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helper.R
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library(ggplot2)
library(plyr)
library(dplyr)
library(dtplyr)
library(reshape2)
library(hts)
library('knitr')
library(reshape2)
# Consistency check
##Entity Plot Function
fnplot<-function(data){
p<-ggplot(data=data, aes(x=Release, y=count , group=class,color=class)) +
geom_line() +
geom_point()+theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5))
return(p)
}
## Calculate Days
fn<-function(ver){
startdate <- as.Date(ver[1])
NumDays <- difftime(as.Date(ver),startdate ,units="days")
return(as.numeric(NumDays))
}
plotPerAll<-function(data){
p<-ggplot(data=data, aes(x=Release, y=variation , group=class,color=class)) +
geom_line() +
geom_point()+theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5))
return(p)
}
# Persistency line plot
persistencyPlot<-function(allEntity){
p<-ggplot(data=allEntity, aes(x=Release, y=count,group=class,color=class))+
geom_line() +
geom_point()+theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5))
return(p)
}
#Shade the area in the persistency plot
shadeAreaP<-function(p,allEntity){
rect <- data.frame(xmin=allEntity[nrow(allEntity)-1,3], xmax=allEntity[nrow(allEntity),3], ymin=-Inf, ymax=Inf)
p <-p + geom_rect(data=rect, aes(xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax),
color="white",
alpha=0.2,
inherit.aes = FALSE)
return(p)
}
shadeAreaPC<-function(p,allEntity){
rect <- data.frame(xmin=allEntity[nrow(allEntity)-1,1], xmax=allEntity[nrow(allEntity),1], ymin=-Inf, ymax=Inf)
p <-p + geom_rect(data=rect, aes(xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax),
color="white",
alpha=0.2,
inherit.aes = FALSE)
return(p)
}
persistencyMeasure<-function(allEntity){
if(allEntity[nrow(allEntity),4]>=allEntity[nrow(allEntity)-1,4])
per=1
if(allEntity[nrow(allEntity),4]<allEntity[nrow(allEntity)-1,4])
per=0
return(per)
}
persistencyMeasureC<-function(allEntity){
if(allEntity[nrow(allEntity),3]>=allEntity[nrow(allEntity)-1,3])
per=1
if(allEntity[nrow(allEntity),3]<allEntity[nrow(allEntity)-1,3])
per=0
return(per)
}
#Function to identity variation in the dataset
histPerAll<-function(entity){
entity$Persistency=1
for( i in 2:nrow(entity)){
temp=entity[,4]
if(temp[i]<temp[i-1])
entity[i,6]=0
}
return(entity)
}
histPerAllC<-function(entity){
entity$Persistency=1
for( i in 2:nrow(entity)){
temp=entity[,3]
if(temp[i]<temp[i-1])
entity[i,4]=0
}
return(entity)
}
HistPersistencyMeasure<-function(entity){
total<-length(unclass)-1
per_sum<-nrow(entity[entity$Persistency==0,])
value=(1-(per_sum/total))*100
return(value)
}
HistPersistencyMeasureC<-function(entity){
total<-length(unique(entity$Release))-1
per_sum<-nrow(entity[entity$Persistency==0,])
value=(1-(per_sum/total))*100
return(value)
}
plotEntity<-function(entity){
en=entity[1:nrow(entity)-1,]
enLm=lm(count~days,data=en)
pred=data.frame(days=entity$days,count=predict(enLm,entity))
summary(enLm)
res=mean(abs(enLm$residuals))
p<-ggplot(entity, aes(x = days, y = count)) +
geom_point() +
