def runOneTest(seed=None):
sys.stdout.write('.')
sys.stdout.flush()
rnd = random.Random()
rnd.seed(seed)
slope = rnd.uniform(-3, 3)
intercept = rnd.uniform(-1,1)
trainingSet = Perceptron.generatePoints(slope, intercept, TRAINING_EXEMPLARS, str(seed)+"training")
p = Perceptron()
trainingSucceeded, iterations = p.train(trainingSet, 1, MAX_ITER, ERROR_THRESHOLD)
misclassifications = 0
if (trainingSucceeded):
testSet = Perceptron.generatePoints(slope, intercept, TEST_VECTORS, str(seed)+"test")
for vector, expected in testSet:
result = p.evaluate(vector)
if (result != expected):
misclassifications += 1
return slope, intercept, trainingSucceeded, iterations, misclassifications
