from populacja import Populacja
from scipy.spatial.distance import squareform, pdist
import numpy as np
from operator import itemgetter
import csv

def generate_disntance_matrix(coordinates_array):
    dist_array = pdist(coordinates_array)
    dist_matrix = squareform(dist_array)
    return dist_matrix

file_name = 'medium_4.ttp'
file = open(file_name, 'r')
# print(file.read())
problem_name = file.readline()
print(problem_name)
knapsack_data_type = file.readline()
print(knapsack_data_type)
dimension = file.readline()
print(dimension)
nr_of_items_line = file.readline()
print(nr_of_items_line)
capacity_of_k_line = file.readline()
print(capacity_of_k_line)
min_speed_line = file.readline()
print(min_speed_line)
max_speed_line = file.readline()
print(max_speed_line)
renting_ratio_line = file.readline()
print(renting_ratio_line)
edge_weight_type = file.readline()
print(edge_weight_type)
sht = file.readline()
print(sht)
location_list = []
loc = file.readline()
while (loc[0].isdigit()):
    loc = list(map(float, loc.split()))
    location_list.append(loc)
    loc = file.readline()
items = file.readline()
items_list = [list(map(float, items.split()))]
item = file.readline()
while bool(item) and item[0].isdigit():
    item = list(map(float, item.split()))
    items_list.append(item)
    item = file.readline()
print(location_list)
print()
print(items_list)
print()
l_os = 0
ww = []
tour_size = 0 #trivial 8
item_eff_meter = 0.0
x_chance = 0.22  # trivial 0.3
m_chance = 0.05 # trivial 0.18
# items_list = [[1.0,100.0,3.0,3.0], [2.0,40.0,2.0,3.0],[3.0,40.0,1.0,3.0], [4.0,20.0,2.0,2.0], [5.0,20.0,2.0,4.0]]
best_r = -11111111110
l_os = 160
tour_size = 100
# d_arr = [[0,5,6,6], [5,0,5,6], [6,5,0,4],[6,6,4,0]]
for tr in range(1):
    run_times = 500

    dist_arr = np.array(location_list)[:,[1,2]]
    dist_arr = generate_disntance_matrix(dist_arr)
    sec_item_list =list(map(lambda x: [int(x[0]), x[1],x[2],int(x[3]), round(x[1]/x[2],5)],items_list))
    sec_item_list = sorted(sec_item_list, key=itemgetter(4))
    current_run = 0
    best_arr = []
    licznik = 0
    d = []
    for i in range(10):
        best_a = -10000000
        d= []
        current_run = 0
        best_array_one = []
        # pop = Populacja(l_os,
        #                 4,
        #                 len(items_list),
        #                 3,
        #                 1.0,
        #                 max_speed_line.split()[-1],
        #                 min_speed_line.split()[-1], m_chance, x_chance, tour_size, items_list, location_list, d_arr,
        #                 sec_item_list, item_eff_meter)
        pop = Populacja(l_os,
                        len(location_list),
                        len(items_list),
                        capacity_of_k_line.split()[-1],
                        renting_ratio_line.split()[-1],
                        max_speed_line.split()[-1],
                        min_speed_line.split()[-1], m_chance, x_chance, tour_size, items_list, location_list, dist_arr,
                        sec_item_list, item_eff_meter)
        # pop.pop[0].trasa = [4, 1, 3, 7, 8, 2, 6, 0, 5]
        # pop.pop[1].trasa = [4, 0, 1, 3, 8, 6, 2, 7, 5]
        # pop.pop[2].trasa = [4, 3, 7, 1, 8, 2, 0, 6, 5]
        # pop.pop[3].trasa = [4, 6, 1, 8, 7, 0, 2, 3, 5]
        # pop.pop[0].trasa = [0,2,1,3]
        # pop.pop[0].plecak = [-1,2,-1,1,-1]
        # pop.ocen_pop()
        # w = pop.pop[0].wartosc_funkcji
        # a = 0
        # print(w)
        # pop.pop[0].trasa = [4,0,3,2,1]
        # pop.pop[0].plecak = [1,4,2,3]
        # pop.pop[0].ocen2()
        # o = pop.pop[0].wartosc_funkcji

        # print(a)
        # best_array_one.append(a)
        current_run = current_run + 1
        print(dist_arr)
        while current_run < run_times:
            print(str(i) + ' ' + str(current_run))
            print('start')
            licznik = licznik+1
            new_pop_list = []
            index = 0
            # print('ocena')
            pop.ocen_pop()
            # print('a')
            best, worst, aver, najl_osobnik = pop.get_best_worst_average()
            if best > best_a:
                best_a = best
            if best > best_r:
                best_r = best
            a = (best, aver, worst, najl_osobnik, best_a, best_r)
            # print(a)
            d = a
            # best_array_one.append(a)
            current_run = current_run + 1
            # best_arr.append(best_array_one)
            # print('selekcja')
            while index < l_os:
                # print(index)
                new_pop_list.append(pop.turniej())
                index = index + 1
            pop.pop = new_pop_list
            # print('mut')
            pop.mutuj_pop()
            # print('kross')
            pop.krosuj_pop()
            best_array_one.append(d)
        print('appending')
        ww.append(best_array_one[-1])
    with open('dd' +file_name+' 3item_eff_meter '+ str(item_eff_meter)+' los ' + str(l_os)+' x_chance ' + str(x_chance)+' m_chance ' + str(m_chance)+ ' tour_size '+ str(tour_size)+ ' run_times ' +str(run_times)+'.csv', 'w') as myfile:
        wr = csv.writer(myfile)
        wr.writerows(ww)
    # best_arr.append(best_array_one)
    # # print(best_arr)
    #
    # size = len(best_arr)
    # ind = 0
    # ret_arr = []
    # for row in best_arr[0]:
    #     suma_najl = 0
    #     suma_najg = 0
    #     suma_avg = 0
    #     suma_best = 0
    #     s_best_best = 0
    #     for lists in range(0,size-1):
    #         suma_najl = suma_najl + best_arr[lists][ind][0]
    #         val = best_arr[lists][ind][0]
    #         check = [lists, ind,0]
    #         print(suma_najg)
    #         val2 = best_arr[lists][ind][2]
    #         suma_najg = suma_najg + val2
    #         check2 = [lists, ind, 2]
    #         suma_avg = suma_avg + best_arr[lists][ind][1]
    #         suma_best = suma_best + best_arr[lists][ind][4]
    #         s_best_best = s_best_best + best_arr[lists][ind][5]
    #     wyn = [suma_najl/size, suma_avg/size, suma_najg/size, suma_best/size, s_best_best/size]
    #     ret_arr.append(wyn)
    #     ind = ind + 1
    #
    # b_a = [item for sublist in best_arr for item in sublist]
    # with open(file_name+' 3item_eff_meter '+ str(item_eff_meter)+' los ' + str(l_os)+' x_chance ' + str(x_chance)+' m_chance ' + str(m_chance)+ ' tour_size '+ str(tour_size)+ ' run_times ' +str(run_times)+'.csv', 'w') as myfile:
    #     wr = csv.writer(myfile)
    #     wr.writerows(b_a)
    #
    #
    # with open(file_name+' 3avg item_eff_meter '+ str(item_eff_meter)+' los '+ str(l_os)+' x_chance ' + str(x_chance)+' m_chance ' + str(m_chance)+ ' tour_size '+ str(tour_size)+ ' run_times ' +str(run_times)+'.csv', 'w') as myfile:
    #     wr = csv.writer(myfile)
    #     wr.writerows(ret_arr)