diff --git a/scripts/plotting/scratch_plots/lineage_dist_dm_om_combined_PS.R b/scripts/plotting/lineage_dist_dm_om_combined_PS.R
similarity index 100%
rename from scripts/plotting/scratch_plots/lineage_dist_dm_om_combined_PS.R
rename to scripts/plotting/lineage_dist_dm_om_combined_PS.R
diff --git a/scripts/plotting/scratch_plots/lineage_dist_dm_om_PS.R b/scripts/plotting/scratch_plots/lineage_dist_dm_om_PS.R
new file mode 100644
index 0000000..37e8cbe
--- /dev/null
+++ b/scripts/plotting/scratch_plots/lineage_dist_dm_om_PS.R
@@ -0,0 +1,360 @@
+#!/usr/bin/env Rscript  
+#########################################################
+# TASK: Lineage dist plots: ggridges
+
+# Output: 2 SVGs for PS stability
+
+# 1) all muts
+# 2) dr_muts
+
+##########################################################
+# 				Installing and loading required packages 			 
+##########################################################
+getwd()
+setwd("~/git/LSHTM_analysis/scripts/plotting/")
+getwd()
+
+source("Header_TT.R")
+library(ggridges)
+source("combining_dfs_plotting.R")
+# PS combined: 
+# 1) merged_df2
+# 2) merged_df2_comp
+# 3) merged_df3
+# 4) merged_df3_comp
+
+# LIG combined: 
+# 5) merged_df2_lig
+# 6) merged_df2_comp_lig
+# 7) merged_df3_lig
+# 8) merged_df3_comp_lig
+
+# 9) my_df_u
+# 10) my_df_u_lig
+
+cat("Directories imported:"
+    , "\n===================="
+    , "\ndatadir:", datadir
+    , "\nindir:", indir
+    , "\noutdir:", outdir
+    , "\nplotdir:", plotdir)
+
+cat("Variables imported:"
+    , "\n====================="
+    , "\ndrug:", drug
+    , "\ngene:", gene
+    , "\ngene_match:", gene_match
+    , "\nAngstrom symbol:", angstroms_symbol
+    , "\nNo. of duplicated muts:", dup_muts_nu
+    , "\nNA count for ORs:", na_count
+    , "\nNA count in df2:", na_count_df2
+    , "\nNA count in df3:", na_count_df3
+    , "\ndr_muts_col:", dr_muts_col
+    , "\nother_muts_col:", other_muts_col
+    , "\ndrtype_col:", resistance_col)
+
+cat("cols imported:"
+    , mcsm_red2, mcsm_red1, mcsm_mid, mcsm_blue1, mcsm_blue2)
+
+#=======
+# output
+#=======
+lineage_dist_combined_dm_om = "lineage_dist_combined_dm_om_PS.svg"
+plot_lineage_dist_combined_dm_om  =  paste0(plotdir,"/", lineage_dist_combined_dm_om)
+#========================================================================
+
+###########################
+# Data for plots
+# you need merged_df2 or merged_df2_comp
+# since this is one-many relationship 
+# i.e the same SNP can belong to multiple lineages
+# using the _comp dataset means
+# we lose some muts and at this level, we should use
+# as much info as available, hence use df with NA
+###########################
+# REASSIGNMENT
+my_df  = merged_df2
+
+# delete variables not required
+rm(my_df_u, merged_df2, merged_df2_comp, merged_df3, merged_df3_comp)
+
+# quick checks
+colnames(my_df)
+str(my_df)
+
+table(my_df$mutation_info)
+
+#===================
+# Data for plots
+#===================
+table(my_df$lineage); str(my_df$lineage)
+
+# select lineages 1-4
+sel_lineages = c("lineage1"
+                 , "lineage2"
+                 , "lineage3"
+                 , "lineage4")
+                 #, "lineage5"
+                 #, "lineage6"
+                 #, "lineage7")
+
+# works nicely with facet wrap using labeller, but not otherwise
+#my_labels = c('Lineage 1'
+#              , 'Lineage 2'
+#              , 'Lineage 3'
+#              , 'Lineage 4')
+#              #, 'Lineage 5'
+#              #, 'Lineage 6'
