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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,64 @@ | ||
| idle_time_flow <- function(log, units) { | ||
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| # activate <- NULL | ||
| # active <- NULL | ||
| # ts <- NULL | ||
| # next_ts <- NULL | ||
| # dur <- NULL | ||
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| # patients %>% | ||
| # mutate(activate = ifelse((!!lifecycle_id_(log)) == "start", 1, ifelse((!!lifecycle_id_(log)) == "complete", -1, 0))) %>% | ||
| # group_by_case() %>% | ||
| # arrange(!!timestamp_(log), .order) %>% | ||
| # mutate(active = cumsum(activate), | ||
| # ts = !!timestamp_(log), | ||
| # next_ts = lead(!!timestamp_(log))) %>% | ||
| # mutate(dur = difftime(next_ts, ts, units = units)) %>% | ||
| # filter(active == 0 & !is.na(dur)) %>% | ||
| # summarize(idle_time = sum(dur)) -> output | ||
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| dt <- data.table(log) | ||
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| LCID <- NULL | ||
| activate <- NULL | ||
| TS <- NULL | ||
| active <- NULL | ||
| next_TS <- NULL | ||
| dur <- NULL | ||
| CID <- NULL | ||
| AID <- NULL | ||
| AIID <- NULL | ||
| start <- NULL | ||
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| # Override column names for handling | ||
| setnames(dt, | ||
| old = c(lifecycle_id(log), case_id(log), timestamp(log), activity_id(log), activity_instance_id(log)), | ||
| new = c("LCID", "CID", "TS", "AID", "AIID")) | ||
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| dt[, .("start" = min(TS), "complete" = max(TS)), by = .(CID,AID, AIID)] -> dt | ||
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| dt <- gather(dt, LCID, TS, start, complete ) %>% data.table() | ||
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| dt[, "activate" := fcase(LCID == "start", 1L, | ||
| LCID == "complete", -1L, | ||
| default = 0L)] | ||
| # Order by timestamp and .order per case | ||
| setorderv(dt, cols = c("TS")) | ||
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| dt[,":="("active" = cumsum(activate), | ||
| "next_TS" = shift(TS, type = "lead"), | ||
| "next_ACT" = shift(AID, type = "lead")), | ||
| by = "CID"][, | ||
| "dur" := difftime(next_TS, TS, units = units)][ | ||
| active == 0L & !is.na(dur)] -> dt | ||
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| # Revert column names to original | ||
| setnames(dt, old = c("CID","AID", "next_ACT", "dur", "AIID"), new = c(case_id(log), "from", "to", "idle_time", activity_instance_id(log))) | ||
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| output <- as_tibble(dt) %>% | ||
| select(-LCID, -TS, -next_TS, -active, -activate) | ||
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| attr(output, "units") <- attr(output[["idle_time"]], "units") | ||
| return(output) | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,24 @@ | ||
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| throughput_time_activity <- function(log, units, work_schedule) { | ||
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| relative_frequency <- NULL | ||
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| throughput_time_activity_instance(log, units = units, work_schedule = work_schedule) -> raw | ||
| log %>% | ||
| as.data.frame() %>% | ||
| distinct(!!sym(activity_id(log)), !!sym(activity_instance_id(log))) -> aid_a_link | ||
| # Store time units, because dplyr transformations remove the attributes. | ||
| time_units <- attr(raw, "units") | ||
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| merge(raw, aid_a_link, by = activity_instance_id(log)) %>% | ||
| group_by(!!sym(activity_id(log))) %>% | ||
| grouped_summary_statistics("throughput_time", relative_frequency = n()) %>% | ||
| mutate(relative_frequency = relative_frequency/sum(relative_frequency)) %>% | ||
| arrange(desc(relative_frequency)) %>% | ||
| select(!!sym(activity_id(log)), relative_frequency, everything()) -> output | ||
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| attr(output, "raw") <- raw | ||
| attr(output, "units") <- time_units | ||
| return(output) | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,33 @@ | ||
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| throughput_time_activity_instance <- function(log, units, work_schedule = NULL) { | ||
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| s <- NULL | ||
| elapsed <- NULL | ||
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| timestamp_classifier <- NULL | ||
| activity_instance_classifier <- activity_instance_id(log) | ||
| colnames(log)[colnames(log) == timestamp(log)] <- "timestamp_classifier" | ||
| colnames(log)[colnames(log) == activity_instance_classifier] <- "activity_instance_classifier" | ||
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| e <- log %>% | ||
| as.data.table %>% | ||
| .[, .(s = min(timestamp_classifier), | ||
| e = max(timestamp_classifier)), .(activity_instance_classifier)] | ||
| colnames(e)[colnames(e) == "activity_instance_classifier"] <- activity_instance_classifier | ||
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| intervals <- as.data.frame(e) | ||
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| if(is.null(work_schedule)) { | ||
| intervals %>% | ||
| mutate(throughput_time = difftime(e, s, units = units)) %>% | ||
| select(-s, -e) -> output | ||
| } else { | ||
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| calculate_work_schedule_times(intervals, work_schedule, units) %>% | ||
| select(-s, -e) %>% | ||
| rename(throughput_time = elapsed) -> output | ||
| } | ||
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| attr(output, "units") <- attr(output[["throughput_time"]], "units") | ||
| return(output) | ||
| } |
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