[R] for loop implementation in below problem

[Duncan Murdoch]

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 <zankrut20 using 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.
>>
> 
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