Ejemplo n.º 1
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def do_analysis(data, lens, name_prefix, nc, po, metric='euclidean'):
    graph = mapper.map(lens,
                       data.values,
                       clusterer=lk.LinkageGap(verbose=0, metric=metric),
                       cover=km.Cover(n_cubes=nc, perc_overlap=po))

    name = "{}_n{}_o{}".format(name_prefix, nc, po)
    mapper.visualize(
        graph,
        # color_values=target.values,
        color_values=lens,
        color_function_name=name_prefix,
        path_html=name + "_nm_diabetes_RM.html",
        title=name + "nm_diabetes_RM")

    nx_graph_simple = expo.kmapper_to_nxmapper(graph)
    expo.cytoscapejson_dump(nx_graph_simple,
                            name + "_nm_diabetes_RM_simple.cyjs")

    extra_data = {x: list(data.loc[:, x]) for x in data.columns}
    extra_transforms = {
        x: np.mean
        for x in extra_data if x != "Clinical_classification"
    }

    nx_graph = expo.kmapper_to_nxmapper(graph,
                                        node_extra_data=extra_data,
                                        node_transforms=extra_transforms)
    expo.cytoscapejson_dump(nx_graph, name + "_nm_diabetes_RM.cyjs")
Ejemplo n.º 2
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def do_analysis(data, lens, name_prefix, nc, po):
    name = "{}_n{}_o{}".format(name_prefix, nc, po)
    graph = mapper.map(lens,
                       data,
                       clusterer=lk.LinkageGap(verbose=0),
                       cover=km.Cover(n_cubes=nc, perc_overlap=po))
    mapper.visualize(graph,
                     color_function=lens,
                     path_html=name + "_cat.html",
                     title=name + "_cat")
Ejemplo n.º 3
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def do_analysis(data, lens, cf, name_prefix, nc, po):
    name = "{:s}_n{:d}_o{:.2f}".format(name_prefix, nc, po)
    graph = mapper.map(lens,
                       data,
                       clusterer=lk.LinkageGap(verbose=0, metric='euclidean'),
                       cover=km.Cover(n_cubes=nc, perc_overlap=po))
    mapper.visualize(graph,
                     color_function=cf,
                     path_html=name + "_travel.html",
                     title=name + "_travel")
Ejemplo n.º 4
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def do_analysis(data, lens, name_prefix, nc, po,metric='euclidean'):
    graph = mapper.map(lens,
                       data.values,
                       clusterer = lk.LinkageGap(verbose=0,metric=metric),
                       cover=km.Cover(n_cubes=nc, perc_overlap=po))

    name = "{}_n{}_o{}".format(name_prefix,nc, po)
    mapper.visualize(graph,
                     # color_function=target.values,
                     color_function=lens,
                     path_html=name + "_nm_diabetes_RM.html",
                     title=name + "nm_diabetes_RM")
Ejemplo n.º 5
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def do_analysis(lens, name_prefix, nc, po):
    graph = mapper.map(
        lens,
        data,
        clusterer=lk.LinkageGap(verbose=0),
        # clusterer=sklearn.cluster.DBSCAN(1, min_samples=0),
        cover=km.Cover(n_cubes=nc, perc_overlap=po))

    name = "{}_n{}_o{}".format(name_prefix, nc, po)
    mapper.visualize(graph,
                     color_function=target,
                     path_html=name + "_iris.html",
                     title=name + "_iris")
def do_analysis(data, dists, lens, name_prefix, nc, po):
    name = "{}_n{}_o{}".format(name_prefix, nc, po)
    graph = mapper.map(lens,
                       dists,
                       clusterer=lk.LinkageGap(verbose=0,
                                               metric="precomputed"),
                       precomputed=True,
                       cover=km.Cover(n_cubes=nc, perc_overlap=po))
    mapper.visualize(graph,
                     color_values=lens,
                     color_function_name=name_prefix,
                     path_html=name + "_cat.html",
                     title=name + "_cat")
Ejemplo n.º 7
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def do_analysis(data, lens, cf, name_prefix, nc, po):
    name = "{:s}_n{:d}_o{:.2f}".format(name_prefix, nc, po)
    graph = mapper.map(lens,
                       data.values,
                       clusterer=lk.LinkageGap(verbose=0, metric='euclidean'),
                       cover=km.Cover(n_cubes=nc, perc_overlap=po))
    mapper.visualize(graph,
                     color_function=cf,
                     path_html=name + "_travel.html",
                     title=name + "_travel")

    extra_data = {x: list(data.loc[:, x]) for x in data.columns}
    extra_transforms = {x: np.mean for x in extra_data}

    nx_graph = expo.kmapper_to_nxmapper(graph,
                                        node_extra_data=extra_data,
                                        node_transforms=extra_transforms)
    expo.cytoscapejson_dump(nx_graph, name + "_travel.cyjs")
Ejemplo n.º 8
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import kmapper as km

import mapperutils.linkage_gap as lk
import mapperutils.visualization as viz

mapper = km.KeplerMapper(verbose=2)

hand = trimesh.load_mesh("../0_data/hand/hand_simplified3k5.stl")
data = np.array(hand.vertices)
lens = data[:, 1:2]

plot = True
if plot:
    viz.scatter3d(data, lens, colorsMap='viridis', show=False)
    viz.plt.gca().view_init(elev=90, azim=0)
    viz.axisEqual3D(viz.plt.gca())
    viz.plt.show()

n = 7
p = 0.2
graph = mapper.map(lens,
                   data,
                   clusterer=lk.LinkageGap(verbose=0),
                   cover=km.Cover(n_cubes=n, perc_overlap=p))

name = "n{}_p{}".format(n, p)
mapper.visualize(graph,
                 color_function=lens,
                 path_html="hand_only_" + name + ".html",
                 title="hand, " + name)
Ejemplo n.º 9
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def test_heuristics_precomputed():
    dists = spd.squareform(spd.pdist(X))

    fg = lk.LinkageGap(heuristic='firstgap', metric='precomputed').fit(dists)
    assert len(np.unique(fg.labels_)) == 3
Ejemplo n.º 10
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def test_heuristics():
    fg = lk.LinkageGap(heuristic='firstgap').fit(X)
    assert len(np.unique(fg.labels_)) == 3

    with pytest.raises(Exception):
        fg = lk.LinkageGap(heuristic='foobar')