My answer is an amalgamation of the above two with extension to drawing sphere of user-defined opacity and some annotation. It finds application in b-vector visualization on a sphere for magnetic resonance image (MRI). Hope you find it useful:
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = fig.gca(projection='3d')
# draw sphere
u, v = np.mgrid[0:2*np.pi:50j, 0:np.pi:50j]
x = np.cos(u)*np.sin(v)
y = np.sin(u)*np.sin(v)
z = np.cos(v)
# alpha controls opacity
ax.plot_surface(x, y, z, color="g", alpha=0.3)
# a random array of 3D coordinates in [-1,1]
bvecs= np.random.randn(20,3)
# tails of the arrows
tails= np.zeros(len(bvecs))
# heads of the arrows with adjusted arrow head length
ax.quiver(tails,tails,tails,bvecs[:,0], bvecs[:,1], bvecs[:,2],
length=1.0, normalize=True, color='r', arrow_length_ratio=0.15)
ax.set_xlabel('X-axis')
ax.set_ylabel('Y-axis')
ax.set_zlabel('Z-axis')
ax.set_title('b-vectors on unit sphere')
plt.show()