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Worked on preprocessing; analyzed what happens with neg. durations; added results to README

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Nora Wickelmaier 2023-08-18 13:42:18 +02:00
parent c63c0a8206
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103
README.md
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@ -2,18 +2,19 @@
## Datenverständnis ## Datenverständnis
* Welche Einheit haben x und y? Pixel? * Welche Einheit haben x und y? Pixel? --> yes
* Welche Einheit hat scale? * Welche Einheit hat scale? --> some kind if bit, does not matter, when
* rotation wirklich degree? calculating a ratio
* rotation wirklich degree? --> yes
* Nach welchem Zeitintervall resettet sich der Tisch wieder in die * Nach welchem Zeitintervall resettet sich der Tisch wieder in die
Ausgangskonfiguration? Ausgangskonfiguration? --> PM needs to look it up
## Tisch-Software ## Tisch-Software
* Gibt es Doku für die Bilder, die über die xml files hinausgeht? Sowas wie * Gibt es Doku für die Bilder, die über die xml files hinausgeht? Sowas wie
ein Manual oder ähnliches? ein Manual oder ähnliches?
* Gibt es evtl. irgendwo noch ein Tablet mit der Anwendung drauf? * Gibt es evtl. irgendwo noch ein Tablet mit der Anwendung drauf?
* Was bedeuten die Farben der Topic Cards? * Was bedeuten die Farben der Topic Cards? --> sieht man in den xml files
## Event Logs ## Event Logs
@ -64,6 +65,97 @@ made.
## Weird behavior of `time_ms` and neg. `duration`values ## Weird behavior of `time_ms` and neg. `duration`values
I think the negative duration values happen, when an event starts in one
log file and completes in another one. The variable `time_ms` seems to be
continuous within one log file but not over several log files.
```{r}
dat_all[which(dat_all$duration < 0), ][1:5, 1:10]
# flipCard
## trace 56
dat3[dat3$trace == 56,]
dat[dat$fileid == "2016_11_15-11_12_57.log" & dat$date == "2016-12-15 11:17:26", ]
dat[dat$fileid == "2016_11_15-11_42_57.log" & dat$date == "2016-12-15 11:46:19", ]
#dat[309:1405, ]
tmp <- dat[300:1405, ]
tmp[tmp$artwork == "051", ]
## -> was closed correctly, but does it belong together?
## trace 61
dat3[dat3$trace == 61,]
dat[dat$fileid == "2016_11_15-11_12_57.log" & dat$date == "2016-12-15 11:17:52", ]
dat[dat$fileid == "2016_11_15-11_42_57.log" & dat$date == "2016-12-15 11:46:19", ]
tmp <- dat[350:1408, ]
tmp[tmp$artwork == "057", ]
## -> was closed correctly, but does it belong together?
# openTopic
dat_all[which(dat_all$duration < 0), ][100:105, 1:10]
# trace 2052
dat4[dat4$trace == 2052,]
dat[dat$fileid == "2016_11_17-14_12_10.log" & dat$date == "2016-12-17 14:21:51", ]
dat[dat$fileid == "2016_11_17-14_22_10.log" & dat$date == "2016-12-17 14:22:25", ]
tmp <- dat[23801:23950, ]
tmp[tmp$artwork == "502", ]
plot(time_ms ~ as.factor(fileid), dat[1:5000,])
```
The boxplot shows that we have a continuous range of values within one log
file but that `time_ms` does not increase over log files.
<!--
TODO: I will probably update how events are closed and the names of these
data frame, especially `dat3` and `dat4` will have to be adjusted.
-->
Since it seems not possible to fix this in a consistent way, I will set
negative durations to `NA`. I will keep `time_ms.start` and `time_ms.stop`
in the data frame, so it is clear why there are no durations. Maybe it
would also be useful to keep `logfileid.start` and `logfileid.stop` in the
data? Maybe just for proof checking this theory...
Part of it was that timestamps that are part of the log file names are not
zero-left-padded. But this fixed only three `move` events, since it only
fixed irregularities *within* one log file.
