@deprecated('The function wishart_log_det is deprecated in 0.18 and will be removed in 0.20.')
def wishart_log_det(a, b, detB, n_features):
 l = np.sum(digamma((0.5 * (a - np.arange((-1), (n_features - 1))))))
 l += (n_features * np.log(2))
 return (l + detB)

@ deprecated ( 'The function wishart_log_det is deprecated in 0.18 and will be removed in 0.20.' ) def wishart_log_det ( a , b , detB , n_features ) : l = np . sum ( digamma ( ( 0.5 * ( a - np . arange ( ( - 1 ) , ( n_features - 1 ) ) ) ) ) ) l += ( n_features * np . log ( 2 ) ) return ( l + detB )
expected value of the log of the determinant of a wishart the expected value of the logarithm of the determinant of a wishart-distributed random variable with the specified parameters .