Finally added old descriptives stuff; needed the plots
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@ -10,6 +10,7 @@
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# (3.5) Topics
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#
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# input: results/haum/event_logfiles_2024-02-21_16-07-33.csv
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# results/haum/raw_logfiles_2024-02-21_16-07-33.csv
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# output:
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#
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# last mod: 2024-03-13
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@ -18,6 +19,9 @@
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library(lattice)
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library(bupaverse)
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#library(mtt)
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devtools::load_all("../../../../../software/mtt")
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# Overall Research Question: How do museum visitors interact with the
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# artworks presented on the MTT?
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@ -74,43 +78,281 @@ lattice::dotplot(xtabs( ~ item + topic, datlogs), auto.key = TRUE)
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mat <- t(as.matrix(xtabs( ~ item + topic, datlogs)))
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mat[mat == 0] <- NA
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image(mat, axes = F, col = rainbow(100))
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heatmap(t(mat))
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datlogs$start <- datlogs$date.start
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datlogs$complete <- datlogs$date.stop
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#--------------- (2) Descriptives ---------------
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### Which item gets touched most often?
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counts_item <- table(datlogs$item)
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lattice::barchart(counts_item)
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items <- unique(datlogs$item)
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#items <- items[!items %in% c("504", "505")]
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datart <- extract_artworks(items,
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paste0(items, ".xml"),
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"../data/haum/ContentEyevisit/eyevisit_cards_light/")
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datart <- datart[order(datart$artwork), ]
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names(counts_item) <- datart$title
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pdf("results/figures/counts_item.pdf", width = 20, height = 10, pointsize = 10)
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par(mai = c(5, .6, .1, .1))
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tmp <- barplot(counts_item, las = 2, ylim = c(0, 60000),
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border = NA, col = "#434F4F")
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text(tmp, counts_item + 1000, datart$artwork)
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dev.off()
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### Which item gets touched most often first?
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datcase <- datlogs[!duplicated(datlogs$case), ]
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counts_case <- table(datcase$item)
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names(counts_case) <- datart$title
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tmp <- barplot(counts_case, las = 2, border = "white")
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text(tmp, counts_case + 100, datart$item)
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counts <- rbind(counts_item, counts_case)
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pdf("results/figures/counts_item_firsttouch.pdf",
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width = 20, height = 10, pointsize = 10)
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par(mai = c(5, .6, .1, .1))
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tmp <- barplot(counts, las = 2, border = NA, col = c("#434F4F", "#FF6900"), ylim = c(0, 65000))
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text(tmp, counts_item + counts_case + 1000, datart$artwork)
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legend("topleft", c("Total interactions", "First interactions"),
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col = c("#434F4F", "#FF6900"), pch = 15, bty = "n")
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dev.off()
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### Which teasers seem to work well?
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barplot(table(datlogs$topic), las = 2)
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### Dwell times/duration
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datagg <- aggregate(duration ~ event + item, datlogs, mean)
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datagg$ds <- datagg$duration / 1000 # in secs
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lattice::bwplot(ds ~ event, datagg)
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# without aggregation
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lattice::bwplot(duration / 1000 / 60 ~ event, datlogs)
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# in min
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set.seed(1027)
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pdf("results/figures/duration.pdf", width = 5, height = 5, pointsize = 10)
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lattice::bwplot(I(duration/1000/60) ~ event, datlogs[sample(nrow(datlogs), 100000), ],
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ylab = "Duration in min")
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dev.off()
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### Move events
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datmove <- aggregate(cbind(duration, scaleSize, rotationDegree, distance, x.start,
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y.start, x.stop, y.stop) ~ item, datlogs,
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mean)
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hist(log(datlogs$scaleSize))
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# --> better interpretable on logscale
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plot(y.start ~ x.start, datmove, pch = 16, col = "gray")
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points(y.start ~ x.start, datmove, col = "#3CB4DC", cex = datmove$scaleSize)
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plot(y.start ~ x.start, datmove, type = "n", xlab = "x", ylab = "y",
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xlim = c(0, 3840), ylim = c(0, 2160))
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with(datmove, text(x.start, y.start, item, col = "gray", cex = 1.5))
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with(datmove,
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arrows(x.start, y.start, x.stop, y.stop, length = 0.07, lwd = 2)
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)
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abline(v = c(0, 3840), h = c(0, 2160), col = "#3CB4DC", lwd = 2)
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datscale <- aggregate(scaleSize ~ item, datlogs, max)
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plot(y.start ~ x.start, datmove, pch = 16, col = "gray")
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points(y.start ~ x.start, datmove, col = "#3CB4DC", cex = datscale$scaleSize)
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plot(y.start ~ x.start, datmove, type = "n", xlab = "x", ylab = "y",
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xlim = c(0, 3840), ylim = c(0, 2160))
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#with(datmove, text(x.stop, y.stop, item))
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with(datmove, text(x.start, y.start, item))
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### Are there certain areas of the table that are touched most often?
