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

[John H. <jdh...@ac...>]

>>>>> "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.  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?

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.