Matplotlib.pyplot 三维绘图的实现示例

所属分类: 脚本专栏 / python 阅读数: 136
收藏 0 赞 0 分享

折线图

Axes3D.plot(xs,ys,*args,**kwargs)

Argument Description
xs, ys x, y coordinates of vertices
zs z value(s), either one for all points or one for each point.
zdir Which direction to use as z (‘x', ‘y' or ‘z') when plotting a 2D set.

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()

散点图

Axes3D.scatter(xs,ys,zs=0,zdir='z',s=20,c=None,depthshade=True,*args,**kwargs)

Argument Description
xs, ys Positions of data points.
zs Either an array of the same length as xs and ys or a single value to place all points in the same plane. Default is 0.
zdir Which direction to use as z (‘x', ‘y' or ‘z') when plotting a 2D set.
s Size in points^2. It is a scalar or an array of the same length as x and y.
c A color. c can be a single color format string, or a sequence of color specifications of length N, or a sequence of N numbers to be mapped to colors using the cmap and norm specified via kwargs (see below). Note that c should not be a single numeric RGB or RGBA sequence because that is indistinguishable from an array of values to be colormapped. c can be a 2-D array in which the rows are RGB or RGBA, however, including the case of a single row to specify the same color for all points.
depthshade Whether or not to shade the scatter markers to give the appearance of depth. Default is True.

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()

线框图

Axes3D.plot_wireframe(X,Y,Z,*args,**kwargs)

Argument Description
X, Y, Data values as 2D arrays
Z  
rstride Array row stride (step size), defaults to 1
cstride Array column stride (step size), defaults to 1
rcount Use at most this many rows, defaults to 50
ccount Use at most this many columns, defaults to 50

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()

表面图

Axes3D.plot_surface(X,Y,Z,*args,**kwargs)

Argument Description
X, Y, Z Data values as 2D arrays
rstride Array row stride (step size)
cstride Array column stride (step size)
rcount Use at most this many rows, defaults to 50
ccount Use at most this many columns, defaults to 50
color Color of the surface patches
cmap A colormap for the surface patches.
facecolors Face colors for the individual patches
norm An instance of Normalize to map values to colors
vmin Minimum value to map
vmax Maximum value to map
shade Whether to shade the facecolors

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()

柱状图

Axes3D.bar(left,height,zs=0,zdir='z',*args,**kwargs)

Argument Description
left The x coordinates of the left sides of the bars.
height The height of the bars.
zs Z coordinate of bars, if one value is specified they will all be placed at the same z.
zdir Which direction to use as z (‘x', ‘y' or ‘z') when plotting a 2D set.

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()

箭头图

Axes3D.quiver(*args,**kwargs)

Arguments:

X, Y, Z:
The x, y and z coordinates of the arrow locations (default is tail of arrow; see pivot kwarg)
U, V, W:
The x, y and z components of the arrow vectors

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np
 
fig = plt.figure()
ax = fig.gca(projection='3d')
 
# Make the grid
x, y, z = np.meshgrid(np.arange(-0.8, 1, 0.2),
           np.arange(-0.8, 1, 0.2),
           np.arange(-0.8, 1, 0.8))
 
# Make the direction data for the arrows
u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
w = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) *
   np.sin(np.pi * z))
 
ax.quiver(x, y, z, u, v, w, length=0.1, normalize=True)
 
plt.show()

2D转3D图

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))
labels = np.random.randint(3, size=80)
 
# 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=labels, 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')
 
# Customize the view angle so it's easier to see that the scatter points lie
# on the plane y=0
ax.view_init(elev=20., azim=-35)
 
plt.show()

文本图

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()

3D拼图

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(1, 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(1, 2, 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()

到此这篇关于Matplotlib.pyplot 三维绘图的实现示例的文章就介绍到这了,更多相关Matplotlib.pyplot 三维绘图内容请搜索脚本之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持脚本之家!

更多精彩内容其他人还在看

使用keras实现非线性回归(两种加激活函数的方式)

这篇文章主要介绍了使用keras实现非线性回归(两种加激活函数的方式),具有很好的参考价值,希望对大家有所帮助。一起跟随小编过来看看吧
收藏 0 赞 0 分享

python线性插值解析

这篇文章主要介绍了python线性插值解析,具有很好的参考价值,希望对大家有所帮助。一起跟随小编过来看看吧
收藏 0 赞 0 分享

Python中flatten( ),matrix.A用法说明

这篇文章主要介绍了Python中flatten( ),matrix.A用法说明,具有很好的参考价值,希望对大家有所帮助。一起跟随小编过来看看吧
收藏 0 赞 0 分享

python cv2.resize函数high和width注意事项说明

这篇文章主要介绍了python cv2.resize函数high和width注意事项说明,具有很好的参考价值,希望对大家有所帮助。一起跟随小编过来看看吧
收藏 0 赞 0 分享

python 图像插值 最近邻、双线性、双三次实例

这篇文章主要介绍了python 图像插值 最近邻、双线性、双三次实例,具有很好的参考价值,希望对大家有所帮助。一起跟随小编过来看看吧
收藏 0 赞 0 分享

Python-openCV开运算实例

这篇文章主要介绍了Python-openCV开运算实例,具有很好的参考价值,希望对大家有所帮助。一起跟随小编过来看看吧
收藏 0 赞 0 分享

python使用opencv resize图像不进行插值的操作

这篇文章主要介绍了python使用opencv resize图像不进行插值的操作,具有很好的参考价值,希望对大家有所帮助。一起跟随小编过来看看吧
收藏 0 赞 0 分享

使用Python-OpenCV消除图像中孤立的小区域操作

这篇文章主要介绍了使用Python-OpenCV消除图像中孤立的小区域操作,具有很好的参考价值,希望对大家有所帮助。一起跟随小编过来看看吧
收藏 0 赞 0 分享

python右对齐的实例方法

在本篇文章里小编给大家整理的是关于python右对齐的实例方法,有需要的朋友们可以学习参考下。
收藏 0 赞 0 分享

python主要用于哪些方向

在本篇文章里小编给大家整理了一篇关于python用于的方向的相关文章,有需要的阅读下吧。
收藏 0 赞 0 分享
查看更多