Python if_matplotlib Examples

Example #1

File: test_hdbscan.py Project: CyberSift/hdbscan

def test_single_linkage_tree_plot():
    clusterer = HDBSCAN(gen_min_span_tree=True).fit(X)
    if_matplotlib(clusterer.single_linkage_tree_.plot)(cmap='Reds')
    if_matplotlib(clusterer.single_linkage_tree_.plot)(vary_line_width=False,
                                                       truncate_mode='lastp',
                                                       p=10, cmap='none',
                                                       colorbar=False)

Example #2

def test_single_linkage_tree_plot():
    clusterer = HDBSCAN(gen_min_span_tree=True).fit(X)
    if_matplotlib(clusterer.single_linkage_tree_.plot)(cmap='Reds')
    if_matplotlib(clusterer.single_linkage_tree_.plot)(vary_line_width=False,
                                                       truncate_mode='lastp',
                                                       p=10, cmap='none',
                                                       colorbar=False)

Example #3

def test_condensed_tree_plot():
    clusterer = HDBSCAN(gen_min_span_tree=True).fit(X)
    if_matplotlib(clusterer.condensed_tree_.plot)(
        select_clusters=True,
        label_clusters=True,
        selection_palette=('r', 'g', 'b'),
        cmap='Reds')
    if_matplotlib(clusterer.condensed_tree_.plot)(log_size=True,
                                                  colorbar=False,
                                                  cmap='none')

Example #4

File: test_hdbscan.py Project: CyberSift/hdbscan

def test_condensed_tree_plot():
    clusterer = HDBSCAN(gen_min_span_tree=True).fit(X)
    if_matplotlib(clusterer.condensed_tree_.plot)(
        select_clusters=True,
        label_clusters=True,
        selection_palette=('r', 'g', 'b'),
        cmap='Reds')
    if_matplotlib(clusterer.condensed_tree_.plot)(log_size=True,
                                                  colorbar=False,
                                                  cmap='none')

Example #5

def test_min_span_tree_plot():
    clusterer = HDBSCAN(gen_min_span_tree=True).fit(X)
    if_matplotlib(clusterer.minimum_spanning_tree_.plot)(edge_cmap='Reds')

    H, y = make_blobs(n_samples=50, random_state=0, n_features=10)
    H = StandardScaler().fit_transform(H)

    clusterer = HDBSCAN(gen_min_span_tree=True).fit(H)
    if_matplotlib(clusterer.minimum_spanning_tree_.plot)(edge_cmap='Reds',
                                                         vary_line_width=False,
                                                         colorbar=False)

    H, y = make_blobs(n_samples=50, random_state=0, n_features=40)
    H = StandardScaler().fit_transform(H)

    clusterer = HDBSCAN(gen_min_span_tree=True).fit(H)
    if_matplotlib(clusterer.minimum_spanning_tree_.plot)(edge_cmap='Reds',
                                                         vary_line_width=False,
                                                         colorbar=False)

Example #6

File: test_hdbscan.py Project: CyberSift/hdbscan

def test_min_span_tree_plot():
    clusterer = HDBSCAN(gen_min_span_tree=True).fit(X)
    if_matplotlib(clusterer.minimum_spanning_tree_.plot)(edge_cmap='Reds')

    H, y = make_blobs(n_samples=50, random_state=0, n_features=10)
    H = StandardScaler().fit_transform(H)

    clusterer = HDBSCAN(gen_min_span_tree=True).fit(H)
    if_matplotlib(clusterer.minimum_spanning_tree_.plot)(edge_cmap='Reds',
                                                         vary_line_width=False,
                                                         colorbar=False)

    H, y = make_blobs(n_samples=50, random_state=0, n_features=40)
    H = StandardScaler().fit_transform(H)

    clusterer = HDBSCAN(gen_min_span_tree=True).fit(H)
    if_matplotlib(clusterer.minimum_spanning_tree_.plot)(edge_cmap='Reds',
                                                         vary_line_width=False,
                                                         colorbar=False)

Example #7

File: test_hdbscan.py Project: Natural209X/hdbscan

def test_condensed_tree_plot():
    clusterer = HDBSCAN().fit(X)
    if_matplotlib(clusterer.condensed_tree_.plot)()

Example #8

File: test_hdbscan.py Project: ddcamiu/hdbscan

def test_condensed_tree_plot():
    clusterer = HDBSCAN().fit(X)
    if_matplotlib(clusterer.condensed_tree_.plot)()