[scilab-Users] Sparse preprocessing

[Pedro Ledoux]

The method of finite diferences frequently give us systens of sparse matrix. Are you using this one? I had some recent experience with it. When the sparse matrix has a 3 diagonal behavior the most eficient thing I tested was thomas method. But We can't use it when the non 0 elements has no pattern :/

 I've used the finite difference method to solve a problem of the propagation of a wave in a wave guide. In this the sparse system to a "L" shaped wave guide gave me a sparse matrix with no pattern to non 0 elements. In the case of waveguide it lead me to a eigenvalue problem. Unfortunately I didn't found a function like eig() from Matlab, is there something similat in Scilab?


--- Em sáb, 2/10/10, Wojciech Artichowicz <w_artichowicz at o2.pl> escreveu:

De: Wojciech Artichowicz <w_artichowicz at o2.pl>
Assunto: [scilab-Users] Sparse preprocessing
Para: users at lists.scilab.org
Data: Sábado, 2 de Outubro de 2010, 7:30




 
 






Hello, 

Fluid mechanics computations often lead to sparse
matrix systems.  Scilab has marvellous sparse functions, however 

I cannot find any function for sparse preprocessing. For
example: 

   

I have built quite big system with sparse matrix with
no explicit pattern of non-zero elements. The best way to solve this system is
to use 

modified SOR method (my own implementation). My
question is: 

Is there any function in Scilab that would remove
zero entries from diagonal (which isn’t in this case very easy), and that
would do some additional stuff like 

placing at diagonal the biggest possible element. 

   

If no, is there any well known not too complicated
algorithm for such a purpose? 

   

Thank You in advance, 

Regards, 

W.A. 



 




      
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