python : 绘制线框 3D 长方体
python : plotting a wireframe 3D cuboid
我想在 python 中绘制 3d 长方体。
输入：
中心（中心3分）
半径（3 个半径值，每个维度一个）
理想情况下，它应该是一个线框图（我需要看看里面有什么）。我不太确定该怎么做。使用 python matplotlib 或 Mayavi 即可。
谢谢！
到目前为止我已经尝试了以下代码..但是它只绘制了一个立方体
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
from itertools import product, combinations
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_aspect("equal")
#draw cube
r = [-1, 1]
for s, e in combinations(np.array(list(product(r,r,r))), 2):
if np.sum(np.abs(s-e)) == r[1]-r[0]:
ax.plot3D(*zip(s,e), color="b")
plt.show()
此代码中缺少的是它只是一个立方体（不是长方体）并且它仅以 0 为中心（我实际上想提供中心）
稍微想了想，this.Which好像是对的。如果您认为它不正确，请告诉我...这是最简单的方法，无需安装 myavi、pygame、povray（我很难在 ipython、conda、my [=31 上安装这些=]笔记本电脑）
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
from itertools import product, combinations
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_aspect("equal")
#draw cube
r1 = [-1, 1]
r2 = [-2, 2]
r3 = [-3, 3]
center =[5,5,5]
for s, e in combinations(np.array(list(product(r1,r2,r3))), 2):
s=np.array(center)+np.array(s)
e=np.array(center)+np.array(e)
ax.scatter3D(*center, color="r")
if np.linalg.norm(s-e) == 2*r1[1] or np.linalg.norm(s-e) == 2*r2[1] or np.linalg.norm(s-e) == 2*r3[1]:
print zip(s,e)
ax.plot3D(*zip(s,e), color="b")
plt.show()
每个人都忘记了 POVray 可以很好地处理 3D。虽然它不渲染线框，但您可以使用半透明纹理来查看框内的内容。
#!/usr/bin/python
# -*- coding: utf-8 -*-
import os
center='-1, -1, -1'
radius='1, 1, 1'
pov='camera { location <0, 2, -3> look_at <0, 1, 2> }\n\
light_source { <2, 4, -3> color rgb 1*1.5}\n\
background {color rgb <0.00, 0.00, 0.00>}\n\
box {<'+center+'>, < '+radius+'>\n\
pigment { color rgbt <0.67, 1.00, 0.39, 0.80> }\n\
rotate <52, 6, 0>\n\
scale 0.9\n\
translate <0, 1.2, 1>}\n\
'
f=open('scene.pov', 'w')
f.write(pov)
f.close()
os.system('povray +W400 +H300 +A +FN scene.pov')
输出"scene.png"
您需要阅读 povray 的文档。
我也遇到过同样的问题，尝试给出如下答案。
def cuboid_data(center, size):
"""
Create a data array for cuboid plotting.
