clustering.py

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

# Copyright (C) 2018  David Arroyo Menéndez

# Author: David Arroyo Menéndez <davidam@gnu.org>
# Maintainer: David Arroyo Menéndez <davidam@gnu.org>

# This file is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3, or (at your option)
# any later version.

# This file is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.

# You should have received a copy of the GNU General Public License
# along with GNU Emacs; see the file COPYING.  If not, write to
# the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor,
# Boston, MA 02110-1301 USA,
import matplotlib.pyplot as plt
from matplotlib import style
import numpy as np
from sklearn.cluster import KMeans
style.use('ggplot')

#ORIGINAL:

X = np.array([[1, 2],
              [1.5, 1.8],
              [5, 8],
              [8, 9],
              [1, 0.6],
              [9, 11]])


plt.scatter(X[:, 0],X[:, 1], s=150, linewidths = 5, zorder = 10)
plt.show()

clf = KMeans(n_clusters=2)
clf.fit(X)

centroids = clf.cluster_centers_
labels = clf.labels_

colors = ["g.","r.","c.","y."]
for i in range(len(X)):
    plt.plot(X[i][0], X[i][1], colors[labels[i]], markersize = 10)
plt.scatter(centroids[:, 0],centroids[:, 1], marker = "x", s=150, linewidths = 5, zorder = 10)
plt.show()