I've got this currently: ## See http://rosettacode.org/wiki/Matrix_transposition#PicoLisp (de trM (M) (apply mapcar M list) )
## According to https://en.wikipedia.org/wiki/Matrix_multiplication ## Handles all scenarios just like Python's nympy's dot(). (de mM @ (let (Am (next) Bm (next) Mrows '((Ar) (make (for Br (trM Bm) (link (sum */ Ar Br (1.0 .))) ) ) ) ) (let Rm (if2 (exlst~flat? Am) (exlst~flat? Bm) ## Both are flat so we just multiply them and sum, ## the return will be a number, see https://en.wikipedia.org/wiki/Dot_product (sum * Am Bm) ## The A matrix is flat, the B matrix is not so we loop the subs of the B and multiply with A. (Mrows Am) ## B is flat, A is not, doesn't work. (prog (println "Shape mismatch") (bye) ) ## They are both multidimensional so we loop both. (make (for Ar Am (link (Mrows Ar) ) ) ) ) (ifn (rest) Rm (nM Rm (next)) ) ) ) ) I didn't see much benefit in using the Rosetta version for matrix multiplication but nice touch there with the sum */ and (1.0 .), that was definitely needed. Will try and translate this one from python to PL now: https://medium.com/technology-invention-and-more/how-to-build-a-multi-layered-neural-network-in-python-53ec3d1d326a On Wed, Feb 21, 2018 at 7:55 PM, Henrik Sarvell <hsarv...@gmail.com> wrote: > Thanks Alex, > > I'll try them out, and modify multiply to handle an arbitrary amount of > matrices. > > On Wed, Feb 21, 2018 at 11:36 AM, Alexander Burger <a...@software-lab.de> > wrote: > >> Hi Henrik, >> >> > For reference, the article / tutorial: >> > https://medium.com/technology-invention-and-more/how-to-buil >> d-a-simple-neural-network-in-9-lines-of-python-code-cc8f23647ca1 >> >> Nice! >> >> >> > (de colM (M Cn) >> > (make >> > (for Col M >> > (link (car (nth Col Cn)))) ) ) >> > >> > ## Transpose matrix: https://en.wikipedia.org/wiki/Transpose >> > (de trM (M) >> > (make >> > (for N (length (car M)) # Number of columns. >> > (link (colM M N)) ) ) ) >> >> Note that there are some matrix manipulation tasks in RosettaCode. >> >> For example, the matrix transposition is simply: >> >> (de matTrans (Mat) >> (apply mapcar Mat list) ) >> >> >> Matrix multiplication (for 2 matrices) in RosettaCode is >> >> (de matMul (Mat1 Mat2) >> (mapcar >> '((Row) >> (apply mapcar Mat2 >> '(@ (sum */ Row (rest) (1.0 .))) ) ) >> Mat1 ) ) >> >> Not sure if this fits your needs ... >> >> ♪♫ Alex >> >> -- >> UNSUBSCRIBE: mailto:picolisp@software-lab.de?subject=Unsubscribe >> > >
