'Inverse of the logit transform
Parameters
z : array-like
The value of the logit transform at `p`
Returns
p : array
Probabilities
Notes
g^(-1)(z) = exp(z)/(1+exp(z))'

def inverse(self, z):

    z = np.asarray(z)
    t = np.exp((- z))
    return (1.0 / (1.0 + t))
