updated lineage dist for LIG for consistency

mcsm_analysis/pyrazinamide/scripts/plotting/lineage_dist_LIG.R

@@ -75,6 +75,29 @@ if (max(my_df$Dis_lig_Ang) < 10){
 ########################################################################
 #               end of data extraction and cleaning for plots          #
 ########################################################################
+#==========================
+# Data for plot: assign as 
+# necessary
+#===========================
+
+# uncomment as necessary
+#!!!!!!!!!!!!!!!!!!!!!!!
+# REASSIGNMENT
+
+#==================
+# data for ALL muts
+#==================
+plot_df = my_df  
+my_plot_name = 'lineage_dist_PS.svg'
+#my_plot_name = 'lineage_dist_PS_comp.svg'
+
+#=======================
+# data for dr_muts ONLY
+#=======================
+#plot_df = my_df_dr 
+#my_plot_name = 'lineage_dist_dr_PS.svg'
+#my_plot_name = 'lineage_dist_dr_PS_comp.svg'
+#!!!!!!!!!!!!!!!!!!!!!!!
 
 #==========================
 # Plot: Lineage Distribution
@@ -117,10 +140,10 @@ if(sum(table(my_df$lineage)[r1]) == nrow(df_lin)) {
   print("Error!: check your numbers")
 } 
 
-#<<<<<<<<<<<<<<<<<<<<<<<<<
+#!!!!!!!!!!!!!!!!!!!!!!!!! 
 # REASSIGNMENT
 df <- df_lin
-#<<<<<<<<<<<<<<<<<<<<<<<<<
+#!!!!!!!!!!!!!!!!!!!!!!!!! 
 
 rm(df_lin)
 
@@ -131,15 +154,15 @@ rm(df_lin)
 library(plotly)
 library(ggridges)
 
-fooNames = c('Lineage 1', 'Lineage 2', 'Lineage 3', 'Lineage 4')
+my_labels = c('Lineage 1', 'Lineage 2', 'Lineage 3', 'Lineage 4')
-names(fooNames) = c('lineage1', 'lineage2', 'lineage3', 'lineage4')
+names(my_labels) = c('lineage1', 'lineage2', 'lineage3', 'lineage4')
 
 g <- ggplot(df, aes(x = ratioPredAff)) + 
   geom_density(aes(fill = Lig_outcome)
                , alpha = 0.5) + 
   facet_wrap( ~ lineage
              , scales = "free"
-             , labeller = labeller(lineage = fooNames) ) +
+             , labeller = labeller(lineage = my_labels) ) +
   coord_cartesian(xlim = c(-1, 1)
 #                  , ylim = c(0, 6)
 #                  , clip = "off"
@@ -153,15 +176,18 @@ ggplotly(g)
 my_ats = 15 # axis text size
 my_als = 20 # axis label size
 
-fooNames = c('Lineage 1', 'Lineage 2', 'Lineage 3', 'Lineage 4')
+my_labels = c('Lineage 1', 'Lineage 2', 'Lineage 3', 'Lineage 4')
-names(fooNames) = c('lineage1', 'lineage2', 'lineage3', 'lineage4')
+names(my_labels) = c('lineage1', 'lineage2', 'lineage3', 'lineage4')
 
 # set output dir for plots
 getwd()
 setwd("~/git/Data/pyrazinamide/output/plots")
 getwd()
 
-svg('lineage_dist_LIG.svg')
+# check plot name
+my_plot_name
+
+svg(my_plot_name)
 
 printFile = ggplot( df, aes(x = ratioPredAff
                           , y = Lig_outcome) ) +
@@ -172,7 +198,7 @@ printFile = ggplot( df, aes(x = ratioPredAff
   facet_wrap( ~lineage
               , scales = "free"
 #              , switch = 'x'
-              , labeller = labeller(lineage = fooNames) ) +
+              , labeller = labeller(lineage = my_labels) ) +
   coord_cartesian( xlim = c(-1, 1)
 #                  , ylim = c(0, 6)
 #                  , clip = "off"
@@ -202,12 +228,6 @@ printFile = ggplot( df, aes(x = ratioPredAff
 
 print(printFile)
 dev.off()
-
-#=!=!=!=!=!=!
-# COMMENT: When you look at all mutations, the lineage differences disappear...
-# The pattern we are interested in is possibly only for dr_mutations
-#=!=!=!=!=!=!
-
 #===================================================
 
 # COMPARING DISTRIBUTIONS