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POIndexing of unknown dimensional matrix
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copied!<p>I have a non-fixed dimensional matrix M, from which I want to access a single element. The element's indices are contained in a vector J.</p> <p>So for example:</p> <pre><code>M = rand(6,4,8,2); J = [5 2 7 1]; output = M(5,2,7,1) </code></pre> <p>This time M has 4 dimensions, but this is not known in advance. This is dependent on the setup of the algorithm I'm writing. It could likewise be that</p> <pre><code>M = rand(6,4); J = [3 1]; output = M(3,1) </code></pre> <p>so I can't simply use</p> <pre><code>output=M(J(1),J(2)) </code></pre> <p>I was thinking of using <a href="http://www.mathworks.nl/help/techdoc/ref/sub2ind.html" rel="nofollow">sub2ind</a>, but this also needs its variables comma separated..</p> <p>@gnovice</p> <p>this works, but I intend to use this kind of element extraction from the matrix <code>M</code> quite a lot. So if I have to create a temporary variable <code>cellJ</code> every time I access <code>M</code>, wouldn't this tremendously slow down the computation??</p> <p>I could also write a separate function</p> <pre><code>function x= getM(M,J) x=M(J(1),J(2)); % M doesn't change in this function, so no mem copy needed = passed by reference end </code></pre> <p>and adapt this for different configurations of the algorithm. This is of course a speed vs flexibility consideration which I hadn't included in my question..</p> <p>BUT: this is only available for getting the element, for setting there is no other way than actually using the indices (and preferably the linear index). I still think sub2ind is an option. The final result I had intended was something like:</p> <pre><code>function idx = getLinearIdx(J, size_M) idx = ... end </code></pre> <hr> <h2>RESULTS:</h2> <pre><code>function lin_idx = Lidx_ml( J, M )%#eml %LIDX_ML converts an array of indices J for a multidimensional array M to %linear indices, directly useable on M % % INPUT % J NxP matrix containing P sets of N indices % M A example matrix, with same size as on which the indices in J % will be applicable. % % OUTPUT % lin_idx Px1 array of linear indices % % method 1 %lin_idx = zeros(size(J,2),1); %for ii = 1:size(J,2) % cellJ = num2cell(J(:,ii)); % lin_idx(ii) = sub2ind(size(M),cellJ{:}); %end % method 2 sizeM = size(M); J(2:end,:) = J(2:end,:)-1; lin_idx = cumprod([1 sizeM(1:end-1)])*J; end </code></pre> <p>method 2 is 20 (small number of index sets (<code>=P</code>) to convert) to 80 (large number of index sets (<code>=P</code>)) times faster than method 1. easy choice</p>

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