我想将曲面绘制成一个立方体matplotlib.我正在尝试使用ax.plot_surface(X, Y, Z),但我有点困惑.它应该是什么X,Y并Z表示为2D数组?
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
points = np.array([[-1, -1, -1],
[1, -1, -1 ],
[1, 1, -1],
[-1, 1, -1],
[-1, -1, 1],
[1, -1, 1 ],
[1, 1, 1],
[-1, 1, 1]])
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
# ax.plot_surface(X, Y, Z) # how?
ax.scatter3D(points[:, 0], points[:, 1], points[:, 2])
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
plt.show()
Run Code Online (Sandbox Code Playgroud)
R z*_* zu 10
修复新的 matplotlib
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
points = np.array([[-1, -1, -1],
[1, -1, -1 ],
[1, 1, -1],
[-1, 1, -1],
[-1, -1, 1],
[1, -1, 1 ],
[1, 1, 1],
[-1, 1, 1]])
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
r = [-1,1]
X, Y = np.meshgrid(r, r)
one = np.ones(4).reshape(2, 2)
ax.plot_wireframe(X,Y,one, alpha=0.5)
ax.plot_wireframe(X,Y,-one, alpha=0.5)
ax.plot_wireframe(X,-one,Y, alpha=0.5)
ax.plot_wireframe(X,one,Y, alpha=0.5)
ax.plot_wireframe(one,X,Y, alpha=0.5)
ax.plot_wireframe(-one,X,Y, alpha=0.5)
ax.scatter3D(points[:, 0], points[:, 1], points[:, 2])
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
plt.show()
Run Code Online (Sandbox Code Playgroud)
plot_surface要在绘制长方体时使用单个调用,可以在两个变量上对表面进行参数化,例如使用球坐标。
下面绘制一个边长为 a、b、c 的长方体:
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
def get_cube():
phi = np.arange(1,10,2)*np.pi/4
Phi, Theta = np.meshgrid(phi, phi)
x = np.cos(Phi)*np.sin(Theta)
y = np.sin(Phi)*np.sin(Theta)
z = np.cos(Theta)/np.sqrt(2)
return x,y,z
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
a = 1
b = 2
c = 3
x,y,z = get_cube()
ax.plot_surface(x*a, y*b, z*c)
ax.set_xlim(-2,2)
ax.set_ylim(-2,2)
ax.set_zlim(-2,2)
plt.show()
Run Code Online (Sandbox Code Playgroud)
立方体的每个面都是一个表面,您可以自己定义每个角,或使用meshgrid:
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
points = np.array([[-1, -1, -1],
[1, -1, -1 ],
[1, 1, -1],
[-1, 1, -1],
[-1, -1, 1],
[1, -1, 1 ],
[1, 1, 1],
[-1, 1, 1]])
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
r = [-1,1]
X, Y = np.meshgrid(r, r)
ax.plot_surface(X,Y,1, alpha=0.5)
ax.plot_surface(X,Y,-1, alpha=0.5)
ax.plot_surface(X,-1,Y, alpha=0.5)
ax.plot_surface(X,1,Y, alpha=0.5)
ax.plot_surface(1,X,Y, alpha=0.5)
ax.plot_surface(-1,X,Y, alpha=0.5)
ax.scatter3D(points[:, 0], points[:, 1], points[:, 2])
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
plt.show()
Run Code Online (Sandbox Code Playgroud)
X,Y和Z是(相同的)2D点列表:
>>> numpy.meshgrid([-1,1], [-1,1])
[array([[-1, 1],
[-1, 1]]), array([[-1, -1],
[ 1, 1]])]
Run Code Online (Sandbox Code Playgroud)