6f879e9070caef58cd37e9ceb07bfc6fa4044668,mir_eval/segment.py,,frame_clustering_rand,#,168

Before Change

    y_true = boundaries_to_frames(annotated_boundaries, frame_size=frame_size)
    y_pred = boundaries_to_frames(predicted_boundaries, frame_size=frame_size)
    // Make sure we have the same number of frames
    assert(len(y_true) == len(y_pred))

    // Compute all the clustering metrics
    //// Adjusted rand index

After Change

    y_true = boundaries_to_frames(annotated_boundaries, frame_size=frame_size)
    y_pred = boundaries_to_frames(predicted_boundaries, frame_size=frame_size)
    // Make sure we have the same number of frames
    if len(y_true) != len(y_pred):
        raise ValueError("Timing mismatch: %.3f vs %.3f" % (annotated_boundaries[-1], predicted_boundaries[-1]))

    // Compute all the clustering metrics
    //// Adjusted rand index

    return metrics.adjusted_rand_score(y_true, y_pred)

def frame_clustering_mutual_information(annotated_boundaries, predicted_boundaries, frame_size=0.1):
    """Frame-clustering segmentation: mutual information metrics.

Instances