FlowChange.FlowChangeParams

FlowChange.FlowChangeParams#

FlowChange.FlowChangeParams.py

It seems that this module is broken. Will fix it later.

get_datafolder()#

Get the data folder path.

Returns:

The data folder path.

Return type:

str

compute_like_values(for_all=False)#

Compute likelihood values for flow change detection on test datasets.

Parameters:

for_all (bool, optional) – If True, process all folders in the data directory. If False, process only predefined test targets. Default is False.

Returns:

Each tuple contains (in_folder, c1, c2, mi, points, segments, abs_likes, rel_likes, peaklike, peakpos)

Return type:

list of tuples

plot_flowchange(in_folder, c1, c2, mi, points, segments, axes=None)#

Plot the flow change analysis results.

Parameters:

  • in_folder (str) – The input folder path.

  • c1 (UvCurve) – The first UV curve.

  • c2 (UvCurve) – The second UV curve.

  • mi (Moment) – The moment information object.

  • points (list of int) – List of points where flow changes are detected.

  • segments (list of int) – List of segment boundaries.

  • axes (list of Axes, optional) – If provided, use these axes for plotting.

Return type:

None

make_test_targets(recs)#

Make test targets from the computed records.

Parameters:

recs (list of tuples) – The computed records from the flow change analysis.

Returns:

Each tuple contains (folder, (i, j)) where i and j are the test target indices.

Return type:

list of tuples

test_params(recs, params_dict, targets=None)#

Test the flow change parameters against expected targets.

Parameters:

  • recs (list of tuples) – The computed records from the flow change analysis.

  • params_dict (dict) – The parameters for the FlowChangeJudge.

  • targets (list of tuples, optional) – The expected targets for the flow change analysis. If None, use the predefined TEST_TARGETS. Default is None.

Return type:

None

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