python画3d图-Python绘制3D图形

时间 2021-04-03

来自:https://www.jb51.net/article/139349.htm

3D图形在数据分析、数据建模、图形和图像处理等领域中都有着广泛的应用，下面将给大家介绍一下如何使用python进行3D图形的绘制，包括3D散点、3D表面、3D轮廓、3D直线（曲线）以及3D文字等的绘制。

准备工作：

python中绘制3D图形，依旧使用常用的绘图模块matplotlib，但需要安装mpl_toolkits工具包，安装方法如下：windows命令行进入到python安装目录下的Scripts文件夹下，执行： pip install --upgrade matplotlib即可；linux环境下直接执行该命令。

安装好这个模块后，即可调用mpl_tookits下的mplot3d类进行3D图形的绘制。

下面以实例进行说明。

1、3D表面形状的绘制

from mpl_toolkits.mplot3dimport Axes3D

import matplotlib.pyplot as plt

import numpy as np

fig= plt.figure()

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

# Make data

u= np.linspace(0,2 * np.pi,100)

v= np.linspace(0, np.pi,100)

x= 10 * np.outer(np.cos(u), np.sin(v))

y= 10 * np.outer(np.sin(u), np.sin(v))

z= 10 * np.outer(np.ones(np.size(u)), np.cos(v))

# Plot the surface

ax.plot_surface(x, y, z, color='b')

plt.show()

球表面，结果如下：

2、3D直线（曲线）的绘制

import matplotlib as mpl

from mpl_toolkits.mplot3dimport 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()

这段代码用于绘制一个螺旋状3D曲线，结果如下：

3、绘制3D轮廓

from mpl_toolkits.mplot3dimport axes3d

import matplotlib.pyplot as plt

from matplotlibimport cm

fig= plt.figure()

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

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

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(-40,40)

ax.set_ylabel('Y')

ax.set_ylim(-40,40)

ax.set_zlabel('Z')

ax.set_zlim(-100,100)

plt.show()

绘制结果如下：

4、绘制3D直方图

from mpl_toolkits.mplot3dimport Axes3D

import matplotlib.pyplot as plt

import numpy as np

fig= plt.figure()

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

x, y= np.random.rand(2,100)* 4

hist, xedges, yedges= np.histogram2d(x, y, bins=4,range=[[0,4], [0,4]])

# Construct arrays for the anchor positions of the 16 bars.

# Note: np.meshgrid gives arrays in (ny, nx) so we use 'F' to flatten xpos,

# ypos in column-major order. For numpy >= 1.7, we could instead call meshgrid

# with indexing='ij'.

xpos, ypos= np.meshgrid(xedges[:-1]+ 0.25, yedges[:-1]+ 0.25)

xpos= xpos.flatten('F')

ypos= ypos.flatten('F')

zpos= np.zeros_like(xpos)

# Construct arrays with the dimensions for the 16 bars.

dx= 0.5 * np.ones_like(zpos)

dy= dx.copy()

dz= hist.flatten()

ax.bar3d(xpos, ypos, zpos, dx, dy, dz, color='b', zsort='average')

plt.show()

绘制结果如下：

5、绘制3D网状线

from mpl_toolkits.mplot3dimport 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()

绘制结果如下：

6、绘制3D三角面片图

from mpl_toolkits.mplot3dimport 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(0.125,1.0, n_radii)

angles= np.linspace(0,2*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.

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

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

# Compute z to make the pringle surface.

z= 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(

绘制结果如下：

7、绘制3D散点图

from mpl_toolkits.mplot3dimport 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, zhighin [('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()

绘制结果如下：

8、绘制3D文字

from mpl_toolkits.mplot3dimport Axes3D

import matplotlib.pyplot as plt

fig= plt.figure()

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

# Demo 1: zdir

zdirs= (None,'x','y','z', (1,1,0), (1,1,1))

xs= (1,4,4,9,4,1)

ys= (2,5,8,10,1,2)

zs= (10,3,8,9,1,8)

for zdir, x, y, zin 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(9,0,0,"red", color='red')

# Demo 3: text2D

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

ax.text2D(0.05,0.95,"2D Text", transform=ax.transAxes)

# Tweaking display region and labels

ax.set_xlim(0,10)

ax.set_ylim(0,10)

ax.set_zlim(0,10)

ax.set_xlabel('X axis')

ax.set_ylabel('Y axis')

ax.set_zlabel('Z axis')

plt.show(

绘制结果如下：

9、3D条状图

from mpl_toolkits.mplot3dimport Axes3D

import matplotlib.pyplot as plt

import numpy as np

fig= plt.figure()

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

for c, zin zip(['r','g','b','y'], [30,20,10,0]):

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()

绘制结果如下：

以上所述是小编给大家介绍的python绘制3D图形，希望对大家有所帮助，如果大家有任何疑问请给我留言，小编会及时回复大家的。在此也非常感谢大家对脚本之家网站的支持