Yes, will do. > On Dec 28, 2014, at 9:58 PM, Mike Anderson <[email protected]> > wrote: > > Looks like you have some good changes in your Vectorz branch - any chance you > could tidy up and make a PR? > > I like the idea of specialised getSlices and getColumns in particular - these > should be much faster than getting the slices one-by-one if the data is very > sparse. > > On Monday, 29 December 2014 09:43:54 UTC+8, Matt Revelle wrote: > >> On Dec 28, 2014, at 7:28 PM, Mike Anderson <[email protected] >> <mailto:[email protected]>> wrote: >> >> Interesting idea. The challenge is that I'm not sure how to add >> representation specification in an implementation independent way. It's a >> quirk of vectorz that it has both indexed and hashed storage, I probably >> wouldn't expect any other implementations to have that. Likewise row and >> column oriented storage are fairly obvious choices but I still wouldn't >> expect every implementation to support both. >> >> Any idea how you would specify the API? >> >> I guess we could simply pass an optional map argument of options, but >> behaviour would be completely implementation specific. > > I think the map is the way to go. You’re probably correct about few other > implementations having as many options, but adding a map of “preferences” > seems like a good option. Creating a sparse matrix might then look like: > > ;; preferences as a separate arg > (new-sparse-array [100000 100000] :vectorz {:order :row :indexed true}) > > ;; an alternative, preferences combined with implementation selection > (new-sparse-array [100000 100000] {:impl :vectorz :order :row :indexed true}) > > Implementations should throw an exception if they don’t support (or > understand) the preferences. > >> On Monday, 29 December 2014 02:12:05 UTC+8, Matt Revelle wrote: >> Glad to see the addition of new-sparse-array to core.matrix. It looks like >> it defaults to SparseRowMatrix for the Vectorz implementation? Should the >> API provide a way to specify which sparse matrix representation (e.g., row- >> vs column-based, indexed vs hashed) should be used? I'd suggest a 3-arity >> new-sparse-array which takes a keyword indicating the representation to use >> as well as a new function which returns a list of available representations >> for a specific implementation. >> >> I think at this point you incorporated (looks like we have some duplication >> too, doh) all the changes I had made for sparse matrix support in Vectorz, >> but will verify. >> >> I definitely haven't covered all the potential code paths - in particular a >> lot of things aren't yet optimised for sparse operations. So any review / >> patches would be appreciated! > > I did some optimization of sparse ops but the code probably needs to be > cleaned up before submitting (e.g., generalized and/or moved to the correct > level in class hierarchy). Those changes were made hastily when I needed to > quickly get a program running fast. > > A branch containing all performance changes based on an older revision of > the develop branch is available here: > https://github.com/mattrepl/vectorz/tree/sparse-speed > <https://github.com/mattrepl/vectorz/tree/sparse-speed> > > There is a related sparse-speed branch in my forks of vectorz-clj and > core.matrix. > > We should also look into other sparse array representations for Vectorz from: > Matlab, MTJ (https://github.com/fommil/matrix-toolkits-java > <https://github.com/fommil/matrix-toolkits-java>, specifically the > LinkedSparseMatrix for row and column ops), etc. > > -Matt > >> >> >> On Saturday, December 27, 2014 4:56:55 AM UTC-5, Mike Anderson wrote: >> Here is a little belated Christmas present for Clojure data aficionados: >> >> ;; setup >> (use 'clojure.core.matrix) >> (set-current-implementation :vectorz) >> >> ;; create a big sparse matrix with a trillion elements (initially zero) >> (def A (new-sparse-array [1000000 1000000])) >> >> ;; we are hopefully smart enough to avoid printing the whole array! >> A >> => #<SparseRowMatrix Large matrix with shape: [1000000,1000000]> >> >> ;; mutable setter operations supported so that you can set individual sparse >> elements >> (dotimes [i 1000] >> (mset! A (rand-int 1000000) (rand-int 1000000) (rand-int 100))) >> >> ;; all standard core.matrix operations supported >> (esum A) >> => 50479.0 >> >> ;; efficient addition >> (time (add A A)) >> => "Elapsed time: 12.849859 msecs" >> >> ;; matrix multiplication / inner products actually complete in sensible time >> ;; (i.e. much faster than than the usual O(n^3) which might take a few >> thousand years) >> (time (mmul A (transpose A))) >> => "Elapsed time: 2673.085171 msecs" >> >> >> Some nice things to note about the implementation: >> - Everything goes through the core.matrix API, so your code won't have to >> change to use sparse matrices :-) >> - Sparse matrices are 100% interoperable with non-sparse (dense) matrices >> - Sparse arrays are fully mutable. Management of storage / indexing happens >> automatically >> - It isn't just matrices - you can have sparse vectors, N-dimensional arrays >> etc. >> - Code is pure JVM - no native dependencies to worry about >> >> This is all still very much alpha - so any comments / patches / more >> rigorous testing much appreciated! >> >> >> >> >> -- >> You received this message because you are subscribed to a topic in the >> Google Groups "Numerical Clojure" group. >> To unsubscribe from this topic, visit >> https://groups.google.com/d/topic/numerical-clojure/LLpq4WHx-k8/unsubscribe >> <https://groups.google.com/d/topic/numerical-clojure/LLpq4WHx-k8/unsubscribe>. >> To unsubscribe from this group and all its topics, send an email to >> [email protected] >> <mailto:[email protected]>. >> For more options, visit https://groups.google.com/d/optout >> <https://groups.google.com/d/optout>. > > > -- > You received this message because you are subscribed to a topic in the Google > Groups "Numerical Clojure" group. > To unsubscribe from this topic, visit > https://groups.google.com/d/topic/numerical-clojure/LLpq4WHx-k8/unsubscribe > <https://groups.google.com/d/topic/numerical-clojure/LLpq4WHx-k8/unsubscribe>. > To unsubscribe from this group and all its topics, send an email to > [email protected] > <mailto:[email protected]>. > For more options, visit https://groups.google.com/d/optout > <https://groups.google.com/d/optout>.
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