def test_simple_perseptron_predict():
sp = SimplePerceptron(3,1,threshold=1.0)
assert sp.predict([0,0,0]) == [0]
assert sp.predict([0,0,1]) == [1]
assert sp.predict([0,1,0]) == [1]
assert sp.predict([1,0,0]) == [1]
assert sp.predict([0,1,1]) == [1]
assert sp.predict([1,0,1]) == [1]
assert sp.predict([1,1,0]) == [1]
assert sp.predict([1,1,1]) == [1]
def simple_sample():
sp = SimplePerceptron( input_neuron_num = 2,
output_neuron_num = 1,
threshold = 1.0,
learning_coefficient = 0.5,
output_function_type = 0)
train_data = [
[[0,0,],[0]],
[[0,1,],[1]],
[[1,0,],[0]],
[[1,1,],[1]],
]
print '---- before'
print sp.predict([0,0,])
print sp.predict([0,1,])
print sp.predict([1,0,])
print sp.predict([1,1,])
for i in range(100):
sp.train(train_data)
print '---- after'
print sp.predict([0,0,])
print sp.predict([0,1,])
print sp.predict([1,0,])
print sp.predict([1,1,])
