绘制非结构化三角形曲面

Question

我正在尝试绘制使用>；创建的曲面；10000个非结构化三角形。我有三角形点的坐标和每个三角形点的列表。我的数据如下：

0.1 0.2 0.1
0.20.40.6
0.40.60.4
.
.
.
1 2 3
.
.
.

前三条线是点的坐标（-X，Y，Z坐标-）（第1行中的点1，第2行中的点2等）。点数超过10000。 “1233”表示我们有一个三角形，它的角点是1，2和3。 我想从第一个三角形开始，一个接一个地绘制曲面。我尝试按照上面的过程进行操作，但没有得到正确的数字，最后得到以下错误消息

Figure size 432x288 with 0 Axes

我尝试了以下代码

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)

我很乐意听取你的意见

Answer 1

函数plo_trisurf正是您想要的

• 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)