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<div>Hello,</div>
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<div>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).</div>
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<div>I tried to overload function "inv" with the following code:</div>
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function y=%s_inv(x),<br>
if ndims(x)>2 then<br>
for k=1:size(x,3),<br>
y(:,:,k)=inv(x(:,:,k));<br>
end;<br>
else <br>
y=inv(x);<br>
end;<br>
endfunction</div>
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<div>expecting that each layer of y is the reciprocal of corresponding layer of x. Instead,
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<div>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.</div>
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<div>Code to reproduce the problem:</div>
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<div>n=4; m=3;<br>
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<div>M=ones(1,1,n).*.rand(m,m);</div>
<div>inv(M)</div>
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<div>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 ?</div>
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<div>In the mean time, I avoided overloading the function "inv" and renamed "%s_inv" to "inverse" to do successfully call "inverse(M)"...
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<div>Best regards</div>
<div>Denis<br>
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