The code below works perfectly. I think this should be included as an mplot3d codex. I'll look into what's required to submit a new example to the documentation.
Thanks Armin! || Jeff Klukas, Research Assistant, Physics || University of Wisconsin -- Madison || jeff.klu...@gmail | jeffyklu...@aim | jeffklu...@skype || http://www.hep.wisc.edu/~jklukas/ On Thu, Mar 18, 2010 at 9:42 AM, Armin Moser <armin.mo...@student.tugraz.at> wrote: > Hi, > > you can create your supporting points on a regular r, phi grid and > transform them then to cartesian coordinates: > > from mpl_toolkits.mplot3d import Axes3D > import matplotlib > import numpy as np > from matplotlib import cm > from matplotlib import pyplot as plt > step = 0.04 > maxval = 1.0 > fig = plt.figure() > ax = Axes3D(fig) > > # create supporting points in polar coordinates > r = np.linspace(0,1.25,50) > p = np.linspace(0,2*np.pi,50) > R,P = np.meshgrid(r,p) > # transform them to cartesian system > X,Y = R*np.cos(P),R*np.sin(P) > > Z = ((R**2 - 1)**2) > ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.jet) > ax.set_zlim3d(0, 1) > ax.set_xlabel(r'$\phi_\mathrm{real}$') > ax.set_ylabel(r'$\phi_\mathrm{im}$') > ax.set_zlabel(r'$V(\phi)$') > ax.set_xticks([]) > plt.show() > > hth > Armin > > > klukas schrieb: >> I'm guessing this is currently impossible with the current mplot3d >> functionality, but I was wondering if there was any way I could generate a >> 3d graph with r, phi, z coordinates rather than x, y, z? >> >> The point is that I want to make a figure that looks like the following: >> http://upload.wikimedia.org/wikipedia/commons/7/7b/Mexican_hat_potential_polar.svg >> >> Using the x, y, z system, I end up with something that has long tails like >> this: >> http://upload.wikimedia.org/wikipedia/commons/4/44/Mecanismo_de_Higgs_PH.png >> >> If I try to artificially cut off the data beyond some radius, I end up with >> jagged edges that are not at all visually appealing. >> >> I would appreciate any crazy ideas you can come up with. >> >> Thanks, >> Jeff >> >> P.S. Code to produce the ugly jaggedness is included below: >> >> ------------------------------------------------------- >> from mpl_toolkits.mplot3d import Axes3D >> import matplotlib >> import numpy as np >> from matplotlib import cm >> from matplotlib import pyplot as plt >> >> step = 0.04 >> maxval = 1.0 >> fig = plt.figure() >> ax = Axes3D(fig) >> X = np.arange(-maxval, maxval, step) >> Y = np.arange(-maxval, maxval, step) >> X, Y = np.meshgrid(X, Y) >> R = np.sqrt(X**2 + Y**2) >> Z = ((R**2 - 1)**2) * (R < 1.25) >> ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.jet) >> ax.set_zlim3d(0, 1) >> #plt.setp(ax.get_xticklabels(), visible=False) >> ax.set_xlabel(r'$\phi_\mathrm{real}$') >> ax.set_ylabel(r'$\phi_\mathrm{im}$') >> ax.set_zlabel(r'$V(\phi)$') >> ax.set_xticks([]) >> plt.show() >> > > > -- > Armin Moser > Institute of Solid State Physics > Graz University of Technology > Petersgasse 16 > 8010 Graz > Austria > Tel.: 0043 316 873 8477 > ------------------------------------------------------------------------------ Download Intel® Parallel Studio Eval Try the new software tools for yourself. Speed compiling, find bugs proactively, and fine-tune applications for parallel performance. See why Intel Parallel Studio got high marks during beta. http://p.sf.net/sfu/intel-sw-dev _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
