160 lines
5.6 KiB
R
160 lines
5.6 KiB
R
# setwd("C:/Users/nwickelmaier/Nextcloud/Documents/MDS/2023ss/60100_master_thesis/code")
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# Read data
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# dat0 <- read.table("../data/haum/event_logfiles_metadata_2023-09-23_01-31-30.csv",
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# sep = ";", header = TRUE)
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dat0 <- read.table("../data/haum/event_logfiles_small_metadata_2023-10-15_10-08-43.csv",
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sep = ";", header = TRUE)
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dat0$date <- as.Date(dat0$date)
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dat0$date.start <- as.POSIXct(dat0$date.start)
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dat0$date.stop <- as.POSIXct(dat0$date.stop)
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dat0$artwork <- sprintf("%03d", dat0$artwork)
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# TODO: Write a function that closes events spanning different log files
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# OR: Remove openTopic and OpenPopup events that do not start with a
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# flipCard (AND openPopup events without openTopic event beforehand)
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table(dat0[!duplicated(dat0$trace), "event"])
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# flipCard move openPopup openTopic
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# 45528 247718 981 3457
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proportions(table(dat0[!duplicated(dat0$trace), "event"]))
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tmp <- dat0[!duplicated(dat0$trace) & dat0$event %in% c("openTopic",
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"openPopup"), ]
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dat <- dat0
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i <- 1
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stop <- 1
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while (stop > 0) {
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stop <- sum(!duplicated(dat$trace) & dat$event %in% c("openTopic", "openPopup"))
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dat <- dat[!(!duplicated(dat$trace) &
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dat$event %in% c("openTopic", "openPopup")), ]
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print(i)
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i <- i + 1
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print(table(dat[!duplicated(dat$trace), "event"]))
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}
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# Creating event logs
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library(bupaverse)
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names(dat)[names(dat) %in% c("date.start", "date.stop")] <- c("start",
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"complete")
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table(table(dat$start))
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# --> hmm...
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summary(aggregate(duration ~ trace, dat, mean))
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# remove fragmented traces
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tab <- xtabs( ~ trace + event, dat)
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fragments <- NULL
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for (i in seq_len(nrow(tab))) {
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if (tab[i, "openPopup"] != 0 & tab[i, "flipCard"] == 0) {
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fragments <- c(fragments, rownames(tab)[i])
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} else if (tab[i, "openTopic"] != 0 & tab[i, "flipCard"] == 0) {
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fragments <- c(fragments, rownames(tab)[i])
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} else if (tab[i, "openPopup"] != 0 & tab[i, "openTopic"] == 0) {
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fragments <- c(fragments, rownames(tab)[i])
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}
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}
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datrm <- dat[!dat$trace %in% fragments, ]
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# TODO: Find trace that has flipCard --> openPopup --> openTopic
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dato <- datrm[datrm$event != "move", ]
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tmp <- lapply(unique(dato$trace), function(x) unique(dato[dato$trace == x, "event"]))
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names(tmp) <- unique(dato$trace)
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ids <- sapply(tmp, length) == 3
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do.call(rbind, tmp[ids])
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# TODO:
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# fragmentary traces: for 4591 openTopic for topic 1 is in the raw log files, but gets
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# probably removed in close_events(); how can I prevent that? How can I fix
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# the traces and eventIds that do not match correctly ???
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ct <- c(4591, 5937, 7080, 8412, 8279)
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datrm[datrm$trace %in% ct, 1:10]
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### WHY?????
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alog <- activitylog(datrm,
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case_id = "trace",
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activity_id = "event",
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#resource_id = "case",
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resource_id = "artwork",
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timestamps = c("start", "complete"))
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process_map(alog)
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process_map(alog, frequency("relative"))
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process_map(alog, frequency("relative_consequent"))
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library(processanimateR)
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animate_process(to_eventlog(alog))
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col_vector <- c("#7FC97F", "#BEAED4", "#FDC086", "#FFFF99", "#386CB0",
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"#F0027F", "#BF5B17", "#666666", "#1B9E77", "#D95F02",
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"#7570B3", "#E7298A", "#66A61E", "#E6AB02", "#A6761D",
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"#666666", "#A6CEE3", "#1F78B4", "#B2DF8A", "#33A02C",
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"#FB9A99", "#E31A1C", "#FDBF6F", "#FF7F00", "#CAB2D6",
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"#6A3D9A", "#FFFF99", "#B15928", "#FBB4AE", "#B3CDE3",
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"#CCEBC5", "#DECBE4", "#FED9A6", "#FFFFCC", "#E5D8BD",
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"#FDDAEC", "#F2F2F2", "#B3E2CD", "#FDCDAC", "#CBD5E8",
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"#F4CAE4", "#E6F5C9", "#FFF2AE", "#F1E2CC", "#CCCCCC",
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"#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00",
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"#FFFF33", "#A65628", "#F781BF", "#999999", "#66C2A5",
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"#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F",
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"#E5C494", "#B3B3B3", "#8DD3C7", "#FFFFB3", "#BEBADA",
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"#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5",
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"#D9D9D9")
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animate_process(to_eventlog(alog), mode = "relative", jitter = 10, legend = "color",
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mapping = token_aes(color = token_scale("artwork",
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scale = "ordinal",
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range = col_vector)))
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elog <- to_eventlog(alog)
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animate_process(elog[elog$artwork == "054", ])
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animate_process(elog[elog$artwork == "080", ])
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animate_process(elog[elog$artwork == "501", ])
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process_map(alog[alog$artwork == "054", ])
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animate_process(elog[elog$artwork %in% c("080", "054"), ],
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mode = "relative", jitter = 10, legend = "color",
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mapping = token_aes(color = token_scale("artwork",
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scale = "ordinal",
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range = c("black", "gray"))))
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# --> not sure, yet, how to interpret this...
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alog080 <- activitylog(dat[dat$artwork %in% "080", ],
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#case_id = "case",
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case_id = "trace",
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activity_id = "event",
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#resource_id = "trace",
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resource_id = "case",
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timestamps = c("start", "complete"))
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process_map(alog080, frequency("relative"))
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alog054 <- activitylog(dat[dat$artwork %in% "054", ],
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#case_id = "case",
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case_id = "trace",
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activity_id = "event",
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#resource_id = "trace",
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resource_id = "case",
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timestamps = c("start", "complete"))
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process_map(alog054, frequency("relative"))
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