Obviously, thank you.

I like the way J encourages the manipulation of these multidimensional
arrays.

On Mon, Mar 23, 2009 at 11:10 AM, R.E. Boss <[email protected]> wrote:

> Not very much faster but more elegant, replacing the for-loop:
>
>   10 ts 'loop test 55'
> 0.057558227 16816768
>
>   10 ts 'outf test 55'
> 0.052024896 20978048
>
>   (outf test 55)-:loop test 55
> 1
>
> with
>
>   'rotate oblique loop outf' =: i.4
>
> and
>
> ProjOutf=: 3 : 0
>     'pop new srv'=:y
>  new=. 1 0 2 |: new NB. it makes it easy to loop on the first dimention
>  p=.  pop,"3 4(new,"1(0)),"0 1"2 3(0,"2 srv)
>  q=.(*(-1 1)|.!.1 "1 2 ])/\.&.|. p
> 1 0 2 3 |:}:"1}:"2 q
> )
>
>
> R.E. Boss
>
>
> -----Oorspronkelijk bericht-----
> Van: [email protected]
> [mailto:[email protected]] Namens Robert Cyr
> Verzonden: zaterdag 21 maart 2009 15:55
> Aan: Programming forum
> Onderwerp: Re: [Jprogramming] Oblique can be slow
>
> In this case, the simple looping solution is 20 times faster than the
> oblique solution, as it avoids some unnecessary calculations and
> manipulation of data.  It is also makes for easier reading and maintenance
>
> Noting that the population data is basically triangular(age service) where
> age-service >= 0 is of little use as we cannot easily create create and use
> a triangular matrix.
>
> try these:
>
> 'rotate oblique loop' =. i.3
>
>   ts 'rotate test 55'
> 0.203641 9.71485e7
>
>   ts 'oblique test 55'
> 0.854339 6.29294e7
>
> ----------------------------------------
> and the winner is...
> ----------------------------------------
>   ts 'loop test 55'
> 0.0385865 1.68559e7
> ----------------------------------------
>
> test=: 3 : 0
> NB. x: 0 for projection, 1 for rotation
> NB. y: number of age and service
> :
>    POP=:((>:/)~i.y)*"2 (1000*i.2)+/(100*i.y)+/1+i.y NB. SERVICE AGE
>    QR=: ((>:/)~i.y)*"2 (0.0001* (1000*i.2)+/(100*i.-y)+/1+i.-y) NB. SERVICE
> AGE
>    NV=: (2, y+4,0) $,10000+(100*i.y+4)+/i.y NB. ANS AGE
>    projrotate`projoblique`[email protected] POP;NV;QR
>  )
>
> ProjLoop=: 3 : 0
>    'pop new srv'=.y
>  new=. 1 0 2 |: new NB. it makes it easy to loop on the first dimention
>  p=.  pop,"3 4(new,"1(0)),"0 1"2 3(0,"2 srv)
>    for_t. i._1+#p do.
>        p=.(((t+1){p)*(-1 1)|.!.1 "1 2 t{p)(t+1)}p
>    end.
> 1 0 2 3 |:}:"1}:"2 p
> )
>
> ProjRotate=: 3 : 0
> NB. Population projection using rotation
> NB. result by sex year age service will allow us to determine the probable
> aging of our population.
> NB. pop: number of active employees by sex(2), age(55=16 to 70), service(55
> = 0 to 54)
> NB. new: number of new employees by sex(2), year of employment(50=years of
> projection), age(55)
> NB. srv: probability of survival (not dying,quitting or retiring) by
> sex(2),age(55),service(55)
>    'pop new srv'=.y
>    p=. pop,"2 3 (new,"1 (0)),"0 1"1 2 (0,"2 srv) NB. setup a matrix :
> sex,year of projection, age,service
>    'a n'=. (1 0)+ 1}.$new
>    r=. (,.)~i.a         NB. to shift each slice to the left and to the top
> by 1 for each year of projection
>    t=.-(0,0,a,a)+$p     NB. to make space for our rotation
>    f=.2,a,1+n,n         NB. to return to the original size
>    }:"2}:"1(-f){.(-r)|.!.0"1 2"2 3 */\"3 r |.!.1"1 2"2 3 t{.!.1 p
> )
>
>
> ProjOblique=: 3 : 0
>    'pop new srv'=.y
>    p=. pop,"2 3 (new,"1 (0)),"0 1"1 2 (0,"2 srv)
>    'a n'=. (1 0)+ 1}.$new
>    r=.  |."1|."2*//./.\"3|."2|."1 p     NB. this is the 3d oblique
> cumulative product, by year of projection
>    b=. (1+i.a)|."0 1 ((a,n)#0 1)        NB. eliminate the unused rows of
> the oblique
>    s=.|:n-(i.n)<./i.a                    NB. a rotation will position the
> required results
>    n{."1 s|."0 1 " 2 3 b#"1 2"2 3 r     NB. we retain the correct number of
> columns
> )
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