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# heatmap
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cuts <- 100
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datlogs$x.start.cat <- cut(datlogs$x.start, cuts)
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datlogs$y.start.cat <- cut(datlogs$y.start, cuts)
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tab <- xtabs( ~ x.start.cat + y.start.cat, datlogs)
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colnames(tab) <- paste0("c", 1:cuts)
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rownames(tab) <- paste0("c", 1:cuts)
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heatmap(tab, Rowv = NA, Colv = NA)
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dattrim <- datlogs[datlogs$x.start < 3840 &
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datlogs$x.start > 0 &
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datlogs$y.start < 2160 &
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datlogs$y.start > 0 &
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datlogs$x.stop < 3840 &
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datlogs$x.stop > 0 &
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datlogs$y.stop < 2160 &
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datlogs$y.stop > 0, ]
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cuts <- 100 # 200, 100, 70, ...
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# start
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dattrim$x.start.cat <- cut(dattrim$x.start, cuts)
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dattrim$y.start.cat <- cut(dattrim$y.start, cuts)
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tab.start <- xtabs( ~ x.start.cat + y.start.cat, dattrim)
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colnames(tab.start) <- NULL
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rownames(tab.start) <- NULL
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pdf("results/figures/heatmap_start.pdf", width = 5, height = 5, pointsize = 10)
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heatmap(tab.start, Rowv = NA, Colv = NA)
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dev.off()
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# stop
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dattrim$x.stop.cat <- cut(dattrim$x.stop, cuts)
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dattrim$y.stop.cat <- cut(dattrim$y.stop, cuts)
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tab.stop <- xtabs( ~ x.stop.cat + y.stop.cat, dattrim)
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colnames(tab.stop) <- NULL
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rownames(tab.stop) <- NULL
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pdf("results/figures/heatmap_stop.pdf", width = 5, height = 5, pointsize = 10)
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heatmap(tab.stop, Rowv = NA, Colv = NA)
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dev.off()
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### How many visitors per day
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datlogs$date <- as.Date(datlogs$date.start)
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# Interactions per day
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datint <- aggregate(case ~ date, datlogs, length)
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plot(datint, type = "h")
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# Cases per day
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datcase <- aggregate(case ~ date, datlogs, function(x) length(unique(x)))
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plot(datcase, type = "h")
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# Paths per day
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datpath <- aggregate(path ~ date, datlogs, function(x) length(unique(x)))
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plot(datpath, type = "h")
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plot(path ~ date, datpath, type = "h", col = "#3CB4DC")
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points(case ~ date, datcase, type = "h")
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pdf("results/figures/cases_per_day.pdf", width = 9, height = 5, pointsize = 10)
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par(mai = c(.6, .6, .1, .1), mgp = c(2.4, 1, 0))
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plot(case ~ date, datcase, type = "h", col = "#434F4F")
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abline(v = datcase$date[datcase$date %in% c("2020-03-13", "2022-10-25")],
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col = "#FF6900", lty = 2)
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text(datcase$date[datcase$date == "2020-03-13"]+470, 80,
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"Corona gap from 2020-03-13 to 2022-10-25",
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col = "#FF6900")
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dev.off()
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### Other stuff
