106 lines
2.7 KiB
R
106 lines
2.7 KiB
R
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#' ---
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#' title: "Programming input"
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#' author: "Nora Wickelmaier"
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#' date: "`r Sys.Date()`"
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#' output: html_document
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#' ---
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#+ include = FALSE
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# setwd("C:/Users/nwickelmaier/Nextcloud/Documents/MDS/2023ss/60100_master_thesis/code")
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#+
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dat0 <- read.table("../data/rawdata_logfiles_small.csv", sep = ";", header = TRUE)
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dat0$date <- as.POSIXct(dat0$date) # create date object
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# Remove irrelevant events
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dat <- subset(dat0, !(dat0$event %in% c("Start Application", "Show Application")))
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str(dat)
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# make data better manageable
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tmp <- dat[!dat$event %in% c("Transform start", "Transform stop"), ]
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rownames(tmp) <- NULL
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#' # Add `trace` variable for closing events
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tmp$trace <- NA
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last_event <- tmp$event[1]
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aws <- unique(tmp$artwork)[unique(tmp$artwork) != "glossar"]
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for (art in aws) { # select artwork
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for (i in 1:nrow(tmp)) { # go through rows
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if (last_event == "Show Info" & tmp$artwork[i] == art) {
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tmp$trace[i] <- i
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j <- i
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} else if (last_event == "Show Front" & tmp$artwork[i] == art) {
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tmp$trace[i] <- j
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} else if (!(last_event %in% c("Show Info", "Show Front")) &
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tmp$artwork[i] == art) {
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tmp$trace[i] <- j
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}
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if (i <= nrow(tmp)) {
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last_event <- tmp$event[i + 1]
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}
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}
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}
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head(tmp[, c("artwork", "event", "trace")], 50)
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#' # Find artwork for glossar entry
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glossar_files <- unique(tmp[tmp$artwork == "glossar", "popup"])
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# Load lookup table for artworks and glossar files
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load("../data/glossar_dict.RData")
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lut <- glossar_dict[glossar_dict$glossar_file %in% glossar_files, ]
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# Fill in trace variable based on last `Show Info`
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for (file in lut$glossar_file) {
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artwork_list <- unlist(lut[lut$glossar_file == file, "artwork"])
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for (i in seq_len(nrow(tmp))) {
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if (tmp$event[i] == "Show Info") {
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current_artwork <- tmp[i, "artwork"]
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j <- i
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k <- i
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} else {
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current_artwork <- current_artwork
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}
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if (tmp$event[i] == "Show Front" & tmp$artwork[i] == current_artwork) {
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# make sure artwork has not been closed, yet!
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k <- i
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}
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if (tmp$artwork[i] == "glossar" &
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(current_artwork %in% artwork_list) &
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tmp$popup[i] == file & (j-k == 0)) {
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tmp[i, "trace"] <- tmp[j, "trace"]
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}
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}
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}
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tmp[tmp$artwork == "glossar", c("artwork", "event", "popup", "trace")]
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proportions(table(is.na(tmp$trace[tmp$artwork == "glossar"])))
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# --> finds about half of the glossar entries for small data set...
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# REMEMBER: It can never be 100% correct, since it is always possible that
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# several cards are open and that they link to the same glossar entry
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# How many glossar_files are only associated with one artwork?
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lut[sapply(lut$artwork, length) == 1, "glossar_file"]
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