============= ================================================
Argument Description
============= ================================================
center center of the cuboid, triple
size size of the cuboid, triple, (x_length,y_width,z_height)
:type size: tuple, numpy.array, list
:param size: size of the cuboid, triple, (x_length,y_width,z_height)
:type center: tuple, numpy.array, list
:param center: center of the cuboid, triple, (x,y,z)
"""
# suppose axis direction: x: to left; y: to inside; z: to upper
# get the (left, outside, bottom) point
o = [a - b / 2 for a, b in zip(center, size)]
# get the length, width, and height
l, w, h = size
x = [[o[0], o[0] + l, o[0] + l, o[0], o[0]], # x coordinate of points in bottom surface
[o[0], o[0] + l, o[0] + l, o[0], o[0]], # x coordinate of points in upper surface
[o[0], o[0] + l, o[0] + l, o[0], o[0]], # x coordinate of points in outside surface
[o[0], o[0] + l, o[0] + l, o[0], o[0]]] # x coordinate of points in inside surface
y = [[o[1], o[1], o[1] + w, o[1] + w, o[1]], # y coordinate of points in bottom surface
[o[1], o[1], o[1] + w, o[1] + w, o[1]], # y coordinate of points in upper surface
[o[1], o[1], o[1], o[1], o[1]], # y coordinate of points in outside surface
[o[1] + w, o[1] + w, o[1] + w, o[1] + w, o[1] + w]] # y coordinate of points in inside surface
z = [[o[2], o[2], o[2], o[2], o[2]], # z coordinate of points in bottom surface
[o[2] + h, o[2] + h, o[2] + h, o[2] + h, o[2] + h], # z coordinate of points in upper surface
[o[2], o[2], o[2] + h, o[2] + h, o[2]], # z coordinate of points in outside surface
[o[2], o[2], o[2] + h, o[2] + h, o[2]]] # z coordinate of points in inside surface
return x, y, z
def test():
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
center = [0, 0, 0]
length = 32 * 2
width = 50 * 2
height = 100 * 2
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.gca(projection='3d')
X, Y, Z = cuboid_data(center, (length, width, height))
ax.plot_surface(X, Y, Z, color='b', rstride=1, cstride=1, alpha=0.1)
ax.set_xlabel('X')
ax.set_xlim(-100, 100)
ax.set_ylabel('Y')
ax.set_ylim(-100, 100)
ax.set_zlabel('Z')
ax.set_zlim(-100, 100)
plt.show()
if __name__ == '__main__':
test()
这是结果：
这是长方体的线框图。
def plot_cuboid(center, size):
"""
Create a data array for cuboid plotting.
============= ================================================
Argument Description
============= ================================================
center center of the cuboid, triple
size size of the cuboid, triple, (x_length,y_width,z_height)
:type size: tuple, numpy.array, list
:param size: size of the cuboid, triple, (x_length,y_width,z_height)
:type center: tuple, numpy.array, list
:param center: center of the cuboid, triple, (x,y,z)
"""
# suppose axis direction: x: to left; y: to inside; z: to upper
# get the (left, outside, bottom) point
import numpy as np
ox, oy, oz = center
l, w, h = size
x = np.linspace(ox-l/2,ox+l/2,num=10)
y = np.linspace(oy-w/2,oy+w/2,num=10)
z = np.linspace(oz-h/2,oz+h/2,num=10)
x1, z1 = np.meshgrid(x, z)
