of GT/pred edges is classified as true positive if both the source and target nodes are true positives, and the GT graph contains the edge. All remaining edges in the GT graph are false negatives, and all remaining edges in the prediction graph are false positives.

Parameters:

  • matched (traccuracy.matchers.Matched) – Matched data object containing gt and pred graphs with their associated mapping

  • relax_skips_gt (bool) – If True, the metric will check if skips in the ground truth graph have an equivalent multi-edge path in predicted graph

  • relax_skips_pred (bool) – If True, the metric will check if skips in the predicted graph have an equivalent multi-edge path in ground truth graph