e52e9c8d7536b6315da655164951060642a52707,sklearn/manifold/tests/test_t_sne.py,,test_barnes_hut_angle,#,609

Before Change

        random_state = check_random_state(0)
        distances = random_state.randn(n_samples, n_features)
        distances = distances.astype(np.float32)
        distances = abs(distances.dot(distances.T))
        np.fill_diagonal(distances, 0.0)
        params = random_state.randn(n_samples, n_components)
        P = _joint_probabilities(distances, perplexity, verbose=0)

After Change

                                              n_samples, n_components)

        n_neighbors = n_samples - 1
        distances_csr = NearestNeighbors().fit(data).kneighbors_graph(
            n_neighbors=n_neighbors, mode="distance")
        P_bh = _joint_probabilities_nn(distances_csr, perplexity, verbose=0)
        kl_bh, grad_bh = _kl_divergence_bh(params, P_bh, degrees_of_freedom,

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