def _standard_rvs(self, n, shape, dim, df, random_state):
        """
        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
        random_state : np.random.RandomState instance
            RandomState used for drawing the random variates.

        Notes
        -----
        As this function does no argument checking, it should not be
        called directly; use 'rvs' instead.

        """
        # Random normal variates for off-diagonal elements
        n_tril = dim * (1-dim) // 2
        covariances = random_state.normal(
            size=n*n_tril).reshape(shape+(n_tril,))

        # Random chi-square variates for diagonal elements
        variances = np.r_[[random_state.chisquare(df-(i+1)+1, size=n)**0.5
             for i in range(dim)]].reshape((dim,) + shape[::-1]).T

        # Create the A matri(ces) - lower triangular
        A = np.zeros(shape + (dim, dim))

        # Input the covariances
        size_idx = tuple([slice(None,None,None)]*len(shape))
        tril_idx = np.tril_indices(dim, k=-1)
        A[size_idx + tril_idx] = covariances

        # Input the variances
        diag_idx = np.diag_indices(dim)
        A[size_idx + diag_idx] = variances

        return A
dataset/ETHPy150Open scipy/scipy/scipy/stats/_multivariate.py/wishart_gen._standard_rvs/swapped operands of `-`