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python绘制三维图

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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')

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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)

= np.linspace(-22100)

= z**2 + 1

= * np.sin(theta)

= * np.cos(theta)

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

ax.legend()

 

plt.show()

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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')

 

= 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, 2332)

    ys = randrange(n, 0100)

    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()

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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()

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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.

= np.arange(-550.25)

= np.arange(-550.25)

X, Y = np.meshgrid(X, Y)

= np.sqrt(X**2 + Y**2)

= 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(-1.011.01)

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()

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六、三角表面图(Tri-Surface plots)

基本用法:

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ax.plot_trisurf(*args, **kwargs)

  • X,Y,Z:数据
  • 其他参数类似surface-plot

code:

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from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt

import numpy as np

 

 

n_radii = 8

n_angles = 36

 

# Make radii and angles spaces (radius r=0 omitted to eliminate duplication).

radii = np.linspace(0.1251.0, n_radii)

angles = np.linspace(02*np.pi, n_angles, endpoint=False)

 

# Repeat all angles for each radius.

angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)

 

# Convert polar (radii, angles) coords to cartesian (x, y) coords.

# (0, 0) is manually added at this stage,  so there will be no duplicate

# points in the (x, y) plane.

= np.append(0, (radii*np.cos(angles)).flatten())

= np.append(0, (radii*np.sin(angles)).flatten())

 

# Compute z to make the pringle surface.

= np.sin(-x*y)

 

fig = plt.figure()

ax = fig.gca(projection='3d')

 

ax.plot_trisurf(x, y, z, linewidth=0.2, antialiased=True)

 

plt.show()

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七、等高线(Contour plots)

基本用法:

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ax.contour(X, Y, Z, *args, **kwargs)

code:

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from mpl_toolkits.mplot3d import axes3d

import matplotlib.pyplot as plt

from matplotlib import cm

 

fig = plt.figure()

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

X, Y, Z = axes3d.get_test_data(0.05)

cset = ax.contour(X, Y, Z, cmap=cm.coolwarm)

ax.clabel(cset, fontsize=9, inline=1)

 

plt.show()

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二维的等高线,同样可以配合三维表面图一起绘制:

code:

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from mpl_toolkits.mplot3d import axes3d

from mpl_toolkits.mplot3d import axes3d

import matplotlib.pyplot as plt

from matplotlib import cm

 

fig = plt.figure()

ax = fig.gca(projection='3d')

X, Y, Z = axes3d.get_test_data(0.05)

ax.plot_surface(X, Y, Z, rstride=8, cstride=8, alpha=0.3)

cset = ax.contour(X, Y, Z, zdir='z', offset=-100, cmap=cm.coolwarm)

cset = ax.contour(X, Y, Z, zdir='x', offset=-40, cmap=cm.coolwarm)

cset = ax.contour(X, Y, Z, zdir='y', offset=40, cmap=cm.coolwarm)

 

ax.set_xlabel('X')

ax.set_xlim(-4040)

ax.set_ylabel('Y')

ax.set_ylim(-4040)

ax.set_zlabel('Z')

ax.set_zlim(-100100)

 

plt.show()

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也可以是三维等高线在二维平面的投影:

code:

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from mpl_toolkits.mplot3d import axes3d

import matplotlib.pyplot as plt

from matplotlib import cm

 

fig = plt.figure()

ax = fig.gca(projection='3d')

X, Y, Z = axes3d.get_test_data(0.05)

ax.plot_surface(X, Y, Z, rstride=8, cstride=8, alpha=0.3)

cset = ax.contourf(X, Y, Z, zdir='z', offset=-100, cmap=cm.coolwarm)

cset = ax.contourf(X, Y, Z, zdir='x', offset=-40, cmap=cm.coolwarm)

cset = ax.contourf(X, Y, Z, zdir='y', offset=40, cmap=cm.coolwarm)

 

ax.set_xlabel('X')

ax.set_xlim(-4040)

ax.set_ylabel('Y')

ax.set_ylim(-4040)

ax.set_zlabel('Z')

ax.set_zlim(-100100)

 

plt.show()

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 八、Bar plots(条形图)

基本用法:

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ax.bar(left, height, zs=0, zdir='z'*args, **kwargs

  • x,y,zs = z,数据
  • zdir:条形图平面化的方向,具体可以对应代码理解。

code:

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from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt

import numpy as np

 

fig = plt.figure()

