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