code: def pdf_link(self, inv_link_f, y, Y_metadata=None):
          
          #objective = (inv_link_f**y) * ((1.-inv_link_f)**(1.-y))
          return np.where(y==1, inv_link_f, 1.-inv_link_f)
docs: Likelihood function given inverse link of f.
  
          .. math::
              p(y_{i}|\\lambda(f_{i})) = \\lambda(f_{i})^{y_{i}}(1-f_{i})^{1-y_{i}}
  
          :param inv_link_f: latent variables inverse link of f.
          :type inv_link_f: Nx1 array
          :param y: data
          :type y: Nx1 array
          :param Y_metadata: Y_metadata not used in bernoulli
          :returns: likelihood evaluated for this point
          :rtype: float
  
          .. Note:
              Each y_i must be in {0, 1}