def q2Test(testFile):
if 'sigmoidDeriv' in testFile.name:
solution = []
percep = NeuralNet.Perceptron()
for line in testFile:
val = float(line)
solution = percep.sigmoidDeriv(val)
else:
testFuncName = testFile.readline().strip()
getData = getattr(NeuralNetUtil, testFuncName)
examples, tests = getData()
testRangeStart = testFile.readline().strip()
testRangeEnd = testFile.readline().strip()
testRangeStart = 0 if testRangeStart == 'None' else int(testRangeStart)
testRangeEnd = len(examples) if testRangeEnd == 'None' else int(
testRangeEnd)
examples = examples[testRangeStart:testRangeEnd]
file = open('test_cases/percep', 'rb')
percep = pickle.load(file)
sPercep = NeuralNet.Perceptron(inSize=percep.inSize - 1,
weights=percep.weights)
if 'update' in testFile.name:
solution = []
for example in examples:
solution.append(sPercep.updateWeights(example[0], 0.1, 0.67))
elif 'sigmoid' in testFile.name:
solution = []
for example in examples:
solution.append(sPercep.sigmoidActivationDeriv(example[0]))
return solution
def q1Test(testFile):
if 'sigmoid' in testFile.name and 'Activation' not in testFile.name:
value = float(testFile.readline().strip())
sPercep = NeuralNet.Perceptron()
solution = sPercep.sigmoid(value)
else:
testFuncName = testFile.readline().strip()
getData = getattr(NeuralNetUtil, testFuncName)
examples, tests = getData()
testRangeStart = testFile.readline().strip()
testRangeEnd = testFile.readline().strip()
testRangeStart = 0 if testRangeStart=='None' else int(testRangeStart)
testRangeEnd = len(examples) if testRangeEnd=='None' else int(testRangeEnd)
examples = examples[testRangeStart:testRangeEnd]
if 'feedforward' in testFile.name:
sNet = NeuralNet.NeuralNet([16,24,10])
file = open('test_cases/nnet')
net = cPickle.load(file)
copyWeights(sNet,net)
solution = []
for example in examples:
solution.append(sNet.feedForward(example[0]))
elif 'Activation' in testFile.name:
file = open('test_cases/percep')
percep = cPickle.load(file)
sPercep = NeuralNet.Perceptron(inSize = percep.inSize-1, weights = percep.weights)
solution = []
for example in examples:
solution.append(sPercep.sigmoidActivation(example[0]))
return solution
