def calculate_p_xi_given_y(self, xi, thetai):
not_missing = np.logical_not(ma.getmaskarray(xi))
z = np.zeros((self.n_hidden, len(xi), self.dim_hidden))
z[:, not_missing, :] = self.marginal_p(xi[not_missing], thetai)
return z # n_hidden, n_samples, dim_hidden
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