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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def make_trans_matrix(y, n_classes, dtype=np.float64):
 """Make a sparse transition matrix for y. Takes a label sequence y and returns an indicator matrix with n_classes² columns of the label transitions in y: M[i, j, k] means y[i-1] == j and y[i] == k. The first row will be empty. """

    indices = np.empty(len(y), dtype=np.int32)

    for i in six.moves.xrange(len(y) - 1):
        indices[i] = y[i] * i + y[i + 1]

    indptr = np.arange(len(y) + 1)
    indptr[-1] = indptr[-2]

    return csr_matrix((np.ones(len(y), dtype=dtype), indices, indptr),
                      shape=(len(y), n_classes ** 2))