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library(mvbutils)
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foodweb(where = "package:mtt")
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pdf("results/figures/fun_depend_mtt.pdf", width = 8, height = 4, pointsize = 10)
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foodweb(where = "package:mtt",
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prune = c("parse_logfiles", "create_eventlogs", "extract_artworks",
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"extract_topics"),
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#expand.ybox = 1.8, #cex = .6,
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#border = TRUE,
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#boxcolor = "gray",
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color.lines = FALSE,
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lwd = 2, mai = c(0, 0, 0, 0))
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dev.off()
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## weird behavior of timeMs
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pdf("results/figures/timeMs.pdf", width = 9, height = 6, pointsize = 10)
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#par(mai = c(.6, .6, .1, .1), mgp = c(2.4, 1, 0))
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#plot(timeMs.start ~ as.factor(fileId), datlogs[1:2000,], xlab = "fileId")
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lattice::bwplot(timeMs.start ~ as.factor(fileId.start), datlogs[1:2000,], xlab = "",
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scales = list(x = list(rot = 90), y = list(rot = 90)))
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dev.off()
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## x,y-coordinates out of range
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set.seed(1522)
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pdf("results/figures/xycoord.pdf", width = 5, height = 5, pointsize = 10)
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par(mai = c(.6, .6, .1, .1), mgp = c(2.4, 1, 0))
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#par(mfrow = c(1, 2))
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plot(y.start ~ x.start, datlogs[sample(nrow(datlogs), 10000), ])
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abline(v = c(0, 3840), h = c(0, 2160), col = "#3CB4DC", lwd = 2)
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#plot(y.stop ~ x.stop, datlogs)
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#abline(v = c(0, 3840), h = c(0, 2160), col = "#3CB4DC", lwd = 2)
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legend("bottomleft", "Random sample of 10,000", bg = "white")
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legend("topleft", "4K-Display: 3840 x 2160", bg = "white")
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dev.off()
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## moves
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dat001 <- datlogs[which(datlogs$item == "001"), ]
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index <- as.numeric(as.factor(dat001$path))
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cc <- sample(colors(), 100)
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plot(y.start ~ x.start, dat001, type = "n", xlab = "x", ylab = "y",
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xlim = c(0, 3840), ylim = c(0, 2160))
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with(dat001[1:200,], arrows(x.start, y.start, x.stop, y.stop,
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length = .07, col = cc[index]))
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plot(y.start ~ x.start, dat001, xlab = "x", ylab = "y",
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xlim = c(0, 3840), ylim = c(0, 2160), pch = 16, col = "gray")
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points(y.start ~ x.start, dat001, xlab = "x", ylab = "y",
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xlim = c(0, 3840), ylim = c(0, 2160), cex = dat001$scaleSize,
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col = "blue")
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cc <- sample(colors(), 70)
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dat1 <- datlogs[!duplicated(datlogs$item), ]
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dat1 <- dat1[order(dat1$item), ]
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plot(y.start ~ x.start, dat1, type = "n", xlim = c(-100, 4500), ylim = c(-100, 2500))
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abline(h = c(0, 2160), v = c(0, 3840), col = "lightgray")
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with(dat1, points(x.start, y.start, col = cc, pch = 16))
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with(dat1, points(x.stop, y.stop, col = cc, pch = 16))
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with(dat1, arrows(x.start, y.start, x.stop, y.stop, length = .07, col = cc))
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# How many events per topic, per path, ...
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# How many popups per artwork?
