[R] wanting to count instances of values in each cell of a series of simulated symmetric matrices of the same size

[Bert Gunter]

Come again?! The diagonal values in your example are not all .5.

If space is not an issue, a straightforward approach is to collect all the
matrices into a 3d array and use indexing.
Here is a simple reprex (as you did not provide one in a convenient form,
e.g via dput())

x <- matrix(1:9, nr = 3); y <- x+10
diag(x) <- diag(y) <- 0
print(x) ; print(y)
## Now you need to populate a 3 x 3 x 2 array with these matrices
## How you do this depends on your naming conventions
## You might use a loop, or ls() and assign(),
##  or collect your matrices into a list and use do.call() or ...
## You will *not*want to do this if you have lots of matrices:
list_of_mats <- list(x,y)
arr <- array(do.call(c,list_of_mats), dim = c(3,3,length(list_of_mats)))
arr
arr[2,3,] ## all the values in the [2,3] cell of the matrices; do whatever
you want with them.

Cheers,
Bert



Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Tue, Jun 1, 2021 at 7:00 PM R. Mark Sharp via R-help <
r-help using r-project.org> wrote:

> I want to capture the entire distribution of values for each cell in a
> sequence of symmetric matrices of the same size. The diagonal values are
> all 0.5 so I need only the values above or below the diagonal.
>
> A small example with three of the structures I am wanting to count follows:
>        F      G      H      I     J
> F 0.6250 0.3750 0.2500 0.1875 0.125
> G 0.3750 0.6250 0.2500 0.1875 0.125
> H 0.2500 0.2500 0.5000 0.1875 0.125
> I 0.1875 0.1875 0.1875 0.5000 0.250
> J 0.1250 0.1250 0.1250 0.2500 0.500
>
>        F      G      H      I     J
> F 0.5625 0.3125 0.1875 0.1250 0.125
> G 0.3125 0.5625 0.1875 0.1250 0.125
> H 0.1875 0.1875 0.5000 0.1875 0.125
> I 0.1250 0.1250 0.1875 0.5000 0.250
> J 0.1250 0.1250 0.1250 0.2500 0.500
>
>         F       G      H       I      J
> F 0.50000 0.25000 0.1250 0.09375 0.0625
> G 0.25000 0.50000 0.1250 0.09375 0.0625
> H 0.12500 0.12500 0.5000 0.18750 0.1250
> I 0.09375 0.09375 0.1875 0.50000 0.2500
> J 0.06250 0.06250 0.1250 0.25000 0.5000
>
>
> To be more specific, I have coded up a solution for a single cell with the
> sequence of values (one from each matrix) in a vector.
>
> I used match() below and it works with a matrix but I do not know how to
> do what is in the if statements with matrices. Since the number of values
> and the values will be different among the various cells a simple array
> structure does not seem appropriate and I am assuming I will need to use a
> list but I would like to do as much as I can with matrices for speed and
> clarity.
>
> #' Counts the number of occurrences of each kinship value seen for a pair
> of
> #' individuals.
> #'
> #' @examples
> #' \donttest{
> #' set.seed(20210529)
> #' kSamples <- sample(c(0, 0.0675, 0.125, 0.25, 0.5, 0.75), 10000, replace
> = TRUE,
> #'                    prob = c(0.005, 0.3, 0.15, 0.075, 0.0375, 0.01875))
> #' kVC <- list(kinshipValues = numeric(0),
> #'             kinshipCounts = numeric(0))
> #' for (kSample in kSamples) {
> #'   kVC <- countKinshipValues(kSample, kVC$kinshipValues,
> kVC$kinshipCounts)
> #' }
> #' kVC
> #' ## $kinshipValues
> #' ## [1] 0.2500 0.1250 0.0675 0.7500 0.5000 0.0000
> #' ##
> #' ## $kinshipCounts
> #' ## [1]  301 2592 5096 1322  592   97
> #' }
> #'
> #' @param kValue numeric value being counted (kinship value in
> #' \emph{nprcgenekeepr})
> #' @param kinshipValues vector of unique values of \code{kValue} seen
> #' thus far.
> #' @param kinshipCounts vector of the counts of the unique values of
> #' \code{kValue} seen thus far.
> #' @export
> countKinshipValues <- function(kValue, kinshipValues = numeric(0),
>                               kinshipCounts = numeric(0)) {
>   kinshipValue <- match(kValue, kinshipValues, nomatch = -1L)
>   if (kinshipValue == -1L) {
>     kinshipValues <- c(kinshipValues, kValue)
>     kinshipCounts[length(kinshipCounts) + 1] <- 1
>   } else {
>     kinshipCounts[kinshipValue] <- kinshipCounts[kinshipValue] + 1
>   }
>   list(kinshipValues = kinshipValues,
>        kinshipCounts = kinshipCounts)
> }
>
> Mark
>
>
> R. Mark Sharp, Ph.D.
> Data Scientist and Biomedical Statistical Consultant
> 7526 Meadow Green St.
> San Antonio, TX 78251
> mobile: 210-218-2868
> rmsharp using me.com
>
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>

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