绘制球体表面上的矩形区域

Question

我想要绘制出球体表面上的矩形区域。

这是我对球的代码：

import numpy as np 
import random as rand 
import matplotlib.pyplot as plt 
from mpl_toolkits.mplot3d import Axes3D 

fig = plt.figure() 

ax = fig.gca(projection='3d') 

ax.set_aspect("equal") 

theta, phi = np.mgrid[0:2*np.pi : 20j ,0:np.pi : 20j] 

r = 6.3 

x = r * np.cos(phi)*np.sin(theta) 
y = r * np.sin(phi)*np.sin(theta) 
z = r * np.cos(theta) 

ax.plot_wireframe(x,y,z, color = "k") 
plt.show() 

这些点将从纬度/经度被转换到购物车COORDS。

lat1x = 46.49913179 * (2*np.pi/360) 
lat2x = 46.4423682 * (2*np.pi/360) 
long1y = -119.4049072 * (2*np.pi/360) 
long2y = -119.5048141 * (2*np.pi/360) 

lat3x = 46.3973998 * (2*np.pi/360) 
lat4x = 46.4532495 * (2*np.pi/360) 
long3y = -119.4495392 * (2*np.pi/360) 
long4y = -119.3492884 * (2*np.pi/360) 


xw1 = r * np.cos(lat1x)*np.cos(long1y) 
yw1 = r * np.cos(lat1x)*np.sin(long1y) 
zw1 = r * np.sin(lat1x) 

xw2 = r * np.cos(lat2x)*np.cos(long2y) 
yw2 = r * np.cos(lat2x)*np.sin(long2y) 
zw2 = r * np.sin(lat2x) 

xw3 = r * np.cos(lat3x)*np.cos(long3y) 
yw3 = r * np.cos(lat3x)*np.sin(long3y) 
zw3 = r * np.sin(lat3x) 

xw4 = r * np.cos(lat4x)*np.cos(long4y) 
yw4 = r * np.cos(lat4x)*np.sin(long4y) 
zw4 = r * np.sin(lat4x) 

p1 = [xw1,yw1,zw1] 
p2 = [xw2,yw2,zw2] 
p3 = [xw3,yw3,zw3] 
p4 = [xw4,yw4,zw4] 

ax.scatter(p1,p2,p3,p4, color = "r") 

这些是点和那里转换到笛卡尔坐标我很难让它们出现在球体的表面上。它们也应该形成粗糙的矩形形状。我希望能够连接点在球体表面绘制一个矩形。因为矩形的意思是非常小的

Answer 1

您的转换为直角坐标可能是错误的。刚创建时球一样，你可能想使用通常的

不过，当然这将取决于如何“LAT”和“结肠”的球体上的定义。

更重要的是，散点图不正确。它总是scatter(x,y,z)，第一个参数x坐标，第二个参数y坐标，第三个参数z坐标。

import numpy as np 
import random as rand 
import matplotlib.pyplot as plt 
from mpl_toolkits.mplot3d import Axes3D 

fig = plt.figure() 

ax = fig.gca(projection='3d') 

ax.set_aspect("equal") 

theta, phi = np.mgrid[0:2*np.pi : 20j ,0:np.pi : 20j] 

r = 6.3 

x = r * np.cos(phi)*np.sin(theta) 
y = r * np.sin(phi)*np.sin(theta) 
z = r * np.cos(theta) 

ax.plot_wireframe(x,y,z, color = "k") 


lat1x = 46.49913179 * (2*np.pi/360) 
lat2x = 46.4423682 * (2*np.pi/360) 
long1y = -119.4049072 * (2*np.pi/360) 
long2y = -119.5048141 * (2*np.pi/360) 

lat3x = 46.3973998 * (2*np.pi/360) 
lat4x = 46.4532495 * (2*np.pi/360) 
long3y = -119.4495392 * (2*np.pi/360) 
long4y = -119.3492884 * (2*np.pi/360) 

def to_cartesian(lat,lon): 
    x = r * np.cos(lon)*np.sin(lat) 
    y = r * np.sin(lon)*np.sin(lat) 
    z = r * np.cos(lat) 
    return [x,y,z] 

p1 = to_cartesian(lat1x,long1y) 
p2 = to_cartesian(lat2x,long2y) 
p3 = to_cartesian(lat3x,long3y) 
p4 = to_cartesian(lat4x,long4y) 

X = np.array([p1,p2,p3,p4]) 
ax.scatter(X[:,0],X[:,1],X[:,2], color = "r") 


plt.show() 

由于矩形非常小，您需要放大很多才能看到它。