Matplotlib如何在3D图中将2D图像居中于XY表面的原点？

Question

I have an image whose size is 330x330 in pixel and 5cm x 5cm in reality. When I tried to use the function plot_surface , the left top corner of the image was stuck to the origin. However, I want the center of the image to locate at the origin like this,

Is there any way I can do this? And how can I change the unit system into cm instead of pixels?

EDIT: Here is my current code:

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

xx, yy = np.meshgrid(np.linspace(0, 1, 330), np.linspace(0, 1, 330))
X = xx
Y = yy
ax.plot_surface(X, Y, 0, rstride=10, cstride=10, facecolors=plt.imread('pattern.jpg') / 255., shade=False)

plt.show()

Answer 1

You can set the size of a figure in matplotlib using the figsize=(width, height) argument. The figure size in pixel is determined by the dpi = 80 argument. For example

plt.figure(figsize=(8,6))
...
plt.savefig("out.png", dpi=100)

will result in a 8 times 6 inch figure, which has 800 x 600 pixels.
You cannot change the units from inch to something else, but since 1 inch = 2.54 cm you can calculate your desired figure size if needed.

All of this has nothing to do with the plotting units that matplotlib uses and plotting in matplotlib is in no way related to real length units, ie you can plot the size of an atom next to the map of the solar system, all in one plot of the size of a sheet of paper.

The position of the origin in a plot is determined by the axis limits. Roughly speeking if your axis goes from 0 to 2 , the origin is on the left side of the figure, if your plot goes from -1 to 1 , the origin is in the middle.

When ax is your axes object, you can set the origin using

ax.set_xlim([-1,1])
ax.set_ylim([-1,1])

in the 2D case or, for the 3D case via

ax.set_xlim3d([-1,1])
ax.set_ylim3d([-1,1])
ax.set_zlim3d([-1,1])

---

Now that we have some code to work with, we can set the image in the center by using appropriate coordinates. As in the case of the axis limits if the image is defines between 0 and 1 it will of course sit there and not be centered at the origin. When we define the image to go from -1 to 1, it should work as expected.

 from mpl_toolkits.mplot3d import Axes3D import numpy as np import matplotlib.pyplot as plt fig = plt.figure() ax = fig.add_subplot(111, projection='3d') xx, yy = np.meshgrid(np.linspace(-1, 1, 330), np.linspace(-1, 1, 330)) X = xx Y = yy c = np.random.rand(330,330,3) ax.plot_surface(X, Y, 0, rstride=30, cstride=30, facecolors=c, shade=False) plt.show()