Computing the softmax function given an array of number of n-dimension. And how to plot it and see that all probabilities sum to one.

softmax.py

import numpy as np

def softmax(x):
    """Compute softmax values for each sets of scores in x."""
    return np.array([np.exp(e) / np.sum(np.exp(x), axis=0) for e in x])

import matplotlib.pyplot as plt
x = np.arange(-2.0, 6.0, 0.1)
scores = np.vstack([x, np.ones_like(x), 0.2 * np.ones_like(x)])

plt.plot(x, softmax(scores).T, linewidth=2)
plt.show()