我已经编写了代码来绘制matplotlib中的一个准parabaloid的三维曲面。
我如何旋转图形,使图形保持不变(即没有垂直或水平移动),然而,它通过θ的角度围绕直线y=0和z=0旋转(我突出显示了图形应该以绿色旋转的线)。这里有一个例子来帮助我想象我所描述的:

例如,如果图形是通过180度的角度绕直线旋转,那么这将导致图形被“倒转”,因此原点现在是最大点。
我也想旋转轴,以便保持彩色地图。下面是绘制该图形的代码:
#parabaloid
import numpy as np
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
#creating grid
y = np.linspace(-1,1,1000)
x = np.linspace(-1,1,1000)
x,y = np.meshgrid(x,y)
#set z values
z = x**2+y**2
#label axes
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_zlabel('z')
#plot figure
ax.plot_surface(x,y,z,linewidth=0, antialiased=False, shade = True, alpha = 0.5)
plt.show()发布于 2016-07-12 12:58:07
以下是我的评论:
import mayavi.mlab as mlab
import numpy as np
x,y = np.mgrid[-1:1:0.001, -1:1:0.001]
z = x**2+y**2
s = mlab.mesh(x, y, z)
alpha = 30 # degrees
mlab.view(azimuth=0, elevation=90, roll=-90+alpha)
mlab.show()

或者跟随@Tamas的回答:
#parabaloid
import numpy as np
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from math import sin, cos, pi
import matplotlib.cm as cm
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
#creating grid
y = np.linspace(-1,1,200)
x = np.linspace(-1,1,200)
x,y = np.meshgrid(x,y)
#set z values
z0 = x**2+y**2
# rotate the samples by pi / 4 radians around y
a = pi / 4
t = np.transpose(np.array([x,y,z0]), (1,2,0))
m = [[cos(a), 0, sin(a)],[0,1,0],[-sin(a), 0, cos(a)]]
x,y,z = np.transpose(np.dot(t, m), (2,0,1))
# or `np.dot(t, m)` instead `t @ m`
#label axes
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_zlabel('z')
#plot figure
ax.plot_surface(x,y,z,linewidth=0, antialiased=False, shade = True, alpha = 0.5, facecolors=cm.viridis(z0))
plt.show()

发布于 2016-07-12 11:26:42
像这样吗?
ax.view_init(-140, 30)在plt.show()命令之前插入它。
发布于 2016-07-12 11:59:51
我能想到的最好的方法就是旋转数据本身。
#parabaloid
import numpy as np
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from math import sin, cos, pi
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
#creating grid
y = np.linspace(-1,1,200)
x = np.linspace(-1,1,200)
x,y = np.meshgrid(x,y)
#set z values
z = x**2+y**2
# rotate the samples by pi / 4 radians around y
a = pi / 4
t = np.transpose(np.array([x,y,z]), (1,2,0))
m = [[cos(a), 0, sin(a)],[0,1,0],[-sin(a), 0, cos(a)]]
x,y,z = np.transpose(t @ m, (2,0,1))
# or `np.dot(t, m)` instead `t @ m`
#label axes
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_zlabel('z')
#plot figure
ax.plot_surface(x,y,z,linewidth=0, antialiased=False, shade = True, alpha = 0.5)
plt.show()

https://stackoverflow.com/questions/38326983
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