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import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
import math


    

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NSAMPLE = 100
x_data = np.float32(np.arange(-10,10,20.0/NSAMPLE)).T
y_sigm = np.float32(1.0/(1+np.exp(-x_data)))
y_tanh = np.float32((2*np.exp(-x_data)-1)/(2*np.exp(-x_data)+1))

plt.figure(figsize=(10, 6), dpi=80)
plt.plot(x_data, y_sigm, color="blue", linewidth=2.0, linestyle="-", label="Sigmoid")
plt.plot(x_data, y_tanh, color="red",  linewidth=2.0, linestyle="-", label="Hyperbolic Tangent")

plt.xlim(x_data.min() * 1.1, x_data.max() * 1.1)
plt.ylim(y_tanh.min() * 1.1, y_tanh.max() * 1.1)

plt.xticks([-10, -5, 0, 5, 10])
plt.yticks([-2, -1, 0, 1, 2])

ax = plt.gca()  # gca stands for 'get current axis'
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.spines['bottom'].set_position(('data',0))
ax.yaxis.set_ticks_position('left')
ax.spines['left'].set_position(('data',0))

plt.legend(loc='upper right')


plt.show()