186 lines
7.3 KiB
R
186 lines
7.3 KiB
R
# setwd("C:/Users/nwickelmaier/Nextcloud/Documents/MDS/2023ss/60100_master_thesis/code")
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# Read data
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dat <- read.table("results/haum/event_logfiles_2024-01-02_19-44-50.csv",
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colClasses = c("character", "character", "POSIXct",
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"POSIXct", "character", "integer",
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"numeric", "character", "character",
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rep("numeric", 3), "character",
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"character", rep("numeric", 11),
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"character", "character"),
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sep = ";", header = TRUE)
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dat$event <- factor(dat$event, levels = c("move", "flipCard", "openTopic",
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"openPopup"))
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dat$weekdays <- factor(weekdays(dat$date.start),
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levels = c("Montag", "Dienstag", "Mittwoch",
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"Donnerstag", "Freitag", "Samstag",
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"Sonntag"),
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labels = c("Monday", "Tuesday", "Wednesday",
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"Thursday", "Friday", "Saturday",
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"Sunday"))
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# Select data pre Corona
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dat <- dat[as.Date(dat$date.start) < "2020-03-13", ]
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dat <- dat[dat["path"] != 81621, ]
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table(dat$event)
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proportions(table(dat$event))
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# Investigate paths (will separate items and give clusters of artworks!)
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length(unique(dat$path))
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datpath <- aggregate(cbind(duration, distance, scaleSize, rotationDegree) ~
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path, dat, function(x) mean(x, na.rm = TRUE), na.action = NULL)
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datpath$length <- aggregate(item ~ path, dat, length)$item
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datpath$nitems <- aggregate(item ~ path, dat, function(x)
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length(unique(x)), na.action = NULL)$item
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datpath$ntopics <- aggregate(topic ~ path, dat,
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function(x) ifelse(all(is.na(x)), NA, length(unique(na.omit(x)))),
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na.action = NULL)$topic
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datpath$vacation <- aggregate(vacation ~ path, dat,
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function(x) ifelse(all(is.na(x)), 0, 1),
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na.action = NULL)$vacation
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datpath$holiday <- aggregate(holiday ~ path, dat,
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function(x) ifelse(all(is.na(x)), 0, 1),
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na.action = NULL)$holiday
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datpath$weekend <- aggregate(weekdays ~ path, dat,
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function(x) ifelse(any(x %in% c("Saturday", "Sunday")), 1, 0),
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na.action = NULL)$weekdays
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datpath$morning <- aggregate(date.start ~ path, dat,
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function(x) ifelse(lubridate::hour(x[1]) > 13, 0, 1),
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na.action = NULL)$date.start
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# Investigate cases (= interactions per time intervall)
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length(unique(dat$case))
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datcase <- aggregate(cbind(duration, distance, scaleSize, rotationDegree) ~
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case, dat, function(x) mean(x, na.rm = TRUE), na.action = NULL)
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datcase$length <- aggregate(item ~ case, dat, length)$item
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datcase$nitems <- aggregate(item ~ case, dat, function(x)
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length(unique(x)), na.action = NULL)$item
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datcase$ntopics <- aggregate(topic ~ case, dat,
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function(x) ifelse(all(is.na(x)), NA, length(unique(na.omit(x)))),
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na.action = NULL)$topic
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datcase$vacation <- aggregate(vacation ~ case, dat,
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function(x) ifelse(all(is.na(x)), 0, 1),
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na.action = NULL)$vacation
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datcase$holiday <- aggregate(holiday ~ case, dat,
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function(x) ifelse(all(is.na(x)), 0, 1),
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na.action = NULL)$holiday
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datcase$weekend <- aggregate(weekdays ~ case, dat,
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function(x) ifelse(any(x %in% c("Saturday", "Sunday")), 1, 0),
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na.action = NULL)$weekdays
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datcase$morning <- aggregate(date.start ~ case, dat,
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function(x) ifelse(lubridate::hour(x[1]) > 13, 0, 1),
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na.action = NULL)$date.start
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# Paths with more than one case associated
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tmp <- aggregate(case ~ path, dat, function(x) length(unique(x)))
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sum(tmp$case > 1)
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table(tmp$case)
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dat$date <- as.Date(dat$date.start)
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tmp <- aggregate(date ~ path, dat, function(x) length(unique(x)))
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sum(tmp$date > 1)
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table(tmp$date)
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tmp[tmp$date > 1, ]
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for (p in tmp$path[tmp$date > 1]) {
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print(dat[dat$path == p, 3:9])
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cat("\n\n")
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}
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dat[dat$date == "2017-02-28" & dat$item == "503", ]
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# Creating event logs
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library(bupaverse)
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dat$start <- dat$date.start
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dat$complete <- dat$date.stop
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table(table(dat$start))
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# --> hmm...
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summary(aggregate(duration ~ path, dat, mean))
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alog <- activitylog(dat,
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case_id = "path",
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activity_id = "event",
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resource_id = "item",
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timestamps = c("start", "complete"))
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process_map(alog,
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type_nodes = frequency("absolute"),
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sec_nodes = frequency("relative"),
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type_edges = frequency("absolute"),
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sec_edges = frequency("relative"),
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rankdir = "LR")
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alog2 <- activitylog(dat,
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case_id = "case",
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activity_id = "event",
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resource_id = "item",
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timestamps = c("start", "complete"))
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process_map(alog2,
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type_nodes = frequency("absolute"),
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sec_nodes = frequency("relative"),
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type_edges = frequency("absolute"),
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sec_edges = frequency("relative"),
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rankdir = "LR")
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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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