def accumulated_cost_matrix(cost_mat, region=None):
    """Compute the accumulated cost matrix.

    Parameters
    ----------
    cost_mat : array-like, shape = (n_timestamps_1, n_timestamps_2)
        Cost matrix.

    region : None or tuple, shape = (2, n_timestamps_1) (default = None)
        Constraint region. If None, there is no contraint region.
        If array-like, the first row indicates the starting indices (included)
        and the second row the ending indices (excluded) of the valid rows
        for each column.

    Returns
    -------
    acc_cost_mat : array, shape = (n_timestamps_1, n_timestamps_2)
        Accumulated cost matrix.

    """
    cost_mat = check_array(cost_mat, ensure_min_samples=2,
                           ensure_min_features=2, ensure_2d=True,
                           force_all_finite=False, dtype='float64')
    cost_mat_shape = cost_mat.shape

    if region is None:
        acc_cost_mat = _accumulated_cost_matrix_no_region(cost_mat)
    else:
        region = check_array(region, dtype='int64')
        region_shape = region.shape
        if region_shape != (2, cost_mat_shape[0]):
            raise ValueError("The shape of 'region' must be equal to "
                             "(2, n_timestamps_1) "
                             "(got {0})".format(region_shape)
                             )
        acc_cost_mat = _accumulated_cost_matrix_region(cost_mat, region)
    return acc_cost_mat
Compute the accumulated cost matrix.

    Parameters
    ----------
    cost_mat : array-like, shape = (n_timestamps_1, n_timestamps_2)
        Cost matrix.

    region : None or tuple, shape = (2, n_timestamps_1) (default = None)
        Constraint region. If None, there is no contraint region.
        If array-like, the first row indicates the starting indices (included)
        and the second row the ending indices (excluded) of the valid rows
        for each column.

    Returns
    -------
    acc_cost_mat : array, shape = (n_timestamps_1, n_timestamps_2)
        Accumulated cost matrix.

    
pyts/metrics/dtw.py