GAのようなもので連立方程式を解いてみる

equation.py

# -*- coding:utf-8 -*-

import numpy as np

class GA(object):
    def __init__(self, num, dim):
        self.gen = np.random.randn(num, dim)

    def run(self, x):
        self.y = self.gen.dot(x.T)
        return self.y

    def learn(self, t):
        w0, w1 = self.__winner(t)
        self.__cross(w0, w1)
        self.__mutation(0.1)

    def __winner(self, t):
        loss = (self.y - t) ** 2

        win0 = np.argmin(loss)
        loss[win0] = np.max(loss) + 1
        win1 = np.argmin(loss)

        return win0, win1

    def __cross(self, w0, w1):
        mask = np.random.randint(2, size=self.gen.shape)
        self.gen = self.gen[w0].reshape(1, -1) * mask + self.gen[w1].reshape(1, -1) * (1 - mask)

    def __mutation(self, coef):
        num = self.gen.shape[0]
        dim = self.gen.shape[1]
        random = np.random.randn(num, dim)
        self.gen += coef * random

ga = GA(num=10, dim=4)

# 0.5a + -1.2b + 3.4c + -d
# (1, -1, 2, 3): 0.5 + 1.2 + 6.8 - 3 = 5.5
# (2, -2, 1, 2): 1 + 2.4 + 3.4 - 2 = 4.8
# (3, 2, 1, -1): 1.5 - 2.4 + 3.4 + 1 = 3.5
# (4, 1, -1, 1): 2 - 1.2 - 3.4 - 1 = -3.6
x = np.array([
    [1, -1, 2, 3],
    [2, -2, 1, 2],
    [3, 2, 1, -1],
    [4, 1, -1, 1]
    ])

t = np.array([5.5, 4.8, 3.5, -3.6])

print(ga.gen)

for i in range(100000):
    y = ga.run(x[i%4].reshape(1, -1))
    ga.learn(t[i%4].reshape(1, -1))

y = ga.run(x[0].reshape(1, -1))
print(y)
print(ga.gen)