This example generates a Mapper built from a point-cloud sampled from a 3D model of a cat. `Visualization of the cat mapper <../../_static/cat.html>`_ """ import numpy as np import sklearn import kmapper as km data = np.genfromtxt('data/cat-reference.csv', delimiter=',') mapper = km.KeplerMapper(verbose=2) lens = mapper.fit_transform(data) graph = mapper.map(lens, data, clusterer=sklearn.cluster.DBSCAN(eps=0.1, min_samples=5), cover=km.Cover(n_cubes=15, perc_overlap=0.2)) mapper.visualize(graph, path_html="output/cat.html") km.draw_matplotlib(graph) import matplotlib.pyplot as plt plt.show()
tooltip_s) # need to make sure to feed it as a NumPy array, not a list # Initialize to use t-SNE with 2 components (reduces data to 2 dimensions). Also note high overlap_percentage. mapper = km.KeplerMapper(verbose=2) # Fit and transform data projected_data = mapper.fit_transform(data, projection=sklearn.manifold.TSNE()) # Create the graph (we cluster on the projected data and suffer projection loss) graph = mapper.map(projected_data, clusterer=sklearn.cluster.DBSCAN(eps=0.3, min_samples=15), cover=km.Cover(35, 0.4)) # Create the visualizations (increased the graph_gravity for a tighter graph-look.) print("Output graph examples to html") # Tooltips with image data for every cluster member mapper.visualize(graph, title="Handwritten digits Mapper", path_html="output/digits_custom_tooltips.html", color_values=labels, custom_tooltips=tooltip_s) # Tooltips with the target y-labels for every cluster member mapper.visualize(graph, title="Handwritten digits Mapper", path_html="output/digits_ylabel_tooltips.html", custom_tooltips=labels) # Matplotlib examples km.draw_matplotlib(graph, layout="spring") plt.show()
def test_nx_input(self, mapper): draw_matplotlib(km.to_networkx(mapper))
copy=True, preference=None, affinity='euclidean', verbose=False)) ############################################################################################################## ###creacion de las vizualizaciones(Incrementado el graph_gravity para una apariencia gráfica más ajustada.)### ############################################################################################################## print("Output: Grafo de ejemplo para HTML") ### Tooltip con datos de imagen para cada miembro del cluster mapper.visualize( graph, title="Algoritmo Mapper en digitos escritos a mano", path_html= "C:\\Users\ServW10\Documents\Spyder Projects\Mapper_AffinityPropagation_dataCluster.html", #color_function=labels, custom_tooltips=tooltip_s) ### Toolptips con el target y-labels para cada miembro del cluster mapper.visualize( graph, title="Algoritmo Mapper en digitos escritos a mano", path_html= "C:\\Users\ServW10\Documents\Spyder Projects\Mapper_AffinityPropagation_labelsCluster.html", custom_tooltips=y) # Matplotlib ejemplo para mostrar en consola y comparar km.draw_matplotlib(graph) #, layout="spring" plt.show()
def test_mapper_input(self, mapper): draw_matplotlib(mapper)