On Wed, Jul 14, 2010 at 05:22:54PM +0200, K.-Michael Aye wrote:
> > x and y can be 1D or 2D arrays (such as returned by numpy.ogrid or 
> > numpy.mgrid), but the points should be located on an orthogonal grid 
> > (possibly non-uniform). In other words, all the points sharing a same 
> > index in the s array need to have the same x or y value. For 
> > arbitrary-shaped position arrays (non-orthogonal grids), see the mesh 
> > function.

> Quite confusing, why does it not matter if x or y are 1D or 2D arrays? 
> What happens in either case? Can I mix it? (x as 1D , y as 2D)?
> I don't understand 'sharing a same index in the s array', respectively 
> the 'need to have'.

Hehe, as usual, it's the grid descriptions that confuse people who are
not familiar with meshing problems. Not that I feel like blaming you: I
have been there.

> Do you mean: All permutations between the given x and y array points 
> are made, and only when they exacly represent a coordinate of the s 
> array, that value is taken and being drawn?

The points should lie on an orthogonal grid: the x position is
independant of the y position, and vice versa. Thus only 1D arrays are
required to describe the problem. However, 2D arrays can be given to make
people's life easier. 

Does that make sens (I am perfectly willing to retry explaining)?

> If you could explain this to me, I am quite willing to work on doc 
> improvements. Obviously I need to understand it well for that to 
> happen. ;)

Thanks, this is really helpful.

> But maybe we should communicate this outside the list now?

No, let's keep it on list. It makes it easier for other people to
comment. And it's not like this mailing list is high traffic.

Cheers,

Gaƫl

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