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

for c, z in zip(['r''g''b''y'], [3020100]):

    xs = np.arange(20)

    ys = np.random.rand(20)

 

    # You can provide either a single color or an array. To demonstrate this,

    # the first bar of each set will be colored cyan.

    cs = [c] * len(xs)

    cs[0= 'c'

    ax.bar(xs, ys, zs=z, zdir='y', color=cs, alpha=0.8)

 

ax.set_xlabel('X')

ax.set_ylabel('Y')

ax.set_zlabel('Z')

 

plt.show()

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九、子图绘制(subplot)

  A-不同的2-D图形,分布在3-D空间,其实就是投影空间不空,对应code:

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from mpl_toolkits.mplot3d import Axes3D

import numpy as np

import matplotlib.pyplot as plt

 

fig = plt.figure()

ax = fig.gca(projection='3d')

 

# Plot a sin curve using the x and y axes.

= np.linspace(01100)

= np.sin(x * 2 * np.pi) / 2 + 0.5

ax.plot(x, y, zs=0, zdir='z', label='curve in (x,y)')

 

# Plot scatterplot data (20 2D points per colour) on the x and z axes.

colors = ('r''g''b''k')

= np.random.sample(20*len(colors))

= np.random.sample(20*len(colors))

c_list = []

for in colors:

    c_list.append([c]*20)

# By using zdir='y', the y value of these points is fixed to the zs value 0

# and the (x,y) points are plotted on the x and z axes.

ax.scatter(x, y, zs=0, zdir='y', c=c_list, label='points in (x,z)')

 

# Make legend, set axes limits and labels

ax.legend()

ax.set_xlim(01)

ax.set_ylim(01)

ax.set_zlim(01)

ax.set_xlabel('X')

ax.set_ylabel('Y')

ax.set_zlabel('Z')

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   B-子图Subplot用法

与MATLAB不同的是,如果一个四子图效果,如:

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MATLAB:

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subplot(2,2,1)

subplot(2,2,2)

subplot(2,2,[3,4])

Python:

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subplot(2,2,1)

subplot(2,2,2)

subplot(2,1,2)

code:

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import matplotlib.pyplot as plt

from mpl_toolkits.mplot3d.axes3d import Axes3D, get_test_data

from matplotlib import cm

import numpy as np

 

 

# set up a figure twice as wide as it is tall

fig = plt.figure(figsize=plt.figaspect(0.5))

 

#===============

#  First subplot

#===============

# set up the axes for the first plot

ax = fig.add_subplot(221, projection='3d')

 

# plot a 3D surface like in the example mplot3d/surface3d_demo

= np.arange(-550.25)

= np.arange(-550.25)

X, Y = np.meshgrid(X, Y)

= np.sqrt(X**2 + Y**2)

= np.sin(R)

surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.coolwarm,

                       linewidth=0, antialiased=False)

ax.set_zlim(-1.011.01)

fig.colorbar(surf, shrink=0.5, aspect=10)

 

#===============

# Second subplot

#===============

# set up the axes for the second plot

ax = fig.add_subplot(2,1,2, projection='3d')

 

# plot a 3D wireframe like in the example mplot3d/wire3d_demo

X, Y, Z = get_test_data(0.05)

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

 

plt.show()

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 补充:

文本注释的基本用法:

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from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt

 

 

fig = plt.figure()

ax = fig.gca(projection='3d')

 

# Demo 1: zdir

zdirs = (None'x''y''z', (110), (111))

xs = (144941)

ys = (2581012)

zs = (1038918)

 

for zdir, x, y, z in zip(zdirs, xs, ys, zs):

    label = '(%d, %d, %d), dir=%s' % (x, y, z, zdir)

    ax.text(x, y, z, label, zdir)

 

# Demo 2: color

ax.text(900"red", color='red')

 

# Demo 3: text2D

# Placement 0, 0 would be the bottom left, 1, 1 would be the top right.

ax.text2D(0.050.95"2D Text", transform=ax.transAxes)

 

# Tweaking display region and labels

ax.set_xlim(010)

ax.set_ylim(010)

ax.set_zlim(010)

ax.set_xlabel('X axis')

ax.set_ylabel('Y axis')

ax.set_zlabel('Z axis')

 

plt.show()

标签:set,python,三维图,plt,fig,ax,np,import,绘制
来源: https://www.cnblogs.com/yinwen/p/16257636.html