diff --git a/code/12_dfgs-case-clusters.R b/code/12_dfgs-case-clusters.R
index a5b2083..574f62c 100644
--- a/code/12_dfgs-case-clusters.R
+++ b/code/12_dfgs-case-clusters.R
@@ -1,4 +1,4 @@
-# 13_dfgs-case-clusters.R
+# 12_dfgs-case-clusters.R
 #
 # content: (1) Read data
 #          (2) Export DFGs for clusters
@@ -10,7 +10,7 @@
 #         ../../thesis/figures/dfg_cases_cluster4_R.pdf
 #         ../../thesis/figures/dfg_cases_cluster5_R.pdf
 #
-# last mod: 2024-03-22
+# last mod: 2024-03-27
 
 # setwd("C:/Users/nwickelmaier/Nextcloud/Documents/MDS/2023ss/60100_master_thesis/analysis/code")
 
@@ -53,25 +53,37 @@ for (i in 1:5) {
                              activity_id = "item",
                              resource_id = "path",
                              timestamps  = c("start", "complete"))
+  if (i %in% c(4, 5)) {
 
-  dfg <- processmapR::process_map(edeaR::filter_infrequent_flows(alog, min_n = ns[i]),
-    type_nodes = processmapR::frequency("relative", color_scale = "Greys"),
-    sec_nodes  = processmapR::frequency("absolute"),
-    type_edges = processmapR::frequency("relative", color_edges = mycols[i]),
-    sec_edges  = processmapR::frequency("absolute"),
-    rankdir    = "LR",
-    render     = FALSE)
+    dfg <- processmapR::process_map(edeaR::filter_infrequent_flows(alog, min_n = ns[i]),
+      type_nodes = processmapR::frequency("relative", color_scale = "Greys"),
+      sec_nodes  = processmapR::frequency("absolute"),
+      type_edges = processmapR::frequency("relative", color_edges = mycols[i]),
+      sec_edges  = processmapR::frequency("absolute"),
+      render     = FALSE)
+
+  } else {
+
+    dfg <- processmapR::process_map(edeaR::filter_infrequent_flows(alog, min_n = ns[i]),
+      type_nodes = processmapR::frequency("relative", color_scale = "Greys"),
+      sec_nodes  = processmapR::frequency("absolute"),
+      type_edges = processmapR::frequency("relative", color_edges = mycols[i]),
+      sec_edges  = processmapR::frequency("absolute"),
+      rankdir    = "TB",
+      render     = FALSE)
+
+  }
 
   processmapR::export_map(dfg,
-    file_name = paste0("../../thesis/figures/dfg_cases_cluster", i, "_R.pdf"),
-    file_type = "pdf",
-    title     = cl_names[i])
+    file_name = paste0("../../thesis/figures/dfg_cases_cluster_", cl_names[i], "_R.pdf"),
+    file_type = "pdf")
 }
 
 # What data is used and how many traces are unique
 
+tr_unique   <- numeric(5)
 perc_filter <- numeric(5)
-perc_unqiue <- numeric(5)
+n_cases     <- numeric(5)
 
 for (i in 1:5) {
 
@@ -81,17 +93,25 @@ for (i in 1:5) {
                              resource_id = "path",
                              timestamps  = c("start", "complete"))
 
-  perc_filter[i] <- nrow(edeaR::filter_infrequent_flows(alog, min_n = ns[i])) /
-    nrow(alog)
-
   cs <- bupaR::cases(alog)
-  infreq_tr <- names(which(table(cs$trace) == 1))
-  infreq_cs <- cs$case[cs$trace %in% infreq_tr]
 
-  perc_unqiue[i] <- nrow(alog[alog$case %in% infreq_cs, ]) / nrow(alog)
+  cs_filtered <- edeaR::filter_infrequent_flows(alog, min_n = ns[i]) |>
+    bupaR::cases()
+
+  n_cases[i] <- nrow(cs_filtered)
+  perc_filter[i] <- n_cases[i] / nrow(cs)
+
+  tr <- bupaR::traces(alog)
+
+  sum_tr <- sum(tr$absolute_frequency == 1)
+  tr_unique[i] <- sum_tr / nrow(tr)
+
+  #infreq_tr <- names(which(table(cs$trace) == 1))
+  #infreq_cs <- cs$case[cs$trace %in% infreq_tr]
+  #cs_filtered[i] <- length(infreq_cs) / length(cs$case)
 
 }
 
-save(ns, perc_filter, perc_unqiue,
+save(ns, n_cases, tr_unique, perc_filter,
      file = "../../thesis/figures/data/dfgs_case-cluster.RData")