Using Kepler Mapper in Jupyter Notebook

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import kmapper as km
from kmapper import jupyter # Creates custom CSS full-size Jupyter screen


    

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# Import the class
import kmapper as km

# Some sample data
from sklearn import datasets
data, labels = datasets.make_circles(n_samples=5000, noise=0.03, factor=0.3)

# Initialize
mapper = km.KeplerMapper(verbose=1)

# Fit to and transform the data
projected_data = mapper.fit_transform(data, projection=[0,1]) # X-Y axis

# Create dictionary called 'graph' with nodes, edges and meta-information
graph = mapper.map(projected_data, data, nr_cubes=10)

# Visualize it
html = mapper.visualize(graph, path_html="make_circles_keplermapper_output.html",
                 title="make_circles(n_samples=5000, noise=0.03, factor=0.3)")

# Inline display
# jupyter.display(path_html="http://mlwave.github.io/tda/word2vec-gender-bias.html")
jupyter.display(path_html="make_circles_keplermapper_output.html")


    

    




..Projecting data using: [0, 1]

..Scaling with: MinMaxScaler(copy=True, feature_range=(0, 1))

Mapping on data shaped (5000, 2) using lens shaped (5000, 2)

Creating 100 hypercubes.

Created 89 edges and 58 nodes in 0:00:00.142366.
Wrote visualization to: make_circles_keplermapper_output.html






    

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