[Scilab-users] 3D interpolation

[Tim Wescott]

I'm not an expert.  But:

I did a quick spin through the help files and came up with splin2d and
interp2d.  It looks like what you want -- get the splines in x and T
using splin2d, and find the y values for a given x and T using
interp2d.

I don't know if this is the very best way to do this mathematically --
I know that this sort of 2D interpolated look-up is used extensively in
engine management units in cars (they're called "maps" in that lingo),
so there's probably a lot of research on accuracy vs. efficiency
tradeoffs.

On Fri, 2017-03-24 at 18:40 +0100, paul.carrico at free.fr wrote:
> Hi all,
> 
> I don't know if my question is relavante (or not), but I'm wondering
> what is the best way to perform a 3D interpolation, from for the
> matrix definition to the interpolation procedure.
> 
> Let me using a basic example: I've some curves y = f(x,T) defining a
> material behaviour at different temperatures i.e. 1 curve (x,y) per
> temperature:
> - y = f(x,20)
> - y = f(x,100)
> - y = f(x,200)
> 
> etc.
> 
> What is the best way to define a single matrix? [x y T] ?
> 
> 
> Next step is to be able to perform a 3D interpolation whatever is the
> temperature (for a given x) ... any advice? (of course I'm looking to
> interp3D flag.
> 
> Thanks for any feedback
> 
> Paul
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-- 

Tim Wescott
www.wescottdesign.com
Control & Communications systems, circuit & software design.
Phone: 503.631.7815
Cell:  503.349.8432