```{r}
table(dat_all[dat_all$duration < 0, "event"])
# flipCard move openPopup openTopic
# 562 100 34 284
dat[dat$event %in% c("Transform start", "Transform stop"), ][1100:1300,]
# --> got fixed by left padding... but only three all together!!
dat_all[735, ]
## what it looked like before left padding
# 1422 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_2_57.log 2016-12-15 12:12:56 599671 Transform start 076 076.xml NA 2092.25 2008.00 0.3000000 13.26874254
# 1423 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_12_57.log 2016-12-15 12:12:57 621 Transform start 076 076.xml NA 2092.25 2008.00 0.3000000 13.26523465
# 1424 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_12_57.log 2016-12-15 12:12:57 677 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997736 13.26239605
# 1425 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_12_57.log 2016-12-15 12:12:57 774 Transform start 076 076.xml NA 2092.25 2008.00 0.2999345 13.26239605
# 1426 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_12_57.log 2016-12-15 12:12:57 850 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997107 13.26223362
# 1427 ../data/haum_logs_2016-2023/_2016b/2016_11_15-12_2_57.log 2016-12-15 12:12:57 599916 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997771 13.26523465
## what it looks like now
# 1422 2016_11_15-12_02_57.log 2016-12-15 12:12:56 599671 Transform start 076 076.xml NA 2092.25 2008.00 0.3000000 13.26874254
# 1423 2016_11_15-12_02_57.log 2016-12-15 12:12:57 599916 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997771 13.26523465
# 1424 2016_11_15-12_12_57.log 2016-12-15 12:12:57 621 Transform start 076 076.xml NA 2092.25 2008.00 0.3000000 13.26523465
# 1425 2016_11_15-12_12_57.log 2016-12-15 12:12:57 677 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997736 13.26239605
# 1426 2016_11_15-12_12_57.log 2016-12-15 12:12:57 774 Transform start 076 076.xml NA 2092.25 2008.00 0.2999345 13.26239605
# 1427 2016_11_15-12_12_57.log 2016-12-15 12:12:57 850 Transform stop 076 076.xml NA 2092.25 2008.00 0.2997107 13.26223362
```
## Events that only close (`date.start` is NA) ## Events that only close (`date.start` is NA)
@ -83,7 +175,6 @@ made.
# Reading list # Reading list
* @Arizmendi2022 [$-$] * @Arizmendi2022 [$-$]

50
code/01_parse-logfiles.R
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@ -2,7 +2,7 @@
#' title: "Preprocessing raw log files" #' title: "Preprocessing raw log files"
#' author: "Nora Wickelmaier" #' author: "Nora Wickelmaier"
#' date: "`r Sys.Date()`" #' date: "`r Sys.Date()`"
#' output: #' output:
#' html_document: #' html_document:
#' default #' default
#' pdf_document: #' pdf_document:
@ -14,10 +14,10 @@
# setwd("C:/Users/nwickelmaier/Nextcloud/Documents/MDS/2023ss/60100_master_thesis/code") # setwd("C:/Users/nwickelmaier/Nextcloud/Documents/MDS/2023ss/60100_master_thesis/code")
#+ setup, include = FALSE #+ setup, include = FALSE
knitr::opts_chunk$set(warning = FALSE, message = FALSE) knitr::opts_chunk$set(warning = FALSE, message = FALSE)
#' The following events can be extracted from the log files: #' The following events can be extracted from the log files:
#' #'
#' ``` #' ```
#' LogEntry classes: #' LogEntry classes:
#' TRANSFORM_START: "Transform start" --> "Transformation Start" in Tool #' TRANSFORM_START: "Transform start" --> "Transformation Start" in Tool
@ -42,9 +42,37 @@ fnames <- dir(dirpaths, pattern = "*.log", full.names = TRUE)
length(fnames) length(fnames)
head(fnames) head(fnames)
