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
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
|
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
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
|
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
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
|
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
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
|
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
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
|
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
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
|
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
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
|
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
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
|
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
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
|
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：
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