geom_line(data=pred,color="red")+
geom_ribbon(data=pred,aes(ymin=count-res,ymax=count+res),alpha=0.2)
return(p)
}
NormDist<-function(entity){
en=entity[1:nrow(entity)-1,]
enLm=lm(count~days,data=en)
pred=data.frame(days=entity$days,count=predict(enLm,entity))
summary(enLm)
res=mean(abs(enLm$residuals))
pr=predict(enLm,entity[nrow(entity),])
lastValue=entity[nrow(entity),]$count
ND=abs(pr-lastValue)/res
return(ND)
}
CheckND<-function(ND){
if(ND<1)
stab=1
if(ND>=1)
stab=0
return(stab)
}
# Function for normalizing property values based on entity count
# Parm: Property dataframe and exact entity count
normalize<-function(property,en){
dTproperty=property
dTproperty<-dTproperty[,order(colnames(dTproperty),decreasing=TRUE)]
d=3
t=11
for(i in 1:11){
norm= dTproperty[,d]/en[t,]$count
# round(x, digits = 0)
# print(dTproperty[,d])
dTproperty[,d]=norm
d=d+1
# print(norm)
t=t-1
}
dTproperty$diffLast=dTproperty[,3]-dTproperty[,4]
return(dTproperty)
}
#Functrion to identify correct property
identifyCorrectProperty<-function(property,en){
dTproperty=property
print(dTproperty)
d=3
t=11
countEntity=100
for(i in 1:11){
#en[t,]$count/10000
# print(countEntity)
# print(length(dTproperty[,d]))
prop=dTproperty[,d]
for(j in 1:length(prop)){
if(prop[j]>countEntity){
prop[j]=prop[j]
}
else{
prop[j]=0
}
}
dTproperty[,d]=prop
d=d+1
t=t-1
}
require(data.table)
DT=data.table(dTproperty)
listCol <- colnames(DT)[grep("-", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
Rproperty=data.frame(DT)
CorrectProperty=Rproperty[Rproperty$Sum!=0,]
#
return(CorrectProperty)
}
#Function to identityfy incorrect property
identifyInCorrectProperty<-function(property,en){
NondTproperty=property
d=3
t=11
for(i in 1:11){
countEntity=100#en[t,]$count/10000
# print(countEntity)
# print(length(dTproperty[,d]))
Nonprop=NondTproperty[,d]
for(j in 1:length(Nonprop)){
if(Nonprop[j]>countEntity){
Nonprop[j]=0
}
else{
Nonprop[j]=Nonprop[j]
}
}
print(Nonprop)
NondTproperty[,d]=Nonprop
d=d+1
t=t-1
}
require(data.table)
DT=data.table(NondTproperty)
listCol <- colnames(DT)[grep("-", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
NonRproperty=data.frame(DT)
IncorrectProperty=NonRproperty[NonRproperty$Sum!=0,]
return(IncorrectProperty)
}
SubSetProperty<-function(dTproperty,en){
avg=(en[11,]$count+en[10,]$count+en[9,]$count)/3
NondTproperty=dTproperty
d=3
t=11
for(i in 1:11){
countEntity=100 #avg/20000#en[t,]$count/10000
# print(countEntity)
# print(length(dTproperty[,d]))
Nonprop=NondTproperty[,d]
for(j in 1:length(Nonprop)){
if(Nonprop[j]>countEntity){
Nonprop[j]=0
}
else{
Nonprop[j]=Nonprop[j]
}
}
print(Nonprop)
NondTproperty[,d]=Nonprop
d=d+1
t=t-1
}
require(data.table)
DT=data.table(NondTproperty)
listCol <- colnames(DT)[grep("-", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
NonRproperty=data.frame(DT)
IncorrectProperty=NonRproperty[NonRproperty$Sum!=0,]
propertySubSet=data.frame(property=IncorrectProperty[,1],v201604=IncorrectProperty[,3],v201510=IncorrectProperty[,4],v201502=IncorrectProperty[,5])
require(data.table)