# Need to left pad file names. If I do not do this, the sorting of the
# timestamps will be off and I get negative durations later on since the
# wrong events get closed.
leftpad_fnames <- function(x) {
z <- gsub(paste0(dirpaths, "/"), "\\1", x)
ys <- strsplit(z, "_")
res <- NULL
for (y in ys) {
y2 <- unlist(strsplit(y[3], "-"))
e1 <- y[1]
e2 <- sprintf("%02d", as.numeric(y[2]))
e3 <- sprintf("%02d", as.numeric(y2[1]))
e4 <- sprintf("%02d", as.numeric(y2[2]))
e5 <- sprintf("%02d", as.numeric(y[4]))
e6 <- sprintf("%02d", as.numeric(gsub(".log", "", y[5])))
e6 <- sprintf("%02d", as.numeric(gsub(".log", "", y[5])))
res <- c(res, paste0(e1, "_", e2, "_", e3, "-", e4, "_", e5, "_", e6, ".log"))
}
res
}
logs <- lapply(fnames, readLines) logs <- lapply(fnames, readLines)
nlog <- sapply(logs, length) nlog <- sapply(logs, length)
dat <- data.frame(fileid = rep(fnames, nlog), logs = unlist(logs)) dat <- data.frame(fileid = rep(leftpad_fnames(fnames), nlog), logs = unlist(logs))
head(dat$logs) head(dat$logs)
#' Remove corrupted lines #' Remove corrupted lines
@ -59,7 +87,7 @@ head(dat$logs)
# From LogEntry.as: # From LogEntry.as:
# //pm: inserted this check to account for some broken logfiles # //pm: inserted this check to account for some broken logfiles
# if (metaData[1] == null){ # if (metaData[1] == null){
# trace("corrupt line... still do not know how these came to happen."); # trace("corrupt line... still do not know how these came to happen.");
# corrupt lines are "" and need to be removed # corrupt lines are "" and need to be removed
@ -73,12 +101,12 @@ d2 <- dim(dat)[1]
#' ### Extract relevant infos #' ### Extract relevant infos
date <- sapply(dat$logs, gsub, date <- sapply(dat$logs, gsub,
pattern = "^\\[(.*)\\], \\[.*$", pattern = "^\\[(.*)\\], \\[.*$",
replacement = "\\1", replacement = "\\1",
USE.NAMES = FALSE) USE.NAMES = FALSE)
timestamp <- sapply(dat$logs, gsub, timestamp <- sapply(dat$logs, gsub,
pattern = "^\\[.*\\], \\[(.*)\\].*$", pattern = "^\\[.*\\], \\[(.*)\\].*$",
replacement = "\\1", replacement = "\\1",
USE.NAMES = FALSE) USE.NAMES = FALSE)
@ -108,6 +136,8 @@ ts_elements <- strsplit(timestamp, ":")
time_ms <- as.numeric(sapply(ts_elements, function(x) x[4])) + time_ms <- as.numeric(sapply(ts_elements, function(x) x[4])) +
as.numeric(sapply(ts_elements, function(x) x[3])) * 1000 + as.numeric(sapply(ts_elements, function(x) x[3])) * 1000 +
as.numeric(sapply(ts_elements, function(x) x[2])) * 1000 * 60 as.numeric(sapply(ts_elements, function(x) x[2])) * 1000 * 60
# TODO: Maybe change to simple gsub()...
# --> This is theoretically sound but a lot of lines for just removing ":"
dat$date <- lubridate::parse_date_time(date, "bdyHMSOp") dat$date <- lubridate::parse_date_time(date, "bdyHMSOp")
dat$time_ms <- time_ms dat$time_ms <- time_ms
@ -125,11 +155,11 @@ dat$logs <- NULL
str(dat) str(dat)
head(dat[, 2:ncol(dat)], 20) head(dat, 20)
# sort by date, since sorting by file names does not make sense because of # sort by fileid, since reading in by file names does not make sense because of
# missing left zero padding # missing left zero padding
dat <- dat[order(dat$date), ] dat <- dat[order(dat$fileid, dat$date, dat$time_ms), ]
## TODO: Replace artwork and popup numbers with informative strings ## TODO: Replace artwork and popup numbers with informative strings

196
code/02_preprocessing.R
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@ -43,46 +43,46 @@ dat <- subset(dat0, !(dat0$event %in% c("Start Application",
######## ########
#' Do it for Transform events first #' Do it for Transform events first
tmp <- dat[dat$event %in% c("Transform start", "Transform stop"), ] dat1 <- dat[dat$event %in% c("Transform start", "Transform stop"), ]
tmp <- tmp[order(tmp$artwork, tmp$date), ] dat1 <- dat1[order(dat1$artwork, dat1$date), ]
rownames(tmp) <- NULL rownames(dat1) <- NULL
# Create event ID for closing events # Create event ID for closing events
num_start <- diff(c(0, which(tmp$event == "Transform stop"))) num_start <- diff(c(0, which(dat1$event == "Transform stop")))
tmp$eventid <- rep(seq_along(num_start), num_start) dat1$eventid <- rep(seq_along(num_start), num_start)
head(tmp[, c("event", "eventid")], 25) head(dat1[, c("event", "eventid")], 25)
table(table(tmp$eventid)) table(table(dat1$eventid))
