struct_models.py 文件源码

def _marg_rounded(self, x, y):
        y_node = y.nodes
        y_link = y.links
        Y_node = label_binarize(y_node, self.prop_encoder_.classes_)
        Y_link = label_binarize(y_link, self.link_encoder_.classes_)

        # XXX can this be avoided?
        Y_node, Y_link = map(_binary_2d, (Y_node, Y_link))

        src_type = Y_node[x.link_to_prop[:, 0]]
        trg_type = Y_node[x.link_to_prop[:, 1]]

        if self.compat_features:
            pw = np.einsum('...j,...k,...l->...jkl',
                           src_type, trg_type, Y_link)
            compat = np.tensordot(x.X_compat.T, pw, axes=[1, 0])
        else:
            # equivalent to compat_features == np.ones(n_links)
            compat = np.einsum('ij,ik,il->jkl', src_type, trg_type, Y_link)

        second_order = []

        if self.coparents_ or self.grandparents_ or self.siblings_:
            link = {(a, b): k for k, (a, b) in enumerate(x.link_to_prop)}
            if self.coparents_:
                second_order.extend(y_link[link[a, b]] & y_link[link[c, b]]
                                    for a, b, c in x.second_order)
            if self.grandparents_:
                second_order.extend(y_link[link[a, b]] & y_link[link[b, c]]
                                    for a, b, c in x.second_order)
            if self.siblings_:
                second_order.extend(y_link[link[b, a]] & y_link[link[b, c]]
                                    for a, b, c in x.second_order)
        second_order = np.array(second_order)

        return Y_node, Y_link, compat, second_order