在给定立方体的所有顶点的情况下，在平面上绘制立方体

Question

我尝试使用 matplotib 在平面顶部绘制一个立方体。

我正在做一个关于无人机（无人机）着陆的项目，我必须将这些测试可视化。我已经绘制了一架着陆飞机，如下所示。

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d.art3d import Poly3DCollection

xs = np.linspace(-10, 10, 100)
ys = np.linspace(-10, 20, 100)

X, Y = np.meshgrid(xs, zs)
Z = 0 / X

fig = plt.figure(figsize=(25,25))
ax = fig.add_subplot(111, projection='3d')
ax.plot_surface(X, Y, Z)
ax.set_ylim([-40, 40])
ax.set_zlim([0, 10])
ax.set_xlim([-10, 10])
# Hide grid lines
# ax.grid(False)
plt.xlabel("X axis")
plt.ylabel("Y axis")

# Hide axes ticks
# ax.set_xticks([])
# ax.set_yticks([])
# ax.set_zticks([])
# plt.savefig("foo.png")
plt.show()

输出如下图。

现在我想在图中绘制一个立方体。我有一个函数可以生成立方体的所有顶点，但我在尝试绘制它时遇到了错误。顶点是从西北顶部、东北顶部、东南顶部、西南顶部生成的。底部也是如此。

这是函数。

def createVertices(c3, stepSize):
    hs = 0.5 * stepSize
    a = [c3[0]-hs,c3[1]+hs,c3[2]+hs]
    b = [c3[0]+hs,c3[1]+hs,c3[2]+hs]
    c = [c3[0]+hs,c3[1]-hs,c3[2]+hs]
    d = [c3[0]-hs,c3[1]-hs,c3[2]+hs]
    e = [c3[0]-hs,c3[1]+hs,c3[2]-hs]
    f = [c3[0]+hs,c3[1]+hs,c3[2]-hs]
    g = [c3[0]+hs,c3[1]-hs,c3[2]-hs]
    h = [c3[0]-hs,c3[1]-hs,c3[2]-hs]
    
    return [a,b,c,d,e,f,g,h]

我必须动态地执行此操作，因为我有 100 多个测试用例。任何帮助将不胜感激。

其他信息：

贾里德提出了几乎类似的问题，但我遇到了来自

 AttributeError: 'int' object has no attribute 'ndim'

的错误

ax.plot_surface(X,Y,1, alpha=0.5)

。

Answer 1

我设法解决了动态创建立方体的问题。这是整个脚本。

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d.art3d import Poly3DCollection

# create an array of all cube's center points
xPoints = np.linspace(30,50,3, dtype = int)
yPoints = np.linspace(-20,20,5, dtype = int)
zPoints = np.linspace(5,35,7, dtype = int)

allPoints= []

for xp in xPoints:
    for yp in yPoints:
        for zp in zPoints:
            allPoints.append([xp,yp,zp])

# plot each of the cube
for c3 in allPoints:
    # figure name
    figName = ""+str(c3[0])+"_"+str(c3[1])+"_"+str(c3[2])+".pdf"
    
    # landing strip
    xs = np.linspace(10, 60, 100)
    ys = np.linspace(-10, 20, 100)

    X, Y = np.meshgrid(xs, ys)
    Z = 0 / X

    # create vertices
    hs = 0.5 * 2
    a = [c3[0]-hs,c3[1]+hs,c3[2]+hs]
    b = [c3[0]+hs,c3[1]+hs,c3[2]+hs]
    c = [c3[0]+hs,c3[1]-hs,c3[2]+hs]
    d = [c3[0]-hs,c3[1]-hs,c3[2]+hs]
    e = [c3[0]-hs,c3[1]+hs,c3[2]-hs]
    f = [c3[0]+hs,c3[1]+hs,c3[2]-hs]
    g = [c3[0]+hs,c3[1]-hs,c3[2]-hs]
    h = [c3[0]-hs,c3[1]-hs,c3[2]-hs]

    # arrange the vertices
    vertices =  [h,g,c,d,e,f,b,a]

    x, y, z = [],[],[]
    for vert in vertices:
        x.append(vert[0])
        y.append(vert[1])
        z.append(vert[2])

     # Face IDs
    vertices = [[0,1,2,3],[1,5,6,2],[3,2,6,7],[4,0,3,7],[5,4,7,6],[4,5,1,0]]
    tupleList = list(zip(x, y, z))

    poly3d = [[tupleList[vertices[ix][iy]] for iy in range(len(vertices[0]))] for ix in range(len(vertices))]

    # finally some plotting ;-)
    fig = plt.figure(figsize=(25,25))
    ax = fig.add_subplot(111, projection='3d')
    ax.scatter(x,y,z)
    ax.add_collection3d(Poly3DCollection(poly3d, facecolors='r', linewidths=1, alpha=0.5))
    ax.plot_surface(X, Y, Z)
    ax.set_ylim([-40, 40])
    ax.set_zlim([0, 40])
    ax.set_xlim([0, 60])
    
    # Hide grid lines
    # ax.grid(False)
    
    plt.xlabel("X axis")
    plt.ylabel("Y axis")
    plt.savefig(figName)

我希望它对将来的人有帮助