python - 绘制非结构化三角形曲面 Python

Question

我正在尝试绘制一个由 >10000 个非结构化三角形创建的表面。我有三角形点的坐标和每个三角形点列表。我的数据如下，

0.1 0.2 0.1
0.2 0.4 0.6
0.4 0.6 0.4
.
.
.
1 2 3
.
.
.

前三行是点(第 1 行中的点 1，第 2 行中的点 2 等)的坐标(-X、Y、Z 坐标-)。点数超过10000。“1 2 3”表示我们有一个三角形，其角点为 1、2 和 3。所以，我想通过从第一个三角形开始并一个一个地绘制它们来绘制曲面。我已尝试按照上述步骤操作，但我没有得到正确的数字，最后我收到以下错误消息。

Figure size 432x288 with 0 Axes

我试过下面的代码。

import matplotlib
import numpy as np
import matplotlib.cm as cm
import matplotlib.pyplot as plt
from matplotlib.tri import Triangulation
# from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits import mplot3d
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d.art3d import Poly3DCollection

fileName = open('surface.txt','r')
print(fileName.readline())
dummy = fileName.readline().split()
npo = int(dummy[2])
nel = int(dummy[4])

xp = np.zeros([npo])
yp = np.zeros([npo])
zp = np.zeros([npo])


el1 = np.zeros([nel])
el2 = np.zeros([nel])
el3 = np.zeros([nel])

for i in range(0,npo):
    dummy = fileName.readline().split()
    xp[i] = float(dummy[0])
    yp[i] = float(dummy[1])
    zp[i] = float(dummy[2])
    # print(i,xp[i],yp[i],zp[i])
for i in range(0,nel):
    dummy = fileName.readline().split()
    el1[i] = int(dummy[0])
    el2[i] = int(dummy[1])
    el3[i] = int(dummy[2])


fig2 = plt.figure()
ax2 = fig2.add_subplot(111, projection='3d')
for i in range(0,nel):
    x1 = xp[int(el1[i])-1]
    y1 = yp[int(el1[i])-1]
    z1 = zp[int(el1[i])-1]
    
    x2 = xp[int(el2[i])-1]
    y2 = yp[int(el2[i])-1]
    z2 = zp[int(el2[i])-1]

    x3 = xp[int(el3[i])-1]
    y3 = yp[int(el3[i])-1]
    z3 = zp[int(el3[i])-1]

    xarr = [x1,x2,x3,x1]
    yarr = [y1,y2,y3,y1]
    zarr = [z1,z2,z3,z1]
    
  
    verts = [list(zip(xarr,yarr,zarr))]
    ax2.add_collection3d(Poly3DCollection(verts))

ax2.set_xbound(0,1)
ax2.set_ybound(0,1)
ax2.set_zbound(0,3)

很高兴听到您的意见。

Answer 1

函数 plo_trisurf 完全符合您的要求。

• x, y, z 是三角形的节点
• tri 包含三角形节点的索引

一个小例子:

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

x = np.array([0, -1, 1, 1])
y = np.array([0, 1, -1, 1])
z = np.array([0, 1, 1, -1])

tri = np.array([[0, 1, 2],
                [0, 1, 3],
                [0, 2, 3]])

fig = plt.figure()
ax = fig.add_subplot(projection='3d')
ax.plot_trisurf(x, y, z, triangles=tri)