+#              #, 'Lineage 7')
+
+#names(my_labels) = c('lineage1'
+#                     , 'lineage2'
+#                     , 'lineage3'
+#                     , 'lineage4')
+#                     #, 'lineage5'
+#                     #, 'lineage6'
+#                     #, 'lineage7')
+
+#==========================
+# subset selected lineages
+#==========================
+df_lin = subset(my_df, subset = lineage %in% sel_lineages)
+table(df_lin$lineage)
+
+#{RESULT: Total number of samples for lineage}
+sum(table(df_lin$lineage)) 
+
+#{RESULT: No of samples within lineage}
+table(df_lin$lineage) 
+
+#{Result: No. of unique mutations the 4 lineages contribute to}
+length(unique(df_lin$mutationinformation)) 
+
+u2 = unique(my_df$mutationinformation)
+u = unique(df_lin$mutationinformation)
+
+#{Result:Muts not present within selected lineages}
+check = u2[!u2%in%u]; print(check) 
+
+# workaround to make labels appear nicely for in otherwise cases
+#==================
+# lineage: labels
+# from "plyr"
+#==================
+table(df_lin$lineage)
+
+df_lin$lineage_labels = mapvalues(df_lin$lineage
+                                  , from = c("lineage1","lineage2", "lineage3", "lineage4")
+                                  , to = c("Lineage 1", "Lineage 2", "Lineage 3", "Lineage 4"))
+table(df_lin$lineage_labels)
+
+table(df_lin$lineage_labels) == table(df_lin$lineage)
+                              
+#========================
+# mutation_info: labels
+#========================
+table(df_lin$mutation_info)
+
+df_lin$mutation_info_labels = ifelse(df_lin$mutation_info == dr_muts_col, "DM", "OM")
+table(df_lin$mutation_info_labels)
+
+table(df_lin$mutation_info) == table(df_lin$mutation_info_labels)
+
+#=======================
+# subset dr muts only
+#=======================
+my_df_dr = subset(df_lin, mutation_info == dr_muts_col) 
+table(my_df_dr$mutation_info)
+table(my_df_dr$lineage)
+
+#=========================
+# subset other muts only
+#=========================
+my_df_other = subset(df_lin, mutation_info == other_muts_col) 
+table(my_df_other$mutation_info)
+table(my_df_other$lineage)
+
+########################################################################
+#               end of data extraction and cleaning for plots          #
+########################################################################
+
+#==========================
+# Distribution plots
+#============================
+
+#%%%%%%%%%%%%%%%%%%%%%%%%%
+# REASSIGNMENT
+df <- df_lin
+#%%%%%%%%%%%%%%%%%%%%%%%%%
+
+rm(df_lin)
+
+#******************
+# generate distribution plot of lineages
+#******************
+# 2 : ggridges (good!)
+my_ats = 15 # axis text size
+my_als = 20 # axis label size
+n_colours = length(unique(df$duet_scaled))
+my_palette <- colorRampPalette(c(mcsm_red2, mcsm_red1, mcsm_mid, mcsm_blue1, mcsm_blue2))(n = n_colours+1)
+
+#=======================================
+# Plot 1: lineage dist: geom_density_ridges_gradient (allows aesthetics to vary along ridgeline, no alpha setting!)
+# else same as geom_density_ridges)
+# x = duet_scaled
+# y = lineage_labels
+# fill = duet_scaled 
+# NO FACET (nf)
+#=======================================
+# output individual svg
+#plot_lineage_dist_duet_nf  =  paste0(plotdir,"/", "lineage_dist_duet_nf.svg")
+#plot_lineage_dist_duet_nf
+#svg(plot_lineage_dist_duet_nf)
+
+p1 = ggplot(df, aes(x = duet_scaled
+                    , y = lineage_labels))+
+  geom_density_ridges_gradient(aes(fill = ..x..)
