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Re: inverse gradient [message #64167 is a reply to message #63980] Tue, 02 December 2008 14:44 Go to previous messageGo to previous message
pgrigis is currently offline  pgrigis
Messages: 436
Registered: September 2007
Senior Member
On Dec 2, 2:42 pm, erano <eran.o...@gmail.com> wrote:
> On Dec 2, 8:59 pm, Paolo <pgri...@gmail.com> wrote:
>
>
>
>> erano wrote:
>
>>>> But you haven't really described how you got dX and dY and
>>>> what is the potential....
>
>>> Well, dX and dY are based on other parameters gradient. I based on
>>> MATLAB code. In MATLAB, we can use "\" for doing Ax=Y: x=A\Y, where A
>>> is M*N matrix. I can attach the code.
>
>> My question was what are dX and dY? What is the potential?
>
>> In IDL you can do x=A#invert(Y) that I guess is similar
>> to what matlab does (modulo transposition of the arrays).
>
>> But if A is large and sparse, then use the sparse methods suggested.
>
>> Paolo
>
>>> Eran- Hide quoted text -
>
>> - Show quoted text -
>
> The potential ia not relevant. The dX and dY can be based on any 2D
> function.

I am still not convinced that total wouldn't work in that case...
maybe increasing the sampling by a factor 2 or 3 if memory allows...
again it depends what your final goal is, of which we haven't a clue.

> And yes, A is (very) large and sparse, but the sparse
> methods are only for N*N matrix...while A is M*N.

OK, you are totally right that IDL sparse-array
function are somewhat... sparse ;-)

I think you can buy an add-on for this kind of things,
but I never used it.

Maybe somebody out there has written an SVD program that
accept non-square, sparse arrays?

Ciao,
Paolo

>
> Eran
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