:orphan:

:py:mod:`traccuracy.track_errors._basic`
========================================

.. py:module:: traccuracy.track_errors._basic


Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   traccuracy.track_errors._basic.classify_basic_errors



Attributes
~~~~~~~~~~

.. autoapisummary::

   traccuracy.track_errors._basic.logger
   traccuracy.track_errors._basic.VALID_MATCHING_TYPES


.. py:data:: logger

   

.. py:data:: VALID_MATCHING_TYPES
   :value: ['one-to-one']

   

.. py:function:: classify_basic_errors(matched: traccuracy.matchers._matched.Matched, relax_skips_gt: bool = False, relax_skips_pred: bool = False) -> None

   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.

   :param matched: Matched data object containing gt
                   and pred graphs with their associated mapping
   :type matched: traccuracy.matchers.Matched
   :param relax_skips_gt: If True, the metric will check if skips in the ground truth
                          graph have an equivalent multi-edge path in predicted graph
   :type relax_skips_gt: bool
   :param relax_skips_pred: If True, the metric will check if skips in the predicted
                            graph have an equivalent multi-edge path in ground truth graph
   :type relax_skips_pred: bool