N0dev

import numpy as np

class Descending:
    """ for np_sortrows: sort column in descending order """
    def __init__(self, column_index):
        self.column_index = column_index

    def __int__(self):  # when cast to integer
        return self.column_index


def np_sortrows(M, columns=None):
    """  sorting 2D matrix by rows
    :param M: 2D numpy array to be sorted by rows
    :param columns: None for all columns to be used,
                    iterable of indexes or Descending objects
    :return: returns sorted M
    """
    if len(M.shape) != 2:
        raise ValueError('M must be 2d numpy.array')
    if columns is None:  # no columns specified, use all (reversed)
        M_columns = tuple(M[:, c] for c in range(M.shape[1]-1, -1, -1))
    else:
        M_columns = []
        for c in columns:
            M_c = M[:, int(c)]
            if isinstance(c, Descending):
                M_columns.append(M_c[::-1])
            else:
                M_columns.append(M_c)
        M_columns.reverse()

    return M[np.lexsort(M_columns), :]


if __name__ == '__main__':

    data = np.array([[3, 0, 0, .24],
                     [4, 1, 1, .41],
                     [2, 1, 3, .25],
                     [2, 1, 1, .63],
                     [1, 1, 3, .38]])

    # to satisfy original question:
    # third column is index 2, fourth column in reversed order
    print(np_sortrows(data, [2, Descending(3)]))