问题
I know that I can do a 4D plot in matplotlib with the following code, with the fourth dimension shown as a colormap:
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
fig = plt.figure()
ax = fig.add_subplot(111,projection= '3d' )
x = np.arange(100)/ 101
y = np.sin(x) + np.cos(x)
X,Y = np.meshgrid(x,y)
Z = (X**2) / (Y**2)
A = np.sin(Z)
ax.plot_surface(X,Y, Z, facecolors=cm.Oranges(A))
plt.show()
But what if my data is not a function of the other data? How do I do this without np.meshgrid? (In other words, my Z series cannot be a function of the output of the X,Y which is the output of np.meshgrid(x,y), because Z is not a function of X and Y.)
回答1:
A surface plot is a mapping of 2D points to a 1D value, i.e. for each pair of (x,y) coordinates you need exactly one z coordinate. So while it isn't strictly necessary to have Z being a function of X and Y, those arrays to plot need to have the same number of elements.
For a plot_surface the restriction is to have X and Y as gridded 2D data. Z does not have to be 2D but needs to have the same number of elements.
This requirement can be weakened using a plot_trisurf where the only requirement is that there is a strict mapping of x,y,z, i.e. the ith value in X and Y corresponds to the ith value in Z.
In any case, even if there is no analytic function to map X and Y to Z, Z still needs to be some kind of mapping. Otherwise it is even questionable what information the resulting plot would convey.
来源：https://stackoverflow.com/questions/42379211/how-to-do-4d-plot-in-matplotlib-without-np-meshgrid