0d78d2a33bb152be3ba5d49dad3433472b0cf9f1,mir_eval/boundary.py,,detection,#Any#Any#Any#Any#Any#,46

Before Change

    dist        = np.abs( np.subtract.outer(reference_boundaries, estimated_boundaries)) <= window

    // Precision: how many estimated intervals were hits?
    precision   = np.mean(dist.max(axis=0))

    // Recall: how many of the intervals did we catch?
    recall      = np.mean(dist.max(axis=1))

After Change

    // Precision = |matching| / |// predictions|
    // Recall    = |matching| / |// annotations|
    
    precision   = matching_size / len(estimated_boundaries)
    recall      = matching_size / len(reference_boundaries)
    
    f_measure   = util.f_measure(precision, recall)
    
    return precision, recall, f_measure

Instances