Re: [Matplotlib-users] another reason 'shape' shouldn't exist for pcolor plots?!...

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

>>>>> "seberino" == seberino  <seb...@sp...> writes:

    seberino> Imagine your arrays had points (Cartesian position
    seberino> vectors) all over the place at completely random points
    seberino> in space.  The 'shape' of this plot depends on max and
    seberino> min values of each coordinate.  I believe Mathematica
    seberino> plotting would automagically calculate these max and min
    seberino> values and set plot ranges for you.  This is why 'shape'
    seberino> attribute of Matplotlib/Numarray seems awkward and
    seberino> unnecessary to me unless I'm missing something.

There are a variety of issues here.  

  - The "shape" attribute comes form Numeric/numarray and is outside
    the realm of matplotlib.  matplotlib plots numerix arrays.  

  - The pcolor interface is determined by matlab.  matlab has a pcolor
    function which I have tried to implement faithfully.  To the
    extent that matplotlib has been successful, this is due in part
    because matlab has a good interface for plotting and replicating
    it generally, is a good thing.

  - Storing the "shape" of a data set allows for memory and efficiency
    savings.  To take your example of a set of x,y,z points, you are
    right you cold reconstruct rectilinear grid from this data -- one
    might have to use interpolation but it can be done -- but it would
    require a lot of unnecessary computation for data which already
    lives on a grid.  So pcolor assumes your data are on a rectilinear
    grid and it is incumbent upon you to get it into that form.
    
    The meshgrid function takes regularly sampled vector data and
    turns it into a rectilinear grid (this is also a matlab function).
    The matlab griddata function (which is not yet implemented in
    matplotlib) does the same for irregularly sampled data.

JDH