Polar 3D plot?

Community matplotlib-users
1

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.klukas@...3030... | jeffyklukas@...3031... | jeffklukas@...3032...
http://www.hep.wisc.edu/~jklukas/

On Thu, Mar 18, 2010 at 9:42 AM, Armin Moser <armin.moser@...2495...> 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