Hi Armin,
Thanks, I added it to the mplot3d examples.
Cheers,
Reinier
On Thu, Mar 18, 2010 at 3:46 PM, 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
>
>
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--
Reinier Heeres
Tel: +31 6 10852639
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