import numpy as np

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

def main():

    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]])

    tr_out = np.array([[0,1,1,0,1,0,0]]).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('weights.nrl')
        print('The weights is already exist!')
    except:
        out_w = open('weights.nrl','w')
        for i in range(200000):
            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
    user_in = np.array([bool(input('First(0,1): ')),int(input('Second(0,1): ')),int(input('Third(0,1): ')),int(input('Fourth(0,1): ')),int(input('Fifth(0,1): '))])

    x = [] # массив
    # заполняем массив из файла с весами
    for s in out_w.readlines():
        x.append([float(s.replace('[', '').replace(']', ''))])

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

if __name__ == '__main__':
    main()