import random
import string
from astar import Astar
from random import shuffle
import numpy as np

A = np.zeros((10, 10), dtype=int)

goals = [[0, 4], [4, 0], [4, 4]]

recordDistance = 0

class DNA:

    def __init__(self, target, recordDistance):
        shuffle(target)
        self.genes = target.copy()
        self.fitness = 1.0
        self.recordDistance = recordDistance

    def calcFitness(self, A):
        start = [0, 0]
        sum = 1

        for goal in self.genes:
            path = Astar(A, start, goal)
            sum = sum + len(path) - 1
            start = goal

        self.fitness = sum

    def crossover(self, partner):

        child = DNA(self.genes, self.recordDistance)
        start = abs(random.randint(0, len(self.genes)) - 1)
        end = abs(random.randint(start - 1, len(self.genes)))

        child.genes = child.genes[start:end]

        for i in range(len(self.genes)):
            node = partner.genes[i]

            if node not in child.genes:
                child.genes.append(node)

        return child

    def mutate(self, mutationRate):

        for i in range(len(self.genes)):
            if random.random() < mutationRate:
                indexA = abs(random.randint(0, len(self.genes)) - 1)
                indexB = (indexA + 1) % len(self.genes)
                self.genes[indexA], self.genes[indexB] = self.genes[indexB], self.genes[indexA]