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Moved plotting code for item clustering to thesis folder

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This commit is contained in:
Nora Wickelmaier 2024-03-21 17:19:47 +01:00
parent 6feea5a251
commit bdeb8fb718
1 changed files with 5 additions and 84 deletions
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89
code/07_item-clustering.R
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@ -10,12 +10,9 @@
# input: results/haum/eventlogs_pre-corona_cleaned.RData
# results/haum/pn_infos_items.csv
# output: results/haum/eventlogs_pre-corona_item-clusters.csv
# results/figures/dendrogram_items.pdf
# results/figures/clustering_items.pdf
# results/figures/clustering_artworks.pdf
# results/figures/clustering_artworks.png
# ../../thesis/figures/data/clustering_items.RData"
#
# last mod: 2024-03-08
# last mod: 2024-03-21
# setwd("C:/Users/nwickelmaier/Nextcloud/Documents/MDS/2023ss/60100_master_thesis/analysis/code")
@ -96,9 +93,6 @@ mycols <- c("#434F4F", "#78004B", "#FF6900", "#3CB4DC", "#91C86E", "Black")
cluster <- cutree(hc, k = k)
pdf("results/figures/dendrogram_items.pdf", width = 6.5, height = 5.5, pointsize = 10)
# TODO: Move code for plots to /thesis/
factoextra::fviz_dend(hc, k = k,
cex = 0.5,
k_colors = mycols,
@ -109,10 +103,6 @@ factoextra::fviz_dend(hc, k = k,
#ggtheme = ggplot2::theme_bw()
)
dev.off()
pdf("results/figures/clustering_items.pdf", width = 6.5, height = 5.5, pointsize = 10)
factoextra::fviz_cluster(list(data = df, cluster = cluster),
palette = mycols,
ellipse.type = "convex",
@ -121,8 +111,6 @@ factoextra::fviz_cluster(list(data = df, cluster = cluster),
main = "",
ggtheme = ggplot2::theme_bw())
dev.off()
aggregate(cbind(precision, generalizability, nvariants, duration, distance,
scaleSize , rotationDegree, npaths, ncases, nmoves,
nflipCard, nopenTopic, nopenPopup) ~ cluster, datitem,
@ -151,75 +139,8 @@ write.table(res,
quote = FALSE,
row.names = FALSE)
# DFGs for clusters
res$start <- res$date.start
res$complete <- res$date.stop
# Save data for plots and tables
for (clst in sort(unique(res$cluster))) {
alog <- bupaR::activitylog(res[res$cluster == clst, ],
case_id = "path",
activity_id = "event",
resource_id = "item",
timestamps = c("start", "complete"))
dfg <- processmapR::process_map(alog,
type_nodes = processmapR::frequency("relative", color_scale = "Greys"),
sec_nodes = processmapR::frequency("absolute"),
type_edges = processmapR::frequency("relative", color_edges = "#FF6900"),
sec_edges = processmapR::frequency("absolute"),
rankdir = "LR",
render = FALSE)
processmapR::export_map(dfg,
file_name = paste0("results/processmaps/dfg_items_cluster", clst, "_R.pdf"),
file_type = "pdf",
title = paste("Cluster", clst))
}
#--------------- (3) Visualization with pictures ---------------
coor_2d <- cmdscale(dist_mat, k = 2)
items <- sprintf("%03d", as.numeric(rownames(datitem)))
pdf("results/figures/clustering_artworks.pdf", height = 8, width = 8, pointsize = 16)
#png("results/figures/clustering_artworks.png", units = "in", height = 8, width = 8, pointsize = 16, res = 300)
par(mai = c(.6,.6,.1,.1), mgp = c(2.4, 1, 0))
plot(coor_2d, type = "n", ylim = c(-3.7, 2.6), xlim = c(-5, 10.5),
xlab = "", ylab = "")
for (item in items) {
if (item == "125") {
pic <- jpeg::readJPEG(paste0("../data/haum/ContentEyevisit/eyevisit_cards_light/",
item, "/", item, ".jpg"))
} else {
pic <- png::readPNG(paste0("../data/haum/ContentEyevisit/eyevisit_cards_light/",
item, "/", item, ".png"))
}
img <- as.raster(pic[,,1:3])
x <- coor_2d[items == item, 1]
y <- coor_2d[items == item, 2]
points(x, y,
col = mycols[cluster[items == item]],
cex = 6,
pch = 15)
rasterImage(img,
xleft = x - .45,
xright = x + .45,
ybottom = y - .2,
ytop = y + .2)
}
legend("topright", paste("Cluster", 1:k), col = mycols, pch = 15, bty = "n")
dev.off()
save(hc, k, res, dist_mat, datitem, df,
file = "../../thesis/figures/data/clustering_items.RData")