No, I am confounded, It does return the value of the expressions
within the respective braces, just like ifelse. Learn something every
day.
Jim
On Mon, Mar 22, 2021 at 9:35 PM Jim Lemon <drjimle...@gmail.com> wrote:
>
> If he's setting PRE to the return value of "if", that is the logical
> value of the expression in the if statement as far as I know. I think
> that the expression within the else clause would be evaluated but not
> assigned to anything and since it is within the loop, would just be
> lost.
>
> PRE<-ifelse(missing(GAY),(GA/GA)*100,(GA/GAY)*100)
>
> would return either value depending upon whether GAY was missing.
> That's what I get from the help pages.
>
> Jim
>
> On Mon, Mar 22, 2021 at 8:34 PM Duncan Murdoch <murdoch.dun...@gmail.com>
> wrote:
> >
> > On 22/03/2021 1:59 a.m., Jim Lemon wrote:
> > > Hi Goyani,
> > > You are setting "PRE" to the return value of "if" which is one of TRUE
> > > (1), FALSE(0) or NULL.
> >
> > That's not true at all. The statement was
> >
> > PRE<- if(missing(GAY)){
> > (GA/GA) * 100
> > } else {
> > (GA/GAY) * 100
> > }
> >
> > so the result is (GA/GA) * 100 or (GA/GAY)*100.
> >
> > > Because GAY is always missing in your example,
> >
> > If that's true and GA isn't missing, the result will always be 100.
> >
> > Duncan Murdoch
> >
> > > "PRE" is always set to 1. Then you always want to pass 1 in the sample
> > > list, and that will not assign anything to PRE. By correcting the "if"
> > > clause and defining matrices that are unlikely to be singular, I can
> > > run a "for" loop as follows:
> > >
> > > selection.index<- function(ID, phen_mat, gen_mat, weight_mat, GAY){
> > > p<-as.matrix(phen_mat)
> > > g<-as.matrix(gen_mat)
> > > w<-as.matrix(weight_mat)
> > > bmat<- solve(phen_mat) %*% gen_mat %*% weight_mat
> > > GA<- 2.063 * t(bmat) %*% g %*% w / (t(bmat) %*% p %*% bmat)^0.5
> > > if(missing(GAY)) PRE<-(GA/GA) * 100
> > > else PRE<-(GA/GAY) * 100
> > > result<-list(ID=ID,b=matrix(round(bmat,4),nrow=1),
> > > GA=round(GA,4),PRE=round(PRE,4))
> > > return(data.frame(result))
> > > }
> > >
> > > pmat<-matrix(sample(1:16,16),4)
> > > gmat<-matrix(sample(17:32),16,4)
> > > wmat<-matrix(sample(1:4,4),4)
> > >
> > > mi<-combn(1:4,2)
> > > sc<-list()
> > > for(i in 1:ncol(matindx)) {
> > > as.numeric(ID<-paste0(mi[,i]))
> > > sc[[i]]<-selection.index(ID,pmat[mi[,i],mi[,i]],gmat[mi[,i],mi[,i]],
> > > wmat[mi[,i]],1)
> > > }
> > >
> > > This produces output for me. Good luck with whatever you are doing with
> > > this.
> > >
> > > Jim
> > >
> > >
> > >
> > >
> > >
> > > On Mon, Mar 22, 2021 at 2:51 PM Goyani Zankrut <zankru...@gmail.com>
> > > wrote:
> > >>
> > >> Greetings of the day,
> > >> Thank you for your response, Sir.
> > >> The full problem statement is given below:
> > >>
> > >> In our case, I'm taking 4 traits.
> > >> library(arrangements)
> > >> a<- combinations(4,2) # gives 6 pairwise combinations
> > >> class(a) # it's a "matrix" "array"
> > >>
> > >> now hypothetical data of three matrix for further calculation:
> > >> pmat<- matrix(1:16, nrow = 4)
> > >> gmat<- matrix(17:32, nrow = 4)
> > >> wmat<- matrix(1:4, nrow = 4)
> > >>
> > >> My custom function for further calculations:
> > >> selection.index<- function(ID, phen_mat, gen_mat, weight_mat, GAY){
> > >> ID = toString(ID)
> > >> p<- as.matrix(phen_mat)
> > >> g<- as.matrix(gen_mat)
> > >> w<- as.matrix(weight_mat)
> > >> bmat<- solve(phen_mat) %*% gen_mat %*% weight_mat
> > >> GA<- 2.063 * t(bmat) %*% g %*% w / (t(bmat) %*% p %*% bmat)^0.5
> > >> PRE<- if(missing(GAY)){
> > >> (GA/GA) * 100
> > >> } else {
> > >> (GA/GAY) * 100
> > >> }
> > >> result<- list("ID" = ID, "b" = matrix(round(bmat,4), nrow = 1), "GA"
> > >> = round(GA,4), "PRE" = round(PRE,4))
> > >> return(data.frame(result))
> > >> }
> > >>
> > >> Now I want to store this data into a list for further calculation:
> > >> sc<- list()
> > >> sc[[1]]<- selection.index(ID = 12, phen_mat = pmat[c(1,2),c(1,2)],
> > >> gen_mat = gmat[c(1,2),c(1,2)], weight_mat = wmat[c(1,2),1])
> > >> sc[[2]]<- selection.index(ID = 13, phen_mat = pmat[c(1,3),c(1,3)],
> > >> gen_mat = gmat[c(1,3),c(1,3)], weight_mat = wmat[c(1,3),1])
> > >> sc[[3]]<- selection.index(ID = 14, phen_mat = pmat[c(1,4),c(1,4)],
> > >> gen_mat = gmat[c(1,4),c(1,4)], weight_mat = wmat[c(1,4),1])
> > >> sc[[4]]<- selection.index(ID = 23, phen_mat = pmat[c(2,3),c(2,3)],
> > >> gen_mat = gmat[c(2,3),c(2,3)], weight_mat = wmat[c(2,3),1])
> > >> sc[[5]]<- selection.index(ID = 24, phen_mat = pmat[c(2,4),c(2,4)],
> > >> gen_mat = gmat[c(2,4),c(2,4)], weight_mat = wmat[c(2,4),1])
> > >> sc[[6]]<- selection.index(ID = 34, phen_mat = pmat[c(3,4),c(3,4)],
> > >> gen_mat = gmat[c(3,4),c(3,4)], weight_mat = wmat[c(3,4),1])
> > >> above list code is monotonous and time consuming for large data
> > >> combination cycles like (7,2) = 21 combinations, (10,2) = 45
> > >> combinations. So I want to use the matrix a's each row as a vector in
> > >> the selection.index function and result stores in a list.
> > >>
> > >> I hope now you will understand the full problem. I have checked the
> > >> selection.index which has no issues and works well.
> > >> Thank you.
> > >>
> > >
> > > ______________________________________________
> > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > > 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.
> > >
> >
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