'Draw random samples from an inverse Wishart distribution.
Parameters
%(_doc_default_callparams)s
size : integer or iterable of integers, optional
Number of samples to draw (default 1).
%(_doc_random_state)s
Returns
rvs : ndarray
Random variates of shape (`size`) + (`dim`, `dim), where `dim` is
the dimension of the scale matrix.
Notes
%(_doc_callparams_note)s'

def rvs(self, df, scale, size=1, random_state=None):

    (n, shape) = self._process_size(size)
    (dim, df, scale) = self._process_parameters(df, scale)
    eye = np.eye(dim)
    (L, lower) = scipy.linalg.cho_factor(scale, lower=True)
    inv_scale = scipy.linalg.cho_solve((L, lower), eye)
    C = scipy.linalg.cholesky(inv_scale, lower=True)
    out = self._rvs(n, shape, dim, df, C, random_state)
    return _squeeze_output(out)