+                               #, jittered_points = TRUE
+                               , scale = 3
+                               , size = 0.3 ) +
+  coord_cartesian( xlim = c(-1, 1)) +
+  scale_fill_gradientn(colours = my_palette, name = "DUET") + 
+  theme(axis.text.x = element_text(size = my_ats
+                                   , angle = 90
+                                   , hjust = 1
+                                   , vjust = 0.4)
+        
+        , axis.text.y = element_text(size = my_ats)
+        , axis.title.x = element_text(size = my_ats)
+        , axis.title.y = element_blank()
+        , axis.ticks.y = element_blank()
+        , plot.title = element_blank()
+        , strip.text = element_text(size = my_als)
+        , legend.text = element_text(size = my_als-10)
+        , legend.title = element_text(size = my_als-3)
+        , legend.position = c(0.8, 0.8)) +
+        #, legend.direction = "horizontal")+
+        #, legend.position = "top", )+
+  labs(x = "DUET") 
+
+p1
+
+#p1_copy = p1 + guides(fill = guide_colourbar(label = FALSE))
+#p1_copy=  p1_copy + guides(size=guide_legend("Source", override.aes=list(shape=15, size = 10)))
+
+#p1_copy
+#=======================================
+# Plot 2: lineage dist: geom_density_ridges, allows alpha to be set
+# x = duet_scaled
+# y = lineage_labels
+# fill = mutation_info
+# NO FACET
+#=======================================
+# output svg
+#plot_lineage_dist_duet_dm_om  =  paste0(plotdir,"/", "lineage_dist_duet_dm_om.svg")
+#plot_lineage_dist_duet_dm_om
+#svg(plot_lineage_dist_duet_dm_om)
+
+p2 = ggplot(df, aes(x = duet_scaled
+                    , y = lineage_labels))+
+  geom_density_ridges(aes(fill = factor(mutation_info_labels))
+                      , scale = 3
+                      , size = 0.3
+                      , alpha = 0.8) +
+  coord_cartesian( xlim = c(-1, 1)) +
+  scale_fill_manual(values = c("#E69F00", "#999999")) +
+  theme(axis.text.x = element_text(size = my_ats
+                                   , angle = 90
+                                   , hjust = 1
+                                   , vjust = 0.4)
+        , axis.text.y = element_text(size = my_ats)
+        , axis.title.x = element_text(size = my_ats)
+        , axis.title.y = element_blank()
+        , axis.ticks.y = element_blank()
+        , plot.title = element_blank()
+        , strip.text = element_text(size = my_als)
+        , legend.text = element_text(size = my_als-2)
+        , legend.title = element_text(size = my_als-3)
+        , legend.position = c(0.8, 0.9)) +
+  labs(x = "DUET"
+       , fill = "Mutation class") # legend title
+
+p2
+
+########################################################################
+#==============
+# combine plot
+#===============
+plot_lineage_dist_combined_dm_om
+svg(plot_lineage_dist_combined_dm_om, width = 12, height = 6)
+
+printFile = cowplot::plot_grid(p1, p2
+                               , rel_widths = c(0.5/2, 0.5/2)
+                               , label_size = my_als+10)
+
+print(printFile)
+dev.off()
+
+
+########################################################################
+# alternate combination
+########################################################################
+#=======================
+# Plot 3: lineage dist: geom_density_ridges_gradient (allows aesthetics to vary along ridgeline, no alpha setting!)
+# else same as geom_density_ridges)
+# x = duet_scaled
+# y = duet_outcome
+# FACET (f) = lineage
+#=======================
+
+# output individual svg
+#plot_lineage_dist_duet  =  paste0(plotdir,"/", "lineage_dist_duet_f.svg")
+#plot_lineage_dist_duet
+#svg(plot_lineage_dist_duet)
+
+p3 = ggplot(df, aes(x = duet_scaled
+                    , y = duet_outcome))+ 
+  
+  geom_density_ridges_gradient(aes(fill = ..x..)
+                               , scale = 3
+                               , size = 0.3) +
+  
+  facet_wrap( ~lineage_labels
+              , scales = "free"
+              #, labeller = labeller(lineage = my_labels) # sorted by lineage_labels
+  ) +
+  coord_cartesian( xlim = c(-1, 1)) +
+  scale_fill_gradientn(colours = my_palette, name = "DUET") + 
+  theme(axis.text.x = element_text(size = my_ats
+                                   , angle = 90
+                                   , hjust = 1
+                                   , vjust = 0.4)
+        
+        , axis.text.y = element_blank()
+        , axis.title.x = element_text(size = my_ats)
+        , axis.title.y = element_blank()
+        , axis.ticks.y = element_blank()
+        , plot.title = element_blank()
+        , strip.text = element_text(size = my_als)
+        , legend.text = element_text(size = my_als-6)
+        , legend.title = element_text(size = my_als-3))+
+  labs(x = "DUET") 
+
+print(p3)
+#dev.off()
+
+#==============
+# combine plot: alt version
+#===============
+plot_lineage_dist_duet_fandnf =  paste0(plotdir,"/", "lineage_dist_duet_fandnf.svg")
+plot_lineage_dist_duet_fandnf
+svg(plot_lineage_dist_duet_fandnf, width = 12, height = 6)
+
+printFile = cowplot::plot_grid(p3, p2
+                               , rel_widths = c(0.5/2, 0.5/2)
+                               , label_size = my_als+10)
+
+print(printFile)
+dev.off()
+
+