y11 = np.ones_like(x1)*(oy-w/2)
y12 = np.ones_like(x1)*(oy+w/2)
x2, y2 = np.meshgrid(x, y)
z21 = np.ones_like(x2)*(oz-h/2)
z22 = np.ones_like(x2)*(oz+h/2)
y3, z3 = np.meshgrid(y, z)
x31 = np.ones_like(y3)*(ox-l/2)
x32 = np.ones_like(y3)*(ox+l/2)
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.gca(projection='3d')
# outside surface
ax.plot_wireframe(x1, y11, z1, color='b', rstride=1, cstride=1, alpha=0.6)
# inside surface
ax.plot_wireframe(x1, y12, z1, color='b', rstride=1, cstride=1, alpha=0.6)
# bottom surface
ax.plot_wireframe(x2, y2, z21, color='b', rstride=1, cstride=1, alpha=0.6)
# upper surface
ax.plot_wireframe(x2, y2, z22, color='b', rstride=1, cstride=1, alpha=0.6)
# left surface
ax.plot_wireframe(x31, y3, z3, color='b', rstride=1, cstride=1, alpha=0.6)
# right surface
ax.plot_wireframe(x32, y3, z3, color='b', rstride=1, cstride=1, alpha=0.6)
ax.set_xlabel('X')
ax.set_xlim(-100, 100)
ax.set_ylabel('Y')
ax.set_ylim(-100, 100)
ax.set_zlabel('Z')
ax.set_zlim(-100, 100)
plt.show()
def test():
center = [0, 0, 0]
length = 32 * 2
width = 50 * 2
height = 100 * 2
plot_cuboid(center, (length, width, height))
if __name__ == '__main__':
test()
这是结果。
我想在 python 中绘制 3d 长方体。
输入： 中心（中心3分） 半径（3 个半径值，每个维度一个）
理想情况下，它应该是一个线框图（我需要看看里面有什么）。我不太确定该怎么做。使用 python matplotlib 或 Mayavi 即可。
谢谢！
到目前为止我已经尝试了以下代码..但是它只绘制了一个立方体
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
from itertools import product, combinations
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_aspect("equal")
#draw cube
r = [-1, 1]
for s, e in combinations(np.array(list(product(r,r,r))), 2):
if np.sum(np.abs(s-e)) == r[1]-r[0]:
ax.plot3D(*zip(s,e), color="b")
plt.show()
此代码中缺少的是它只是一个立方体（不是长方体）并且它仅以 0 为中心（我实际上想提供中心）
稍微想了想，this.Which好像是对的。如果您认为它不正确，请告诉我...这是最简单的方法，无需安装 myavi、pygame、povray（我很难在 ipython、conda、my [=31 上安装这些=]笔记本电脑）
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
from itertools import product, combinations
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_aspect("equal")
#draw cube
r1 = [-1, 1]
r2 = [-2, 2]
r3 = [-3, 3]
center =[5,5,5]
for s, e in combinations(np.array(list(product(r1,r2,r3))), 2):
s=np.array(center)+np.array(s)
e=np.array(center)+np.array(e)
ax.scatter3D(*center, color="r")
if np.linalg.norm(s-e) == 2*r1[1] or np.linalg.norm(s-e) == 2*r2[1] or np.linalg.norm(s-e) == 2*r3[1]:
print zip(s,e)
ax.plot3D(*zip(s,e), color="b")
plt.show()
每个人都忘记了 POVray 可以很好地处理 3D。虽然它不渲染线框，但您可以使用半透明纹理来查看框内的内容。
#!/usr/bin/python
# -*- coding: utf-8 -*-
import os
center='-1, -1, -1'
radius='1, 1, 1'
pov='camera { location <0, 2, -3> look_at <0, 1, 2> }\n\
light_source { <2, 4, -3> color rgb 1*1.5}\n\
background {color rgb <0.00, 0.00, 0.00>}\n\
box {<'+center+'>, < '+radius+'>\n\
pigment { color rgbt <0.67, 1.00, 0.39, 0.80> }\n\
rotate <52, 6, 0>\n\
scale 0.9\n\
translate <0, 1.2, 1>}\n\
'
f=open('scene.pov', 'w')
f.write(pov)
f.close()
os.system('povray +W400 +H300 +A +FN scene.pov')
输出"scene.png"
您需要阅读 povray 的文档。
我也遇到过同样的问题，尝试给出如下答案。
def cuboid_data(center, size):
"""
Create a data array for cuboid plotting.