# 1 2 3 4 5 6 7 8 10 11 # 1 2 3 4 5 6 7 8 10 11
# 73 78429 5156 842 222 66 18 14 3 1 # 73 78429 5156 842 222 66 18 14 3 1
# --> compare to table(num_start)! # --> compare to table(num_start)!
# Find out how often "Transform stop" follows each other # Find out how often "Transform stop" follows each other
num_stop <- c(diff(c(0, which(tmp$event == "Transform start")))) num_stop <- c(diff(c(0, which(dat1$event == "Transform start"))))
table(num_stop) table(num_stop)
tmp$eventrep <- rep(num_start, num_start) dat1$eventrep <- rep(num_start, num_start)
tmp$dupl <- duplicated(tmp[, c("event", "eventid")]) # keep first dat1$dupl <- duplicated(dat1[, c("event", "eventid")]) # keep first
tmp$dupl <- duplicated(tmp[, c("event", "eventid")], fromLast = TRUE) # keep last dat1$dupl <- duplicated(dat1[, c("event", "eventid")], fromLast = TRUE) # keep last
tmp[tmp$eventrep == 10, ] dat1[dat1$eventrep == 10, ]
tmp$dupl <- NULL dat1$dupl <- NULL
tmp$eventrep <- NULL dat1$eventrep <- NULL
# remove duplicated "Transform start" events # remove duplicated "Transform start" events
tmp <- tmp[!duplicated(tmp[, c("event", "eventid")]), ] dat1 <- dat1[!duplicated(dat1[, c("event", "eventid")]), ]
# remove duplicated "Transform stop" events # remove duplicated "Transform stop" events
id_stop <- which(tmp$event == "Transform stop") id_stop <- which(dat1$event == "Transform stop")
id_rm_stop <- id_stop[diff(id_stop) == 1] id_rm_stop <- id_stop[diff(id_stop) == 1]
tmp <- tmp[-(id_rm_stop + 1), ] dat1 <- dat1[-(id_rm_stop + 1), ]
# transform to wide data format # transform to wide data format
tmp$event <- ifelse(tmp$event == "Transform start", "start", "stop") dat1$event <- ifelse(dat1$event == "Transform start", "start", "stop")
trans_wide <- reshape(tmp, direction = "wide", trans_wide <- reshape(dat1, direction = "wide",
idvar = c("eventid", "artwork"), idvar = c("eventid", "artwork"),
timevar = "event", drop = c("fileid", "popup", "card") timevar = "event", drop = c("fileid", "popup", "card")
) )
@ -100,14 +100,14 @@ trans_wide$eventid <- NULL
rownames(trans_wide) <- NULL rownames(trans_wide) <- NULL
trans_wide$duration <- trans_wide$time_ms.stop - trans_wide$time_ms.start trans_wide$duration <- trans_wide$time_ms.stop - trans_wide$time_ms.start
#trans_wide$duration2 <- trans_wide$date.stop - trans_wide$date.start #trans_wide$duration <- trans_wide$date.stop - trans_wide$date.start
# only seconds - not fine grained enough # only seconds - not fine grained enough
trans_wide$distance <- apply( trans_wide$distance <- apply(
trans_wide[, c("x.start", "y.start", "x.stop", "y.stop")], 1, trans_wide[, c("x.start", "y.start", "x.stop", "y.stop")], 1,
function(x) dist(matrix(x, 2, 2, byrow = TRUE))) function(x) dist(matrix(x, 2, 2, byrow = TRUE)))
trans_wide$rotationDegree <- trans_wide$rotation.stop - trans_wide$rotationDegree <- trans_wide$rotation.stop -
trans_wide$rotation.start trans_wide$rotation.start
trans_wide$scaleSize <- trans_wide$scale.stop - trans_wide$scale.start trans_wide$scaleSize <- trans_wide$scale.stop / trans_wide$scale.start
trans_wide$trace <- NA trans_wide$trace <- NA
trans_wide$card <- NA trans_wide$card <- NA
@ -115,7 +115,7 @@ trans_wide$popup <- NA
