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File Content: `plot_digits_agglomeration.py`

#!/usr/bin/python
# -*- coding: utf-8 -*-

"""
=========================================================
Feature agglomeration
=========================================================

These images how similar features are merged together using
feature agglomeration.
"""
print(__doc__)

# Code source: Gaël Varoquaux
# Modified for documentation by Jaques Grobler
# License: BSD 3 clause

import numpy as np
import matplotlib.pyplot as plt

from sklearn import datasets, cluster
from sklearn.feature_extraction.image import grid_to_graph

digits = datasets.load_digits()
images = digits.images
X = np.reshape(images, (len(images), -1))
connectivity = grid_to_graph(*images[0].shape)

agglo = cluster.FeatureAgglomeration(connectivity=connectivity,
                                     n_clusters=32)

agglo.fit(X)
X_reduced = agglo.transform(X)

X_restored = agglo.inverse_transform(X_reduced)
images_restored = np.reshape(X_restored, images.shape)
plt.figure(1, figsize=(4, 3.5))
plt.clf()
plt.subplots_adjust(left=.01, right=.99, bottom=.01, top=.91)
for i in range(4):
    plt.subplot(3, 4, i + 1)
    plt.imshow(images[i], cmap=plt.cm.gray, vmax=16, interpolation='nearest')
    plt.xticks(())
    plt.yticks(())
    if i == 1:
        plt.title('Original data')
    plt.subplot(3, 4, 4 + i + 1)
    plt.imshow(images_restored[i], cmap=plt.cm.gray, vmax=16,
               interpolation='nearest')
    if i == 1:
        plt.title('Agglomerated data')
    plt.xticks(())
    plt.yticks(())

plt.subplot(3, 4, 10)
plt.imshow(np.reshape(agglo.labels_, images[0].shape),
           interpolation='nearest', cmap=plt.cm.spectral)
plt.xticks(())
plt.yticks(())
plt.title('Labels')
plt.show()

Name	Size	Permission
README.txt	101 bytes	0644
plot_adjusted_for_chance_measures.py	4300 bytes	0644
plot_affinity_propagation.py	2304 bytes	0644
plot_agglomerative_clustering.py	2931 bytes	0644
plot_agglomerative_clustering_metrics.py	4492 bytes	0644
plot_birch_vs_minibatchkmeans.py	3694 bytes	0644
plot_cluster_comparison.py	4681 bytes	0644
plot_cluster_iris.py	2593 bytes	0644
plot_color_quantization.py	3444 bytes	0644
plot_dbscan.py	2479 bytes	0644
plot_dict_face_patches.py	2747 bytes	0644
plot_digits_agglomeration.py	1694 bytes	0644
plot_digits_linkage.py	2959 bytes	0644
plot_face_compress.py	2479 bytes	0644
plot_face_segmentation.py	2839 bytes	0644
plot_face_ward_segmentation.py	2460 bytes	0644
plot_feature_agglomeration_vs_univariate_selection.py	3903 bytes	0644
plot_kmeans_assumptions.py	2040 bytes	0644
plot_kmeans_digits.py	4524 bytes	0644
plot_kmeans_silhouette_analysis.py	5888 bytes	0644
plot_kmeans_stability_low_dim_dense.py	4324 bytes	0644
plot_mean_shift.py	1793 bytes	0644
plot_mini_batch_kmeans.py	4092 bytes	0644
plot_segmentation_toy.py	3522 bytes	0644
plot_ward_structured_vs_unstructured.py	3369 bytes	0644

File Content: plot_digits_agglomeration.py

File Content: `plot_digits_agglomeration.py`