## page was renamed from Cookbook/mplot3D The examples below show simple 3D plots using matplotlib. matplotlib's 3D capabilities were added by incorporating John Porter's mplot3d module, thus no additional download is required any more, the following examples will run with an up to date matplotlib installation. '''Note, this code is not supported in the matplotlib-0.98 branch, but you can use either the latest 0.99 release or the 0.91 maintenance version if you need this functionality. ''' Alternatively, the Mayavi2 project provides a pylab-like API for extensive 3D plotting: http://code.enthought.com/projects/mayavi/docs/development/html/mayavi/mlab.html Note that not all examples on this page are up to date, so some of them might not be working. For other examples, see http://matplotlib.sourceforge.net/examples/mplot3d/ 3D Plotting examples: {{{ #!python from numpy import * import pylab as p #import matplotlib.axes3d as p3 import mpl_toolkits.mplot3d.axes3d as p3 # u and v are parametric variables. # u is an array from 0 to 2*pi, with 100 elements u=r_[0:2*pi:100j] # v is an array from 0 to 2*pi, with 100 elements v=r_[0:pi:100j] # x, y, and z are the coordinates of the points for plotting # each is arranged in a 100x100 array x=10*outer(cos(u),sin(v)) y=10*outer(sin(u),sin(v)) z=10*outer(ones(size(u)),cos(v)) }}} Wireframe (works on 0.87.5): {{{ #!python fig=p.figure() ax = p3.Axes3D(fig) ax.plot_wireframe(x,y,z) ax.set_xlabel('X') ax.set_ylabel('Y') ax.set_zlabel('Z') p.show() }}} attachment:wireframe.jpg 3D Plot: {{{ #!python # this connects each of the points with lines fig=p.figure() ax = p3.Axes3D(fig) # plot3D requires a 1D array for x, y, and z # ravel() converts the 100x100 array into a 1x10000 array ax.plot3D(ravel(x),ravel(y),ravel(z)) ax.set_xlabel('X') ax.set_ylabel('Y') ax.set_zlabel('Z') fig.add_axes(ax) p.show() }}} attachment:plot.jpg Scatter (works on 0.87.5, shows some artefacts): {{{ #!python fig=p.figure() ax = p3.Axes3D(fig) # scatter3D requires a 1D array for x, y, and z # ravel() converts the 100x100 array into a 1x10000 array ax.scatter3D(ravel(x),ravel(y),ravel(z)) ax.set_xlabel('X') ax.set_ylabel('Y') ax.set_zlabel('Z') p.show() }}} attachment:scatter.jpg Surface (works on 0.87.5): {{{ #!python fig=p.figure() ax = p3.Axes3D(fig) # x, y, and z are 100x100 arrays ax.plot_surface(x,y,z) ax.set_xlabel('X') ax.set_ylabel('Y') ax.set_zlabel('Z') p.show() }}} attachment:surface.jpg Contour3D (works on 0.87.5): {{{ #!python delta = 0.025 x = arange(-3.0, 3.0, delta) y = arange(-2.0, 2.0, delta) X, Y = p.meshgrid(x, y) Z1 = p.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0) Z2 = p.bivariate_normal(X, Y, 1.5, 0.5, 1, 1) # difference of Gaussians Z = 10.0 * (Z2 - Z1) fig=p.figure() ax = p3.Axes3D(fig) ax.contour3D(X,Y,Z) ax.set_xlabel('X') ax.set_ylabel('Y') ax.set_zlabel('Z') p.show() }}} attachment:contour3D.jpg Contourf3D: {{{ #!python # in mplt3D change: # levels, colls = self.contourf(X, Y, Z, 20) # to: # C = self.contourf(X, Y, Z, *args, **kwargs) # levels, colls = (C.levels, C.collections) fig=p.figure() ax = p3.Axes3D(fig) ax.contourf3D(X,Y,Z) ax.set_xlabel('X') ax.set_ylabel('Y') ax.set_zlabel('Z') fig.add_axes(ax) p.show() }}} attachment:contourf3D.jpg 2D Contour Plots (work on 0.87.5): {{{ #!python x=r_[-10:10:100j] y=r_[-10:10:100j] z= add.outer(x*x, y*y) ### Contour plot of z = x**2 + y**2 p.contour(x,y,z) ### ContourF plot of z = x**2 + y**2 p.figure() p.contourf(x,y,z) p.show() }}} attachment:contour.jpg attachment:contourf.jpg For some other examples of 3d plotting capability, run the following commands. See the source of matplotlib/axes3d.py for more information: {{{ #!python # note that for the following to work you have to modify the test funcitons in your site-packages/matplotlib/axes3d.py like this: #def test_xxxx(): # import pylab # ax = Axes3D(pylab.figure()) # .... # .... # pylab.show() # the following then work on 0.87.5 p3.test_bar2D() p3.test_contour() p3.test_scatter() p3.test_scatter2D() p3.test_surface() # the following fail on 0.87.5 p3.test_plot() p3.test_polys() p3.test_wir