赢得10 x64 Anaconda Python 2.7
我使用以下代码在高斯曲面上绘制渐开线螺旋。
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
# Spiral parameters
samNum = 1000
spConst = 10.0
t = np.linspace(0, 6*np.pi, samNum)
# Coordinates of involute spiral on xy-plane
coords = np.zeros([samNum, 3])
coords[:,0] = spConst * (np.cos(t) + t * np.sin(t)) # x coord
coords[:,1] = spConst * (np.sin(t) - t * np.cos(t)) # y coord
# Paramters for 2D Gaussian surface
amp = 200
sigma_x = 75.0
sigma_y = 75.0
theta = np.pi
a = np.cos(theta)**2 / (2 * sigma_x**2) + np.sin(theta)**2 / (2 * sigma_y**2)
b = -np.sin(2 * theta) / (4 * sigma_x**2) + np.sin(2 * theta) / (4 * sigma_y**2)
c = np.sin(theta)**2 / (2 * sigma_x**2) + np.cos(theta)**2 / (2 * sigma_y**2)
# z coords of spiral projected onto Gaussian surface
coords[:,2] = amp * np.exp(-(a * coords[:,0]**2 - 2 * b * coords[:,0]*coords[:,1] + c * coords[:,1]**2)) # z coord
# plot 3D spiral
ax.scatter(coords[:,0], coords[:,1], coords[:,2], s=1, c='k')
# plot lines projecting 3D spiral on to the xy-plane
for p in range(samNum):
ax.plot([coords[p,0], coords[p,0]], [coords[p,1], coords[p,1]], [0, coords[p,2]], color='g', linewidth=0.1)
ax.set_xlabel('X axis')
ax.set_ylabel('Y axis')
ax.set_zlabel('Z axis')
这给出了以下输出...
我想将绿丝带转换为连续的表面。我看过
matplotlib
中的参数化曲面,但无法理解如何将其隐藏到曲面中。那有可能吗?任何指针表示赞赏。
最佳答案
原则上,您已经拥有了所需的一切,
t = np.linspace(0, 6*np.pi, samNum)
T, Z = np.meshgrid(t, [0,1])
X = spConst * (np.cos(T) + T* np.sin(T))
Y = spConst * (np.sin(T) - T * np.cos(T))
给出
X
和Y
坐标,而上Z
坐标是通过Z[1,:] = coords[:,2]
获得的。import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
# Spiral parameters
samNum = 1000
spConst = 10.0
t = np.linspace(0, 6*np.pi, samNum)
T, Z = np.meshgrid(t, [0,1])
X = spConst * (np.cos(T) + T* np.sin(T))
Y = spConst * (np.sin(T) - T * np.cos(T))
# Coordinates of involute spiral on xy-plane
coords = np.zeros([samNum, 3])
coords[:,0] = spConst * (np.cos(t) + t * np.sin(t)) # x coord
coords[:,1] = spConst * (np.sin(t) - t * np.cos(t)) # y coord
# Paramters for 2D Gaussian surface
amp = 200
sigma_x = 75.0
sigma_y = 75.0
theta = np.pi
a = np.cos(theta)**2 / (2 * sigma_x**2) + np.sin(theta)**2 / (2 * sigma_y**2)
b = -np.sin(2 * theta) / (4 * sigma_x**2) + np.sin(2 * theta) / (4 * sigma_y**2)
c = np.sin(theta)**2 / (2 * sigma_x**2) + np.cos(theta)**2 / (2 * sigma_y**2)
# z coords of spiral projected onto Gaussian surface
coords[:,2] = amp * np.exp(-(a * coords[:,0]**2 - 2 * b * coords[:,0]*coords[:,1] + c * coords[:,1]**2)) # z coord
Z[1,:] = coords[:,2]
ax.plot_surface(X,Y,Z)
# plot 3D spiral
ax.scatter(coords[:,0], coords[:,1], coords[:,2], s=1, c='k')
ax.set_xlabel('X axis')
ax.set_ylabel('Y axis')
ax.set_zlabel('Z axis')
plt.show()
关于python - 将图转换为表面图,matplotlib?,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/43926473/