Some alternatives from remodeling the data are more efficient.
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`projloop`projoutf`projmodel1`[email protected]
POP;NV;QR
)
ProjModel1=: 3 : 0
'pop new srv'=.y
'srv pop'=.(i...@# |."0 1 |:)"2 srv,:pop
srv=.(* <:@# >+/~@:i...@#)"2 srv
'new'=. 1 0 2 |: new
1 0 3 2|:(-...@i.@# |."0 1 ])"2>(,"1 2 [:}:"2 srv&*)&.>/\. &.|.pop;;/new
)
ProjModel1a=: 3 : 0 NB. same as before but with for-loop
'pop new srv'=.y
'srv pop'=.(i...@# |."0 1 |:)"2 srv,:pop
srv=.(* <:@# >+/~@:i...@#)"2 srv
'new'=. 1 0 2 |: new
z=. ,: pop
for_t. new do.
z=.z, t ,"1 2 }:"2 srv * {:z
end.
1 0 3 2|:(-...@i.@# |."0 1 ])"2 z
)
[sc=:scores(":,.i.6)<@,"1 ' test 55'
0.33658643 76295872
1.4320343 58728320
0.082450888 16817472
0.056301756 12590144
0.040160138 16623744
0.043919412 12588608
[rn=:rnkng sc
4 46.447614 8.3811073 6.0607076
5 152.11316 35.658103 4.6651957
3 2.507967 2.0530529 1.3359278
2 1.2820897 1.4019313 1.000122
1 1.2075074 1 1.3205387
0 1 1.0936071 1
('ProjRotate';'ProjOblique';'ProjLoop';'ProjOutf';'ProjModel1';'ProjModel1a'
)dspl rn
+-----------+----+-------+------+------+
|verb |rank|rlt_prf|rlt_et|rlt_sz|
+-----------+----+-------+------+------+
|ProjRotate | 4 | 46.45 | 8.38 |6.06 |
+-----------+----+-------+------+------+
|ProjOblique| 5 |152.11 |35.66 |4.67 |
+-----------+----+-------+------+------+
|ProjLoop | 3 | 2.51 | 2.05 |1.34 |
+-----------+----+-------+------+------+
|ProjOutf | 2 | 1.28 | 1.40 |1.00 |
+-----------+----+-------+------+------+
|ProjModel1 | 1 | 1.21 | 1.00 |1.32 |
+-----------+----+-------+------+------+
|ProjModel1a| 0 | 1.00 | 1.09 |1.00 |
+-----------+----+-------+------+------+
ProjModel1a is the overall champion, ProjModel1 is fastest.
2-:/\(i.6) test"0[ 55
1 1 1 1 1
Their output match.
ts=: 6!:2 , 7!:2...@]
scores=: 5 ts&> ]
rnkng=: 3 : '([:(,~/:@/:@{.) [:(%<./)"1(,~*/)) &.|: y'
dspl=: 4 : 0
z=: '2.0,0.2,0.2,0.2'(8!:0) y
z=: ('rank';'rlt_prf';'rlt_et';'rlt_sz'),z
('verb';x),.z
)
R.E. Boss
-----Oorspronkelijk bericht-----
Van: [email protected]
[mailto:[email protected]] Namens Robert Cyr
Verzonden: maandag 23 maart 2009 18:44
Aan: Programming forum
Onderwerp: Re: [Jprogramming] Oblique can be slow
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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>
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