#' Assess quality of the fitting via correlation
#'
#' @param TargetStruct
#' @param ProcStruct
#' @param DistVect
#' @param CorMet
#'
#' @importFrom magrittr %>%
#'
#' @return
#' @export
#'
#' @examples
DistanceGraphCor <- function(TargetStruct, ProcStruct, DistVect = 4:10, CorMet = "spe") {
AllDist <- distances(TargetStruct$Net[[length(TargetStruct$Net)]])
AllDist_Reord <- colnames(AllDist) %>%
strsplit(., split = '_', fixed = TRUE) %>%
sapply(., "[[", 2) %>%
as.integer %>%
order %>%
AllDist[., .]
AllPos <- rbind(TargetStruct$Data, TargetStruct$PrinGraph$Nodes) %>%
stats::dist(.) %>%
as.matrix(.)
CellDist <- AllPos[1:nrow(TargetStruct$Data), -c(1:nrow(TargetStruct$Data))]
AssignedNodes <- apply(CellDist, 1, which.min)
CorVal <- sapply(DistVect, function(thr){
sapply(X = 1:length(AssignedNodes), FUN = function(i){
SelDistVect <- AllDist_Reord[AssignedNodes[i],]
cor(SelDistVect[SelDistVect <= thr], CellDist[i, SelDistVect <= thr], method = CorMet)
})
})
rownames(CorVal) <- names(AssignedNodes)
colnames(CorVal) <- paste("P", DistVect, sep = "=")
return(CorVal)
}
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