DT=data.table(propertySubSet)
listCol <- colnames(DT)[grep("v", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
propertySubSet=data.frame(DT)
FilteredProperty=propertySubSet[propertySubSet$Sum!=0,]
FilteredProperty=FilteredProperty[,-c(5)]
return(FilteredProperty)
}
FilteredPropertyfun<-function(dTproperty,entityDataSet){
unclass=unique(entityDataSet$class)
en=entityDataSet[entityDataSet$class==unclass[1],]
dTproperty<-dTproperty[,order(colnames(dTproperty),decreasing=TRUE)]
NondTproperty=dTproperty
NondTproperty=dTproperty
CorrectProperty = identifyCorrectProperty(dTproperty,en)
# InCorrectPropery= identifyInCorrectProperty(NondTproperty,en)
avg=(en[11,]$count+en[10,]$count+en[9,]$count)/3
NondTproperty=dTproperty
d=3
t=11
for(i in 1:11){
countEntity=100#avg/20000#en[t,]$count/10000
Nonprop=NondTproperty[,d]
for(j in 1:length(Nonprop)){
if(Nonprop[j]>countEntity){
Nonprop[j]=0
}
else{
Nonprop[j]=Nonprop[j]
}
}
print(Nonprop)
NondTproperty[,d]=Nonprop
d=d+1
t=t-1
}
require(data.table)
DT=data.table(NondTproperty)
listCol <- colnames(DT)[grep("-", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
NonRproperty=data.frame(DT)
IncorrectProperty=NonRproperty[NonRproperty$Sum!=0,]
#head(IncorrectProperty)
NdTproperty=CorrectProperty[,-c(14)]
propertySubSet=data.frame(property=IncorrectProperty[,1],v201604=IncorrectProperty[,3],v201510=IncorrectProperty[,4],v201502=IncorrectProperty[,5])
require(data.table)
DT=data.table(propertySubSet)
listCol <- colnames(DT)[grep("v", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
propertySubSet=data.frame(DT)
FilteredProperty=propertySubSet[propertySubSet$Sum!=0,]
FilteredProperty=FilteredProperty[,-c(5)]
nrow(FilteredProperty)
CorrectProperty = identifyCorrectProperty(dTproperty,en)
InCorrectPropery= identifyInCorrectProperty(NondTproperty,en)
SubSetProp=SubSetProperty(NondTproperty,en)
NdTproperty=CorrectProperty[,-c(14)]
# normalize(NdTproperty,en)
d=3
t=11
for(i in 1:11){
norm= NdTproperty[,d]/en[t,]$count
NdTproperty[,d]=norm
d=d+1
# print(norm)
t=t-1
}
NdTproperty$diffLast=NdTproperty[,3]-NdTproperty[,4]
consistencyData=NdTproperty[NdTproperty$diffLast<0,]
nrow(dTproperty)
nrow(consistencyData)
dataSet=data.frame(property=consistencyData$property,Version201604=consistencyData$X2016.04.01,Version201510=consistencyData$X2015.10.02,NormFreqDiff=consistencyData$diffLast)
#entityVal=en
#entityVal$WeightValue=en$count/10000
CorrectProperty$diff=CorrectProperty[,3]+CorrectProperty[,4]
TwoSeries=CorrectProperty[CorrectProperty$diff!=0,]
TwoSeriesData=data.frame(Property=TwoSeries$property,version201604=TwoSeries$X2016.04.01,version201510=TwoSeries$X2015.10.02,version201504=TwoSeries$X2015.02.05)
InCdata=data.frame(Property=InCorrectPropery$property,v201604=InCorrectPropery$X2016.04.01,v201510=InCorrectPropery$X2015.10.02,v201502=InCorrectPropery$X2015.02.05)
return(FilteredProperty)
}
TwoSeriesDataFun<-function(dTproperty,entityDataSet){
unclass=unique(entityDataSet$class)
en=entityDataSet[entityDataSet$class==unclass[1],]