dat_trans <- trans_wide[trans_wide$distance != 0 & dat_trans <- trans_wide[trans_wide$distance != 0 &
trans_wide$rotationDegree != 0 & trans_wide$rotationDegree != 0 &
trans_wide$scaleSize != 0, trans_wide$scaleSize != 1,
c("event", "artwork", "trace", "date.start", "date.stop", c("event", "artwork", "trace", "date.start", "date.stop",
"time_ms.start", "time_ms.stop", "duration", "time_ms.start", "time_ms.stop", "duration",
"card", "popup", "card", "popup",
@ -125,7 +125,7 @@ dat_trans <- trans_wide[trans_wide$distance != 0 &
"rotationDegree")] "rotationDegree")]
# removes almost 2/3 of the data (for small data set) # removes almost 2/3 of the data (for small data set)
rm(tmp, id_rm_stop, id_stop, trans_wide, num_start, num_stop) rm(id_rm_stop, id_stop, trans_wide, num_start, num_stop)
summary(dat_trans) summary(dat_trans)
@ -138,56 +138,53 @@ plot(time_ms.stop ~ time_ms.start, dat_trans,
plot(date.stop ~ date.start, dat_trans[1:1000,], type = "b") plot(date.stop ~ date.start, dat_trans[1:1000,], type = "b")
# TODO: How to handle duration < 0
# --> Replace with NA for now...
dat_trans[dat_trans$duration < 0, "duration"] <- NA
#' # Close other events #' # Close other events
tmp <- dat[!dat$event %in% c("Transform start", "Transform stop"), ] dat2 <- dat[!dat$event %in% c("Transform start", "Transform stop"), ]
tmp$x <- NULL dat2$x <- NULL
tmp$y <- NULL dat2$y <- NULL
tmp$scale <- NULL dat2$scale <- NULL
tmp$rotation <- NULL dat2$rotation <- NULL
rownames(tmp) <- NULL rownames(dat2) <- NULL
# Create event ID for closing events # Create event ID for closing events
# num_start <- diff(c(0, which(tmp$event == "Show Front"))) # num_start <- diff(c(0, which(dat2$event == "Show Front")))
# tmp$trace <- rep(seq_along(num_start), num_start) # dat2$trace <- rep(seq_along(num_start), num_start)
# head(tmp[, c("artwork", "event", "trace")], 50) # head(dat2[, c("artwork", "event", "trace")], 50)
# --> does not work because of glossar entries... can't sort by artwork # --> does not work because of glossar entries... can't sort by artwork
tmp$trace <- NA dat2$trace <- NA
last_event <- tmp$event[1] last_event <- dat2$event[1]
aws <- unique(tmp$artwork)[unique(tmp$artwork) != "glossar"] aws <- unique(dat2$artwork)[unique(dat2$artwork) != "glossar"]
# #
for (art in aws) { # select artwork for (art in aws) { # select artwork
for (i in 1:nrow(tmp)) { # go through rows for (i in 1:nrow(dat2)) { # go through rows
if (last_event == "Show Info" & tmp$artwork[i] == art) { if (last_event == "Show Info" & dat2$artwork[i] == art) {
tmp$trace[i] <- i dat2$trace[i] <- i
j <- i j <- i
} else if (last_event == "Show Front" & tmp$artwork[i] == art) { } else if (last_event == "Show Front" & dat2$artwork[i] == art) {
tmp$trace[i] <- j dat2$trace[i] <- j
} else if (!(last_event %in% c("Show Info", "Show Front")) & } else if (!(last_event %in% c("Show Info", "Show Front")) &
tmp$artwork[i] == art) { dat2$artwork[i] == art) {
tmp$trace[i] <- j dat2$trace[i] <- j
} }
if (i <= nrow(tmp)) { if (i <= nrow(dat2)) {
last_event <- tmp$event[i + 1] last_event <- dat2$event[i + 1]
} }
} }
} }
head(tmp[, c("artwork", "event", "trace")], 50) head(dat2[, c("artwork", "event", "trace")], 50)
tail(tmp[, c("artwork", "event", "trace")], 50) tail(dat2[, c("artwork", "event", "trace")], 50)
