perceptron.py

import timing
import sys
from random import randint, uniform


class Perceptron:
	weights = []
	c = 0.01

	error_0 = 0
	error_1 = 0
	error_n1 = 0

	def __init__(self):
		self.weights = [uniform(-1, 1), uniform(-1, 1), 1]
		#self.weights = [-7.064101819032928, 3.030346989299225, 1]

	def feedforward(self, inputs):
		total_sum = 0
		for index, weight in enumerate(self.weights):
			total_sum += inputs[index] * weight
		return self.activate(total_sum)

	def activate(self, total_sum):
		if total_sum > 0:
			return 1
		return -1

	def train(self, inputs, desired):
		guess = self.feedforward(inputs)
		error = desired - guess
		self.count_results(error)
		for index, weight in enumerate(self.weights):
			self.weights[index] += self.c * error * inputs[index]
			if index == 2:
				self.weights[index] = 1
		return error

	def count_results(self, error):
		if error == 0:
			self.error_0 += 1
		elif error == 2:
			self.error_1 += 1
		else:
			self.error_n1 += 1


class Trainer:
	inputs = []
	answer = 0

	def __init__(self, x, y, a):
		self.inputs = [x, y, 1]
		self.answer = a


def f(x):
	return 2 * x + 1


def setup():
	training = []

	for i in range(1000000):
		x = randint(0, 10)
		y = randint(0, 10)
		answer = 1
		if y < f(x):
			answer = -1
		training.append(Trainer(x, y, answer))
	return training


def set_up(number_of_iterations):
	for i in range(number_of_iterations):
		x = randint(0, 10)
		y = randint(0, 10)
		answer = 1
		if y < f(x):
			answer = -1
		yield Trainer(x, y, answer)


def main():
	if len(sys.argv) > 1:
		number_of_iterations = int(sys.argv[1])
	else:
		number_of_iterations = 1000000

	ptron = Perceptron()
	first_score = 0
	last_score = 0
	range_score = 20

	for i, train in enumerate(set_up(number_of_iterations)):

		result = ptron.train(train.inputs, train.answer)

		if i == (number_of_iterations / 10000) - 1:
			print 'De %s hay %s Aciertos: ' % (i + 1, ptron.error_0)
		if i == (number_of_iterations / 100) - 1:
			print 'De %s hay %s Aciertos: ' % (i + 1, ptron.error_0)
		if i == number_of_iterations - 1:
			print 'De %s hay %s Aciertos: ' % (i + 1, ptron.error_0)

		if result == 0:
			if i < range_score:
				first_score += 1
			elif i >= number_of_iterations - range_score:
				last_score += 1

	print 'Score first %s: %s' % (range_score, first_score)
	print 'Score last %s: %s' % (range_score, last_score)
	print ptron.weights

if __name__ == "__main__":
	main()