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# Number of events per artwork
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tab <- xtabs( ~ artwork + event, datlogs)
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tab <- xtabs( ~ item + event, datlogs)
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addmargins(tab)
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proportions(tab, margin = "artwork")
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proportions(tab, margin = "item")
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proportions(tab, margin = "event")
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cc <- palette.colors(palette = "Okabe-Ito")[c(3,2,4,8)]
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pdf("../figures/event-dist.pdf", height = 3.375, width = 12, pointsize = 10)
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pdf("results/figures/event-dist.pdf", height = 3.375, width = 12, pointsize = 10)
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par(mai = c(.4,.4,.1,.1), mgp = c(2.4, 1, 0))
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barplot(t(proportions(tab, margin = "artwork")), las = 2, col = cc,
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barplot(t(proportions(tab, margin = "item")), las = 2, col = c("#78004B", "#3CB4DC", "#91C86E", "#FF6900"),
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legend.text = levels(datlogs$event), args.legend = list(x = "bottomleft", bg = "white"))
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dev.off()
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#barchart(proportions(tab, margin = "artwork"), las = 2)
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#barchart(proportions(tab, margin = "item"), las = 2)
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# Proportion of events
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proportions(xtabs( ~ event, datlogs))
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# Mean proportion of event per path
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colMeans(proportions(xtabs( ~ path + event, datlogs), margin = "path"))
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# Mean proportion of event per artwork
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colMeans(proportions(tab, margin = "artwork"))
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# Mean proportion of event per item
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colMeans(proportions(tab, margin = "item"))
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# Proportion of unclosed events
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@ -126,15 +368,17 @@ sum(datlogs$fileId.start != datlogs$fileId.stop, na.rm = TRUE) / nrow(datlogs)
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#--------------- (3.1) Check data quality ---------------
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datlogs$start <- datlogs$date.start
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datlogs$complete <- datlogs$date.stop
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alog <- activitylog(datlogs,
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case_id = "path",
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activity_id = "event",
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#resource_id = "case",
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resource_id = "artwork",
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resource_id = "item",
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timestamps = c("start", "complete"))
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# process_map(alog, frequency("relative"))
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map_as_pdf(alog, file = "../figures/pm_trace-event.pdf")
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process_map(alog, frequency("relative"))
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alogf <- edeaR::filter_trace_frequency(alog, percentage = 0.9)
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@ -188,7 +432,7 @@ alog080 <- activitylog(datlogs[datlogs$artwork == "080",],
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resource_id = "artwork",
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timestamps = c("start", "complete"))
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map_as_pdf(alog080, file = "../figures/pm_trace-event_080.pdf")
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process_map(alog80, frequency("relative"))
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alog087 <- activitylog(datlogs[datlogs$artwork == "087",],
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case_id = "path",
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@ -196,7 +440,7 @@ alog087 <- activitylog(datlogs[datlogs$artwork == "087",],
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resource_id = "artwork",
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timestamps = c("start", "complete"))
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map_as_pdf(alog087, file = "../figures/pm_trace-event_087.pdf")
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process_map(alog087, frequency("relative"))
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alog504 <- activitylog(datlogs[datlogs$artwork == "504",],
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case_id = "path",
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@ -204,7 +448,7 @@ alog504 <- activitylog(datlogs[datlogs$artwork == "504",],
