Matplotlib 3D Scatter Plot with Colorbar
This produces a colorbar (though possibly not the one you need):
Replace this line:
ax.scatter(xs, ys, zs, c=cs, marker=m)
with
p = ax.scatter(xs, ys, zs, c=cs, marker=m)
then use
fig.colorbar(p)
near the end
Using the above answer did not solve my problem. The colorbar colormap was not linked to the axes (note also the incorrect colorbar limits):
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
data = np.random.rand(3, 100)
x, y, z = data # for show
c = np.arange(len(x)) / len(x) # create some colours
p = ax.scatter(x, y, z, c=plt.cm.magma(0.5*c))
ax.set_xlabel('$\psi_1$')
ax.set_ylabel('$\Phi$')
ax.set_zlabel('$\psi_2$')
ax.set_box_aspect([np.ptp(i) for i in data]) # equal aspect ratio
fig.colorbar(p, ax=ax)
The solution (see here also) is to use cmap
in ax.scatter
:
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
data = np.random.rand(3, 100)
x, y, z = data # for show
c = np.arange(len(x)) / len(x) # create some colours
p = ax.scatter(x, y, z, c=0.5*c, cmap=plt.cm.magma)
ax.set_xlabel('$\psi_1$')
ax.set_ylabel('$\Phi$')
ax.set_zlabel('$\psi_2$')
ax.set_box_aspect([np.ptp(i) for i in data]) # equal aspect ratio
fig.colorbar(p, ax=ax)