python画3d图-Python绘制3D图形
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
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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
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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
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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
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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
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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
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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
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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
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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
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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