'Parameters
n : integer
Number of variates to generate
shape : iterable
Shape of the variates to generate
dim : int
Dimension of the scale matrix
df : int
Degrees of freedom
scale : ndarray
Scale matrix
C : ndarray
Cholesky factorization of the scale matrix, lower triangular.
%(_doc_random_state)s
Notes
As this function does no argument checking, it should not be
called directly; use \'rvs\' instead.'

def _rvs(self, n, shape, dim, df, C, random_state):

    random_state = self._get_random_state(random_state)
    A = self._standard_rvs(n, shape, dim, df, random_state)
    for index in np.ndindex(shape):
        CA = np.dot(C, A[index])
        A[index] = np.dot(CA, CA.T)
    return A
