pylab 3d scatter plots with 2d projections of plotted data
You can add 2D projections of your 3D scatter data by using the plot
method and specifying zdir
:
import numpy as np
import matplotlib.pyplot as plt
x= np.random.random(100)
y= np.random.random(100)
z= np.sin(3*x**2+y**2)
fig= plt.figure()
ax= fig.add_subplot(111, projection= '3d')
ax.scatter(x,y,z)
ax.plot(x, z, 'r+', zdir='y', zs=1.5)
ax.plot(y, z, 'g+', zdir='x', zs=-0.5)
ax.plot(x, y, 'k+', zdir='z', zs=-1.5)
ax.set_xlim([-0.5, 1.5])
ax.set_ylim([-0.5, 1.5])
ax.set_zlim([-1.5, 1.5])
plt.show()
The other answer works with matplotlib 0.99, but 1.0 and later versions need something a bit different (this code checked with v1.3.1):
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
x= np.random.random(100)
y= np.random.random(100)
z= np.sin(3*x**2+y**2)
fig= plt.figure()
ax = Axes3D(fig)
ax.scatter(x,y,z)
ax.plot(x, z, 'r+', zdir='y', zs=1.5)
ax.plot(y, z, 'g+', zdir='x', zs=-0.5)
ax.plot(x, y, 'k+', zdir='z', zs=-1.5)
ax.set_xlim([-0.5, 1.5])
ax.set_ylim([-0.5, 1.5])
ax.set_zlim([-1.5, 1.5])
plt.show()
You can see what version of matplotlib you have by importing it and printing the version string:
import matplotlib
print matplotlib.__version__