71 lines
1.7 KiB
Python
71 lines
1.7 KiB
Python
from Perceptron import Perceptron
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from random import Random
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from Dataset import Dataset
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from Graph import *
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graph = Graph(640, 480, "Perceptron")
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graph.drawLine(Point(-1000, -1000 + 20), Point(1000, 1000 + 20))
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rand = Random()
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data = Dataset(open("input.txt").read().split('\n'), open("target.txt").read().split('\n'))
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learn_rate = 0.01
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p = Perceptron()
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i = data.inputs
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def line_perceptron():
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p.add_input("1", 1, rand.uniform(-1, 1))
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p.add_input("2", 1, rand.uniform(-1, 1))
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def answer(p_x, p_y):
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if p_y > calc_y(p_x):
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return 1
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else:
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return -1
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def calc_y(p_x):
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return p_x + 2
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for ind in range(0, 1000):
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x = rand.randint(-640 / 2, 640 / 2)
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y = rand.randint(-480 / 2, 480 / 2)
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print(x, y)
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p.input(x, y)
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print("error: %f" % p.guess(answer(x, y), learn_rate))
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for i in range(0, 1000):
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x = int(input("x: "))
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y = int(input("y: "))
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p.input(x, y)
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if p.activation() == 1:
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graph.win.plot(x, y, "green")
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print("TRUE")
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else:
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graph.win.plot(x, y, "red")
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print("FALSE")
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def and_perceptron():
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p.add_input("1", 1, rand.uniform(-1, 1))
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p.add_input("2", 1, rand.uniform(-1, 1))
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p.add_input("bias", 1, rand.uniform(-1, 1))
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# train
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for ind in range(0, 500):
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i = data.inputs
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for key in data.inputs:
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p.input(i[key].value1, i[key].value2)
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print("error: %f" % p.guess(i[key].target, learn_rate))
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for i in range(0, 1000):
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x = input("Arg1: ")
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y = input("Arg2: ")
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p.input(x, y)
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if p.activation() == 1:
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print("TRUE")
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else:
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print("FALSE")
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line_perceptron() |