我用Matplotlib搜索了如何用尽可能少的指令绘制一些东西,但我在文档中找不到任何帮助。
我想画出以下内容:
的线框立方体
<>F29的向量
如何做到这一点?
发布于 2012-06-22 20:39:27
这有点复杂,但您可以通过以下代码绘制所有对象:
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
from itertools import product, combinations
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_aspect("equal")
# draw cube
r = [-1, 1]
for s, e in combinations(np.array(list(product(r, r, r))), 2):
if np.sum(np.abs(s-e)) == r[1]-r[0]:
ax.plot3D(*zip(s, e), color="b")
# draw sphere
u, v = np.mgrid[0:2*np.pi:20j, 0:np.pi:10j]
x = np.cos(u)*np.sin(v)
y = np.sin(u)*np.sin(v)
z = np.cos(v)
ax.plot_wireframe(x, y, z, color="r")
# draw a point
ax.scatter([0], [0], [0], color="g", s=100)
# draw a vector
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 draw(self, renderer):
xs3d, ys3d, zs3d = self._verts3d
xs, ys, zs = proj3d.proj_transform(xs3d, ys3d, zs3d, renderer.M)
self.set_positions((xs[0], ys[0]), (xs[1], ys[1]))
FancyArrowPatch.draw(self, renderer)
a = Arrow3D([0, 1], [0, 1], [0, 1], mutation_scale=20,
lw=1, arrowstyle="-|>", color="k")
ax.add_artist(a)
plt.show()
发布于 2017-01-26 21:44:20
对于仅绘制箭头,有一种更简单的方法:
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_aspect("equal")
#draw the arrow
ax.quiver(0,0,0,1,1,1,length=1.0)
plt.show()
箭袋实际上可以用来一次绘制多个向量。用法如下:- from [http://matplotlib.org/mpl_toolkits/mplot3d/tutorial.html?highlight=quiver#mpl_toolkits.mplot3d.Axes3D.quiver]
箭图(X,Y,Z,U,V,W,**kwargs)
参数:
X,Y,Z:箭头位置的x,y和z坐标
U,V,W:箭头向量的x,y和z分量
参数可以是类似数组的或标量的。
关键字参数:
length : 1.0 | float每个箭图的长度,默认为1.0,单位与轴相同
arrow_length_ratio: 0.3 |浮动箭头相对于箭嘴的比率,默认为0.3
pivot :‘尾部’|‘中间’|‘尖端’位于网格点的箭头部分;箭头围绕该点旋转,因此得名pivot。默认值为‘tail’
normalize: False | True如果为True,则所有箭头的长度都相同。默认值为False,其中箭头的长度将根据u、v、w的值而有所不同。
发布于 2020-09-02 23:16:33
我的答案是将以上两者结合起来,并扩展到绘制用户定义的不透明度的球体和一些注释。它在磁共振图像(MRI)的球面上的b矢量可视化中得到了应用。希望你会发现它很有用:
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = fig.gca(projection='3d')
# draw sphere
u, v = np.mgrid[0:2*np.pi:50j, 0:np.pi:50j]
x = np.cos(u)*np.sin(v)
y = np.sin(u)*np.sin(v)
z = np.cos(v)
# alpha controls opacity
ax.plot_surface(x, y, z, color="g", alpha=0.3)
# a random array of 3D coordinates in [-1,1]
bvecs= np.random.randn(20,3)
# tails of the arrows
tails= np.zeros(len(bvecs))
# heads of the arrows with adjusted arrow head length
ax.quiver(tails,tails,tails,bvecs[:,0], bvecs[:,1], bvecs[:,2],
length=1.0, normalize=True, color='r', arrow_length_ratio=0.15)
ax.set_xlabel('X-axis')
ax.set_ylabel('Y-axis')
ax.set_zlabel('Z-axis')
ax.set_title('b-vectors on unit sphere')
plt.show()
https://stackoverflow.com/questions/11140163
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