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resource_id = "artwork",
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timestamps = c("start", "complete"))
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map_as_pdf(alog504, file = "../figures/pm_trace-event_504.pdf")
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process_map(alog504, frequency("relative"))
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#--------------- (3.3) Patterns of cases ---------------
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@ -221,7 +465,7 @@ alog <- activitylog(datlogs,
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resource_id = "path",
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timestamps = c("start", "complete"))
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map_as_pdf(alog, file = "../figures/pm_case-event.pdf")
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process_map(alog, frequency("relative"))
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alog_no_move <- alog[alog$event != "move", ]
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@ -233,7 +477,7 @@ processmapR::trace_explorer(alog_no_move[alog_no_move$path %in%
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abbreviate = T)
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dev.off()
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map_as_pdf(alog080, file = "../figures/pm_case-event_080.pdf")
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process_map(alog080, frequency("relative"))
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alog087 <- activitylog(datlogs[datlogs$artwork == "087",],
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case_id = "case",
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@ -241,7 +485,7 @@ alog087 <- activitylog(datlogs[datlogs$artwork == "087",],
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resource_id = "path",
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timestamps = c("start", "complete"))
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map_as_pdf(alog087, file = "../figures/pm_case-event_087.pdf")
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process_map(alog087, frequency("relative"))
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### Mornings and afternoons
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@ -253,7 +497,7 @@ alog <- activitylog(datlogs[datlogs$tod == "morning",],
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resource_id = "path",
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timestamps = c("start", "complete"))
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map_as_pdf(alog, file = "../figures/pm_case-event_morning.pdf")
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process_map(alog, frequency("relative"))
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alog <- activitylog(datlogs[datlogs$tod == "afternoon",],
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case_id = "case",
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@ -261,7 +505,7 @@ alog <- activitylog(datlogs[datlogs$tod == "afternoon",],
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resource_id = "path",
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timestamps = c("start", "complete"))
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map_as_pdf(alog, file = "../figures/pm_case-event_afternoon.pdf")
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process_map(alog, frequency("relative"))
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# Are the same artworks looked at?
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pdf("../figures/bp_tod.pdf", height = 3.375, width = 12, pointsize = 10)
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@ -283,7 +527,7 @@ alog <- activitylog(datlogs[datlogs$wd == "weekend",],
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resource_id = "path",
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timestamps = c("start", "complete"))
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map_as_pdf(alog, file = "../figures/pm_case-event_weekend.pdf")
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||||
process_map(alog, frequency("relative"))
|
||||
|
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alog <- activitylog(datlogs[datlogs$wd == "weekday",],
|
||||
case_id = "case",
|
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@ -291,7 +535,7 @@ alog <- activitylog(datlogs[datlogs$wd == "weekday",],
|
||||
resource_id = "path",
|
||||
timestamps = c("start", "complete"))
|
||||
|
||||
map_as_pdf(alog, file = "../figures/pm_case-event_weekday.pdf")
|
||||
process_map(alog, frequency("relative"))
|
||||
|
||||
# Are the same artworks looked at?
|
||||
pdf("../figures/bp_wd.pdf", height = 3.375, width = 12, pointsize = 10)
|
||||
@ -314,7 +558,7 @@ alog <- activitylog(datlogs[which(datlogs$wds == "school"),],
|
||||
resource_id = "path",
|
||||
timestamps = c("start", "complete"))
|
||||
|
||||
map_as_pdf(alog, file = "../figures/pm_case-event_school.pdf")
|
||||
process_map(alog, frequency("relative"))
|
||||
|
||||
alog <- activitylog(datlogs[which(datlogs$wds == "vacation"),],
|
||||
case_id = "case",
|
||||
@ -322,7 +566,7 @@ alog <- activitylog(datlogs[which(datlogs$wds == "vacation"),],
|
||||
resource_id = "path",
|
||||
timestamps = c("start", "complete"))
|
||||
|
||||
map_as_pdf(alog, file = "../figures/pm_case-event_vacation.pdf")
|
||||
process_map(alog, frequency("relative"))
