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figure-uniform.py
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figure-uniform.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (c) 2009 Nicolas Rougier - INRIA - CORTEX Project
#
# This program 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 of the License, or (at your option)
# any later version.
#
# This program 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 this program. If not, see <http://www.gnu.org/licenses/>.
#
# Contact: CORTEX Project - INRIA
# INRIA Lorraine,
# Campus Scientifique, BP 239
# 54506 VANDOEUVRE-LES-NANCY CEDEX
# FRANCE
if __name__ == '__main__':
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from network import NG,SOM,DSOM
from distribution import uniform, normal, ring
n = 8
epochs = 20000
N = 10000
np.random.seed(123)
samples = uniform(n=N)
print 'Neural Gas'
np.random.seed(123)
ng = NG((n,n,2))
ng.learn(samples,epochs)
print 'Self-Organizing Map'
np.random.seed(123)
som = SOM((n,n,2))
som.learn(samples,epochs)
print 'Dynamic Self-Organizing Map'
np.random.seed(123)
dsom = DSOM((n,n,2), elasticity=1.75)
dsom.learn(samples,epochs)
fig = plt.figure(figsize=(21,8))
fig.patch.set_alpha(0.0)
axes = plt.subplot(1,3,1)
ng.plot(axes)
axes = fig.add_subplot(1,3,2)
som.plot(axes)
axes = fig.add_subplot(1,3,3)
dsom.plot(axes)
fig.savefig('uniform.png',dpi=150)