def test_non_consicutive_labels():
    # regression tests for labels with gaps
    h, c, v = homogeneity_completeness_v_measure([0, 0, 0, 2, 2, 2], [0, 1, 0, 1, 2, 2])
    assert_almost_equal(h, 0.67, 2)
    assert_almost_equal(c, 0.42, 2)
    assert_almost_equal(v, 0.52, 2)

    h, c, v = homogeneity_completeness_v_measure([0, 0, 0, 1, 1, 1], [0, 4, 0, 4, 2, 2])
    assert_almost_equal(h, 0.67, 2)
    assert_almost_equal(c, 0.42, 2)
    assert_almost_equal(v, 0.52, 2)

def test_not_complete_and_not_homogeneous_labeling():
    # neither complete nor homogeneous but not so bad either
    h, c, v = homogeneity_completeness_v_measure(
        [0, 0, 0, 1, 1, 1],
        [0, 1, 0, 1, 2, 2])
    assert_almost_equal(h, 0.67, 2)
    assert_almost_equal(c, 0.42, 2)
    assert_almost_equal(v, 0.52, 2)

def test_complete_but_not_homogeneous_labeling():
    # complete but not homogeneous clustering
    h, c, v = homogeneity_completeness_v_measure(
        [0, 0, 1, 1, 2, 2],
        [0, 0, 1, 1, 1, 1])
    assert_almost_equal(h, 0.58, 2)
    assert_almost_equal(c, 1.00, 2)
    assert_almost_equal(v, 0.73, 2)

def test_homogeneous_but_not_complete_labeling():
    # homogeneous but not complete clustering
    h, c, v = homogeneity_completeness_v_measure(
        [0, 0, 0, 1, 1, 1],
        [0, 0, 0, 1, 2, 2])
    assert_almost_equal(h, 1.00, 2)
    assert_almost_equal(c, 0.69, 2)
    assert_almost_equal(v, 0.81, 2)

def test_non_consecutive_labels():
    # regression tests for labels with gaps
    h, c, v = homogeneity_completeness_v_measure(
        [0, 0, 0, 2, 2, 2],
        [0, 1, 0, 1, 2, 2])
    assert_almost_equal(h, 0.67, 2)
    assert_almost_equal(c, 0.42, 2)
    assert_almost_equal(v, 0.52, 2)

    h, c, v = homogeneity_completeness_v_measure(
        [0, 0, 0, 1, 1, 1],
        [0, 4, 0, 4, 2, 2])
    assert_almost_equal(h, 0.67, 2)
    assert_almost_equal(c, 0.42, 2)
    assert_almost_equal(v, 0.52, 2)

    ari_1 = adjusted_rand_score([0, 0, 0, 1, 1, 1], [0, 1, 0, 1, 2, 2])
    ari_2 = adjusted_rand_score([0, 0, 0, 1, 1, 1], [0, 4, 0, 4, 2, 2])
    assert_almost_equal(ari_1, 0.24, 2)
    assert_almost_equal(ari_2, 0.24, 2)

def test_beta_parameter():
    # test for when beta passed to
    # homogeneity_completeness_v_measure
    # and v_measure_score
    beta_test = 0.2
    h_test = 0.67
    c_test = 0.42
    v_test = ((1 + beta_test) * h_test * c_test
              / (beta_test * h_test + c_test))

    h, c, v = homogeneity_completeness_v_measure(
        [0, 0, 0, 1, 1, 1],
        [0, 1, 0, 1, 2, 2],
        beta=beta_test)
    assert_almost_equal(h, h_test, 2)
    assert_almost_equal(c, c_test, 2)
    assert_almost_equal(v, v_test, 2)

    v = v_measure_score(
        [0, 0, 0, 1, 1, 1],
        [0, 1, 0, 1, 2, 2],
        beta=beta_test)
    assert_almost_equal(v, v_test, 2)

def test_homogeneity_completeness_v_measure_sparse():
    labels_a = np.array([1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3])
    labels_b = np.array([1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 3, 1, 3, 3, 3, 2, 2])
    h, c, v = homogeneity_completeness_v_measure(labels_a, labels_b)
    h_s, c_s, v_s = homogeneity_completeness_v_measure(labels_a, labels_b, sparse=True)
    assert_array_almost_equal([h, c, v], [h_s, c_s, v_s])

cluster_ap = clusterer_ap.fit_predict(data)
cluster_agg_ap = clusterer_agg_ap.fit_predict(data_agg)
cluster_agg_ap2 = clusterer_agg_ap.fit_predict(data_agg2)
cluster_agg_ap4 = clusterer_agg_ap.fit_predict(data_agg4)
cluster_agg_ap4_w = clusterer_agg_ap.fit_predict(data_agg4_w)
cluster_agg_ap4_ws = clusterer_agg_ap.fit_predict(data_agg4_ws)
cluster_agg_ap4_just_season = clusterer_agg_ap.fit_predict(data_agg4_just_season)
cluster_agg_ap4_just_leaf = clusterer_agg_ap.fit_predict(data_agg4_just_leaf)
cluster_agg_ap4_just_seed = clusterer_agg_ap.fit_predict(data_agg4_just_seed)
cluster_agg_ap4_just_weather = clusterer_agg_ap.fit_predict(data_agg4_just_weather)


mutual_info_score = adjusted_mutual_info_score(labels,cluster_ap)
mutual_info_score_agg = adjusted_mutual_info_score(labels,cluster_agg_ap)

v_score = homogeneity_completeness_v_measure(labels,cluster_ap)
v_score_agg2 = homogeneity_completeness_v_measure(labels,cluster_agg_ap2)
v_score_agg4 = homogeneity_completeness_v_measure(labels,cluster_agg_ap4)
v_score_agg4_w = homogeneity_completeness_v_measure(labels,cluster_agg_ap4_w)
v_score_agg4_ws = homogeneity_completeness_v_measure(labels,cluster_agg_ap4_ws)
v_score_agg4_just_season = homogeneity_completeness_v_measure(labels,cluster_agg_ap4_just_season)
v_score_agg4_just_leaf = homogeneity_completeness_v_measure(labels,cluster_agg_ap4_just_leaf)
v_score_agg4_just_seed = homogeneity_completeness_v_measure(labels,cluster_agg_ap4_just_seed)
v_score_agg4_just_weather = homogeneity_completeness_v_measure(labels,cluster_agg_ap4_just_weather)


print(v_score)
print(v_score_agg2)
print(v_score_agg4_just_leaf)
print(v_score_agg4_just_seed)
print(v_score_agg4) # Leaf and seed