dTproperty<-dTproperty[,order(colnames(dTproperty),decreasing=TRUE)]
NondTproperty=dTproperty
NondTproperty=dTproperty
CorrectProperty = identifyCorrectProperty(dTproperty,en)
# InCorrectPropery= identifyInCorrectProperty(NondTproperty,en)
avg=(en[11,]$count+en[10,]$count+en[9,]$count)/3
NondTproperty=dTproperty
d=3
t=11
for(i in 1:11){
countEntity=100#avg/20000#en[t,]$count/10000
Nonprop=NondTproperty[,d]
for(j in 1:length(Nonprop)){
if(Nonprop[j]>countEntity){
Nonprop[j]=0
}
else{
Nonprop[j]=Nonprop[j]
}
}
print(Nonprop)
NondTproperty[,d]=Nonprop
d=d+1
t=t-1
}
require(data.table)
DT=data.table(NondTproperty)
listCol <- colnames(DT)[grep("-", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
NonRproperty=data.frame(DT)
IncorrectProperty=NonRproperty[NonRproperty$Sum!=0,]
#head(IncorrectProperty)
NdTproperty=CorrectProperty[,-c(14)]
propertySubSet=data.frame(property=IncorrectProperty[,1],v201604=IncorrectProperty[,3],v201510=IncorrectProperty[,4],v201502=IncorrectProperty[,5])
require(data.table)
DT=data.table(propertySubSet)
listCol <- colnames(DT)[grep("v", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
propertySubSet=data.frame(DT)
FilteredProperty=propertySubSet[propertySubSet$Sum!=0,]
FilteredProperty=FilteredProperty[,-c(5)]
nrow(FilteredProperty)
CorrectProperty = identifyCorrectProperty(dTproperty,en)
InCorrectPropery= identifyInCorrectProperty(NondTproperty,en)
SubSetProp=SubSetProperty(NondTproperty,en)
NdTproperty=CorrectProperty[,-c(14)]
# normalize(NdTproperty,en)
d=3
t=11
for(i in 1:11){
norm= NdTproperty[,d]/en[t,]$count
NdTproperty[,d]=norm
d=d+1
# print(norm)
t=t-1
}
NdTproperty$diffLast=NdTproperty[,3]-NdTproperty[,4]
consistencyData=NdTproperty[NdTproperty$diffLast<0,]
nrow(dTproperty)
nrow(consistencyData)
dataSet=data.frame(property=consistencyData$property,Version201604=consistencyData$X2016.04.01,Version201510=consistencyData$X2015.10.02,NormFreqDiff=consistencyData$diffLast)
#entityVal=en
#entityVal$WeightValue=en$count/10000
CorrectProperty$diff=CorrectProperty[,3]+CorrectProperty[,4]
TwoSeries=CorrectProperty[CorrectProperty$diff!=0,]
TwoSeriesData=data.frame(Property=TwoSeries$property,version201604=TwoSeries$X2016.04.01,version201510=TwoSeries$X2015.10.02,version201504=TwoSeries$X2015.02.05)
InCdata=data.frame(Property=InCorrectPropery$property,v201604=InCorrectPropery$X2016.04.01,v201510=InCorrectPropery$X2015.10.02,v201502=InCorrectPropery$X2015.02.05)
return(TwoSeriesData)
}
dataSetFun<-function(dTproperty,entityDataSet){
unclass=unique(entityDataSet$class)
en=entityDataSet[entityDataSet$class==unclass[1],]
dTproperty<-dTproperty[,order(colnames(dTproperty),decreasing=TRUE)]
NondTproperty=dTproperty
NondTproperty=dTproperty
CorrectProperty = identifyCorrectProperty(dTproperty,en)
# InCorrectPropery= identifyInCorrectProperty(NondTproperty,en)
avg=(en[11,]$count+en[10,]$count+en[9,]$count)/3
NondTproperty=dTproperty
d=3
t=11
for(i in 1:11){
countEntity=100#avg/20000#en[t,]$count/10000
Nonprop=NondTproperty[,d]
for(j in 1:length(Nonprop)){
if(Nonprop[j]>countEntity){
