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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def Ey(self, f):
 r""" Expected value of the Poisson likelihood. Parameters f: ndarray latent function from the GLM prior (:math:`\mathbf{f} = \boldsymbol\Phi \mathbf{w}`) Returns ------- Ey: ndarray expected value of y, :math:`\mathbb{E}[\mathbf{y}|\mathbf{f}]`. """

        return np.exp(f) if self.tranfcn == 'exp' else softplus(f)