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