Index matrix to sparse matrix... saving memory
in [Matlab]
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From: Matt J on 29 May 2010 14:28 "Anthony Hopf" <anthony.hopf(a)gmail.com> wrote in message <htrlad$in3$1(a)fred.mathworks.com>... > Matt, that is a very good point. but I use the index values to pick out points in a 3d xyz data structure, add them and replace the value in the 3d xyz matrix, these index values, as noted above, are not uniform from spot to spot (I am simulating a beam sampling space so the number of valid points increase with range from the sensor). > > I'll think about it, maybe I can apply this technique... Thanks again! ====== Well, do think about it, because I don't see why any of the above matters. For any vector of linear indices idx, there is an equivalent vector of logical indices idx_logical, which can be used to do all the same indexing operations with the exact same syntax.
From: Anthony Hopf on 29 May 2010 17:56 "Matt J " <mattjacREMOVE(a)THISieee.spam> wrote in message <htrmbl$nn6$1(a)fred.mathworks.com>... > "Anthony Hopf" <anthony.hopf(a)gmail.com> wrote in message <htrlad$in3$1(a)fred.mathworks.com>... > > > Matt, that is a very good point. but I use the index values to pick out points in a 3d xyz data structure, add them and replace the value in the 3d xyz matrix, these index values, as noted above, are not uniform from spot to spot (I am simulating a beam sampling space so the number of valid points increase with range from the sensor). > > > > I'll think about it, maybe I can apply this technique... Thanks again! > ====== > > Well, do think about it, because I don't see why any of the above matters. For any vector of linear indices idx, there is an equivalent vector of logical indices idx_logical, which can be used to do all the same indexing operations with the exact same syntax. > > I have two questions concerning the above and something else that goes to the above 1. I am curious about the best way to build these sparse matrices. Right now I do an element by element comparison to find the values within a certain range: for v=1:length(r_bin) index_temp = find( r_3d >= rL(v) & r_3d <rH(v)); index_range(v,1:length(index_temp)) = index_temp; clear index_temp; end The reason I am asking is because I don't really know how many points there will be in each vector index_temp... so I end up not being able to allocate all the space I would like in index_range... can I do this with a sparse matrix, or should I just do what I am doing here and make index_range a sparse matrix afterwords? (rL and rH are the upper and lower bounds of the range bin) 2. Given what you see here in number 1 I don't understand how I could create a logical array to do the same thing since each vector indexes points to different parts within r_3d and other matrices I'm not showing... Matt could you give me a clue? Thanks again Anthony
From: Matt J on 29 May 2010 19:48 "Anthony Hopf" <anthony.hopf(a)gmail.com> wrote in message <hts2hl$3tk$1(a)fred.mathworks.com>... > "Matt J " <mattjacREMOVE(a)THISieee.spam> wrote in message <htrmbl$nn6$1(a)fred.mathworks.com>... > > "Anthony Hopf" <anthony.hopf(a)gmail.com> wrote in message <htrlad$in3$1(a)fred.mathworks.com>... > > > > > Matt, that is a very good point. but I use the index values to pick out points in a 3d xyz data structure, add them and replace the value in the 3d xyz matrix, these index values, as noted above, are not uniform from spot to spot (I am simulating a beam sampling space so the number of valid points increase with range from the sensor). > > > > > > I'll think about it, maybe I can apply this technique... Thanks again! > > ====== > > > > Well, do think about it, because I don't see why any of the above matters. For any vector of linear indices idx, there is an equivalent vector of logical indices idx_logical, which can be used to do all the same indexing operations with the exact same syntax. > > > > > > I have two questions concerning the above and something else that goes to the above > > 1. I am curious about the best way to build these sparse matrices. Right now I do an element by element comparison to find the values within a certain range: > > for v=1:length(r_bin) > index_temp = find( r_3d >= rL(v) & r_3d <rH(v)); > index_range(v,1:length(index_temp)) = index_temp; > clear index_temp; > end > > The reason I am asking is because I don't really know how many points there will be in each vector index_temp... so I end up not being able to allocate all the space I would like in index_range... can I do this with a sparse matrix, or should I just do what I am doing here and make index_range a sparse matrix afterwords? (rL and rH are the upper and lower bounds of the range bin) > > 2. Given what you see here in number 1 I don't understand how I could create a logical array to do the same thing since each vector indexes points to different parts within r_3d and other matrices I'm not showing... Matt could you give me a clue? ================ Combining all the recommendations in this thread (e.g., loading the indices column-wise instead of row-wise), I get to the following: %preallocate N=length(r_bin); I=cell(1,N); J=I; %compute sparse-indices for v=1:N I{v}=find( r_3d >= rL(v) & r_3d <rH(v) ); J{v}=I{v}; J{v}(:)=v; end index_range=sparse([I{:}], [J{:}],true); %final sparse logical matrix
From: Bruno Luong on 30 May 2010 05:07 "Anthony Hopf" <anthony.hopf(a)gmail.com> wrote in message <hts2hl$3tk$1(a)fred.mathworks.com>... > > > 1. I am curious about the best way to build these sparse matrices. Right now I do an element by element comparison to find the values within a certain range: > > for v=1:length(r_bin) > index_temp = find( r_3d >= rL(v) & r_3d <rH(v)); > index_range(v,1:length(index_temp)) = index_temp; > clear index_temp; > end > You should definitively learn how to use function HISTC and family. Bruno
From: Anthony Hopf on 30 May 2010 07:25
"Bruno Luong" <b.luong(a)fogale.findmycountry> wrote in message <htt9rq$1s8$1(a)fred.mathworks.com>... > "Anthony Hopf" <anthony.hopf(a)gmail.com> wrote in message <hts2hl$3tk$1(a)fred.mathworks.com>... > > > > > > 1. I am curious about the best way to build these sparse matrices. Right now I do an element by element comparison to find the values within a certain range: > > > > for v=1:length(r_bin) > > index_temp = find( r_3d >= rL(v) & r_3d <rH(v)); > > index_range(v,1:length(index_temp)) = index_temp; > > clear index_temp; > > end > > > > You should definitively learn how to use function HISTC and family. > > Bruno Bruno, I had downloaded your histcn function at one point to try and understand how it could be applied to my problem, but I must not fully understand it's abilities. To me, I would think you would need to work from the edge of a matrix to use the HISTC and HISTCN functions. Starting from an arbitrary point (r=0 in the above case could be in the center of the matrix), I don't understand how the function could be used to bin evenly spaced cartesian 3d space into bins defined by their spherical transforms? In the code above I am doing the first step of the indexing, indexing in range. r_3d is the range of (r,theta,phi) to each point within a 3d cartesian space referenced to some point within the 3d space. Can you work with me on how I would go about utilizing these functions to solve such a problem? Thank you for the continued help, You guys are truly a essential piece to the matlab community! Anthony |