|
||||
|
||||
# Are the same artworks looked at?
|
||||
pdf("../figures/bp_wds.pdf", height = 3.375, width = 12, pointsize = 10)
|
||||
@ -345,7 +589,7 @@ alog <- activitylog(datlogs[which(datlogs$corona == "pre"),],
|
||||
resource_id = "path",
|
||||
timestamps = c("start", "complete"))
|
||||
|
||||
map_as_pdf(alog, file = "../figures/pm_case-event_pre-corona.pdf")
|
||||
process_map(alog, frequency("relative"))
|
||||
|
||||
alog <- activitylog(datlogs[which(datlogs$corona == "post"),],
|
||||
case_id = "case",
|
||||
@ -353,7 +597,7 @@ alog <- activitylog(datlogs[which(datlogs$corona == "post"),],
|
||||
resource_id = "path",
|
||||
timestamps = c("start", "complete"))
|
||||
|
||||
map_as_pdf(alog, file = "../figures/pm_case-event_post-corona.pdf")
|
||||
process_map(alog, frequency("relative"))
|
||||
|
||||
# Are the same artworks looked at?
|
||||
pdf("../figures/bp_corona.pdf", height = 3.375, width = 12, pointsize = 10)
|
||||
@ -398,7 +642,7 @@ alog <- activitylog(datlogs[datlogs$artwork %in% often080, ],
|
||||
resource_id = "path",
|
||||
timestamps = c("start", "complete"))
|
||||
|
||||
map_as_pdf(alog, file = "../figures/pm_case-artwork_often080.pdf")
|
||||
process_map(alog, frequency("relative"))
|
||||
|
||||
|
||||
pdf("../figures/traceexplore_case-artwork_often080.pdf", height = 8, width = 12, pointsize = 10)
|
||||
@ -420,7 +664,7 @@ alog <- activitylog(datlogs[which(datlogs$event == "openTopic"),],
|
||||
resource_id = "path",
|
||||
timestamps = c("start", "complete"))
|
||||
|
||||
map_as_pdf(alog, file = "../figures/pm_case-topic.pdf")
|
||||
process_map(alog, frequency("relative"))
|
||||
|
||||
# Order of topics for Vermeer
|
||||
# alog080 <- activitylog(datlogs[datlogs$artwork == "080",],
|
||||
@ -429,9 +673,6 @@ map_as_pdf(alog, file = "../figures/pm_case-topic.pdf")
|
||||
# resource_id = "path",
|
||||
# timestamps = c("start", "complete"))
|
||||
#
|
||||
# map_as_pdf(alog080, file = "../figures/pm_case-topic_080.pdf")
|
||||
#
|
||||
#
|
||||
# alog080 <- activitylog(datlogs[datlogs$artwork == "080",],
|
||||
# case_id = "case",
|
||||
# activity_id = "topicFile",
|
||||
@ -446,8 +687,6 @@ map_as_pdf(alog, file = "../figures/pm_case-topic.pdf")
|
||||
# activity_id = "topic",
|
||||
# resource_id = "path",
|
||||
# timestamps = c("start", "complete"))
|
||||
#
|
||||
# map_as_pdf(alog083, file = "../figures/pm_case-topic_083.pdf")
|
||||
|
||||
# artworks that have the same topics than Vermeer
|
||||
which(rowSums(xtabs( ~ artwork + topic, datlogs[datlogs$topic %in%
|
||||
@ -464,7 +703,7 @@ for (art in c("037", "046", "062", "080", "083", "109")) {
|
||||
resource_id = "path",
|
||||
timestamps = c("start", "complete"))
|
||||
|
||||
map_as_pdf(alog, file = paste0("../figures/pm_case-topic_", art, ".pdf"))
|
||||
process_map(alog, frequency("relative"))
|
||||
}
|
||||
|
||||
|
||||
@ -518,13 +757,3 @@ plot(path ~ time, tmp, cex = 2, col = rgb(0,0,0,.3))
|
||||
lattice::barchart(path ~ time, tmp, horizontal=F)
|
||||
|
||||
|
||||
|
||||
###########################################################################
|
||||
# HELPER
|
||||
|
||||
map_as_pdf <- function(alog, file, type = frequency("relative")) {
|
||||
map <- process_map(alog, type = type)
|
||||
g <- DiagrammeR::grViz(map$x$diagram) |> DiagrammeRsvg::export_svg() |> charToRaw()
|
||||
rsvg::rsvg_pdf(g, file)
|
||||
}
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user