""" Odd/even Classifier with a Feed Forward Neural Network """
import keras
import matplotlib.pyplot as plt
import numpy as np
from sklearn.model_selection import train_test_split


def tobin(d, pad=8):
    return [int(i) for i in bin(2**pad + d)[2:]][1:]


input_numbers = np.array([tobin(i) for i in range(256)])
input_labels = np.array([i % 2 for i in range(256)])

in_train, in_test, out_train, out_test = train_test_split(input_numbers, input_labels, test_size=0.33)

model = keras.models.Sequential([
    keras.layers.Dense(8, input_dim=8),
    keras.layers.Dense(1)
])

model.compile(loss='mean_squared_error', optimizer='sgd')

model.fit(
    in_train,
    out_train,
    epochs=50
)

print(model.evaluate(in_test, out_test))

p = model.predict(input_numbers)
sq = sum(([0 if i < 0.5 else 1 for i in p] - input_labels)**2)

print("Square error: #{} → {}%".format(sq, 100 * sq / len(input_numbers)))

plt.plot([0 if i < 0.5 else 1 for i in model.predict(input_numbers)])