Nonprop[j]=0
}
else{
Nonprop[j]=Nonprop[j]
}
}
print(Nonprop)
NondTproperty[,d]=Nonprop
d=d+1
t=t-1
}
require(data.table)
DT=data.table(NondTproperty)
listCol <- colnames(DT)[grep("-", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
NonRproperty=data.frame(DT)
IncorrectProperty=NonRproperty[NonRproperty$Sum!=0,]
#head(IncorrectProperty)
NdTproperty=CorrectProperty[,-c(14)]
propertySubSet=data.frame(property=IncorrectProperty[,1],v201604=IncorrectProperty[,3],v201510=IncorrectProperty[,4],v201502=IncorrectProperty[,5])
require(data.table)
DT=data.table(propertySubSet)
listCol <- colnames(DT)[grep("v", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
propertySubSet=data.frame(DT)
FilteredProperty=propertySubSet[propertySubSet$Sum!=0,]
FilteredProperty=FilteredProperty[,-c(5)]
nrow(FilteredProperty)
CorrectProperty = identifyCorrectProperty(dTproperty,en)
InCorrectPropery= identifyInCorrectProperty(NondTproperty,en)
SubSetProp=SubSetProperty(NondTproperty,en)
NdTproperty=CorrectProperty[,-c(14)]
# normalize(NdTproperty,en)
d=3
t=11
for(i in 1:11){
norm= NdTproperty[,d]/en[t,]$count
NdTproperty[,d]=norm
d=d+1
# print(norm)
t=t-1
}
NdTproperty$diffLast=NdTproperty[,3]-NdTproperty[,4]
consistencyData=NdTproperty[NdTproperty$diffLast<0,]
nrow(dTproperty)
nrow(consistencyData)
dataSet=data.frame(property=consistencyData$property,Version201604=consistencyData$X2016.04.01,Version201510=consistencyData$X2015.10.02,NormFreqDiff=consistencyData$diffLast)
#entityVal=en
#entityVal$WeightValue=en$count/10000
CorrectProperty$diff=CorrectProperty[,3]+CorrectProperty[,4]
TwoSeries=CorrectProperty[CorrectProperty$diff!=0,]
TwoSeriesData=data.frame(Property=TwoSeries$property,version201604=TwoSeries$X2016.04.01,version201510=TwoSeries$X2015.10.02,version201504=TwoSeries$X2015.02.05)
InCdata=data.frame(Property=InCorrectPropery$property,v201604=InCorrectPropery$X2016.04.01,v201510=InCorrectPropery$X2015.10.02,v201502=InCorrectPropery$X2015.02.05)
return(dataSet)
}
TwoSeriesDataFun<-function(dTproperty,entityDataSet){
unclass=unique(entityDataSet$class)
en=entityDataSet[entityDataSet$class==unclass[1],]
dTproperty<-dTproperty[,order(colnames(dTproperty),decreasing=TRUE)]
NondTproperty=dTproperty
NondTproperty=dTproperty
CorrectProperty = identifyCorrectProperty(dTproperty,en)
# InCorrectPropery= identifyInCorrectProperty(NondTproperty,en)
avg=(en[11,]$count+en[10,]$count+en[9,]$count)/3
NondTproperty=dTproperty
d=3
t=11
for(i in 1:11){
countEntity=100#avg/20000#en[t,]$count/10000
Nonprop=NondTproperty[,d]
for(j in 1:length(Nonprop)){
if(Nonprop[j]>countEntity){
Nonprop[j]=0
}
else{
Nonprop[j]=Nonprop[j]
}
}
print(Nonprop)
NondTproperty[,d]=Nonprop
d=d+1
t=t-1
}
require(data.table)
DT=data.table(NondTproperty)
listCol <- colnames(DT)[grep("-", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
NonRproperty=data.frame(DT)
IncorrectProperty=NonRproperty[NonRproperty$Sum!=0,]
#head(IncorrectProperty)
NdTproperty=CorrectProperty[,-c(14)]
