From 96129ddc340712407e7c3bea172fa43f7174fae3 Mon Sep 17 00:00:00 2001
From: Tanushree Tunstall <tanu@tunstall.in>
Date: Fri, 10 Sep 2021 18:19:56 +0100
Subject: [PATCH] tidied script plotting_data.R by removing superceded code

---
 scripts/functions/plotting_data.R | 56 -------------------------------
 1 file changed, 56 deletions(-)

diff --git a/scripts/functions/plotting_data.R b/scripts/functions/plotting_data.R
index fa4e9c1..faaebca 100755
--- a/scripts/functions/plotting_data.R
+++ b/scripts/functions/plotting_data.R
@@ -31,62 +31,6 @@ dup_muts    = data.frame()
 
 cat("\nInput dimensions:", dim(df)) 
 
-#==================================
-# add foldx outcome category
-# and foldx scaled values 
-
-# This will enable to always have these variables available
-# when calling for plots
-# included this now in combine_dfs.py!!!! finallyS
-#==================================
-
-#------------------------------
-# # adding foldx scaled values
-# # scale data b/w -1 and 1
-# #------------------------------
-# n = which(colnames(df) == "ddg"); n 
-# 
-# my_min = min(df[,n]); my_min 
-# my_max = max(df[,n]); my_max 
-# 
-# df$foldx_scaled = ifelse(df[,n] < 0
-#                          , df[,n]/abs(my_min)
-#                          , df[,n]/my_max) 
-# # sanity check
-# my_min = min(df$foldx_scaled); my_min 
-# my_max = max(df$foldx_scaled); my_max
-# 
-# if (my_min == -1 && my_max == 1){
-#   cat("\nPASS: foldx ddg successfully scaled b/w -1 and 1"
-#       , "\nProceeding with assigning foldx outcome category")
-# }else{
-#   cat("\nFAIL: could not scale foldx ddg values"
-#       , "Aborting!\n")
-# }
-
-#------------------------------
-# adding foldx outcome category
-# ddg<0 = "Stabilising" (-ve)
-#------------------------------
-# c1 = table(df$ddg < 0)
-# df$foldx_outcome = ifelse(df$ddg < 0, "Stabilising", "Destabilising")
-# c2 = table(df$ddg < 0)
-# 
-# if ( all(c1 == c2) ){
-#   cat("\nPASS: foldx outcome successfully created")
-# }else{
-#   cat("\nFAIL: foldx outcome could not be created. Aborting!\n")
-#   exit()
-# }
-
-#------------------------------
-# renaming foldx column from 
-# "ddg" --> "ddg_foldx"
-#------------------------------
-
-# # change name to foldx
-# colnames(df)[n] <- "ddg_foldx"
-
 #==================================
 # extract unique mutation entries
 #==================================