Skip to content

Speed up process_map function by using data.table #68

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
gertjanssenswillen merged 1 commit into from
Jul 7, 2025
Merged

Speed up process_map function by using data.table #68

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
40 changes: 24 additions & 16 deletions R/process_map.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -162,29 +162,37 @@ process_map.eventlog <- function(log,
as.data.frame() -> base_log
}

#create end points for graph

base_log %>%
group_by(CASE_CLASSIFIER_) %>%
arrange(start_time, min_order) -> points_temp

points_temp %>%
slice(1) %>%
mutate(ACTIVITY_CLASSIFIER_ = "ARTIFICIAL_START",
end_time = start_time,
min_order = -Inf) -> end_points_start
points_temp %>%
slice(n()) %>%
mutate(ACTIVITY_CLASSIFIER_ = "ARTIFICIAL_END",
start_time = end_time,
min_order = Inf) -> end_points_end
#create end points for graph using data.table slicing
dt <- as.data.table(base_log)
#set correct ordering within groups
data.table::setorder(dt, CASE_CLASSIFIER_, start_time, min_order, na.last=TRUE)
#specifying order of columns to reorder end_points_start and end_points_end
colorder <- c('ACTIVITY_CLASSIFIER_', 'ACTIVITY_INSTANCE_CLASSIFIER_', 'CASE_CLASSIFIER_', 'start_time', 'end_time', 'min_order')

end_points_start <- dt[, .SD[1], by = CASE_CLASSIFIER_]
end_points_start[, min_order := as.numeric(min_order)] #prevents warning when setting value to -Inf
end_points_start[, `:=`(ACTIVITY_CLASSIFIER_ = "ARTIFICIAL_START",
end_time = start_time,
min_order = -Inf)]
data.table::setcolorder(end_points_start, colorder)

end_points_end <- dt[, .SD[.N], by = CASE_CLASSIFIER_]
end_points_end[, min_order := as.numeric(min_order)] #prevents warning when setting value to Inf
end_points_end[, `:=`(ACTIVITY_CLASSIFIER_ = "ARTIFICIAL_END",
start_time = end_time,
min_order = Inf)]
data.table::setcolorder(end_points_end, colorder)

#add endpoints to base log

suppressWarnings(
bind_rows(end_points_start, end_points_end, base_log) %>%
ungroup() -> base_log
)

#converting ACTIVITY_CLASSIFIER_ to character to keep `base_log` identical to the previous dplyr method
base_log <- base_log %>%
mutate(ACTIVITY_CLASSIFIER_ = as.character(ACTIVITY_CLASSIFIER_))

#create base nodes list

Expand Down