繪製球體表面上的矩形區域

Question

我想要繪製出球體表面上的矩形區域。

這是我對球的代碼：

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() 

這些點將從緯度/經度被轉換到購物車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") 

這些是點和那裏轉換到笛卡爾座標我很難讓它們出現在球體的表面上。它們也應該形成粗糙的矩形形狀。我希望能夠連接點在球體表面繪製一個矩形。因爲矩形的意思是非常小的

Answer 1

您的轉換爲直角座標可能是錯誤的。剛創建時球一樣，你可能想使用通常的

不過，當然這將取決於如何「LAT」和「結腸」的球體上的定義。

更重要的是，散點圖不正確。它總是scatter(x,y,z)，第一個參數x座標，第二個參數y座標，第三個參數z座標。

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() 

由於矩形非常小，您需要放大很多才能看到它。