neural

import numpy as np

def sigmoid(x):
    return 1 / (1+np.exp(-x))

tr_in = np.array([[0,0,1,0,0],
                  [1,1,1,0,1],
                  [1,0,1,1,1],
                  [0,1,0,0,1],
                  [1,1,1,1,1],
                  [1,0,0,0,0],
                  [0,0,0,0,0],
                  [0,0,0,0,0],
                  [0,1,0,0,0]])

tr_out = np.array([[0,1,1,0,1,0,0,0,0]]).T

np.random.seed(1)

syn_w = 2 * np.random.random((5,1)) - 1

print('Random weights')
print(syn_w)

output_err = open('err.txt','w')
output_adj = open('adj.txt','w')


try:
    out_w = open('weights2.nrl')
    print('The weights is already exist!')
except:
    out_w = open('weights2.nrl','w')
    for i in range(40000):
        in_lyr = tr_in
        out = sigmoid( np.dot(in_lyr, syn_w) )

        err = tr_out - out
        adj = np.dot( in_lyr.T, err * (out * (1- out)) )

        syn_w += adj

        output_err.write(str(err))
        output_adj.write(str(adj))
    out_w.write(str(syn_w))
finally:
    output_err.close()
    output_adj.close()

print( 'W after thinkin:' )
print(syn_w)

print('Result after thinkin:')
print('non') #add later

#test
while True:
    user_in = np.array([bool(input('First(0,1): ')),int(input('Second(0,1): ')),int(input()),int(input('Fourth(0,1): ')),int(input('Fifth(0,1): '))])
    x = [] # массив
    out_w_r = open('weights1.nrl','r')
        # заполняем массив из файла с весами
    for s in out_w_r.readlines():
        x.append([float(s.replace('[', '').replace(']', ''))])

        # передаем массив с весами в функцию
    output = sigmoid(np.dot(user_in, x))
    out_w.close()
    out_w_r.close()
    print('Result:')
    print(output)

    if __name__ == '__main__':
        print('main()')
    restart = str(input('Wanna restart?(any button/n)'))
    if not restart == 'n' or 'N':
        continue
    else:
        print('Goodbye')
        break