[Numpy-discussion] Interpolation question

Andrea Gavana andrea.gavana at gmail.com
Sun Mar 28 06:33:01 EDT 2010

On 28 March 2010 08:26, Anne Archibald wrote:
> On 27 March 2010 20:24, Andrea Gavana <andrea.gavana at gmail.com> wrote:
>> Hi All,
>>    I have an interpolation problem and I am having some difficulties
>> in tackling it. I hope I can explain myself clearly enough.
>> Basically, I have a whole bunch of 3D fluid flow simulations (close to
>> 1000), and they are a result of different combinations of parameters.
>> I was planning to use the Radial Basis Functions in scipy, but for the
>> moment let's assume, to simplify things, that I am dealing only with
>> one parameter (x). In 1000 simulations, this parameter x has 1000
>> values, obviously. The problem is, the outcome of every single
>> simulation is a vector of oil production over time (let's say 40
>> values per simulation, one per year), and I would like to be able to
>> interpolate my x parameter (1000 values) against all the simulations
>> (1000x40) and get an approximating function that, given another x
>> parameter (of size 1x1) will give me back an interpolated production
>> profile (of size 1x40).
> If I understand your problem correctly, you have a function taking one
> value as input (or one 3D vector) and returning a vector of length 40.
> You want to know whether there are tools in scipy to support this.
> I'll say first that it's not strictly necessary for there to be: you
> could always just build 40 different interpolators, one for each
> component of the output. After all, there's no interaction in the
> calculations between the output coordinates. This is of course
> awkward, in that you'd like to just call F(x) and get back a vector of
> length 40, but that can be remedied by writing a short wrapper
> function that simply calls all 40 interpolators.

Thank you Anne and Josef, my explanation was very bad but your
suggestions opened up my mind :-D . I believe I am going to give the
40 interpolators a try, although you mentioned that RBFs are going to
have some problems if the vectors' sizes are too big...

I planned for a multidimensional interpolation of about 10 parameters
(each of these has 1000 elements), but at this point I am afraid it
will not work. If any of you is aware of another methodology/library I
could use (Fortran is also fine, as long as I can wrap it with f2py)
for this problem please feel free to put me on the right track.

Thank you again for your suggestions.


"Imagination Is The Only Weapon In The War Against Reality."

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