mtt_haum/code/specs.R

# 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])