def min_row_dist_sum_idx(dists):
    """Find the index of the row with the minimum row distance sum 

    This should return the index of the row index with the least distance overall 
    to all other rows. 

    Args:
        dists (np.array): must be square distance matrix

    Returns:
        int: index of row with min dist row sum
    """
    row_sums = np.apply_along_axis(arr=dists, axis=0, func1d=np.sum)
    return row_sums.argmin()
Find the index of the row with the minimum row distance sum 

    This should return the index of the row index with the least distance overall 
    to all other rows. 

    Args:
        dists (np.array): must be square distance matrix

    Returns:
        int: index of row with min dist row sum