# matplot 之 3D 绘图指南

 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') 

3D 图形分为如下几类：

## 线形图

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.

  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() 

## 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 Nnumbers 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.

  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 34 35 36 37 38  ''' ============== 3D scatterplot ============== Demonstration of a basic scatterplot in 3D. ''' 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

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22  ''' ================= 3D wireframe plot ================= A very basic demonstration of a wireframe plot. ''' 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

  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 34 35 36 37 38 39 40 41 42  ''' ====================== 3D surface (color map) ====================== Demonstrates plotting a 3D surface colored with the coolwarm color map. The surface is made opaque by using antialiased=False. Also demonstrates using the LinearLocator and custom formatting for the z axis tick labels. ''' 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() 

## 2D/3D 图形共存

  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 34 35 36 37 38 39 40 41 42 43 44 45 46  """ ======================= Plot 2D data on 3D plot ======================= Demonstrates using ax.plot's zdir keyword to plot 2D data on selective axes of a 3D plot. """ 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') # 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() 

## 加入文字

Axes3D.text(x, y, z, s, zdir=None, **kwargs)

  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 34 35 36 37 38 39 40 41 42 43 44 45 46 47  ''' ====================== Text annotations in 3D ====================== Demonstrates the placement of text annotations on a 3D plot. Functionality shown: - Using the text function with three types of 'zdir' values: None, an axis name (ex. 'x'), or a direction tuple (ex. (1, 1, 0)). - Using the text function with the color keyword. - Using the text2D function to place text on a fixed position on the ax object. ''' 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)W 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()