AreaIntegrator.r

AreaIntegrator = function(A,kva,gorl=1)
{
  if(gorl==1)
  {
    B = fn$sqldf("select * from A where Rep_KVA>$kva")
  }
  else if(gorl==-1)
  {
    B = fn$sqldf("select * from A where Rep_KVA<$kva")
  }
  if(length(B$Day)!=0)
  {
    B$Row_no = seq(1,length(B$Day))
    B$ModifiedRep = ifelse((gorl*(B$Rep_KVA-kva)>0),(gorl*(B$Rep_KVA-kva)),0)
    return(sum(B$ModifiedRep))
  }
  else
  {
    return(0.0)
  }
}

CentralAnalyser.r

CentralAnalyser <- function(z)
{
t=z
tn = as.numeric(sqldf("select count(distinct Day) from t"))
final=data.frame(  Day=as.Date(character()),
                   Time=character(), 
                   Rep_KVA=numeric(), 
                   stringsAsFactors=FALSE) 

for (j in 1:tn)
{
  e = fn$sqldf("select * from t where Time=(select Time from t limit $j-1,1)")
  for (i in 1:7)
  {
    f = fn$sqldf("select * from e where Date%7=$i-1 and Global_active_power!='NA'")
    plot(f$Date,f$KVA,xlab='Day No.',ylab='KVA', main = "Graphical representation of KVA value in 6 months for particular time.")
    lines(f$Date,f$KVA)
    # Finding the best optimized central tendency for the dataset (for particular weekday and particular time)
    nn = as.numeric(sqldf("select count(*) from f"))
    hippo =d = NULL
    for (i1 in seq(1,nn))
    {
      d=NULL
      d1 = as.numeric(fn$sqldf("select KVA from f limit $i1-1,1"))
      for (j1 in 1:nn)
      {
        d2 = as.numeric(fn$sqldf("select KVA from f limit $j1-1,1"))
        d[j1]=ifelse(d2-d1>0,(d2-d1)*.16*.4,0)
      }
      f$hippo[i1]=sum(d)+d1*(nn)*0.1*.4
      #k = k+1
      #f$hippo[k]=hippo[i1]
      #print(paste0("Hippo: for ", d1, " and ", d2,"  = ", hippo[i1]))
    }
    if(!is.na(f$hippo[1]))
    {
      rep_data=sqldf("select * from f where hippo=(select min(hippo)from f) limit 1")
      repkva = as.numeric((sqldf("select KVA from rep_data")))
      reptime = as.character(sqldf("select Time from rep_data"))
      repweekday = weekdays(rep_data$Date)
      final=rbind(final,data.frame(Day=repweekday,Time=reptime,Rep_KVA=repkva))
    }
    else
    {
      final=rbind(final,data.frame(Day=f$Day[1],Time=f$Time[1],Rep_KVA=0))
    }
  }
}
}

Pricecal.r

# Finding KVA min
PriceCalculation = function(tib,Hour,Set,Weekday="Sunday",Time="00:00 am")
{
  library(Hmisc)
  weekdaylist=c("Sunday", "Monday", "Tuesday","Wednesday","Thursday","Friday","Saturday")
  # Daywise working
  TotalPrice=0
    jo=index=match(Weekday,weekdaylist)
    time1=as.numeric(strsplit(Time,':')[[1]][1])
    time2=(substring(strsplit(Time,':')[[1]][2],1,2))
    if(length(grep('p', g, ignore.case = TRUE)))
    {time1 = as.numeric(time1 +12)}
    else { if(!(time1==10 || time1==11 || time1==12))
      time1 = paste0("0",time1)}
  cou=1
  while( (jo>=index || (index+Set)%%7>jo) && cou<=7) 
  {
    cou=cou+1
    day1= weekdaylist[[jo]]
    fuf=sqldf(paste0("select * from tib where Day='",day1,"'"))
    fuf$Row_no=seq(1:length(fuf$Row_no))
      if (is.na(Weekday))
      {Weekday=day1}
    PlanLabel=as.character(paste0(day1," - ",time1,":",time2,":00"))
    divtocover=Hour*4
    Point1=as.integer(fn$sqldf(paste0("select Row_no from fuf where Label='",PlanLabel,"'")))
    # Block Table
    Table1=fn$sqldf(paste0("select * from fuf where Row_no>=$Point1 and Row_no<($Point1+$divtocover)"))
    # Index Table
    Table2=fn$sqldf(paste0("select * from fuf where Row_no<$Point1 or Row_no>=($Point1+$divtocover)"))
    BlockP=Hour*0.4*0.1*4
    
    if(length(Table1$Row_no)!=0)
    {
      mkva=MinKvaCalculation(Table1)
      p=mkva[[1]]
      ond=0
      while(p>=mkva[[1]] && p<=(mkva[[2]])+1 )
      {
        if(p*divtocover*.10<=AreaIntegrator(Table1,kva=p)*.16)
        {
          ond[p]=AreaIntegrator(Table1,kva=p,gorl=-1)
          p=p+1
        }
        else{
          ond[p]=0
          break}
      }
      
      usekva=mkva[1]+(match(min(ond),ond))-1
      IndexP1=AreaIntegrator(Table1,kva=usekva)*.16*.4
    }
    else     
      IndexP1=0
    if(length(Table2$Row_no)!=0)
    {
      IndexP2=AreaIntegrator(Table2,kva=0)*.16*.4
    }
    else IndexP2=0
    TotalPrice[jo]=BlockP+IndexP1+IndexP2
    if(jo==7)
      jo=1
    else  jo=jo+1
  }
  if(Set==5)
  {
    Table3=fn$sqldf(paste0("select * from tib where Day='",weekdaylist[jo],"'"))
    TotalPrice[jo]=AreaIntegrator(Table3,kva=0)*.16*.4
    Table4=fn$sqldf(paste0("select * from tib where Day='",weekdaylist[jo+1],"'"))
    TotalPrice[jo+1]=AreaIntegrator(Table4,kva=0)*.16*.4
  }
  return(sum(TotalPrice))
}

