gigiduru

import neurolab as nl
import numpy as np

# Create train samples
x = np.linspace(-7, 7, 20)
y = np.sin(x)

xG = np.linspace(-7, 7, 200)
yG = np.sin(xG)

size = len(x)

inp = x.reshape(size,1)
tar = y.reshape(size,1)

# Create network with 2 layers and random initialized
net = nl.net.newff([[-7, 7]],[5, 1])

# Train network
error = net.train(inp, tar, epochs=500, show=100, goal=0.00001)

# Simulate network
out = net.sim(inp)

# Plot result
import pylab as pl
pl.subplot(211)
pl.plot(error)
pl.xlabel('Epoch number')
pl.ylabel('error (default SSE)')


y2 = net.sim(xG.reshape(xG.size,1)).reshape(xG.size)

y3 = out.reshape(size)

pl.subplot(212)
pl.plot(x , y, 'og', xG,yG,'g',xG, y2, '-r',x, y3, 'ro')
pl.legend(['train target', 'net output'])
pl.show()