用Python绘制三维立体图形，从易到难（附完整代码）

本文仅仅梳理最基本的绘图方法。

一、初始化

假设已经安装了matplotlib工具包。

利用matplotlib.figure.Figure创建一个图框：

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import matplotlib.pyplot as plt

from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure()

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

二、直线绘制（Line plots）

基本用法：

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ax.plot(x,y,z,label=' ')

code:

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import matplotlib as mpl

from mpl_toolkits.mplot3d import Axes3D

import numpy as np

import matplotlib.pyplot as plt

mpl.rcParams['legend.fontsize'] = 10

fig = plt.figure()

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

theta = np.linspace(-4 * np.pi, 4 * np.pi, 100)

z = np.linspace(-2, 2, 100)

r = z**2 + 1

x = r * np.sin(theta)

y = r * np.cos(theta)

ax.plot(x, y, z, label='parametric curve')

ax.legend()

plt.show()

三、散点绘制（Scatter plots）

基本用法：

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ax.scatter(xs, ys, zs, s=20, c=None, depthshade=True, *args, *kwargs)

xs,ys,zs：输入数据；
s:scatter点的尺寸
c:颜色，如c = 'r'就是红色；
depthshase:透明化，True为透明，默认为True，False为不透明
*args等为扩展变量，如maker = 'o'，则scatter结果为’o‘的形状

code:

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from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt

import numpy as np

def randrange(n, vmin, vmax):

    '''

    Helper function to make an array of random numbers having shape (n, )

    with each number distributed Uniform(vmin, vmax).

    '''

    return (vmax - vmin)*np.random.rand(n) + vmin

fig = plt.figure()

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

n = 100

# For each set of style and range settings, plot n random points in the box

# defined by x in [23, 32], y in [0, 100], z in [zlow, zhigh].

for c, m, zlow, zhigh in [('r', 'o', -50, -25), ('b', '^', -30, -5)]:

    xs = randrange(n, 23, 32)

    ys = randrange(n, 0, 100)

    zs = randrange(n, zlow, zhigh)

    ax.scatter(xs, ys, zs, c=c, marker=m)

ax.set_xlabel('X Label')

ax.set_ylabel('Y Label')

ax.set_zlabel('Z Label')

plt.show()

四、线框图（Wireframe plots）

基本用法：

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ax.plot_wireframe(X, Y, Z, *args, **kwargs)

X,Y,Z：输入数据
rstride:行步长
cstride:列步长
rcount:行数上限
ccount:列数上限

code:

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from mpl_toolkits.mplot3d import axes3d

import matplotlib.pyplot as plt

fig = plt.figure()

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

# Grab some test data.

X, Y, Z = axes3d.get_test_data(0.05)

# Plot a basic wireframe.

ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)

plt.show()

五、表面图（Surface plots）

基本用法：

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ax.plot_surface(X, Y, Z, *args, **kwargs)

X,Y,Z：数据
rstride、cstride、rcount、ccount:同Wireframe plots定义
color:表面颜色
cmap:图层

code:

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from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt

from matplotlib import cm

from matplotlib.ticker import LinearLocator, FormatStrFormatter

import numpy as np

fig = plt.figure()

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

# Make data.

X = np.arange(-5, 5, 0.25)

Y = np.arange(-5, 5, 0.25)

X, Y = np.meshgrid(X, Y)

R = np.sqrt(X**2 + Y**2)

Z = np.sin(R)

# Plot the surface.

surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,

linewidth=0, antialiased=False)

# Customize the z axis.

ax.set_zlim(-1.01, 1.01)

ax.zaxis.set_major_locator(LinearLocator(10))

ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

# Add a color bar which maps values to colors.

fig.colorbar(surf, shrink=0.5, aspect=5)

plt.show()