Python可视化-matplotlib用法详解(二)3D图形绘制

一、绘制线形图

Axes3D.plot 函数用来绘制线形图。

import matplotlib.pyplot as plt
import numpy as np

from mpl_toolkits.mplot3d import Axes3D

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

x = np.linspace(-10, 10, 1000)
y = np.linspace(-10, 10, 1000)
z = np.add(x, y)

ax.plot(x, y, z)
plt.show()

二、散点图

Axes3D.scatter 函数用来绘制散点图。

import matplotlib.pyplot as plt
import numpy as np

from mpl_toolkits.mplot3d import Axes3D

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

count = 100
range1 = 100

xs = np.random.rand(count) * range1
ys = np.random.rand(count) * range1
zs = np.random.rand(count) * range1

ax.scatter(xs, ys, zs, s=zs, c=zs)

ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')

plt.show()

三、线框图

Axes3D.plot_wireframe 函数用来绘制线框图。

# meshgrid_demo.py

import numpy as np

x = np.arange(1, 4)
y = np.arange(11, 16)
print(x)
print(y)

X, Y = np.meshgrid(x, y)
print(X)
print(Y)

[1 2 3]
[11 12 13 14 15]
[[1 2 3]
 [1 2 3]
 [1 2 3]
 [1 2 3]
 [1 2 3]]
[[11 11 11]
 [12 12 12]
 [13 13 13]
 [14 14 14]
 [15 15 15]]

import matplotlib.pyplot as plt
import numpy as np

from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure()
ax = fig.add_subplot