09be7c8d-1819-4f95-81b3-5e521be4aafa 12 6 5 auto

&[DATE] &[TIME] - &[FILENAME]

Vectorise a matrix over a function

Smath takes the matrix as the argument to the function 'f' where 'f' is algo name. It then proceeds elements wise, a native Smath functionality, hyperfast. All modules "Optimiz: Numeric" 1. Vectorise(f,M) champion vectoriser. 2. Scale(#,0,255) natural coding. 3. xd(L,H,N) the champion discretiser. 4. Sym(f(x,y),U,V)champion matrix compactor. [1, 2, 3, 4] can be collapsed upstream the WS.

t0 1 time :

f M Vectorise i 1 M rows range j 1 M cols range V i j el M i j el f eval : for for V 21 line :

You need that one for scaling grayscale image M Min Max Scale Max Min - (M M min - M max M min - / (* Min + :

Mesh U, V  within the bounds L, H L H N xd U 0 : dx H L - N / : i 1 N 1 + range U i el L dx i * dx - (+ : for U 21 line 31 line :

L 1 - :

H 1 :

N 32 :

U L H N xd :

V U :

x y f 1 x 2^y 2^+ (- 0.25 / exp * :

Generate the symmetric square matrix x y f U V Sym r 1 : i 1 U rows range c 1 : j 1 V rows range M r c el U i el V j el f eval : c c 1 + : 21 line for r r 1 + : 31 line for M 31 line :

N x y f U V Sym :

x f x sqrt :

Z f N Vectorise :

N N 0255 Scale :

Z Z 0255 Scale :

image N Z augment :

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1 time t0 - 4.2 sec *