which data structure to choose to keep multile objects?

[clue_less]

I have a function called nnmf which takes in one matrix and  returns two matrices. for example,

> X
     [,1] [,2] [,3] [,4]
[1,]    1    4    7   10
[2,]    2    5    8   11
[3,]    3    6    9   12

> z=nnmf(X,2)

> z$W
          [,1]      [,2]
[1,] 0.8645422 0.6643681
[2,] 1.7411863 0.5377504
[3,] 2.6179287 0.4111063
> z$H
           [,1]     [,2]     [,3]     [,4]
[1,] 1.14299486 1.692260 2.241279  2.79030
[2,] 0.01838514 3.818559 7.619719 11.42087

----------------------------------------

Now I would like to run it many times --

z2 = nnmf(X,2)
z3 = nnmf(X,3)
z4 = nnmf(X,4)
z5 = nnmf(X,5)
...

But I would like to do it automatically , something like -
 
xprocess<-function(max_val) {
   for (iter in  2: max_val) {
     
      zz = sprintf( "z%s", iter )
 
      zz <-nnmf(X,iter)
 
   }

}

xprocess(10)
 

----

But how could I keep collection of my results each run?

Shall I have a data structure to keep appending results?

something like

theta = {}

?

which data structure to choose to keep multile objects?

Thanks!

Tim

[jholtman]

your could try something like this:

xprocess<-function(max_val) {
  result <- list()
  for (iter in  2: max_val) {

     zz = sprintf( "z%s", iter )
     # use 'character' for indexing the list
     result[[as.character(iter)]] <-nnmf(X,iter)

  }
  result

}

xprocess(10)

On Fri, Nov 6, 2009 at 6:58 PM, clue_less <suhai_tim_liu@...> wrote:

>
> I have a function called nnmf which takes in one matrix and  returns two
> matrices. for example,
>
>> X
>     [,1] [,2] [,3] [,4]
> [1,]    1    4    7   10
> [2,]    2    5    8   11
> [3,]    3    6    9   12
>
>> z=nnmf(X,2)
>
>> z$W
>          [,1]      [,2]
> [1,] 0.8645422 0.6643681
> [2,] 1.7411863 0.5377504
> [3,] 2.6179287 0.4111063
>> z$H
>           [,1]     [,2]     [,3]     [,4]
> [1,] 1.14299486 1.692260 2.241279  2.79030
> [2,] 0.01838514 3.818559 7.619719 11.42087
>
> ----------------------------------------
>
> Now I would like to run it many times --
>
> z2 = nnmf(X,2)
> z3 = nnmf(X,3)
> z4 = nnmf(X,4)
> z5 = nnmf(X,5)
> ...
>
> But I would like to do it automatically , something like -
>
> xprocess<-function(max_val) {
>   for (iter in  2: max_val) {
>
>      zz = sprintf( "z%s", iter )
>
>      zz <-nnmf(X,iter)
>
>   }
>
> }
>
> xprocess(10)
>
>
> ----
>
> But how could I keep collection of my results each run?
>
> Shall I have a data structure to keep appending results?
>
> something like
>
> theta = {}
>
> ?
>
> which data structure to choose to keep multile objects?
>
> Thanks!
>
> Tim
>
> --
> View this message in context: http://old.nabble.com/which-data-structure-to-choose-to-keep-multile-objects--tp26231601p26231601.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help@... mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

--
Jim Holtman
Cincinnati, OH
[phone]

What is the problem that you are trying to solve?

______________________________________________
R-help@... mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

[Barry Rowlingson]

On Fri, Nov 6, 2009 at 11:58 PM, clue_less <suhai_tim_liu@...> wrote:

>
> I have a function called nnmf which takes in one matrix and  returns two
> matrices. for example,
>
>> X
>     [,1] [,2] [,3] [,4]
> [1,]    1    4    7   10
> [2,]    2    5    8   11
> [3,]    3    6    9   12
>
>> z=nnmf(X,2)
>
>> z$W
>          [,1]      [,2]
> [1,] 0.8645422 0.6643681
> [2,] 1.7411863 0.5377504
> [3,] 2.6179287 0.4111063
>> z$H
>           [,1]     [,2]     [,3]     [,4]
> [1,] 1.14299486 1.692260 2.241279  2.79030
> [2,] 0.01838514 3.818559 7.619719 11.42087
>
> ----------------------------------------
>
> Now I would like to run it many times --
>
> z2 = nnmf(X,2)
> z3 = nnmf(X,3)
> z4 = nnmf(X,4)
> z5 = nnmf(X,5)
> ...
>
> But I would like to do it automatically , something like -
>
> xprocess<-function(max_val) {
>   for (iter in  2: max_val) {
>
>      zz = sprintf( "z%s", iter )
>
>      zz <-nnmf(X,iter)
>
>   }
>
> }
>
> xprocess(10)
>
>
> ----
>
> But how could I keep collection of my results each run?
>
> Shall I have a data structure to keep appending results?
>
> something like
>
> theta = {}
>
> ?
>
> which data structure to choose to keep multile objects?
>

 You're already using one! It's called a list:

zz=list()
 for(i in 1:10){
  zz[[i]] = nnmf(X,i)
}

then you can do:

zz[[1]]$W and zz[[1]]$H

 Note the BIG difference between zz[1] and zz[[1]] though.

Barry

______________________________________________
R-help@... mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

[Greg Snow-2]

If you use the replicate or lapply functions then this will be taken care of for you (a list will be created containing your function output).

--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow@...
801.408.8111

> -----Original Message-----
> From: r-help-bounces@... [mailto:r-help-bounces@r-
> project.org] On Behalf Of clue_less
> Sent: Friday, November 06, 2009 4:58 PM
> To: r-help@...
> Subject: [R] which data structure to choose to keep multile objects?
>
>
> I have a function called nnmf which takes in one matrix and  returns
> two
> matrices. for example,
>
> > X
>      [,1] [,2] [,3] [,4]
> [1,]    1    4    7   10
> [2,]    2    5    8   11
> [3,]    3    6    9   12
>
> > z=nnmf(X,2)
>
> > z$W
>           [,1]      [,2]
> [1,] 0.8645422 0.6643681
> [2,] 1.7411863 0.5377504
> [3,] 2.6179287 0.4111063
> > z$H
>            [,1]     [,2]     [,3]     [,4]
> [1,] 1.14299486 1.692260 2.241279  2.79030
> [2,] 0.01838514 3.818559 7.619719 11.42087
>
> ----------------------------------------
>
> Now I would like to run it many times --
>
> z2 = nnmf(X,2)
> z3 = nnmf(X,3)
> z4 = nnmf(X,4)
> z5 = nnmf(X,5)
> ...
>
> But I would like to do it automatically , something like -
>
> xprocess<-function(max_val) {
>    for (iter in  2: max_val) {
>
>       zz = sprintf( "z%s", iter )
>
>       zz <-nnmf(X,iter)
>
>    }
>
> }
>
> xprocess(10)
>
>
> ----
>
> But how could I keep collection of my results each run?
>
> Shall I have a data structure to keep appending results?
>
> something like
>
> theta = {}
>
> ?
>
> which data structure to choose to keep multile objects?
>
> Thanks!
>
> Tim
>
> --
> View this message in context: http://old.nabble.com/which-data-
> structure-to-choose-to-keep-multile-objects--tp26231601p26231601.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help@... mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.

______________________________________________
R-help@... mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.