3544c70a5c7e63d172baacb9b380a613f1fa92e0,tslearn/metrics.py,,cdist_dtw,#Any#Any#Any#Any#Any#Any#,597

Before Change

        // TODO
        return njit_cdist_dtw_self(
            dataset1,
            global_constraint_code[global_constraint_str],
            sakoe_chiba_radius, itakura_max_slope)
    else:
        dataset2 = to_time_series_dataset(dataset2)

After Change

        // Inspired from code by @GillesVandewiele:
        // https://github.com/rtavenar/tslearn/pull/128//discussion_r314978479
        matrix = numpy.zeros((len(dataset1), len(dataset1)))
        indices = numpy.triu_indices(len(dataset1), k=1, m=len(dataset1))
        matrix[indices] = Parallel(n_jobs=n_jobs)(
            delayed(dtw)(
                dataset1[i], dataset1[j],
                global_constraint=global_constraint,

Instances