from copy import deepcopy
import numpy as np
step = 0.5
e1 = 1
w11 = [0.2, 0.3, 1]
w12 = [0.4, 0.5, 1]
w13 = [0.7, 0.6, 1]
w14 = [0.5, 0.9, 1]
w1 = [w11, w12, w13, w14]
w2 = [0.2, 0.4, 0.6, 0.8, 1]
dataset = [
      [0, 0, 1],
      [0, 1, 1],
      [0, 2, 1],
      [0, 3, 1],
      [1, 0, 1],
      [1, 1, 1],
      [1, 2, 1],
      [1, 3, 1],
      [2, 0, 1],
      [2, 1, 1],
      [2, 2, 1],
      [2, 3, 1],
      [3, 0, 1],
      [3, 1, 1],
      [3, 2, 1],
      [3, 3, 1]
  ]
y_pr_dataset = [1,1,1,1,0,1,0,1,0,0,1,1,0,0,0,1]
for ii in range(16):
  x = dataset[ii]
  y_pr = y_pr_dataset[ii]
  e1 = 1
  iterations = 0
  while e1 >= 0.1 and iterations < 1000:
    z = np.dot(w1, x)
    y_hid = 1 / (1 + np.exp(-z))
    y_hid = np.append(y_hid, 1)
    z_out = np.dot(y_hid, w2)
    y_out = 1 / (1 + np.exp(-z_out))

    e1 = ((y_pr - y_out) ** 2) / 2
    delta1 = e1 * y_out * (1 - y_out)

    w2_new = []
    for i in range(len(y_hid)):
      w2_new.append(w2[i] - step * delta1 * y_hid[i])

    e2 = [e1 * w for w in w2_new]
    delta2 = [e2[i] * y_hid[i] for i in range(len(e2) - 1) ]
    w1_new = []
    for i in range(len(w1)):
      w11_new = []
      for j in range(len(x)):
        w11_new.append(w1[i][j] - step * delta2[i] * x[j])
      w1_new.append(w11_new)
    w1 = deepcopy(w1_new)
    w2 = deepcopy(w2_new)
    z_out = np.dot(y_hid, w2)
    y_out = 1 / (1 + np.exp(-z_out))
    iterations += 1
  #print(e1)

for ii in range(16):
  x = dataset[ii]
  y_pr = y_pr_dataset[ii]
  z = np.dot(w1, x)
  y_hid = 1 / (1 + np.exp(-z))
  y_hid = np.append(y_hid, 1)
  z_out = np.dot(y_hid, w2)
  y_out = 1 / (1 + np.exp(-z_out))
  print(y_out)