**********************
Competing layer (newc)
**********************

Use  :py:func:`neurolab.net.newc`

::

	import neurolab as nl
	import numpy as np
	import numpy.random as rand

	# Create train samples
	centr = np.array([[0.2, 0.2], [0.4, 0.4], [0.7, 0.3], [0.2, 0.5]])
	rand_norm = 0.05 * rand.randn(100, 4, 2)

	inp = np.array([centr + r for r in rand_norm]).reshape(100*4, 2)
	rand.shuffle(inp) 

	# Create net with 2 inputs and 4 neurons
	net = nl.net.newc([[0.0, 1.0],[0.0, 1.0]], 4)
	# train with rule: Conscience Winner Take All algoritm (CWTA)
	error = net.train(inp, epochs=200, show=20)

	# Plot results:
	import pylab as pl
	pl.title('Classification Problem')
	pl.subplot(211)
	pl.plot(error)
	pl.xlabel('Epoch number')
	pl.ylabel('error (default MAE)')

	w = net.layers[0].np['w']

	pl.subplot(212)
	pl.plot(inp[:,0], inp[:,1], '.', \
			centr[:,0], centr[:, 1] , 'yv', \
			w[:,0], w[:,1], 'p')
	pl.legend(['train samples', 'real centers', 'train centers'])
	pl.show()

:Result:
	.. image:: _static/classifer.png