def test_compute_delta(self):
dblActivation = random.random()
dblError = 2.0 * random.random() - 1.0
dblDelta = nn.compute_delta(dblActivation, dblError)
dblActivationPrime = sigmoid_prime_from_sigmoid(dblActivation)
self.assertAlmostEqual(dblError, dblDelta / dblActivationPrime)
self.assertAlmostEqual(dblActivationPrime, dblDelta / dblError)
def test_compute_delta(self):
dblActivation = random.random()
dblError = 2.0*random.random() - 1.0
dblDelta = nn.compute_delta(dblActivation, dblError)
dblActivationPrime = sigmoid_prime_from_sigmoid(dblActivation)
self.assertAlmostEqual(dblError, dblDelta/dblActivationPrime)
self.assertAlmostEqual(dblActivationPrime, dblDelta/dblError)
def test_update_pcpt(self):
dblLearningRate = random.random() + 0.5
cWeight = random.randint(10, 20)
listDblInput = randlist(-0.5, 0.5, cWeight)
listDblW = randlist(-0.5, 0.5, cWeight)
dblW0 = random.random() - 0.5
dblActivation = random.random() * 0.5 + 0.25
dblError = random.random() - 0.5
dblDelta = nn.compute_delta(dblActivation, dblError)
ixPcpt = random.randint(0, 100)
pcpt = nn.Perceptron(list(listDblW), dblW0, ixPcpt)
nn.update_pcpt(pcpt, listDblInput, dblDelta, dblLearningRate)
self.assertEqual(len(listDblW), len(pcpt.listDblW))
dblProductBase = dblLearningRate * dblActivation * dblError
for dblW, dblIn, dblWOrig in zip(pcpt.listDblW, listDblInput, listDblW):
dblProduct = dblProductBase * dblIn
dblExpected = dblProduct - (dblW - dblWOrig)
self.assertAlmostEqual(dblProduct * dblActivation, dblExpected)
self.assertAlmostEqual(dblProductBase * dblActivation, dblProductBase - (pcpt.dblW0 - dblW0))
def test_update_pcpt(self):
dblLearningRate = random.random() + 0.5
cWeight = random.randint(10,20)
listDblInput = randlist(-0.5,0.5,cWeight)
listDblW = randlist(-0.5,0.5,cWeight)
dblW0 = random.random() - 0.5
dblActivation = random.random()*0.5 + 0.25
dblError = random.random() - 0.5
dblDelta = nn.compute_delta(dblActivation,dblError)
ixPcpt = random.randint(0,100)
pcpt = nn.Perceptron(list(listDblW), dblW0, ixPcpt)
nn.update_pcpt(pcpt, listDblInput, dblDelta, dblLearningRate)
self.assertEqual(len(listDblW), len(pcpt.listDblW))
dblProductBase = dblLearningRate*dblActivation*dblError
for dblW,dblIn,dblWOrig in zip(pcpt.listDblW,listDblInput,listDblW):
dblProduct = dblProductBase*dblIn
dblExpected = dblProduct - (dblW - dblWOrig)
self.assertAlmostEqual(dblProduct*dblActivation, dblExpected)
self.assertAlmostEqual(dblProductBase*dblActivation,
dblProductBase - (pcpt.dblW0 - dblW0))
