def _random_genes(self):
net = Network(2, 1)
net.add_neuron(connections=['in0', 'in1'],
weights=[self._random_weight(),
self._random_weight()],
bias=self._random_weight(),
activation='sigmoid')
net.add_neuron(connections=['in0', 'in1'],
weights=[self._random_weight(),
self._random_weight()],
bias=self._random_weight(),
activation='sigmoid')
net.neurons['out0'].connections = ['h0', 'h1']
net.neurons['out0'].weights = [
self._random_weight(),
self._random_weight()
]
net.neurons['out0'].neuron_type = 'feed_forward_neuron'
net.neurons['out0'].bias = self._random_weight()
net.neurons['out0'].activation = 'sigmoid'
return net
def main():
net = Network(2, 1)
net.add_neuron(connections=['in0', 'in1'],
weights=[+20, +20],
bias=-30,
activation='sigmoid')
net.add_neuron(connections=['in0', 'in1'],
weights=[-20, -20],
bias=+10,
activation='sigmoid')
net.neurons['out0'].connections = ['h0', 'h1']
net.neurons['out0'].weights = [+20, +20]
net.neurons['out0'].neuron_type = 'feed_forward_neuron'
net.neurons['out0'].bias = -10
net.neurons['out0'].activation = 'sigmoid'
net.save_network_to_file('truth.network.json')
print('Truth network (#%s):' % net.name)
print('%0.4f' % net.fitness(dataset))
test_sample(net, [0, 0])
test_sample(net, [0, 1])
test_sample(net, [1, 0])
test_sample(net, [1, 1])
print '------------------------------------'
try:
net = Network()
net.load_network_from_file('result.network.json')
print('result network (#%s):' % net.name)
print('%0.4f' % net.fitness(dataset))
test_sample(net, [0, 0])
test_sample(net, [0, 1])
test_sample(net, [1, 0])
test_sample(net, [1, 1])
print '------------------------------------'
except IOError:
pass