Function df

test/test_da.py:986–994

(G)

        return res

    def df(G):
        W = nx.zeros(G.shape, type_as=G)
        for i in range(G.shape[1]):
            for lab in lstlab:
                temp = G[labels_a == lab, i]
                n = nx.norm(temp)
                if n:
                    W[labels_a == lab, i] = temp / n
        return W

    # new vectorized implementation for the cost estimator
    labels_u, labels_idx = nx.unique(labels_a, return_inverse=True)