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')
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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)
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- 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：
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ax.plot_wireframe(X, Y, Z, *args, **kwargs)
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- 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() |
五、表面图（Surface plots）
基本用法：
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ax.plot_surface(X, Y, Z, *args, **kwargs)
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- 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：
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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)
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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() |
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
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- 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 labelsax.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 tallfig = plt.figure(figsize=plt.figaspect(0.5))
#===============# First subplot#===============# set up the axes for the first plotax = fig.add_subplot(2, 2, 1, projection='3d')
# plot a 3D surface like in the example mplot3d/surface3d_demoX = 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 plotax = fig.add_subplot(2,1,2, projection='3d')
# plot a 3D wireframe like in the example mplot3d/wire3d_demoX, 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: zdirzdirs = (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: colorax.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 labelsax.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：