def test_can_create_cyclical_network(self):
a = model.NotNeuron(None)
a.inputs = [a]
net = model.Network(a)
self.assertEqual(list(net), [a])
def build_net(a, b):
"""
[1] Built as guided by the description provided.
For the equation of the network, see:
http://hyperphysics.phy-astr.gsu.edu/hbase/electronic/ietron/xor4.gif
"""
return model.AndNeuron(
model.OrNeuron(a, b),
model.NotNeuron(model.AndNeuron(a, b))
),
def test_not_neuron(self):
a = model.Input("a")
gate = model.NotNeuron(a)
a.state = 0
gate.update()
self.assertEquals(gate.state, 1)
a.state = 1
gate.update()
self.assertEquals(gate.state, 0)
def test_cyclical_network_is_self_propelling(self):
a = model.NotNeuron(None, state=0)
a.inputs = [a]
net = model.Network(a)
self.assertEqual(a.state, 0)
net.update()
self.assertEqual(a.state, 1)
net.update()
self.assertEqual(a.state, 0)
net.update()
self.assertEqual(a.state, 1)
net.update()
self.assertEqual(a.state, 0)
def test_cyclical_network_doesnt_explode_during_update(self):
a = model.NotNeuron(None)
a.inputs = [a]
net = model.Network(a)
net.update()