From 2ce3daa0629382e203a4f9067fd24f06608d6ef9 Mon Sep 17 00:00:00 2001
From: Mike Holmes <mike.holmes@linaro.org>
Date: Wed, 14 Jun 2017 12:48:08 -0400
Subject: plot raw percentage

---
 Signed_off_heatmaps.R | 89 +++++++++++++++++++++++++++++++++++++++++++--------
 1 file changed, 75 insertions(+), 14 deletions(-)

diff --git a/Signed_off_heatmaps.R b/Signed_off_heatmaps.R
index c8c635d..523ae7f 100644
--- a/Signed_off_heatmaps.R
+++ b/Signed_off_heatmaps.R
@@ -78,6 +78,22 @@ get_team <- function (df){
   return (unique_people)
 }
 
+get_team_sum <- function (df){
+  sum <- length(df$contribution$tag)
+  return (sum)
+}
+
+get_patch_percentage <- function (row, sum_allteam){
+  percentage = (row$sum / sum_allteam) * 100
+  return (percentage)
+}
+
+get_people_percentage <- function (row, sum_all_people){
+  num.unique.people <- length(unique(row$contributions$person))
+  percentage = (num.unique.people / sum_all_people) * 100
+  return (percentage)
+}
+
 get_team_size <- function (df){
   unique_people <- unique(df$contributions$person)
   number_of_people <- length(unique_people)
@@ -103,7 +119,6 @@ if (id[2] == '') {
   stop()
 }
 
-
 home <- getwd()
 print(paste("Outputdir = ", home))
 user_password <- paste(id[1], id[2], sep=":")
@@ -154,6 +169,16 @@ df$tested <- apply(df,1, get_tested)
 df$reported<- apply(df,1, get_reported)
 df$team_size<- apply(df,1, get_team_size)
 
+df$sum_patches<- apply(df,1, get_team_sum)
+
+#percentage of patches
+sum_allteam <- sum(df$sum_patches)
+df$percentage_patches<- apply(df,1, get_patch_percentage, sum_allteam=sum_allteam)
+
+#percentage of people
+sum_all_people <- length(unique.persons)
+df$percentage_people<- apply(df,1, get_people_percentage, sum_all_people=sum_all_people)
+
 #normalise by the number of contributors
 df$signed <- df$signed / df$team_size
 df$acked <- df$acked / df$team_size
@@ -161,10 +186,10 @@ df$reviewed <- df$reviewed / df$team_size
 df$tested <- df$tested / df$team_size
 df$reported<- df$reported/ df$team_size
 
-#cut out what we want to plot
+#cut out what we want to plot whick is Mainter type sign offs
 m <- as.matrix(df[,c("signed","acked","reviewed")])
 
-png(file=paste(Sys.Date(),"Linaro_team_maintainer_roll.png", sep = "_"), title = paste(Sys.Date(),"team vs maintainer",sep = " "))
+png(file=paste(Sys.Date(),"Linaro_maintainer_overview.png", sep = "_"), title = paste(Sys.Date(),"team vs maintainer",sep = " "))
 op <- par(mar=c(15,4,4,2))
 
 inverse.m <- t(m)
@@ -178,10 +203,11 @@ barplot(inverse.m, las=2,
         )
 dev.off()
 
-#cut out what we want to plot
+#cut out what we want to plot which is the non maintainer type work
 m <- as.matrix(df[,c("tested", "reported")])
 
-png(file=paste(Sys.Date(),"Linaro_team_support_roll.png", sep = "_"), title = paste(Sys.Date(),"team vs. git stats",sep = " "))
+
+png(file=paste(Sys.Date(),"Linaro_support_overview.png", sep = "_"), title = paste(Sys.Date(),"team vs. git stats",sep = " "))
 op <- par(mar=c(15,4,4,2))
 inverse.m <- t(m)
 
@@ -194,6 +220,44 @@ barplot(inverse.m, las=2,
 )
 dev.off()
 
+
+#cut out what we want to plot
+percentage_patches <- as.matrix(df[,"percentage_patches"])
+row.names(percentage_patches) <- row.names(df)
+
+png(file=paste(Sys.Date(),"Linaro_percentage_signoffs.png", sep = "_"), title = paste(Sys.Date(),"team vs. git stats",sep = " "))
+op <- par(mar=c(15,4,4,2))
+inverse.percentage_patches <- t(percentage_patches)
+percentage_patches
+barplot(inverse.percentage_patches, las=2,  
+        main="Team conribution as % of Linaro", 
+        ylab = "%", 
+        col =colours, 
+        legend.text=TRUE, 
+        args.legend=list(x='topleft')
+)
+
+dev.off()
+
+#cut out what we want to plot
+percentage_people <- as.matrix(df[,"percentage_people"])
+row.names(percentage_people) <- row.names(df)
+
+png(file=paste(Sys.Date(),"Linaro_percentage_of_authors.png", sep = "_"), title = paste(Sys.Date(),"team vs. git stats",sep = " "))
+op <- par(mar=c(15,4,4,2))
+inverse.percentage_people <- t(percentage_people)
+percentage_people
+barplot(inverse.percentage_people, las=2,  
+        main="Team size as % of Linaro", 
+        ylab = "%", 
+        col =colours, 
+        legend.text=TRUE, 
+        args.legend=list(x='topleft')
+)
+
+dev.off()
+
+
 #a bar plot showing each teams contribution to a tag type
 for (title in unique.tags) {
   png(file=paste(Sys.Date(),"Linaro_team",title,"git.png", sep = "_"), title = paste(Sys.Date(),"team vs. ",title,"git stats",sep = " "))
@@ -203,9 +267,6 @@ for (title in unique.tags) {
   dev.off()
 }
 
-
-
-
 #Stats by team
 setwd(home)
 dir.create("teams")
@@ -224,8 +285,6 @@ for (team in row.names(df)) {
   colnames(all_people) <- lunique.tags
   all_people[] <- 0L
   
-  print(team)
-
   tab <- as.data.frame( table(contributions))
 
   for (r in 1:nrow(tab)) {
@@ -234,7 +293,7 @@ for (team in row.names(df)) {
     Freq <- (tab[r,"Freq"])
     all_people[person,tag] <- all_people[person,tag] + Freq
   }
-  
+
   barplot(
     main = paste("Non author contributions", team, sep = " "),
     t(all_people),
@@ -276,12 +335,11 @@ for (team in row.names(df)) {
   }
 }
 
-#sort by 
-all_people[order(all_people[,1]),]
 
+inverse.all_people <- t(all_people)
 barplot(
   main = "Maintainers",
-  t(all_people),
+  inverse.all_people,
   las = 2,
   bty='L',
   col = colours,
@@ -345,3 +403,6 @@ for (r in 1:nrow(all_people)) {
 #all_patch_data <- sapply(df$id,get_patches)
 #str(all_patch_data)
 
+
+#always return to the home
+setwd(home)
-- 
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