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# Aproximation of the 0.5*sin(x)

Import: |
    >>> import neurolab as nl
    >>> import numpy as np
Create train samples:
    >>> input = np.linspace(-10, 10, 30).reshape([30,1])
    >>> target = (np.sin(input) * 0.5)
    >>> # Create network with 2 layers and random initialized
    >>> net = nl.net.newff([[-0.5, 0.5]],[15, 15, 1])
    >>> # Change train function
    >>> net.trainf = nl.train.train_bfgs
Train process: |
    >>> error = net.train(input, target, epochs=500, goal=0.2)
    >>> output = net.sim(input)
Plot result: |
    >>> import pylab as pl
    >>> pl.title('Aproximation of the 0.5*sin')
    >>> pl.subplot(211)
    >>> pl.plot(error)
    >>> pl.xlabel('Epoch number')
    >>> pl.ylabel('error (default SSE)')
    >>> pl.subplot(212)
    >>> pl.plot(input.flat , target.flat, '.', input.flat, output.flat, 'p')
    >>> pl.legend(['train target', 'net output'])
    >>> pl.show()
Result: |

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