Python绘制3D图形

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.mplot3d import 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.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()

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.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) 
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.mplot3d import 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.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()

绘制结果如下：

6、绘制3D三角面片图

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(0.125, 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.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()

绘制结果如下：

8、绘制3D文字

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', (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, 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(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.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'], [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：

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