Example #1
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def test_plot2d_graph():
    df = pd.DataFrame([[1, 1], [6, 5], [6, 6], [0, 0], [1, 2], [2, 1], [5, 5],
                       [7, 6]])

    pregraph = knn_graph(df, 3)
    graph = pre_part_graph(pregraph, 10, df)
    plot2d_graph(graph)
Example #2
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def test_pre_part_graph():
    df = pd.DataFrame([[1, 1], [6, 5], [6, 6], [0, 0], [1, 2], [5, 5], [7, 2]])
    k = 3

    pregraph = knn_graph(df, k, verbose=False)
    _ = pre_part_graph(pregraph, 2, df, verbose=False)
    print(df["cluster"].values)
    assert (df["cluster"].values == np.array([0, 1, 1, 0, 0, 1, 1])).all()
Example #3
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def test_rebuild_labels():
    df = pd.DataFrame([[1, 1], [6, 5], [6, 6], [0, 0], [1, 2], [5, 5], [7, 2]])

    pregraph = knn_graph(df, 3, verbose=False)
    _ = pre_part_graph(pregraph, 10, df, verbose=False)

    df_bis = rebuild_labels(df)

    assert sorted(list(df_bis["cluster"])) == [1, 1, 1, 1, 2, 2, 2]
Example #4
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def test_len_edges():
    df = pd.DataFrame([[1, 1], [6, 5], [6, 6], [0, 0], [1, 2], [5, 5], [7, 2]])

    pregraph = knn_graph(df, 3, verbose=False)
    graph = pre_part_graph(pregraph, 10, df, verbose=False)

    condition0 = len_edges(graph, [0, 3, 4]) == 3
    condition1 = len_edges(graph, [1, 2, 5, 6]) == 6

    assert condition0 & condition1
Example #5
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def test_connecting_edges():
    df = pd.DataFrame([[1, 1], [6, 5], [6, 6], [0, 0], [1, 2], [5, 5], [7, 2]])

    pregraph = knn_graph(df, 3, verbose=False)
    graph = pre_part_graph(pregraph, 10, df, verbose=False)

    assert connecting_edges(([0, 3, 4], [1, 2, 5, 6]), graph) == [
        (0, 5),
        (3, 5),
        (4, 5),
    ]
Example #6
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def test_get_cluster():
    df = pd.DataFrame([[1, 1], [6, 5], [6, 6], [0, 0], [1, 2], [5, 5], [7, 2]])
    k = 3

    pregraph = knn_graph(df, 3, verbose=False)
    graph = pre_part_graph(pregraph, k, df, verbose=False)

    condition0 = get_cluster(graph, [0]) == [0, 3, 4]
    condition1 = get_cluster(graph, [k - 1]) == [1, 2, 5, 6]

    assert condition0 & condition1
Example #7
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def test_conn_comp():
    df = pd.DataFrame([[1, 1], [6, 5], [6, 6], [0, 0], [1, 2], [2, 1], [5, 5],
                       [7, 6]])

    pregraph = knn_graph(df, 3)
    graph = pre_part_graph(pregraph, 10, df)

    res = conn_comp(graph)
    condition0 = sorted(res[0]) == [0, 3, 4, 5]
    condition1 = sorted(res[1]) == [1, 2, 6, 7]

    assert condition0 & condition1
Example #8
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def test_plot2d_data():
    df = pd.DataFrame(make_blobs(60, random_state=42)[0])
    knn = 6

    pregraph = knn_graph(df, knn, verbose=False)
    graph = pre_part_graph(pregraph, 10, df, verbose=False)
    df, max_score, ci = merge_best(graph=graph,
                                   df=df,
                                   a=2,
                                   k=3,
                                   verbose=False,
                                   verbose2=False)

    plot2d_data(df)
Example #9
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def test_merge_best():
    df = pd.DataFrame(make_blobs(60, random_state=42)[0])
    knn = 6

    pregraph = knn_graph(df, knn, verbose=False)
    graph = pre_part_graph(pregraph, 10, df, verbose=False)
    df, max_score, ci = merge_best(graph=graph,
                                   df=df,
                                   a=2,
                                   k=3,
                                   verbose=False,
                                   verbose2=False)

    condition0 = round(max_score) == 1
    condition1 = ci == 5

    assert condition0 & condition1