[R] Odp: Running something without a loop when the result from the previous iteration is require for the current iteration
Petr PIKAL
petr.pikal at precheza.cz
Thu Aug 12 09:21:45 CEST 2010
Hi
without toy example it is rather complicated to check your function. So
only few remarks:
Instead of generating 1 random number inside a loop generate whole vector
of random numbers outside a loop and choose a number
Do not mix ifelse with if. ifelse is intended to work with whole vector.
Work with matrices instead of data frames whenever possible if speed is an
issue.
If I understand correctly you want to put 1 or 0 into one column based on:
previous value in the same column
comparison of some random number with predefined probabilities in vector
of 6 values
So here is vectorised version of your 4 ifs based on assumption
0 in col1 0 in col 2 = 5
0 in col1 1 in col 2 = 9
1 in col1 0 in col 2 = 6
1 in col1 1 in col 2 =10
col1<-sample(1:2, 20, replace=T)
col2<-sample(c(4,8), 20, replace=T)
col1+col2
[1] 5 6 9 6 6 5 9 10 9 9 6 9 10 6 10 9 10 9 5 5
cols<-as.numeric(as.factor(col1+col2))
cols
[1] 1 2 3 2 2 1 3 4 3 3 2 3 4 2 4 3 4 3 1 1
And here is computed comparison of six values p (ortho obs used) with 20
generated random values
ran<-runif(20)
p<-runif(8)
comparison <- outer(ran,p, "<")
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
[1,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE
[2,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
[3,] FALSE TRUE FALSE TRUE FALSE TRUE TRUE FALSE
[4,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
[5,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
[6,] FALSE TRUE FALSE TRUE FALSE TRUE FALSE FALSE
[7,] FALSE TRUE FALSE TRUE FALSE TRUE FALSE FALSE
[8,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE
[9,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE
[10,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
[11,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
[12,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE
[13,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
[14,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE
[15,] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
[16,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE
[17,] FALSE TRUE FALSE TRUE FALSE TRUE FALSE FALSE
[18,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE
[19,] FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE
[20,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
Now the only what you need to put in loop is to select appropriate column
from matrix comparison based on value on cols vector and 0 or 1 in
previous row of station column.
Something like (untested)
gen.log<-rep(NA, nrow(genmat)-1)
for (i in 2:nrow(genmat)) {
gen.log[i] <- if( genmat[i-1, num] ==0) comparison[i, cols[i]] else
comparison[i,cols[i+5]]
}
genmat[2:nrow(genmat), num] <- gen.log*1
Regards
Petr
r-help-bounces at r-project.org napsal dne 11.08.2010 18:35:37:
> Hello Everyone!
>
> Here's what I'm trying to do. I'm working on generating occurrences of
> precipitation based upon precipitation occurrence for a station during
the
> previous day and two stations that have already been generated by joint
> probablities and 1st order Markov chains or by the same generation
process.
> This has to be done for each remaining stations for each month.
