import random
import numpy.matlib
import numpy as np
import MachineLearning as ml
test = ml.NeuralNetwork(2, 9, 1)
#Training the model to learn XOR
for i in range(0, 1000):
test.train(np.array([[1], [0]]), np.array([[1]]))
test.train(np.array([[0], [1]]), np.array([[1]]))
test.train(np.array([[1], [1]]), np.array([[0]]))
test.train(np.array([[0], [0]]), np.array([[0]]))
print("IH weights: " + str(test.weightIH))
print("HO weights: " + str(test.weightHO))
print("Bias H: " + str(test.biasH))
print("Bias O: " + str(test.biasO))
print("\n\n")
#Testing the model with XOR
print(test.feedforward(np.array([[1], [0]])))
print(test.feedforward(np.array([[0], [1]])))
print(test.feedforward(np.array([[1], [1]])))
print(test.feedforward(np.array([[0], [0]])))
