计算Python中向量字段的卷曲并使用matplotlib进行绘制 [英] Calculate curl of a vector field in Python and plot it with matplotlib

问题描述

我需要计算向量场的卷曲并用 matplotlib 绘制它.我正在寻找的一个简单示例可以像这样:

I need to calculate the curl of a vector field and plot it with matplotlib. A simple example of what I am looking for could be put like that:

如何在 quiver3d_demo.py 在 matplotlib 库中?

How can I calculate and plot the curl of the vector field in the quiver3d_demo.py in the matplotlib gallery?

推荐答案

您可以使用

You can use sympy.curl() to calculate the curl of a vector field.

示例:

假设 F(x,y,z) = y²zi - xyj + z²k，则:

Suppose F(x,y,z) = y²zi - xyj + z²k, then:

• y 将是 R[1]，x 是 R[0] 和 z 是 R[2]
• 3个轴的单位向量i、j、k，分别为Rx、<代码>Ry，Rz.

• y would be R[1], x is R[0] and z is R[2]
• the unit vectors i, j, k of the 3 axes, would be respectively R.x, R.y, R.z.

计算矢量场卷曲的代码为:

from sympy.physics.vector import ReferenceFrame
from sympy.physics.vector import curl
R = ReferenceFrame('R')

F = R[1]**2 * R[2] * R.x - R[0]*R[1] * R.y + R[2]**2 * R.z

G = curl(F, R)  

在这种情况下，G等于 R_y ** 2 * R.y +(-2 * R_y * R_z-R_y)* R.z 或换句话说，
G = 0i + y²j + (-2yz-y)k.

In that case G would be equal to R_y**2*R.y + (-2*R_y*R_z - R_y)*R.z or, in other words,
G = 0i + y²j + (-2yz-y)k.

要绘制它，您需要将上述结果转换为 3 个单独的函数；你，v，w.

To plot it you need to convert the above result into 3 separate functions; u,v,w.

(以下示例摘自此 matplotlib示例):

(example below adapted from this matplotlib example):

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np

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

x, y, z = np.meshgrid(np.arange(-0.8, 1, 0.2),
                      np.arange(-0.8, 1, 0.2),
                      np.arange(-0.8, 1, 0.8))

u = 0
v = y**2
w = -2*y*z - y

ax.quiver(x, y, z, u, v, w, length=0.1)

plt.show()

最终结果是:

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