# TODO: How to handle popups from glossar??? # TODO: How to handle popups from glossar???
rm(aws, i, j, last_event, art) rm(aws, i, j, last_event, art)
@ -196,13 +193,13 @@ rm(aws, i, j, last_event, art)
### Find artwork for glossar entry ### Find artwork for glossar entry
glossar_files <- unique(tmp[tmp$artwork == "glossar", "popup"]) glossar_files <- unique(dat2[dat2$artwork == "glossar", "popup"])
# load lookup table for artworks and glossar files # load lookup table for artworks and glossar files
load("../data/glossar_dict.RData") load("../data/glossar_dict.RData")
lut <- glossar_dict[glossar_dict$glossar_file %in% glossar_files, ] lut <- glossar_dict[glossar_dict$glossar_file %in% glossar_files, ]
head(tmp[, c("artwork", "event", "popup", "trace")], 20) head(dat2[, c("artwork", "event", "popup", "trace")], 20)
#df <- NULL #df <- NULL
@ -211,11 +208,11 @@ for (file in lut$glossar_file) {
artwork_list <- unlist(lut[lut$glossar_file == file, "artwork"]) artwork_list <- unlist(lut[lut$glossar_file == file, "artwork"])
for (i in seq_len(nrow(tmp))) { for (i in seq_len(nrow(dat2))) {
if (tmp$event[i] == "Show Info") { if (dat2$event[i] == "Show Info") {
current_artwork <- tmp[i, "artwork"] current_artwork <- dat2[i, "artwork"]
j <- i j <- i
k <- i k <- i
@ -225,25 +222,25 @@ for (file in lut$glossar_file) {
} }
if (tmp$event[i] == "Show Front" & tmp$artwork[i] == current_artwork) { if (dat2$event[i] == "Show Front" & dat2$artwork[i] == current_artwork) {
# make sure artwork has not been closed, yet! # make sure artwork has not been closed, yet!
k <- i k <- i
} }
if (tmp$artwork[i] == "glossar" & if (dat2$artwork[i] == "glossar" &
(current_artwork %in% artwork_list) & (current_artwork %in% artwork_list) &
tmp$popup[i] == file & (j-k == 0)) { dat2$popup[i] == file & (j-k == 0)) {
#df <- rbind(df, data.frame(file, current_artwork, i, j)) #df <- rbind(df, data.frame(file, current_artwork, i, j))
tmp[i, "trace"] <- tmp[j, "trace"] dat2[i, "trace"] <- dat2[j, "trace"]
} }
} }
} }
# dim(tmp[is.na(tmp$trace), ]) # dim(dat2[is.na(dat2$trace), ])
# --> finds about half of the glossar entries for the small data set... # --> finds about half of the glossar entries for the small data set...
# tmp[apply(df[, c("j", "i")], 1, c), c("artwork", "event", "popup", "trace")] # dat2[apply(df[, c("j", "i")], 1, c), c("artwork", "event", "popup", "trace")]
# REMEMBER: It can never bo 100% correct, since it is always possible that # REMEMBER: It can never bo 100% correct, since it is always possible that
# several cards are open and that they link to the same glossar entry # several cards are open and that they link to the same glossar entry
@ -261,28 +258,28 @@ lut[sapply(lut$artwork, length) == 1, "glossar_file"]
# #
# artwork_list <- unlist(lut[lut$glossar_file == file, "artwork"]) # artwork_list <- unlist(lut[lut$glossar_file == file, "artwork"])
# #
# for (i in seq_len(nrow(tmp))) { # for (i in seq_len(nrow(dat2))) {
# #
# if (tmp$event[i] == "Show Info") { # if (dat2$event[i] == "Show Info") {
# #
# artworks <- NULL # artworks <- NULL
# current_artwork <- tmp[i, "artwork"] # current_artwork <- dat2[i, "artwork"]
# j <- i # j <- i
# #
# } else { # } else {
# #
# print(current_artwork) # print(current_artwork)
# artworks <- c(artworks, tmp[i, "artwork"]) # artworks <- c(artworks, dat2[i, "artwork"])
# print(artworks) # print(artworks)
# #
# } # }
# #
# # if (tmp$artwork[i] == "glossar" & # # if (dat2$artwork[i] == "glossar" &
# # (current_artwork %in% artwork_list) & # # (current_artwork %in% artwork_list) &
# # tmp$popup[i] == file) { # # dat2$popup[i] == file) {
# # # #
# # #df <- rbind(df, data.frame(file, current_artwork, i, j)) # # #df <- rbind(df, data.frame(file, current_artwork, i, j))
# # tmp[i, "trace"] <- tmp[j, "trace"] # # dat2[i, "trace"] <- dat2[j, "trace"]
# #
# # } # # }
# } # }
@ -296,20 +293,20 @@ lut[sapply(lut$artwork, length) == 1, "glossar_file"]