>
> > genmat # 7 stations in this example, line_before is the climatology of
the
> last day of the previous month. Stations 4 and 6 have been generated
already
> in this example
> [,1] [,2] [,3] [,4] [,5] [,6] [,7]
> line_before 1 1 1 0 1 1 1
> NA NA NA 1 NA 0 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 1 NA 0 NA
> NA NA NA 1 NA 1 NA
> NA NA NA 1 NA 1 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 1 NA 1 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 1 NA 1 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 1 NA 1 NA
> NA NA NA 1 NA 1 NA
> NA NA NA 1 NA 1 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 0 NA 1 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 0 NA 0 NA
> NA NA NA 1 NA 1 NA
> NA NA NA 1 NA 1 NA
> NA NA NA 1 NA 1 NA
> NA NA NA 0 NA 0 NA
> > num # station to generate
> [1] 2
> > use1 # 1st station to use in generation
> [1] 6
> > use2 # 2nd station to use in generation
> [1] 4
>
> > genmat = event.gen2(genmat,use1,use2,num,ortho_obs_used) # Generation
> function shown below
> > genmat # genmat - after it has gone through station 2
> [,1] [,2] [,3] [,4] [,5] [,6] [,7]
> line_before 1 1 1 0 1 1 1
> NA 0 NA 1 NA 0 NA
> NA 0 NA 0 NA 0 NA
> NA 0 NA 0 NA 0 NA
> NA 0 NA 0 NA 0 NA
> NA 0 NA 0 NA 0 NA
> NA 0 NA 0 NA 0 NA
> NA 0 NA 0 NA 0 NA
> NA 0 NA 1 NA 0 NA
> NA 1 NA 1 NA 1 NA
> NA 1 NA 1 NA 1 NA
> NA 1 NA 0 NA 0 NA
> NA 0 NA 0 NA 0 NA
> NA 1 NA 1 NA 1 NA
> NA 0 NA 0 NA 0 NA
> NA 0 NA 0 NA 0 NA
> NA 0 NA 0 NA 0 NA
> NA 0 NA 0 NA 0 NA
> NA 0 NA 0 NA 0 NA
> NA 1 NA 1 NA 1 NA
> NA 0 NA 0 NA 0 NA
> NA 1 NA 1 NA 1 NA
> NA 0 NA 1 NA 1 NA
> NA 1 NA 1 NA 1 NA
> NA 0 NA 0 NA 0 NA
> NA 1 NA 0 NA 1 NA
> NA 0 NA 0 NA 0 NA
> NA 0 NA 0 NA 0 NA
> NA 1 NA 1 NA 1 NA
> NA 1 NA 1 NA 1 NA
> NA 1 NA 1 NA 1 NA
> NA 0 NA 0 NA 0 NA
>
> Where event.gen2 is this function:
>
> event.gen2 = function(genmat,use1,use2,num,ortho_obs_used){
>
> for(r in 2:nrow(genmat)){
>
> ran = runif(1,0,1)
>
> if(genmat[r,use1]==0 & genmat[r,use2]==0){
>
genmat[r,num]<-ifelse(genmat[r-1,num]==0,ifelse(ran<ortho_obs_used$Pr[1],1,
> 0),ifelse(ran<ortho_obs_used$Pr[4],1,0))
> }
>
> if(genmat[r,use1]==0 & genmat[r,use2]==1){
>
genmat[r,num]<-ifelse(genmat[r-1,num]==0,ifelse(ran<ortho_obs_used$Pr[2],1,
> 0),ifelse(ran<ortho_obs_used$Pr[5],1,0))
> }
>
> if(genmat[r,use1]==1 & genmat[r,use2]==0){
>
genmat[r,num]<-ifelse(genmat[r-1,num]==0,ifelse(ran<ortho_obs_used$Pr[3],1,
> 0),ifelse(ran<ortho_obs_used$Pr[7],1,0))
> }
>
> if(genmat[r,use1]==1 & genmat[r,use2]==1){
>
genmat[r,num]<-ifelse(genmat[r-1,num]==0,ifelse(ran<ortho_obs_used$Pr[6],1,
> 0),ifelse(ran<ortho_obs_used$Pr[8],1,0))
> }
>
> gc()
> }
>
> genmat
>
> }
>
> ####
>
> ortho_obs_used is a data frame that contains the probablity of
precipitation
> occurring on a given day for a specific set of condtions.
> For instance ortho_obs_used$Pr[1] is the probablity of rain at station s
for
> day d, given that there was no rain at station s for day d-1 and no rain
at
> either of the other two stations for day d.
>
> The event.gen2 function handles the generation, and it runs quickly for
the
> 5 remaining stations and one month, but I have to run this for 317
stations
> over 48 months or more, and it becomes a really bad bottleneck. So what
I'd
> like to know is if there is anyway that I can re-write this function to
work
> without a loop. I couldn't find anything from previous posts about
getting
> out of loops where the previous iteration is required to determine the
next
> calculation.
>
> Sorry for the length of the post, but I thought it best to try to
explain
> what I was doing first, before diving into my question
>
> Thanks in advance!
>
> Adrienne Wootten
> Graduate Research Assistant/Environmental Meteorologist
> M.S. Atmospheric Science
> NC State University
> State Climate Office of North Carolina
> Raleigh, NC 27695
>
> [[alternative HTML version deleted]]
>
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