[Scilab-users] Overloading "inv" and/or "p" does not seem to work with Scilab 6.1.0

[Samuel Gougeon]

Hello Denis,

Le 07/05/2020 à 14:58, CRETE Denis a écrit :
> Hello,
>
> I redefined a few functions in Scilab 6.1.0 to extend them to arrays 
> with 3 dimensions (formerly called hypermatrix). Overloading works 
> with "clean", "multiply", "left division" and "element by element 
> division" (after defining functions %s_clean, %s_m_s, %s_l_s and %s_d_s).
>
> I tried to overload function "inv" with the following code:
>
> function y=%s_inv(x),
>     if ndims(x)>2 then
>         for k=1:size(x,3),
>             y(:,:,k)=inv(x(:,:,k));
>         end;
>     else
>         y=inv(x);
>     end;
> endfunction
>
> expecting that each layer of y is the reciprocal of corresponding 
> layer of x. Instead,
> inv(ones(1,1,2).*.rand(2,2)) returns the reciprocal of x layer 1 in y 
> layer 1 AND x LAYER n IN y LAYER n, WHEN n>1. I use "layer" to 
> designate the matrix obtain for a fixed value the index along the 3rd 
> dimension.
>
> Code to reproduce the problem:
>
> n=4; m=3;
> M=ones(1,1,n).*.rand(m,m);
> inv(M)
>
> Attempts to circumvent this problem by using M^(-1) instead of inv(M) 
> run into the same problem (after redefining function %s_p). Is this a 
> bug or did I miss something ?


It's a bug. inv() should display an error message inviting to define 
%s_inv(), or use %s_inv().
By the way, the hook to the overload existed in Scilab 5.5.2. Hence, 
this issue is a regression.
Could you please report it?
Thanks

Samuel


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