Cleaned up files

This commit is contained in:
Nora Wickelmaier 2023-12-21 14:53:34 +01:00
parent 9992a94712
commit e2137dec04
3 changed files with 0 additions and 201 deletions

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digraph {
graph [layout = "dot",
outputorder = "edgesfirst",
bgcolor = "white",
rankdir = "LR"]
node [fontname = "Helvetica",
fontsize = "10",
shape = "circle",
fixedsize = "true",
width = "0.5",
style = "filled",
fillcolor = "aliceblue",
color = "gray70",
fontcolor = "gray50"]
edge [fontname = "Helvetica",
fontsize = "8",
weight = "1.5",
color = "gray80",
arrowsize = "0.5"]
"1" [label = "End", shape = "circle", style = "rounded,filled", fontcolor = "brown4", color = "brown4", tooltip = "ARTIFICIAL_END
8681", penwidth = "1.5", fixedsize = "FALSE", fontname = "Arial", fontsize = "10", fillcolor = "#FFFFFF"]
"2" [label = "Start", shape = "circle", style = "rounded,filled", fontcolor = "chartreuse4", color = "chartreuse4", tooltip = "ARTIFICIAL_START
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"3" [label = "flipCard
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3457", penwidth = "1.5", fixedsize = "FALSE", fontname = "Arial", fontsize = "10", fillcolor = "#FFF7FB"]
"4" [label = "move
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}

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# setwd("C:/Users/nwickelmaier/Nextcloud/Documents/MDS/2023ss/60100_master_thesis/code")
dat <- as.data.frame(do.call(rbind, XML::xmlToList("../museums/haum/trans.xml")))
dat$a <- as.numeric(dat$a)
dat$b <- as.numeric(dat$b)
dat$c <- as.numeric(dat$c)
dat$d <- as.numeric(dat$d)
dat$tx <- as.numeric(dat$tx)
dat$ty <- as.numeric(dat$ty)
dat$idx <- sprintf("%03d", as.numeric(dat$idx))
# --> artwork names are different from names in data set ???
plot(ty ~ tx, dat, xlim = c(0, 3840), ylim = c(0, 2160))
# read log data
datlogs <- read.table("results/haum/event_logfiles_metadata_2023-09-23_01-31-30.csv",
sep = ";", header = TRUE)
datlogs$date <- as.Date(datlogs$date)
datlogs$date.start <- as.POSIXct(datlogs$date.start)
datlogs$date.stop <- as.POSIXct(datlogs$date.stop)
datlogs$artwork <- sprintf("%03d", datlogs$artwork)
datmove <- aggregate(cbind(duration, scaleSize, rotationDegree, x.start,
y.start, x.stop, y.stop) ~ artwork, datlogs,
mean)
plot(y.start ~ x.start, datmove, xlab = "x", ylab = "y",
xlim = c(0, 3840), ylim = c(0, 2160))
points(y.stop ~ x.stop, datmove, xlim = c(0, 3840), ylim = c(0, 2160), col = "blue")
points(ty ~ tx, dat, xlim = c(0, 3840), ylim = c(0, 2160), col = "red")
legend("topleft", c("start", "stop", "trans"), col = c("black", "blue", "red"), pch = 21)
# --> does not seem to be a good way to compare *if* trans values are valid

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# setwd("C:/Users/nwickelmaier/Nextcloud/Documents/MDS/2023ss/60100_master_thesis/code")
library(lubridate)
dat <- read.table("../data/haum/rawdata_logfiles.csv", header = TRUE, sep = ";")
# dat$event <- factor(dat$event, levels = c("Start Application",
# "Show Application",
# "Transform start",
# "Transform stop",
# "Show Info",
# "Show Front",
# "Artwork/OpenCard",
# "Artwork/CloseCard",
# "ShowPopup", "HidePopup"))
#
dat$date <- as.POSIXct(dat$date) # create date object
dat <- dat[order(dat$date), ]
rownames(dat) <- NULL
str(dat)
head(dat)
#' Log files between December 2016 and December 2018
range(dat$date)
#' Number of log files per year
table(year(dat$date))
#' Number of events total and per year
table(dat$event)
# Artwork/CloseCard Artwork/OpenCard
# 80026 92588
# HidePopup Show Application
# 59932 3179
# Show Front Show Info
# 106945 108113
# ShowPopup Start Application
# 60350 3210
# Transform start Transform stop
# 3219109 2966724
# --> more "openups" than "closes" (not surprisingly)
table(dat$event, year(dat$date))
#' Number of log files per week day
table(weekdays(dat$date))
#' Anzahl der Tage
length(unique(as.Date(dat$date)))
#' Which artworks are looked at most often
table(dat$artwork)
lattice::barchart(table(dat$artwork))
#' ## Corona Gaps
table(diff(as.Date(dat$date)))
dat[diff(as.Date(dat$date)) > 50, ]
#' ## Plots from Visualization Tool
dat16 <- dat[year(dat$date) == 2016, ]
counts <- table(as.Date(dat16$date), dat16$event)
lattice::barchart(counts, auto.key = TRUE)
start_events <- c("Transform start", "Show Info", "ShowPopup", "Artwork/OpenCard")
counts <- table(as.Date(dat16$date[dat16$event %in% start_events]),
dat16$event[dat16$event %in% start_events])
counts
lattice::barchart(counts, auto.key = TRUE)
### Example for log file in order to show structure
write.table(dat[240:660, 3:12], "tmp_set.txt", quote = FALSE)
# is then edited by hand to have all possible events...
select <- c(243, 244, 245, 246, 253, 254, 255, 256, 257, 259, 260, 262,
265, 266, 267, 268, 269, 270, 271, 287, 288, 289, 294, 295,
296, 303, 304, 305, 306, 307, 318, 319, 320, 321, 322, 323,
324, 325, 326, 357, 358, 359, 360, 361, 362, 363, 408, 409,
410, 411, 412, 413, 414, 415, 416, 417, 418, 439, 440, 441,
516, 518, 519, 587, 588, 589, 590, 591, 592, 593, 594, 595,
652, 653, 654, 655, 656, 657)
writeLines(dat[select, "logs"], "tmp_set_logs.txt")
tab <- table(diff(dat$date)) # uninformative on raw log data!
plot(tab[tab > 2000])