Matplotlib.pyplot 三维绘图的实现示例_Python

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.

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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()

Matplotlib.pyplot 三维绘图的实现示例

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.

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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()

Matplotlib.pyplot 三维绘图的实现示例

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()

Matplotlib.pyplot 三维绘图的实现示例

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

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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()

Matplotlib.pyplot 三维绘图的实现示例

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()

Matplotlib.pyplot 三维绘图的实现示例

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

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									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()

Matplotlib.pyplot 三维绘图的实现示例

2D转3D图

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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))

									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()

Matplotlib.pyplot 三维绘图的实现示例

文本图

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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()

Matplotlib.pyplot 三维绘图的实现示例

3D拼图

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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(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()