:orphan:

:py:mod:`traccuracy.metrics._complete_tracks`
=============================================

.. py:module:: traccuracy.metrics._complete_tracks


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

Classes
~~~~~~~

.. autoapisummary::

   traccuracy.metrics._complete_tracks.CompleteTracks




.. py:class:: CompleteTracks(error_type: str = 'basic')




   The fraction of tracklets and lineages that are completely correctly reconstructed.

   If the reconstruction continues beyond the ground truth track, this is NOT
   counted as incorrect, nor are false positive tracks penalized, making this suitable
   for evaluating with sparse ground truth annotations.

   If a False Positive Division occurs within the ground truth track (or, for the CTC
   errors, a wrong semantic edge), this IS counted as incorrect.

   :param error_type: Whether to use "basic" or "ctc" errors for
                      computing if tracks are correct or not. Defaults to "basic".
   :type error_type: str, optional

   The compute function returns a results dictionary with the following entries:

       - `total_lineages` - the number of connected components in the ground truth graph
       - `correct_lineages` - the number of fully correct connected components
       - `complete_lineages` - `correct_lineages` / `total_lineages`, or np.nan if
         `total_lineages` is 0
       - `total_tracklets` - the number of tracklets in the ground truth graph,
         defined as the connected components of the graph after division edges are removed.
         Division edges are not included in the tracklets, or counted at all in the tracklet
         metrics.
       - `correct_tracklets` - the number of fully correct tracklets
       - `complete_tracklets` - `correct_tracklets` / `total_tracklets`, or np.nan if
         `total_tracklets` is 0


   .. py:property:: info
      :type: dict[str, Any]

      Dictionary with Metric name and any parameters

   .. py:method:: compute(matched: traccuracy.matchers._matched.Matched, override_matcher: bool = False, relax_skips_gt: bool = False, relax_skips_pred: bool = False) -> traccuracy.metrics._results.Results

      The compute methods of Metric objects return a Results object populated with results
      and associated metadata

      :param matched: Matched data object to compute metrics on
      :type matched: traccuracy.matchers.Matched
      :param override_matcher: If True, the metric will not validate the matcher type
      :type override_matcher: bool
      :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

      :returns:

                Object containing metric results
                    and associated pipeline metadata
      :rtype: traccuracy.metrics._results.Results