![]() This may not be the approach actually used by Matlab, though. Putting these three facts together shows that it is possible to do it without a significant amount of extra memory. Transposition can be done inline, requiring only a fixed amount of extra memory, independent of array size, or growing very slowly with array size. Permute(., ) %// interchange dims 3 and 4: we have dims Įach of these elementary operations (interchanging two dimensions) is essentially a transpose along a given plane of the multidimensional array, performed repeatedly along all other dimensions. Permute(., ) %// interchange dims 2 and 4: we have dims For example, permute(x, ) is equivalent to this sequence of elementary permute operations (the sequence is not unique): permute(., ) %// interchange dims 1 and 4: we have dims permute (A, dimorder) Parameters: This function accepts two parameters, which are illustrated below: A: This is the specified array matrix. Permuting of dimensions can always be done as a sequence of elementary permute operations, where" elementary" means interchanging only two dimensions. This is only a guess, as I don't really know what permute does under the hood. data dimension, matlab data, plotting axis, anatomical. While this is not exactly the best way to profile memory usage (better use a proper memory profiler, something like Intel Inspector XE), it does show to some degree that permute is indeed not working in-place. The pixel display is arranged in the same way as youd see the matrix display in text. You can see how at its peak the function reached twice as much memory usage as when it returned. For the latter option, the subroutine also finds scaling factors that may be used to scale the original matrix so that the nonzero diagonal entries of the. I also repeated the test under perfmon.exe which showed the same pattern: ![]() I then ran the function simply as: %clear aĪnd watched the memory usage It went from 1.8 gigs in use, and rose to 5.2 then quickly down to 3.6 gigs. Permute expr, gr returns the list of permuted forms of expr under the elements of the permutation group gr. To permute the columns, the permutation matrix is p x p, and the matrix multiplication requires O ( Np 2) operations. Out = rand() % about 1.8 GB = 1e3*5e2*5e2*8/2^30 Permute expr, perm permutes the positions of the elements of expr according to the permutation perm. I only have 8 gigs of RAM on my laptop, so to avoid thrashing I modified your function as: function out = mtest() Here's my solution, using implicit expansion (tested with Octave 5.2.0 and MATLAB Online): n 3 Get all permutations of length n p perms (1:n) Number of permutations np size (p, 1) Set up indices, where to set elements to 1 p p + (0:n:n2-1) + (0:n2:n2np-1). Matrix Operations Description The Permute Matrix block reorders the rows or columns of an M-by-Ninput matrix Aas specified by indexing input P. I also set the "update speed" to "high" to get a finer time resolution. In Windows 10, I opened the "task manager" on the "performance" tab with the "memory" graphs in view. P perms(v) returns a matrix containing all permutations of the elements of vector v in reverse lexicographic order. The permute method in fact does create a second copy of the matrix with the data permuted and returns it. $$P_,$ would swap the columns $1$ and $3.Your argument is flawed because the MATLAB memory profiler is not telling you the truth! If we want to exchange rows $n$ and $m,$ we need to swap the corresponding rows of the $I$ matrix: If $m=3$ and $n=1,$ The Dulmage-Mendelsohn decomposition (dmperm in MATLAB) can be used to do this for symmetric matrices (or just turn your non-symmetric matrix into a matrix of 0's and 1's with 1's replacing all non-zero entries in the original matrix.) Share Cite Follow answered at 3:58 Brian Borchers 10. $IA,$ with $I$ being the identity matrix, selects every row of $A$ and leaves it in its place. Use the Permute Matrix block to permute a matrix by row or column.
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