import neural_net
import random

def crossover(neural_net1, neural_net2):
    nn = neural_net.NN(2,4,1)
    nn1 = neural_net.NN(2,4,1)
    cross_point_i = random.randint(1,neural_net1.ni-1)
    cross_point_o = random.randint(1,neural_net1.nh-1)
    #print(cross_point_o)
    nn.wi = neural_net1.wi
    nn.wo = neural_net1.wo

    nn1.wi = neural_net2.wi
    nn1.wo = neural_net2.wo
    
    temp_list = []
    temp_list = neural_net1.wi[0:cross_point_i]
    nn.wi[0:cross_point_i] = neural_net2.wi[0:cross_point_i]
    nn1.wi[0:cross_point_i] = temp_list

    temp_list = []
    temp_list = neural_net1.wo[0:cross_point_o]
    nn.wo[0:cross_point_o] = neural_net2.wo[0:cross_point_o]
    nn1.wo[0:cross_point_o] = temp_list

    return nn, nn1

##def crossover(neural_net1, neural_net2):
##    nn = neural_net.NN(4,10,1)
##    nn1 = neural_net.NN(4,10,1)
##    cross_point_i = random.randint(1,neural_net1.nh-1)
##    cross_point_o = random.randint(1,neural_net1.nh-1)
##    #print(cross_point_o)
##    nn.wi = neural_net1.wi
##    nn.wo = neural_net1.wo
##
##    nn1.wi = neural_net2.wi
##    nn1.wo = neural_net2.wo
##    
##    temp_list = []
##    temp_list = neural_net1.wi[0:4][0:cross_point_i]
##    nn.wi[0:4][0:cross_point_i] = neural_net2.wi[0:4][0:cross_point_i]
##    nn1.wi[0:4][0:cross_point_i] = temp_list
##
##    temp_list = []
##    temp_list = neural_net1.wo[0:cross_point_o]
##    nn.wo[0:cross_point_o] = neural_net2.wo[0:cross_point_o]
##    nn1.wo[0:cross_point_o] = temp_list
##
##    return nn, nn1
##

def mutate(neural_net1, mutation_rate):
    wi =  neural_net1.wi
    wo = neural_net1.wo
    nn = neural_net.NN(2,4,1)
    for i in range(len(wi)):
        for j in range(len(wi[i])):
            if random.random() < mutation_rate:
                nn.wi[i][j] = random.uniform(-0.5,0.5)
                #print(str(i) + ' ' + str(j))

    for i in range(len(wo)):
        for j in range(len(wo[i])):
            if random.random() < mutation_rate:
                nn.wo[i][j] = random.uniform(-0.5,0.5)
                #print(str(i) + ' ' + str(j))
    
    return nn

def create_new_pop(neural_net1,neural_net2, lista_sieci,mutation_rate):
    lista_sieci.append(mutate(neural_net1,0.01))
    lista_sieci.append(mutate(neural_net1,0.02))

    nn1, nn2 = crossover(neural_net1, neural_net2)
    nn3 = neural_net1
    nn4 = neural_net2
    nn5, nn6 = crossover(nn3, nn4)
    nn7 = mutate(nn5,mutation_rate)
    nn8 = mutate(nn6,mutation_rate)
    

    mutate(nn1,mutation_rate)
    mutate(nn2,mutation_rate)
    mutate(nn3,mutation_rate)
    mutate(nn4,mutation_rate)
   
    
    lista_sieci.append(nn1)
    lista_sieci.append(nn2)
    lista_sieci.append(nn3)
    lista_sieci.append(nn4)
    lista_sieci.append(nn5)
    lista_sieci.append(nn6)
    lista_sieci.append(nn7)
    lista_sieci.append(nn8)
    lista_sieci.append(mutate(neural_net1,0.01))
    lista_sieci.append(mutate(neural_net1,0.01))
    
    
    
#nn = neural_net.NN(4,10,1)
##nn1 = neural_net.NN(4,10,1)
###mutation_rate = 0.1
##print('Weights')
#print(nn.wi)
##print(nn1.wi)
###mutate(nn)
##nn2,nn3 = crossover(nn,nn1)
##
##print('Weights')
##print(nn2.wi)
##print(nn3.wi)
##
###print('Whatever')
###print(nn.ai)
###print(nn.ah)
###print(nn.ao)