propertySubSet=data.frame(property=IncorrectProperty[,1],v201604=IncorrectProperty[,3],v201510=IncorrectProperty[,4],v201502=IncorrectProperty[,5])
require(data.table)
DT=data.table(propertySubSet)
listCol <- colnames(DT)[grep("v", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
propertySubSet=data.frame(DT)
FilteredProperty=propertySubSet[propertySubSet$Sum!=0,]
FilteredProperty=FilteredProperty[,-c(5)]
nrow(FilteredProperty)
CorrectProperty = identifyCorrectProperty(dTproperty,en)
InCorrectPropery= identifyInCorrectProperty(NondTproperty,en)
SubSetProp=SubSetProperty(NondTproperty,en)
NdTproperty=CorrectProperty[,-c(14)]
# normalize(NdTproperty,en)
d=3
t=11
for(i in 1:11){
norm= NdTproperty[,d]/en[t,]$count
NdTproperty[,d]=norm
d=d+1
# print(norm)
t=t-1
}
NdTproperty$diffLast=NdTproperty[,3]-NdTproperty[,4]
consistencyData=NdTproperty[NdTproperty$diffLast<0,]
nrow(dTproperty)
nrow(consistencyData)
dataSet=data.frame(property=consistencyData$property,Version201604=consistencyData$X2016.04.01,Version201510=consistencyData$X2015.10.02,NormFreqDiff=consistencyData$diffLast)
#entityVal=en
#entityVal$WeightValue=en$count/10000
CorrectProperty$diff=CorrectProperty[,3]+CorrectProperty[,4]
TwoSeries=CorrectProperty[CorrectProperty$diff!=0,]
TwoSeriesData=data.frame(Property=TwoSeries$property,version201604=TwoSeries$X2016.04.01,version201510=TwoSeries$X2015.10.02,version201504=TwoSeries$X2015.02.05)
InCdata=data.frame(Property=InCorrectPropery$property,v201604=InCorrectPropery$X2016.04.01,v201510=InCorrectPropery$X2015.10.02,v201502=InCorrectPropery$X2015.02.05)
return(TwoSeriesData)
}
dataSetFun<-function(dTproperty,entityDataSet){
unclass=unique(entityDataSet$class)
en=entityDataSet[entityDataSet$class==unclass[1],]
dTproperty<-dTproperty[,order(colnames(dTproperty),decreasing=TRUE)]
NondTproperty=dTproperty
NondTproperty=dTproperty
CorrectProperty = identifyCorrectProperty(dTproperty,en)
# InCorrectPropery= identifyInCorrectProperty(NondTproperty,en)
avg=(en[11,]$count+en[10,]$count+en[9,]$count)/3
NondTproperty=dTproperty
d=3
t=11
for(i in 1:11){
countEntity=100#avg/20000#en[t,]$count/10000
Nonprop=NondTproperty[,d]
for(j in 1:length(Nonprop)){
if(Nonprop[j]>countEntity){
Nonprop[j]=0
}
else{
Nonprop[j]=Nonprop[j]
}
}
print(Nonprop)
NondTproperty[,d]=Nonprop
d=d+1
t=t-1
}
require(data.table)
DT=data.table(NondTproperty)
listCol <- colnames(DT)[grep("-", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
NonRproperty=data.frame(DT)
IncorrectProperty=NonRproperty[NonRproperty$Sum!=0,]
#head(IncorrectProperty)
NdTproperty=CorrectProperty[,-c(14)]
propertySubSet=data.frame(property=IncorrectProperty[,1],v201604=IncorrectProperty[,3],v201510=IncorrectProperty[,4],v201502=IncorrectProperty[,5])
require(data.table)
DT=data.table(propertySubSet)
listCol <- colnames(DT)[grep("v", colnames(DT))]
DT[, Sum := Reduce('+', .SD), .SDcols=listCol][]
propertySubSet=data.frame(DT)
FilteredProperty=propertySubSet[propertySubSet$Sum!=0,]
FilteredProperty=FilteredProperty[,-c(5)]
nrow(FilteredProperty)
CorrectProperty = identifyCorrectProperty(dTproperty,en)