[英]Plotting a 3D vector field on 2D plane in Python
I would like to plot a 3D vector field on a 2D plane.我想 plot 3D 二维平面上的矢量场。
i tried plotting but not able to get a 3D view of the vector fields
我尝试绘图但无法获得向量场的 3D 视图
any help would be highly appreciated and thankful任何帮助将不胜感激和感激
tried plotting using matplotlib 3d but with no success尝试使用 matplotlib 3d 进行绘图但没有成功
Here's a version inspired by this post that gives a much cleaner picture.这是一个受这篇文章启发的版本,它提供了更清晰的图片。
import numpy as np
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.patches import FancyArrowPatch
from mpl_toolkits.mplot3d import proj3d
class Arrow3D(FancyArrowPatch):
def __init__(self, xs, ys, zs, *args, **kwargs):
FancyArrowPatch.__init__(self, (0,0), (0,0), *args, **kwargs)
self._verts3d = xs, ys, zs
def do_3d_projection(self, renderer=None):
xs3d, ys3d, zs3d = self._verts3d
xs, ys, zs = proj3d.proj_transform(xs3d, ys3d, zs3d, self.axes.M)
self.set_positions((xs[0],ys[0]),(xs[1],ys[1]))
return np.min(zs)
coords_y = np.arange(-4,5)
coords_z = np.arange(-4,5)
coords = np.vstack([[0,y,z] for y in coords_y for z in coords_z])
angle = pi/4
R_mat = np.array([[cos(angle),-sin(angle)],[sin(angle),cos(angle)]])
vel_yz = coords[:,1:]@R_mat.T
vel = np.hstack([.1*np.ones([len(coords),1]),vel_yz])
fig,ax = plt.subplots(figsize = (10,10),subplot_kw = {"projection":"3d"})
ax.view_init(vertical_axis = 'x')
ax.plot3D(*coords.T, 'ro')
for p,v in zip(coords,.2*vel):
a = Arrow3D(*zip(p,p+v), mutation_scale=20,
lw=2, arrowstyle="-|>", color="b")
ax.add_artist(a)
Result:结果:
Here's something that gets pretty close to what you're looking for, using that 3D quiver method and setting the x-axis to be the vertical axis.使用 3D quiver 方法并将 x 轴设置为垂直轴,这与您正在寻找的东西非常接近。
I'm still looking into how we could get the arrows to look a little nicer.我仍在研究如何让箭头看起来更漂亮。
import numpy as np
import matplotlib.pyplot as plt
from numpy.random import randn
from numpy import sin, cos, pi
coords_y = np.arange(-4,5)
coords_z = np.arange(-4,5)
coords = np.vstack([[0,y,z] for y in coords_y for z in coords_z])
R_mat = np.array([[cos(pi/4),-sin(pi/4)],[sin(pi/4),cos(pi/4)]])
vel_yz = coords[:,1:]@R_mat.T
vel = np.hstack([.1*np.ones([len(coords),1]),vel_yz])
fig,ax = plt.subplots(figsize = (10,10),subplot_kw = {"projection":"3d"})
ax.view_init(vertical_axis = 'x')
ax.plot3D(*coords.T, 'ro')
ax.quiver(*coords.T, *vel.T, length = .1)
Sample result:示例结果:
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