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)