============= ================================================
Argument Description
============= ================================================
center center of the cuboid, triple
size size of the cuboid, triple, (x_length,y_width,z_height)
:type size: tuple, numpy.array, list
:param size: size of the cuboid, triple, (x_length,y_width,z_height)
:type center: tuple, numpy.array, list
:param center: center of the cuboid, triple, (x,y,z)
"""
# suppose axis direction: x: to left; y: to inside; z: to upper
# get the (left, outside, bottom) point
o = [a - b / 2 for a, b in zip(center, size)]
# get the length, width, and height
l, w, h = size
x = [[o[0], o[0] + l, o[0] + l, o[0], o[0]], # x coordinate of points in bottom surface
[o[0], o[0] + l, o[0] + l, o[0], o[0]], # x coordinate of points in upper surface
[o[0], o[0] + l, o[0] + l, o[0], o[0]], # x coordinate of points in outside surface
[o[0], o[0] + l, o[0] + l, o[0], o[0]]] # x coordinate of points in inside surface
y = [[o[1], o[1], o[1] + w, o[1] + w, o[1]], # y coordinate of points in bottom surface
[o[1], o[1], o[1] + w, o[1] + w, o[1]], # y coordinate of points in upper surface
[o[1], o[1], o[1], o[1], o[1]], # y coordinate of points in outside surface
[o[1] + w, o[1] + w, o[1] + w, o[1] + w, o[1] + w]] # y coordinate of points in inside surface
z = [[o[2], o[2], o[2], o[2], o[2]], # z coordinate of points in bottom surface
[o[2] + h, o[2] + h, o[2] + h, o[2] + h, o[2] + h], # z coordinate of points in upper surface
[o[2], o[2], o[2] + h, o[2] + h, o[2]], # z coordinate of points in outside surface
[o[2], o[2], o[2] + h, o[2] + h, o[2]]] # z coordinate of points in inside surface
return x, y, z
def test():
import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
center = [0, 0, 0]
length = 32 * 2
width = 50 * 2
height = 100 * 2
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.gca(projection='3d')
X, Y, Z = cuboid_data(center, (length, width, height))
ax.plot_surface(X, Y, Z, color='b', rstride=1, cstride=1, alpha=0.1)
ax.set_xlabel('X')
ax.set_xlim(-100, 100)
ax.set_ylabel('Y')
ax.set_ylim(-100, 100)
ax.set_zlabel('Z')
ax.set_zlim(-100, 100)
plt.show()
if __name__ == '__main__':
test()
这是结果：
这是长方体的线框图。
def plot_cuboid(center, size):
"""
Create a data array for cuboid plotting.
============= ================================================
Argument Description
============= ================================================
center center of the cuboid, triple
size size of the cuboid, triple, (x_length,y_width,z_height)
:type size: tuple, numpy.array, list
:param size: size of the cuboid, triple, (x_length,y_width,z_height)
:type center: tuple, numpy.array, list
:param center: center of the cuboid, triple, (x,y,z)
"""
# suppose axis direction: x: to left; y: to inside; z: to upper
# get the (left, outside, bottom) point
import numpy as np
ox, oy, oz = center
l, w, h = size
x = np.linspace(ox-l/2,ox+l/2,num=10)
y = np.linspace(oy-w/2,oy+w/2,num=10)
z = np.linspace(oz-h/2,oz+h/2,num=10)
x1, z1 = np.meshgrid(x, z)
y11 = np.ones_like(x1)*(oy-w/2)
y12 = np.ones_like(x1)*(oy+w/2)
x2, y2 = np.meshgrid(x, y)
z21 = np.ones_like(x2)*(oz-h/2)
z22 = np.ones_like(x2)*(oz+h/2)
y3, z3 = np.meshgrid(y, z)
x31 = np.ones_like(y3)*(ox-l/2)
x32 = np.ones_like(y3)*(ox+l/2)
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.gca(projection='3d')
# outside surface
ax.plot_wireframe(x1, y11, z1, color='b', rstride=1, cstride=1, alpha=0.6)
# inside surface
ax.plot_wireframe(x1, y12, z1, color='b', rstride=1, cstride=1, alpha=0.6)
# bottom surface
ax.plot_wireframe(x2, y2, z21, color='b', rstride=1, cstride=1, alpha=0.6)
# upper surface
ax.plot_wireframe(x2, y2, z22, color='b', rstride=1, cstride=1, alpha=0.6)
# left surface
ax.plot_wireframe(x31, y3, z3, color='b', rstride=1, cstride=1, alpha=0.6)
# right surface
ax.plot_wireframe(x32, y3, z3, color='b', rstride=1, cstride=1, alpha=0.6)
ax.set_xlabel('X')
ax.set_xlim(-100, 100)
ax.set_ylabel('Y')
ax.set_ylim(-100, 100)
ax.set_zlabel('Z')
ax.set_zlim(-100, 100)
plt.show()
def test():
center = [0, 0, 0]
length = 32 * 2
width = 50 * 2
height = 100 * 2
plot_cuboid(center, (length, width, height))
if __name__ == '__main__':
test()
这是结果。