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#' Find Kernel Ranged Group
#'
#' The goal is to find the Kernel Ranged Group information for a candidate c.
#'
#' @param c candidate
#' @param d set of transactions
#' @param gamma minimum temporal frequency
#' @param beta minimum group size
#' @param adjacency_matrix adjacency matrix
#' @return Kernel Ranged-Group(s) of c updated
find_kernel_ranged_group <- function(c, d, gamma, beta, adjacency_matrix) {
rows <- nrow(d)
columns <- ncol(d) - 1
timestamp <- strtoi(d[1, columns + 1])
if (
c$range_s > strtoi(d[rows, columns + 1]) ||
c$range_e < strtoi(d[1, columns + 1])
) {
return(c)
}
pos <- c$pos
i <- 1
while (sum(pos) > 0 && i <= rows) {
p <- c(d[i, 1:columns] == substr(c$seq, i, i))
pos <- pos & p
i <- i + 1
}
if (sum(pos) > 0) {
groups <- split_groups(pos, adjacency_matrix)
r_s <- timestamp
r_e <- timestamp
freq <- 1
cresce <- 1 / gamma - 1
e_s <- r_s - cresce
e_e <- r_e + cresce + 1
rows <- length(c$rgs$group)
for (i in 1:length(groups)) { # nolint
c$rgs$time <- rbind(c$rgs$time, c(r_s, r_e, freq, e_s, e_e))
c$rgs$group[[rows + i]] <- groups[[i]]
occurrences <- matrix(nrow = 0, ncol = 2)
colnames(occurrences) <- c("x", "y")
for (j in which(groups[[i]])) {
occurrences <- rbind(occurrences, c(j, timestamp))
}
c$rgs$occ[[rows + i]] <- occurrences
}
c <- merge_open_kernel_ranged_groups(
c,
timestamp,
gamma,
beta,
adjacency_matrix
)
}
return(c)
}
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