如何用颜色渐变填充 3D 三角形 [英] How to fill a 3D triangle with a color gradient

问题描述

我正在尝试将颜色图应用于 3d 多边形.多边形很好，显示在正确的位置.我唯一不能做的就是用渐变填充它.

这是我的代码:

将 matplotlib.pyplot 导入为 plt从 mpl_toolkits.mplot3d 导入 Axes3D从 matplotlib.colors 导入 LinearSegmentedColormap从 mpl_toolkits.mplot3d.art3d 导入 Poly3DCollectionfig = plt.figure()ax = Axes3D(图)x = [0,0,0]y = [0,1,0]z = [0,0,1]verts = [zip(x, y,z)] #(0,0,0) (0,1,0) (0,0,1)颜色 = ['红色'、'灰色'、'灰色'、'绿色']指数 = [0.0, 0.49, 0.509, 1.0]cm = LinearSegmentedColormap.from_list('my_colormap', zip(index, colors))集合 = Poly3DCollection(verts, cmap=cm)ax.add_collection3d(集合)plt.show()

有人可以帮我吗?

此外，渐变看起来应该像

这里，contourf 的使用有点小技巧.为了获得其他方向的梯度，最好使用曲面图 (plot_surface).

from mpl_toolkits.mplot3d 导入axes3d导入 matplotlib.pyplot 作为 plt将 numpy 导入为 npfig = plt.figure()ax = fig.add_subplot(projection='3d')点数=50Y, Z = np.meshgrid(np.linspace(0,1,points), np.linspace(0,1,points))Z = Z*(1-Y)颜色 =(1-Y+Z)*0.5ax.plot_surface(np.zeros_like(Y), Y, Z, facecolors=plt.cm.jet(color),rcount=points，ccount=points，shade=False)ax.set_xlabel('X')ax.set_xlim(0, 1)ax.set_ylabel('Y')ax.set_ylim(0,1)ax.set_zlabel('Z')ax.set_zlim(0,1)plt.show()

为了获得更流畅的图片，您可以增加points，但这也可能会显着增加绘制时间.

I am trying to apply a colormap to a 3d Polygon. The polygon is fine, shows up in the correct position. The only thing I can't do is filling it with a gradient.

Here is my code:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.colors import LinearSegmentedColormap
from mpl_toolkits.mplot3d.art3d import Poly3DCollection

fig = plt.figure()
ax = Axes3D(fig)

x = [0,0,0]
y = [0,1,0]
z = [0,0,1]
verts = [zip(x, y,z)] #(0,0,0) (0,1,0) (0,0,1)

colors = ['red', 'gray', 'gray', 'green']
index  = [0.0, 0.49, 0.509, 1.0]
cm = LinearSegmentedColormap.from_list('my_colormap', zip(index, colors))

collection = Poly3DCollection(verts, cmap=cm)
ax.add_collection3d(collection)
plt.show()

Can someone help me, please?

EDIT:

Moreover the gradient should look like this

解决方案

Since every member of a collection can only have a single color associated with it, you cannot simply use a triangle to achieve a gradient fill.

One way of obtaining a gradient in a triangle is to use plt.contourf.

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np

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

X, Y = np.meshgrid(np.linspace(0,1), np.linspace(0,1)) 
Z = 1.-X-Y
Z[Z<0] = 0

cset = ax.contourf(X, Y, Z, zdir='x', levels=np.linspace(0,1),offset=0, cmap=plt.cm.jet)
ax.set_xlabel('X')
ax.set_xlim(0, 1)
ax.set_ylabel('Y')
ax.set_ylim(0,1)
ax.set_zlabel('Z')
ax.set_zlim(0,1)    
plt.show()

Here, the use of contourf is a bit of a hack. In order to obtain a gradient in some other direction it would probably be better to use a surface plot (plot_surface).

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np
 
fig = plt.figure()
ax = fig.add_subplot(projection='3d')
points=50
Y, Z = np.meshgrid(np.linspace(0,1,points), np.linspace(0,1,points)) 
Z = Z*(1-Y)
color =(1-Y+Z)*0.5

ax.plot_surface(np.zeros_like(Y), Y, Z, facecolors=plt.cm.jet(color), 
                rcount=points, ccount=points, shade=False)

ax.set_xlabel('X')
ax.set_xlim(0, 1)
ax.set_ylabel('Y')
ax.set_ylim(0,1)
ax.set_zlabel('Z')
ax.set_zlim(0,1)    
plt.show()

To obtain a smoother picture, you can increase points, but this may also increase drawing time significantly.

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