In [1]:

    

### Load packages

import matplotlib.pyplot as plt
import numpy as np


    

In [2]:

    

### Define softmax function

def softmax(scores):
    """Compute softmax values for scores"""
    expscores = np.exp(scores)
    return expscores/np.sum(expscores)


    

In [3]:

    

### Generate a set of scores

x = np.arange(-2.0, 6.0, 0.1)
scores = np.vstack([x, np.ones_like(x), 0.2 * np.ones_like(x)])

softmaxvalues = np.empty(scores.shape)

for i in np.arange(0, scores.shape[1]):
    softmaxvalues[:, i] = softmax(scores[:, i])


    

In [4]:

    

### Plot softmax curves

colors = ('red', 'green', 'blue')

for i in np.arange(0, softmaxvalues.shape[0]):
    plt.plot(x, softmaxvalues[i, :], color=colors[i], linewidth=2)

plt.show()