# TODO: For now: Exclude not matched glossar entries # TODO: For now: Exclude not matched glossar entries
df <- subset(tmp, !is.na(tmp$trace)) df <- subset(dat2, !is.na(dat2$trace))
df <- df[order(df$trace), ] df <- df[order(df$trace), ]
rownames(df) <- NULL rownames(df) <- NULL
rm(tmp, lut, current_artwork, file, glossar_dict, i, j, k, artwork_list, rm(lut, current_artwork, file, glossar_dict, i, j, k, artwork_list,
glossar_files) glossar_files)
#' ## Close flipCard #' ## Close flipCard
tmp <- subset(df, df$event %in% c("Show Info", "Show Front")) dat3 <- subset(df, df$event %in% c("Show Info", "Show Front"))
tmp$event <- ifelse(tmp$event == "Show Info", "start", "stop") dat3$event <- ifelse(dat3$event == "Show Info", "start", "stop")
flipCard_wide <- reshape(tmp, direction = "wide", flipCard_wide <- reshape(dat3, direction = "wide",
idvar = c("trace", "artwork"), idvar = c("trace", "artwork"),
timevar = "event", timevar = "event",
drop = c("fileid", "popup", "card")) drop = c("fileid", "popup", "card"))
@ -317,10 +314,6 @@ flipCard_wide$event <- "flipCard"
flipCard_wide$duration <- flipCard_wide$time_ms.stop - flipCard_wide$duration <- flipCard_wide$time_ms.stop -
flipCard_wide$time_ms.start flipCard_wide$time_ms.start
# TODO: How to handle duration < 0
# --> Replace with NA for now...
flipCard_wide$duration <- ifelse(flipCard_wide$duration < 0,
NA, flipCard_wide$duration)
flipCard_wide$card <- NA flipCard_wide$card <- NA
flipCard_wide$popup <- NA flipCard_wide$popup <- NA
@ -345,30 +338,26 @@ dat_flipCard <- flipCard_wide[, c("event", "artwork", "trace",
"scaleSize", "rotation.start", "scaleSize", "rotation.start",
"rotation.stop", "rotationDegree")] "rotation.stop", "rotationDegree")]
rm(tmp, flipCard_wide) rm(flipCard_wide)
#' ## Close openTopic #' ## Close openTopic
tmp <- subset(df, df$event %in% c("Artwork/OpenCard", "Artwork/CloseCard")) dat4 <- subset(df, df$event %in% c("Artwork/OpenCard", "Artwork/CloseCard"))
tmp <- tmp[order(tmp$artwork, tmp$date), ] dat4 <- dat4[order(dat4$artwork, dat4$date), ]
rownames(tmp) <- NULL rownames(dat4) <- NULL
num_start <- diff(c(0, which(tmp$event == "Artwork/CloseCard"))) num_start <- diff(c(0, which(dat4$event == "Artwork/CloseCard")))
tmp$eventid <- rep(seq_along(num_start), num_start) dat4$eventid <- rep(seq_along(num_start), num_start)
tmp$event <- ifelse(tmp$event == "Artwork/OpenCard", "start", "stop") dat4$event <- ifelse(dat4$event == "Artwork/OpenCard", "start", "stop")
openTopic_wide <- reshape(tmp, direction = "wide", openTopic_wide <- reshape(dat4, direction = "wide",
idvar = c("eventid", "trace", "artwork", "card"), idvar = c("eventid", "trace", "artwork", "card"),
timevar = "event", drop = c("fileid", "popup")) timevar = "event", drop = c("fileid", "popup"))
openTopic_wide$event <- "openTopic" openTopic_wide$event <- "openTopic"
openTopic_wide$duration <- openTopic_wide$time_ms.stop - openTopic_wide$duration <- openTopic_wide$time_ms.stop -
openTopic_wide$time_ms.start openTopic_wide$time_ms.start
openTopic_wide$duration <- ifelse(openTopic_wide$duration < 0,
NA, openTopic_wide$duration)
