SzybciorSmartTraktor/genetical_algorithm.py

import random
from copy import copy
import settings
import tree


def evaluate_values(fuel, water, feritizer, seeds, fields_with_plants, k):
    fields_to_sow = 0
    fields_to_water = 0
    fields_to_feritize = 0
    fields_to_harvest = 0
    width = settings.Field.horizontal_count()
    height = settings.Field.vertical_count()
    ans = 0
    for i in range(width):
        for j in range(height):
            if fields_with_plants[i][j] == 'potato_empty' or fields_with_plants[i][j] == 'carrot_empty' or \
                    fields_with_plants[i][j] == 'wheat_empty':
                fields_to_sow += 1
            elif fields_with_plants[i][j] == 'potato_sow' or fields_with_plants[i][j] == 'carrot_sow' or \
                    fields_with_plants[i][j] == 'wheat_sow':
                fields_to_water += 1
            elif fields_with_plants[i][j] == 'potato_watered' or fields_with_plants[i][j] == 'carrot_watered' or \
                    fields_with_plants[i][j] == 'wheat_watered':
                fields_to_feritize += 1
            elif fields_with_plants[i][j] == 'potato_feritized' or fields_with_plants[i][j] == 'carrot_feritized' or \
                    fields_with_plants[i][j] == 'wheat_feritized':
                fields_to_harvest += 1
    t = tree.treelearn()
    if water < fields_to_water or feritizer < fields_to_feritize or seeds < fields_to_sow or fuel < 1000:
        return 5
    if tree.make_decision(t, fuel, water, feritizer, 0, 0, 0, 0, 0, seeds):
        return 5
    if fuel > 2000:
        return 0
    if k == 0:
        ans += (fuel) / 30 - fields_to_harvest
        ans += water - fields_to_water
        ans += feritizer - fields_to_feritize - fields_to_water
        ans += seeds - fields_to_harvest - fields_to_sow
        fuel = fuel - 1500
        water = water - fields_to_water
        feritizer = feritizer - fields_to_feritize - fields_to_water
        seeds = seeds - fields_to_harvest - fields_to_sow
        if water < 0:
            return 10
        if feritizer < 0:
            return 10
        if seeds < 0:
            return 10
        if fuel < 0:
            return 10
    if k == 1:
        ans += water - fields_to_water
        ans += feritizer - fields_to_water - fields_to_feritize
        ans += seeds - fields_to_sow
        ans += (fuel - 1100) / 30 - fields_to_harvest
        fuel = fuel - 1500
        water = water - fields_to_water
        feritizer = feritizer - fields_to_water - fields_to_feritize
        seeds = seeds - fields_to_sow
        if water < 0:
            return 10
        if feritizer < 0:
            return 10
        if seeds < 0:
            return 10
        if fuel < 0:
            return 10
    if k == 2:
        ans += feritizer - fields_to_feritize
        ans += seeds - fields_to_sow
        ans += (fuel - 800) / 15 - fields_to_feritize - fields_to_harvest
        ans += water - fields_to_water - fields_to_sow
        feritizer = feritizer - fields_to_feritize
        seeds = seeds - fields_to_sow
        fuel -= 1500
        water = water - fields_to_water - fields_to_sow
        if water < 0:
            return 10
        if feritizer < 0:
            return 10
        if seeds < 0:
            return 10
        if fuel < 0:
            return 10
    if k == 3:
        ans += seeds - fields_to_sow
        ans += (fuel - 400) / 30 - fields_to_harvest
        ans += water - fields_to_water - fields_to_sow
        ans += feritizer - fields_to_feritize - fields_to_water - fields_to_sow
        fuel -= 1500
        seeds = seeds - fields_to_sow
        water = water - fields_to_water - fields_to_sow
        feritizer = feritizer - fields_to_feritize - fields_to_water - fields_to_sow
        if water < 0:
            return 10
        if feritizer < 0:
            return 10
        if seeds < 0:
            return 10
        if fuel < 0:
            return 10
    if tree.make_decision(t, fuel, water, feritizer, 15, 15, 15, 10, 10, seeds):
        return 15
    if k == 0:
        fuel = fuel-500
        if tree.make_decision(t, fuel, water, feritizer, 15, 15, 15, 10, 10, seeds):
            return ans
        else:
            ans += 50
        water = water - fields_to_harvest - fields_to_sow-10
    if k == 1:
        water = water - fields_to_harvest - fields_to_sow-10
        if tree.make_decision(t, fuel - 400, water, feritizer, 15, 15, 15, 10, 10, seeds):
            return ans
        else:
            ans += 50
    if k == 2:
        feritizer = feritizer - fields_to_sow - fields_to_water-10
        if tree.make_decision(t, fuel - 400, water, feritizer, 15, 15, 15, 10, 10, seeds):
            return ans
        else:
            ans += 50
    if k == 3:
        seeds = seeds - fields_to_water - fields_to_feritize-10
        if tree.make_decision(t, fuel - 400, water, feritizer, 15, 15, 15, 10, 10, seeds):
            return ans
        else:
            ans += 50
    return ans

def fitness(solution, fields_plants, k):
    fuel = solution[0]
    water = solution[1]
    feritizer = solution[2]
    seeds = solution[3]
    if fuel / 30 + water + feritizer + seeds > 200:
        ans = 0
    else:
        ans = evaluate_values(fuel, water, feritizer, seeds, fields_plants, k)
    return ans


def solution(fields_with_plants, l):
    solutions = []
    ranked_solutions = []
    for i in range(10000):
        solution = []
        fuel = random.randint(0, 2000)
        water = random.randint(0, 100)
        feritizer = random.randint(0, 100)
        seeds = random.randint(0, 100)
        solution.append(fuel)
        solution.append(water)
        solution.append(feritizer)
        solution.append(seeds)
        solutions.append(solution)
    for s in solutions:
        ranked_solutions.append((fitness(s, fields_with_plants, l), s))
    ranked_solutions.sort()
    ranked_solutions.reverse()
    best_solutions = ranked_solutions[:100]
    k = 1
    print("Gen 1 best solution: " + str(ranked_solutions[0]))
    for q in range(4):
        k += 1
        random_cross = random.randint(0, 3)
        random_mutation_place = random.randint(0, 3)
        random_mutation = random.randint(1, 5)
        ranked_solutions = []
        solutions = []
        solutions.append(best_solutions[0][1])
        for i in range(100):
            for j in range(100):
                if i == j:
                    continue
                random_mutation_chance = random.randint(1, 100)
                solution = copy(best_solutions[i][1])
                solution[random_cross:4] = best_solutions[j][1][random_cross:4]
                if random_mutation_chance <= 3:
                    if random_mutation_place == 0:
                        solution[random_mutation_place] = solution[random_mutation_place] + random_mutation * 30
                    else:
                        solution[random_mutation_place] = solution[random_mutation_place] + random_mutation
                solutions.append(copy(solution))

        for s in solutions:
            ranked_solutions.append((fitness(s, fields_with_plants, l), s))
        ranked_solutions.sort()
        ranked_solutions.reverse()

        best_solutions = ranked_solutions[:100]
        print("Gen " + str(k) + " best solution: " + str(ranked_solutions[0]))

    return ranked_solutions[0][1][0], ranked_solutions[0][1][1], ranked_solutions[0][1][2], ranked_solutions[0][1][3]