https://www.cnblogs.com/xingshansi/p/6777945.html
python绘制三维图
作者：桂。
时间：2017-04-27 23:24:55
链接：http://www.cnblogs.com/xingshansi/p/6777945.html
本文仅仅梳理最基本的绘图方法。
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'
)
|
二、直线绘制（Line plots）
基本用法：
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ax.plot(x,y,z,label
=
' '
)
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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
)
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()
|
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'
)
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()
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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.
X
=
np.arange(
-
5
,
5
,
0.25
)
Y
=
np.arange(
-
5
,
5
,
0.25
)
X, Y
=
np.meshgrid(X, Y)
R
=
np.sqrt(X
*
*
2
+
Y
*
*
2
)
Z
=
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(
-
1.01
,
1.01
)
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)
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- 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(
0.125
,
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()
|
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(
-
40
,
40
)
ax.set_ylabel(
'Y'
)
ax.set_ylim(
-
40
,
40
)
ax.set_zlabel(
'Z'
)
ax.set_zlim(
-
100
,
100
)
plt.show()
|
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(
-
40
,
40
)
ax.set_ylabel(
'Y'
)
ax.set_ylim(
-
40
,
40
)
ax.set_zlabel(
'Z'
)
ax.set_zlim(
-
100
,
100
)
plt.show()
|
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'
], [
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()
|
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.
x
=
np.linspace(
0
,
1
,
100
)
y
=
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'
)
x
=
np.random.sample(
20
*
len
(colors))
y
=
np.random.sample(
20
*
len
(colors))
c_list
=
[]
for
c
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(
0
,
1
)
ax.set_ylim(
0
,
1
)
ax.set_zlim(
0
,
1
)
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：
MATLAB：
subplot(2,2,1)subplot(2,2,2)subplot(2,2,[3,4])Python:
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(
2
,
2
,
1
, projection
=
'3d'
)
# plot a 3D surface like in the example mplot3d/surface3d_demo
X
=
np.arange(
-
5
,
5
,
0.25
)
Y
=
np.arange(
-
5
,
5
,
0.25
)
X, Y
=
np.meshgrid(X, Y)
R
=
np.sqrt(X
*
*
2
+
Y
*
*
2
)
Z
=
np.sin(R)
surf
=
ax.plot_surface(X, Y, Z, rstride
=
1
, cstride
=
1
, cmap
=
cm.coolwarm,
linewidth
=
0
, antialiased
=
False
)
ax.set_zlim(
-
1.01
,
1.01
)
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()
|
补充：
文本注释的基本用法：
code:
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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'
, (
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()
|
参考：
作者：桂。
时间：2017-04-27 23:24:55
链接：http://www.cnblogs.com/xingshansi/p/6777945.html
本文仅仅梳理最基本的绘图方法。
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：
|
1
2
3
4
|
import
matplotlib.pyplot as plt
from
mpl_toolkits.mplot3d
import
Axes3D
fig
=
plt.figure()
ax
=
fig.add_subplot(
111
, projection
=
'3d'
)
|
二、直线绘制（Line plots）
基本用法：
|
1
|
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
)
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()
|
三、散点绘制（Scatter plots）
基本用法：
|
1
|
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'
)
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()
|
四、线框图（Wireframe plots）
基本用法：
|
1
|
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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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()
|
五、表面图（Surface plots）
基本用法：
|
1
|
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.
X
=
np.arange(
-
5
,
5
,
0.25
)
Y
=
np.arange(
-
5
,
5
,
0.25
)
X, Y
=
np.meshgrid(X, Y)
R
=
np.sqrt(X
*
*
2
+
Y
*
*
2
)
Z
=
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(
-
1.01
,
1.01
)
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()
|
六、三角表面图（Tri-Surface plots）
基本用法：
|
1
|
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(
0.125
,
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()
|
七、等高线（Contour plots）
基本用法：
|
1
|
ax.contour(X, Y, Z,
*
args,
*
*
kwargs)
|
code:
|
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5
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9
10
11
|
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()
|
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(
-
40
,
40
)
ax.set_ylabel(
'Y'
)
ax.set_ylim(
-
40
,
40
)
ax.set_zlabel(
'Z'
)
ax.set_zlim(
-
100
,
100
)
plt.show()
|
也可以是三维等高线在二维平面的投影：
code:
|
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19
20
|
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(
-
40
,
40
)
ax.set_ylabel(
'Y'
)
ax.set_ylim(
-
40
,
40
)
ax.set_zlabel(
'Z'
)
ax.set_zlim(
-
100
,
100
)
plt.show()
|
八、Bar plots（条形图）
基本用法：
|
1
|
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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20
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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'
], [
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()
|
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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31
|
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.
x
=
np.linspace(
0
,
1
,
100
)
y
=
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'
)
x
=
np.random.sample(
20
*
len
(colors))
y
=
np.random.sample(
20
*
len
(colors))
c_list
=
[]
for
c
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(
0
,
1
)
ax.set_ylim(
0
,
1
)
ax.set_zlim(
0
,
1
)
ax.set_xlabel(
'X'
)
ax.set_ylabel(
'Y'
)
ax.set_zlabel(
'Z'
)
|
B-子图Subplot用法
与MATLAB不同的是，如果一个四子图效果，如：
MATLAB：
subplot(2,2,1)subplot(2,2,2)subplot(2,2,[3,4])Python:
subplot(2,2,1)subplot(2,2,2)subplot(2,1,2)
code:
|
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13
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23
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29
30
31
32
33
34
35
36
37
|
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(
2
,
2
,
1
, projection
=
'3d'
)
# plot a 3D surface like in the example mplot3d/surface3d_demo
X
=
np.arange(
-
5
,
5
,
0.25
)
Y
=
np.arange(
-
5
,
5
,
0.25
)
X, Y
=
np.meshgrid(X, Y)
R
=
np.sqrt(X
*
*
2
+
Y
*
*
2
)
Z
=
np.sin(R)
surf
=
ax.plot_surface(X, Y, Z, rstride
=
1
, cstride
=
1
, cmap
=
cm.coolwarm,
linewidth
=
0
, antialiased
=
False
)
ax.set_zlim(
-
1.01
,
1.01
)
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()
|
补充：
文本注释的基本用法：
code:
|
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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()
|
参考：