MinKvaCalculation = function(tob)
{
  nom=as.numeric(sqldf("select count(*) from tob"))
  hr=nom/4
  mink=as.numeric(sqldf("select Min(Rep_KVA) from tob"))
  maxk=as.numeric(sqldf("select Max(Rep_KVA) from tob"))
  return(c(floor(mink),ceiling(maxk)))
}

pricesheet.r

#Creating price sheet
pricesheet=NULL
pricesheet = rbind(pricesheet,data.frame(Hour=24,Size=7))
pricesheet = rbind(pricesheet,data.frame(Hour=24,Size=5))
pricesheet = rbind(pricesheet,data.frame(Hour=16,Size=7))
pricesheet = rbind(pricesheet,data.frame(Hour=16,Size=5))
pricesheet = rbind(pricesheet,data.frame(Hour=8,Size=7))
pricesheet = rbind(pricesheet,data.frame(Hour=8,Size=5))
pricesheet$Price=pricesheet$Hour*pricesheet$Size*.10*0.4

#UserChoice
choice = NULL
print(paste0("Enter number of blocks to be taken of your choice. "))
block= as.integer(readline())
for (g in 1:block)
{
  print(paste0("Enter hour plan to be taken for block choice ",g))
  choice$Hour[g] = as.numeric(readline())
  print(paste0("Enter set plan to be taken for block choice ",g))
  choice$Set[g] =  as.numeric(readline())
  if(choice$Hour[g]!=24)
  {
    print(paste0("Enter time plan to be taken for block choice ",g))
    choice$Time[g] =  as.character(readline())
  }
  else
  {
    choice$Time[g] =  NA
  }
  if (choice$Set[g]==5)
  {
    print(paste0("Enter Start Day plan to be taken  for block choice ",g))
    choice$Day[g] =  as.character(readline())
  }
  else
  {
    choice$Day[g] =  NA
  }
}

choice=data.frame(choice)

#Updating price column
choice$Price = choice$Hour*choice$Set*.10*0.4

#Updating Amount to be paid
for( oo in 1:length(choice$Hour))
choice$Amount[oo]=PriceCalculation(h3,Hour=choice$Hour[oo],Set=choice$Set[oo],Time=as.character(choice$Time[oo]))

reading.r

library(sqldf)

# Reading content from file
x<-read.table("//home//innovator//Documents//Internship//Data//household_power_consumption.txt",header=TRUE,sep=';',dec = '.',stringsAsFactors=FALSE)

# Performing necessary conversions
x$Date<- as.Date(x$Date,"%d/%m/%Y")
x$Time  =  format(as.POSIXlt(x$Time, format = "%H:%M:%S"), format="%H:%M:%S")
x$Global_active_power = as.numeric(x$Global_active_power)
x$Global_reactive_power = as.numeric(x$Global_reactive_power)

# Defining KVA
x$KVA = sqrt(x$Global_active_power*x$Global_active_power+x$Global_reactive_power*x$Global_reactive_power)

# Creating Day column
x$Day = weekdays(x$Date)


## Creating sample pools for six month data
# The starting date
first<- as.Date('16-12-2008',format = '%d-%m-%Y')
# The Ending Date
second <- as.Date('30-06-2009',format = '%d-%m-%Y')

y = fn$sqldf("select * from x where Date>=$first and Date<=$second")

## Creating sample pools of data at time 0, 15min, 30min, 45min
z  = fn$sqldf("select * from y where substr(Time,4,2)='00' or substr(Time,4,2)='15' or substr(Time,4,2)='30' or substr(Time,4,2)='45'")

rearranger.r

Rearranger <- function(final)
{
# Rearranging the distinct Days in our sequence
weekdaylist= c( "Sunday","Monday","Tuesday", "Wednesday","Thursday","Friday","Saturday" )
yyy =sqldf("select distinct Day from final")
tutu=NULL
for (iii in 1:length(yyy$Day))
{
  day = weekdaylist[iii]
  if(grep(day, yyy$Day)!=0)
  {
    tut=data.frame(Day=day)
  }
  else
    tut=NULL
  tutu= rbind(tutu,tut)
}
yyy=tutu


# Created Dataset based on Daywise grouping
h3=NULL
for (h1 in 1:length(yyy$Day))
{
  h0 = fn$sqldf("select * from final where Day=(select Day from yyy limit $h1-1,1)")
  h2 = fn$sqldf("select * from h0 order by Time")
  plot(h2$Time,h2$Rep_KVA,xlab="Time on Day",ylab="Rep_KVA",las=2)
  lines(h2$Time,h2$Rep_KVA,xlab="Time on Day",ylab="Rep_KVA",las=2)
  
  # Analysing this weekday for apt pricing plan
  h3 = rbind(h3,h2)
}

# Labelling of the data
h3$Label=as.character(h3$Label)
h3=transform(Label=paste0(h3$Day," - ",h3$Time),h3)

# One week representation of Data
Row_no =seq(1,length(h3$Day))
h3 = cbind(Row_no,h3)
plot(h3$Row_no,h3$Rep_KVA)
lines(h3$Row_no,h3$Rep_KVA)
}