from astar import Astar
import numpy as np
from DNA import DNA
import random
import copy

def genetic(goals, A):
    recordDistance = 1000000000

    #count = 0
    generation = 0
    totalPopulaton = 10
    population = []
    matingPool = []

    mutationRate = 0.01

    for i in range(totalPopulaton):
        population.append(DNA(goals, recordDistance))

    for j in range(totalPopulaton):
        matingPool.clear()
        generation = generation + 1
        for i in range(totalPopulaton):
            population[i].calcFitness(A)

            if population[i].fitness < recordDistance:
                recordDistance = population[i].fitness
                best = copy.deepcopy(population[i])
                bestGeneration = generation

        for i in range(totalPopulaton):
            n = population[i].fitness * 100

            for j in range(int(n)):
                matingPool.append(population[i])

        for i in range(totalPopulaton):
            if matingPool:
                a = random.randint(0, len(matingPool) - 1)
                b = random.randint(0, len(matingPool) - 1)

                partnerA = matingPool[a]
                partnerB = matingPool[b]

                child = partnerA.crossover(partnerB)

                child.mutate(mutationRate)

                population[i] = child

    return best