Since some years ago I use matlab for my plots (mostly density plots), but now I want to change to matplotlib. I have a problem trying to figure out how to get analogous plots in matplotlib. I have to represent a 2D array. In matlab I used to use the surf function, and then change to view(2) (az=0 and el=90). An example:
surf(X,Y,log10(z),'FaceColor','interp','EdgeColor','none')
view(2)
In matplotlib I have tried some functions, but I have not got the same feeling. m3plot is a computationally expensive toolkit and it is not the same as using surf. imshow does not allow to use log functions in his arguments (like the example), and log values is something mandatory for me. Then it is pcolor, but I can not find a 'FaceColor'-like option to smooth the edges. I would like to know if someone knows what is the best equivalent in matplotlib.
Thank you for your time!
Try installing mayavi which has the surf function (mayavi is a fully-blown 3D visualisation library using hardware acceleration)
Finally, the solution that suits me is to use the routine pcolormesh(). This combined with the option shading='gouraud' interpolates the data and smooth the edges. In addition, it works pretty well with large arrays in comparision with pcolor.
I am generating 3d graphs in matplotlib and am generally pleased with the results. One thing I have noticed, however, is that the performance of the default 3d viewer is very slow with a few hundred points of data. Is there any way to export the generated graph to a model that could be viewed in some other 3d model viewer?
No, not unless you write it ;). mayavi (docs) which is a openGL based renderer might do better. You might also want to look in to vtk.
community wiki because this is basically Joe Kington's answer from the comments.
I want to draw 3D primitives like spheres, cylinders and planes (patches) in a 3D plot and I would like to be able to interactively rotate, translate and zoom the scene. I want to do that in Python. I'm use to use Matplotlib for 2d graphs but I never worked with 3D graphics with Python.
Any suggestions?
Any link to tutorials?
Any ideas?
If you're used to matplotlib, then mplot3d is probably a good option if it meets your requirements.
Alternatively there is VPython. This allows you greater freedom to create arbitrary objects and manipulate them, but, of course, more to learn.
What are my options for 3D plotting in Python?
It also must be redistributable.
I assume you're asking for reccomendations, rather than just what modules are available...
Personally, I mostly use Mayavi/Mlab/TVTK. It's essentially a higher level interface to VTK. It's available under a BSD-style license (If I recall correctly...), so it should be freely re-distributable. If you're visualizing scientific data, it's an excellent choice.
For simpler 3D plots, matplotlib's Axes3D is quite nice. Take a look at the 3D examples (towards the bottom) on the matplotlib gallery page. However, it's not well suited to visualize volumetric data or more complex surfaces.
Naturally, those aren't the only options, but they're the two I would reccomend.
If you want to drop down to a lower level, there's always PyOpenGL, too.
At any rate, hopefully that points you in the right direction...
One more variant is Python interface to MathGL. This is GPL library with large set of 2D and 3D plotting graphics types.
I need to plot some data in various forms. Currently I'm using Matplotlib and I'm fairly happy with the plots I'm able to produce.
This question is on how to plot the last one. The data is similar to the "distance table", like this (just bigger, my table is 128x128 and still have 3 or more number per element).
Now, my data is much better "structured" than a distance table (my data doesn't varies "randomly" like in a alphabetically sorted distance table), thus a 3D barchart, or maybe 3 of them, would be perfect. My understanding is that such a chart is missing in Matplotlib.
I could use a (colored) Countor3d like these or something in 2D like imshow, but it isn't really well representative of what the data is (the data has meaning just in my 128 points, there isn't anything between two points). And the height of bars is more readable than color, IMO.
Thus the questions:
is it possible to create 3D barchart in Matplotlib? It should be clear that I mean with a 2D domain, not just a 2D barchart with a "fake" 3D rendering for aesthetics purposes
if the answer to the previous question is no, then is there some other library able to do that? I strongly prefer something Python-based, but I'm OK with other Linux-friendly possibilities
if the answer to the previous question is no, then do you have any suggestions on how to show that data? E.g. create a table with the values, superimposed to the imshow or other colored way?
For some time now, matplotlib had no 3D support, but it has been added back recently. You will need to use the svn version, since no release has been made since, and the documentation is a little sparse (see examples/mplot3d/demo.py). I don't know if mplot3d supports real 3D bar charts, but one of the demos looks a little like it could be extended to something like that.
Edit: The source code for the demo is in the examples but for some reason the result is not. I mean the test_polys function, and here's how it looks like:
example figure http://www.iki.fi/jks/tmp/poly3d.png
The test_bar2D function would be even better, but it's commented out in the demo as it causes an error with the current svn version. Might be some trivial problem, or something that's harder to fix.
MyavaVi2 can make 3D barcharts (scroll down a bit). Once you have MayaVi/VTK/ETS/etc. installed it all works beautifully, but it can be some work getting it all installed. Ubuntu has all of it packaged, but they're the only Linux distribution I know that does.
One more possibility is Gnuplot, which can draw some kind of pseudo 3D bar charts, and gnuplot.py allows interfacing to Gnuplot from Python. I have not tried it myself, though.
This is my code for a simple Bar-3d using matplotlib.
import mpl_toolkits
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
%matplotlib inline
## The value you want to plot
zval=[0.020752244,0.078514652,0.170302899,0.29543857,0.45358061,0.021255922,0.079022499,\
0.171294169,0.29749654,0.457114286,0.020009631,0.073154019,0.158043498,0.273889264,0.419618287]
fig = plt.figure(figsize=(12,9))
ax = fig.add_subplot(111,projection='3d')
col=["#ccebc5","#b3cde3","#fbb4ae"]*5
xpos=[1,2,3]*5
ypos=range(1,6,1)*5
zpos=[0]*15
dx=[0.4]*15
dy=[0.5]*15
dz=zval
for i in range(0,15,1):
ax.bar3d(ypos[i], xpos[i], zpos[i], dx[i], dy[i], dz[i],
color=col[i],alpha=0.75)
ax.view_init(azim=120)
plt.show()
http://i8.tietuku.com/ea79b55837914ab2.png
You might check out Chart Director:
http://www.advsofteng.com
It has a pretty wide variety of charts and graphs and has a nice Python (and several other languages) API.
There are two editions: The free version puts a blurb on the generated image, and the
pay version is pretty reasonably priced.
Here's one of the more interesting looking 3d stacked bar charts:
(source: advsofteng.com)