Re: Contour plots [Was: Re: [Matplotlib-users] how to make matplotlib faster?]

[Peter G. <pgr...@ge...>]

John Hunter wrote:

>>>>>> "Peter" == Peter Groszkowski <pgr...@ge...> writes:
>>>>>
>
> Peter> I use Hardy's multiquadric interpolation to to do the math,
> Peter> then use imshow (or pcolor) to make a surface map. I only
> Peter> have data for the 120 points (where the circle are - those
> Peter> are actuators), and interpolate the rest.
>
> Peter> If people are interested, I can clean up the code a little
> Peter> and post it.
>
> This sounds pretty close to matlab's griddata function. 

Yup. That's the functionality I needed. As it says in MATLAB docstrig 
below, GRIDDATA uses Delaunay triangulation however.

> It would be
> very nice to have this in matplotlib.mlab, perhaps as a wrapper to
> some core scipy functionality, which could be conditionally imported.
> What requirements does your code have -- pure python, extension code,
> scipy, numarray?
>
The interpolating is done all in python with the use of Numeric (this is 
what I have been using, and what my matplotlib installation uses - maybe 
will upgrade to numarray one of these days). Performance wise, It's not 
very practical for a very large number of points N as it has to solve a 
NxN system (my N=120 and takes ~2.3seconds on a P4 3.2Ghz with 2GB ram - 
cant remember how long MATLAB's griddata took). Maybe numarray would be 
faster?!

The drawing of the mirror, actuators, etc is done using matplotlibs 
imshow(), plot() and fill() - all very straight forward.

I will post the code in the next few days when I have a minute to clean 
it up a litte.

Cheers,

--
Peter Groszkowski         Gemini Observatory
Tel: +1 808 9742509       670 N. A'ohoku Place
Fax: +1 808 9359235       Hilo, Hawai'i 96720, USA





> Here is the matlab docstring, FYI
>
> GRIDDATA Data gridding and surface fitting.
> ZI = GRIDDATA(X,Y,Z,XI,YI) fits a surface of the form Z = F(X,Y)
> to the data in the (usually) nonuniformly-spaced vectors (X,Y,Z)
> GRIDDATA interpolates this surface at the points specified by
> (XI,YI) to produce ZI. The surface always goes through the data
> points. XI and YI are usually a uniform grid (as produced by
> MESHGRID) and is where GRIDDATA gets its name.
>
> XI can be a row vector, in which case it specifies a matrix with
> constant columns. Similarly, YI can be a column vector and it
> specifies a matrix with constant rows.
>
> [XI,YI,ZI] = GRIDDATA(X,Y,Z,XI,YI) also returns the XI and YI
> formed this way (the results of [XI,YI] = MESHGRID(XI,YI)).
>
> [...] = GRIDDATA(...,'method') where 'method' is one of
> 'linear' - Triangle-based linear interpolation (default).
> 'cubic' - Triangle-based cubic interpolation.
> 'nearest' - Nearest neighbor interpolation.
> 'v4' - MATLAB 4 griddata method.
> defines the type of surface fit to the data. The 'cubic' and 'v4'
> methods produce smooth surfaces while 'linear' and 'nearest' have
> discontinuities in the first and zero-th derivative respectively. All
> the methods except 'v4' are based on a Delaunay triangulation of the
> data.
>
> See also GRIDDATA3, GRIDDATAN, DELAUNAY, INTERP2, MESHGRID.
>
>
>
>