如何在 matplotlib 的 3d 视图中绘制 2d 流线 [英] How to plot a 2d streamline in 3d view in matplotlib

问题描述

我需要在像this这样的3d视图中绘制2d流线.正如 post 所建议的，我需要从 2d 中提取流线和箭头绘图，然后将其转换为 3d 数据.如何将此 2d 流线数据转换为 3d 数据并使用 mplot3d 进行绘图?

I need to plot a 2d streamline in 3d view like this. As suggested by the post, I need to extract streamlines and arrows from a 2d plot and then transform it to 3d data. How to transform this 2d streamline data to 3d data and plot using mplot3d?

提前致谢

拉杰

@gg349，在您的帮助下，我可以在 3d 视图中绘制流线图.情节是这里

@gg349, with your help I could plot streamline in 3d view. The plot is here

我有两个问题:

1. 如何从流图中提取箭头并将其绘制在 3d 中，就像您在之前的 post

如何提取 imshow() 数据并将其绘制为 3d.imshow() 的 2d 流线是 here

How to extract a imshow() data and plot it in 3d. The 2d streamline with imshow() is here

推荐答案

这个例子应该会让你开始:

this example should get you started:

import matplotlib.pyplot as plt
import numpy as np

fig_tmp, ax_tmp = plt.subplots()
x, y = np.mgrid[0:2.5:1000j, -2.5:2.5:1000j]
vx, vy = np.cos(x - y), np.sin(x - y)
res = ax_tmp.streamplot(x.T, y.T, vx, vy, color='k')
fig_tmp.show()
# extract the lines from the temporary figure
lines = res.lines.get_paths()
#for l in lines:
#    plot(l.vertices.T[0],l.vertices.T[1],'k')

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
for line in lines:
    old_x = line.vertices.T[0]
    old_y = line.vertices.T[1]
    # apply for 2d to 3d transformation here
    new_z = np.exp(-(old_x ** 2 + old_y ** 2) / 4)
    new_x = 1.2 * old_x
    new_y = 0.8 * old_y
    ax.plot(new_x, new_y, new_z, 'k')

这会生成一个中间临时图:

this generates an intermediate temporary figure:

从中提取行.然后根据自己的喜好应用 2d 到 3d 点变换，并在新的 3d 图中绘制相同的线条:

from which the lines are extracted. Then you apply your 2d to 3d point transformation of your liking, and plot the same lines in a new 3d figure:

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