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NeuralNetworkTestcase.py
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NeuralNetworkTestcase.py
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from NeuralNetwork import Neuron, NeuralNetwork
import unittest
class NeuronStaticTestcase(unittest.TestCase):
def test_sigma(self):
self.assertTrue(Neuron.equal(Neuron.sigma(0.0), 0.5))
self.assertTrue(Neuron.equal(Neuron.sigma(1.0), 0.75))
self.assertTrue(Neuron.equal(Neuron.sigma(-1.0), 0.25))
def test_sigma_derivative(self):
self.assertTrue(Neuron.equal(Neuron.sigma_derivative(0.0), 0.25))
self.assertTrue(Neuron.equal(Neuron.sigma_derivative(-5), 0.0))
self.assertTrue(Neuron.equal(Neuron.sigma_derivative(+5), 0.0))
def test_sigma_derivative_with_sigma(self):
for x in range(-5, 5):
alternative = Neuron.sigma(x) - Neuron.sigma(x) * Neuron.sigma(x)
self.assertAlmostEqual(Neuron.sigma_derivative(x), alternative, 5)
for x in range(-5, 5):
alternative = Neuron.sigma(x) * (1 - Neuron.sigma(x))
self.assertAlmostEqual(Neuron.sigma_derivative(x), alternative, 5)
def test_equal(self):
self.assertTrue(Neuron.equal(0.0, 0.0))
self.assertTrue(Neuron.equal(0.0, 0.01))
self.assertTrue(Neuron.equal(0.0, 0.05))
self.assertTrue(Neuron.equal(1.0, 0.95))
self.assertTrue(Neuron.equal(1.0, 1.05))
self.assertFalse(Neuron.equal(0.0, 1.0))
self.assertFalse(Neuron.equal(1.0, 0.0))
class NeuronTestcase(unittest.TestCase):
def setUp(self):
self.neuron = Neuron(['a', 'b', 'c'])
self.neuron.input_weights['a'] = 0.25
self.neuron.input_weights['b'] = 0.50
self.neuron.input_weights['c'] = 0.75
def test_calc(self):
self.assertAlmostEqual(self.neuron.calc({'a': 1.0, 'b': 0.0, 'c': 0.0}), 0.562177, 4)
self.assertAlmostEqual(self.neuron.calc({'a': 0.0, 'b': 1.0, 'c': 0.0}), 0.622459, 4)
self.assertAlmostEqual(self.neuron.calc({'a': 0.0, 'b': 0.0, 'c': 1.0}), 0.679179, 4)
self.assertAlmostEqual(self.neuron.calc({'a': 1.0, 'b': 1.0, 'c': 1.0}), 0.817574, 4)
self.assertAlmostEqual(self.neuron.calc({'a': 1.0, 'b': 1.0, 'c': 0.0}), 0.679179, 4)
self.assertAlmostEqual(self.neuron.calc({'a': 1.0, 'b': 0.0, 'c': 1.0}), 0.731059, 4)
self.assertAlmostEqual(self.neuron.calc({'a': 0.0, 'b': 1.0, 'c': 1.0}), 0.7773, 4)
class NeuralNetworkTestcase(unittest.TestCase):
def setUp(self):
self.nn = NeuralNetwork(['a', 'b'], 2)
self.nn.hidden_neurons[0].input_weights['a'] = 0.25
self.nn.hidden_neurons[0].input_weights['b'] = 0.50
self.nn.hidden_neurons[0].bias = 0.0
self.nn.hidden_neurons[1].input_weights['a'] = 0.75
self.nn.hidden_neurons[1].input_weights['b'] = 0.75
self.nn.hidden_neurons[1].bias = 0.0
self.nn.final_neuron.input_weights[0] = 0.5
self.nn.final_neuron.input_weights[1] = 0.5
self.nn.final_neuron.bias = 0.0
def test_calc(self):
self.nn.classify({'a': 1.0, 'b': 0.0})
self.assertAlmostEquals(self.nn.final_neuron.last_output, 0.650373, 5)
class NeuralNetworkXORTestcase(unittest.TestCase):
def setUp(self):
self.nn = NeuralNetwork(['a', 'b'], 2)
self.nn.hidden_neurons[0].input_weights['a'] = 1.0
self.nn.hidden_neurons[0].input_weights['b'] = 1.0
self.nn.hidden_neurons[0].bias = 0.0
self.nn.hidden_neurons[1].input_weights['a'] = 1.0
self.nn.hidden_neurons[1].input_weights['b'] = 1.0
self.nn.hidden_neurons[1].bias = 0.0
self.nn.final_neuron.input_weights[0] = -1
self.nn.final_neuron.input_weights[1] = 1
self.nn.final_neuron.bias = 0.0
def test_classifiy(self):
self.assertAlmostEquals(self.nn.classify({'a': 1.0, 'b': 0.0}), 1.0, 5)
self.assertAlmostEquals(self.nn.classify({'a': 0.0, 'b': 1.0}), 1.0, 5)
self.assertAlmostEquals(self.nn.classify({'a': 1.0, 'b': 1.0}), 0.0, 5)
self.assertAlmostEquals(self.nn.classify({'a': 0.0, 'b': 0.0}), 0.0, 5)
def test_train(self):
self.nn = NeuralNetwork(['a', 'b'], 2)
self.nn.train([[{'a': 1.0, 'b': 0.0}, 1.0]])
self.nn.train([[{'a': 0.0, 'b': 1.0}, 1.0]])
self.nn.train([[{'a': 1.0, 'b': 0.0}, 1.0]])
self.nn.train([[{'a': 0.0, 'b': 1.0}, 1.0]])
self.nn.train([[{'a': 1.0, 'b': 0.0}, 1.0]])
self.nn.train([[{'a': 0.0, 'b': 1.0}, 1.0]])
self.nn.train([[{'a': 1.0, 'b': 0.0}, 1.0]])
self.nn.train([[{'a': 0.0, 'b': 1.0}, 1.0]])
self.assertAlmostEquals(self.nn.classify({'a': 1.0, 'b': 0.0}), 1.0, 5)
self.assertAlmostEquals(self.nn.classify({'a': 0.0, 'b': 1.0}), 1.0, 5)
self.assertAlmostEquals(self.nn.classify({'a': 1.0, 'b': 1.0}), 0.0, 5)
self.assertAlmostEquals(self.nn.classify({'a': 0.0, 'b': 0.0}), 0.0, 5)
self.nn.hidden_neurons[0].input_weights
if __name__ == '__main__':
unittest.main()