# TODO: How to handle duration < 0
# --> Replace with NA for now...
openTopic_wide$popup <- NA openTopic_wide$popup <- NA
openTopic_wide$x.start <- NA openTopic_wide$x.start <- NA
@ -393,23 +382,23 @@ dat_openTopic <- openTopic_wide[, c("event", "artwork", "trace",
"rotation.stop", "rotationDegree")] "rotation.stop", "rotationDegree")]
# TODO: card should have a unique identifier for each artwork # TODO: card should have a unique identifier for each artwork
rm(openTopic_wide, num_start, tmp) rm(openTopic_wide, num_start)
#' ## close openPopup #' ## close openPopup
tmp <- subset(df, df$event %in% c("ShowPopup", "HidePopup")) dat5 <- subset(df, df$event %in% c("ShowPopup", "HidePopup"))
tmp <- tmp[order(tmp$artwork, tmp$date), ] dat5 <- dat5[order(dat5$artwork, dat5$date), ]
rownames(tmp) <- NULL rownames(dat5) <- NULL
num_start <- diff(c(0, which(tmp$event == "HidePopup"))) num_start <- diff(c(0, which(dat5$event == "HidePopup")))
# last event is "ShowPopup"! Needs to be fixed # last event is "ShowPopup"! Needs to be fixed
num_start <- c(num_start, 1) num_start <- c(num_start, 1)
# TODO: Needs to be caught in a function # TODO: Needs to be caught in a function
tmp$eventid <- rep(seq_along(num_start), num_start) dat5$eventid <- rep(seq_along(num_start), num_start)
tmp$event <- ifelse(tmp$event == "ShowPopup", "start", "stop") dat5$event <- ifelse(dat5$event == "ShowPopup", "start", "stop")
openPopup_wide <- reshape(tmp, direction = "wide", openPopup_wide <- reshape(dat5, direction = "wide",
idvar = c("eventid", "trace", "artwork", "popup"), idvar = c("eventid", "trace", "artwork", "popup"),
timevar = "event", drop = c("fileid", "card")) timevar = "event", drop = c("fileid", "card"))
# there is a pathological entry which gets deleted... # there is a pathological entry which gets deleted...
@ -423,10 +412,6 @@ openPopup_wide$event <- "openPopup"
openPopup_wide$duration <- openPopup_wide$time_ms.stop - openPopup_wide$duration <- openPopup_wide$time_ms.stop -
openPopup_wide$time_ms.start openPopup_wide$time_ms.start
openPopup_wide$duration <- ifelse(openPopup_wide$duration < 0,
NA, openPopup_wide$duration)
# TODO: How to handle duration < 0
# --> Replace with NA for now...
openPopup_wide$card <- NA openPopup_wide$card <- NA
openPopup_wide$x.start <- NA openPopup_wide$x.start <- NA
@ -449,7 +434,7 @@ dat_openPopup <- openPopup_wide[, c("event", "artwork", "trace",
"distance", "scale.start", "scale.stop", "distance", "scale.start", "scale.stop",
"scaleSize", "rotation.start", "scaleSize", "rotation.start",
"rotation.stop", "rotationDegree")] "rotation.stop", "rotationDegree")]
rm(num_start, openPopup_wide, tmp) rm(num_start, openPopup_wide)
# Merge all # Merge all
@ -609,6 +594,12 @@ rownames(dat_all) <- NULL
# Make `trace` a consecutive number # Make `trace` a consecutive number
dat_all$trace <- as.numeric(as.factor(dat_all$trace)) dat_all$trace <- as.numeric(as.factor(dat_all$trace))
# TODO: How to handle duration < 0
# --> Replace with NA for now...
dat_all$duration <- ifelse(dat_all$duration < 0, NA, dat_all$duration)
#' # Export data #' # Export data
write.table(dat_all, "../data/event_logfiles.csv", write.table(dat_all, "../data/event_logfiles.csv",
@ -630,3 +621,6 @@ write.table(dat_all, "../data/event_logfiles.csv",
# TODO: Write function for closing events # TODO: Write function for closing events