Python-сообщество

import pybrain
from pybrain.datasets import *
from pybrain.tools.shortcuts import buildNetwork
from pybrain.supervised.trainers import BackpropTrainer
import pickle
import numpy as np
def main():
    ds = SupervisedDataSet(12, 1)
    hello1 = np.load("C://Python27/QPSK/numpyarray/hello1.npy")
    hello2 = np.load("C://Python27/QPSK/numpyarray/hello2.npy")
    hello3 = np.load("C://Python27/QPSK/numpyarray/hello3.npy")
    bugs = np.load("C://Python27/QPSK/numpyarray/bugs.npy")
    b1 = np.load("C://Python27/QPSK/numpyarray/bye-bye-1.npy")
    b2 = np.load("C://Python27/QPSK/numpyarray/bye-bye-2.npy")
    b3 = np.load("C://Python27/QPSK/numpyarray/bye-bye-3.npy")
    b4 = np.load("C://Python27/QPSK/numpyarray/bye-bye-4.npy")
    b5 = np.load("C://Python27/QPSK/numpyarray/bye-bye-5.npy")
    b6 = np.load("C://Python27/QPSK/numpyarray/bye-bye-6.npy")
    ds.addSample( (hello1[0:12]), (0,))
    ds.addSample( (hello2[0:12]), (0,))
    ds.addSample( (hello3[0:12]), (0,))
    ds.addSample( (b1[0:12]), (1,))
    ds.addSample( (b2[0:12]), (1,))
    ds.addSample( (b4[0:12]), (1,))
    ds.addSample( (b5[0:12]), (1,))
    ds.addSample( (b6[0:12]), (1,))
    net = buildNetwork(12, 24, 1, bias=True)
    try:
        f = open('_learned2', 'r')
        net = pickle.load(f)
        f.close()
    except:
        trainer = BackpropTrainer(net, ds, learningrate = 0.01, momentum = 0.99, verbose = False)
        errors = trainer.trainUntilConvergence(dataset=None, maxEpochs=None, verbose=None, continueEpochs=10, validationProportion=0.25)
        f = open('_learned2', 'w')
        pickle.dump(net, f)
        f.close()
    
    print np.round(net.activate(hello1[0:12])[0]), np.round(net.activate(hello2[0:12])[0]), np.round(net.activate(hello3[0:12])[0])
    print np.round(net.activate(bugs[0:12])[0])
    print np.round(net.activate(b3[0:12])[0])
    print np.round(net.activate(b1[0:12])[0]), np.round(net.activate(b2[0:12])[0]), np.round(net.activate(b4[0:12])[0]), np.round(net.activate(b5[0:12])[0]), np.round(net.activate(b6[0:12])[0])
if __name__ == "__main__":
    main()