使用带有内部随机点数的matplotlib 3D图绘制椭圆体时出错：Python

Question

While plotting an ellipsoid using axes3D, I met with an error

TypeError: unbound method plot() must be called with Axes3D instance as first argument (got ndarray instance instead)

I need to plot the ellipsoid with random number of points inside. SO i used random module. But I couldn't identify the reason for such an error. The program is given below.

import random
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import *

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
n = 1000000
a = input("Enter the value of semi major axis: \n")
b = input("Enter the value of semi minor axis: \n")
c = input("Enter the value of c \n")
x = random.uniform(-a, a, n)
y = random.uniform(-b, b, n)
z = random.uniform(-c, c, n)
r = (x ** 2 / a ** 2) + (y ** 2 / b ** 2) + (z ** 2 / c ** 2)
rd = r[:] <= 1
xd = x[rd]
yd = y[rd]
zd = z[rd]
Axes3D.plot3D(xd, yd, zd, "*")
plot.show()

May be there some errors. I am a beginner and please help me.

Answer 1

Your import random cannot work, leading to problems even before you try to plot your cloud of points, because random.uniform has a different signature from what you use.

I suppose that the real statement you use is from numpy import random ...

Further, the standard way (and there is a reason) to import the 3d capabilities is from mpl_toolkits.mplot3d import Axes3D — this modifies the definition of the axes object, and that's all you need.

Finally, you use the .plot() method when what you really need is .scatter() , that doesn't draw the lines connecting the individual points.

My version of what you're trying to accomplish is as follows (note that I use the modified ax object, not Axes3D ...)

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from numpy.random import uniform

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

n, a, b, c = 2000, 10.0, 6.0, 20.0
x, y, z = [uniform(-d, d, n) for d in (a, b, c)]
inside =  ((x/a)**2 + (y/b)**2 + (z/c)**2) <= 1.0

ax.scatter(x[inside], y[inside], z[inside])

plt.show()