0_reporting_functions.R

set_report_parameters <- function(ParameterFilePath){
  
  report_cfg <- config::get(file = ParameterFilePath)
  
  Contents <- as_tibble(report_cfg$Contents)
  for (x in 1:length(Contents)){  
    assign(colnames(Contents)[x], Contents[[x]], envir = .GlobalEnv)
  } 
  
  
  ParameterFile <<- as_tibble(report_cfg$Naming)
  for (x in 1:length(ParameterFile)){  
    assign(colnames(ParameterFile)[x], ParameterFile[[x]], envir = .GlobalEnv)
  } 
  
  Benchmarks <- as_tibble(report_cfg$Benchmarks)
  for (x in 1:length(Benchmarks)){  
    assign(colnames(Benchmarks)[x], Benchmarks[[x]], envir = .GlobalEnv)
  } 
  
  start_year <<- as.numeric(Startyear)
  no_companies <<- as.numeric(No.Companies)
  
  if(!exists("inc_sda_approach")){
    inc_sda_approach <<- FALSE
    print("inc_sda_approach not in parameter file. Default value set to FALSE.")
  }
  
  AccountingPrinciple <<- if_else(AccountingPrinciple == "PortfolioWeight","portfolio_weight",AccountingPrinciple)
  AccountingPrinciple <<- if_else(AccountingPrinciple == "Ownership","ownership_weight",AccountingPrinciple)  
}

get_report_list <- function(Ports.Overview){
  
  port.list <- Ports.Overview %>%
    select(investor_name,portfolio_name) %>%
    unique()
  
  port.list <- port.list %>%
    select(investor_name, portfolio_name) %>%
    group_by(investor_name) %>%
    mutate(count = n() ) %>%
    unique()
  
  port.list$Type <- ifelse(port.list$count > 1,"Portfolio","InvestorSingle")  
  port.list$Type <- ifelse(port.list$investor_name == port.list$portfolio_name, "InvestorMeta",port.list$Type) 
  
  return(port.list)
}

ReportData <- function(){
  
  # company_name <- portfolio_name_select
  # 
  # company_name <- gsub("&","\\\\\\\\&",company_name)
   
  SizePortfolio <-  subgroup_overview %>%
    filter(portfolio_name == portfolio_name_select) %>%
    distinct(portfolio_value_usd)
  SizeofPortfolio <- SizePortfolio[[1]]
  
  
  SizeofPortfolio <- comprss_long(SizeofPortfolio)
  TodaysDate <- format(Sys.Date(),format = "%d.%m.%Y")
  
  
  NoPeers <- nrow(test_list)-1
  
  if(has_equity & has_debt){AssetClass <- paste0("Listed equity; ",BondReference)
  }else if(has_equity & !has_debt){AssetClass <- "Listed equity"
  }else if(!has_equity & has_debt){AssetClass <- BondReference
  }else if(!has_equity & !has_debt){AssetClass <- "No Climate Relevant Holdings"}
  
  scenarioDF <- data.frame("ShortName" = 
                             c("CPS","NPS","B2DS","BNEF","GPER","SDS"), 
                           "scenarioText" = 
                             c("CPS: Current Policy scenario",
                               "NPS: New Policy scenario",
                               "B2DS: Beyond 2 Degree scenario",
                               "BNEF: Bloomberg New Energy Finance",
                               "GPER: Greenpeace scenario",
                               "SDS: Sustainable Development scenario"),
                           "scenarioName" = 
                             c("Current Policy scenario",
                               "New Policy scenario",
                               "Beyond 2 Degree scenario",
                               "Bloomberg New Energy Finance",
                               "Greenpeace scenario",
                               "Sustainable Development scenario"), 
                           "scenarioDescription" = 
                             c("The Current Policy scenario (CPS) represents a transition if no changes were made to current policies.", 
                               "The New Policy scenario (NPS) represents new policies that have been put in place.", 
                               "The Beyond 2 Degree scenario (B2DS) is consistent with a 50\\\\% chance of limiting average future temperature rise to 1.75\\\\degree C.",
                               "Bloomberg New Energy Finance scenario (BNEF) is a scenario proposed by Bloomberg.",
                               "The Greenpeace scenario", 
                               "The Sustainable Development scenario (SDS) is consistent with a 50\\\\% chance of limiting average future temperature rise to 2\\\\degree C."),
                           "scenarioTemp" = 
                             c("6","4","well below 2","2","2","2")
  )
  scenarioText <- as.character(scenarioDF$scenarioText[scenarioDF$ShortName %in% Scenariochoose])
  scenarioTemp <- as.character(scenarioDF$scenarioTemp[scenarioDF$ShortName %in% Scenariochoose])
  scenarioName <- as.character(scenarioDF$scenarioName[scenarioDF$ShortName %in% Scenariochoose])
  scenarioDescription <- as.character(scenarioDF$scenarioDescription[scenarioDF$ShortName %in% Scenariochoose])
  
  BenchmarkValue <- "market"
  
  if(has_sb){
    SovBondCov <- SB.Values$SBPerc[SB.Values$investor_name == investor_name_select & SB.Values$portfolio_name == portfolio_name_select]
    SovBondCov <- ifelse(identical(SovBondCov, numeric(0)),0,SovBondCov)  
    SovBondCov <<- round(SovBondCov*100,1)
    
    
    sb <- read.csv(paste0(SB.DATA.PATH, "Fig.1_2 Credit ratingbycountry_Rev1_5.csv"),strip.white = T, stringsAsFactors = F)
    sb_countries <- SB.Summary %>% filter(investor_name == investor_name_select, portfolio_name == portfolio_name_select) 
    downgrade_countries <- sb %>% filter(iso2c %in% sb_countries$country_of_domicile, iso2c != "CO", S.P %in% c("BBB","BBB-") ) 
    sb_downgrade <- sb_countries %>% filter(country_of_domicile %in% downgrade_countries) %>% summarise(ValUSD = sum(ValueUSD,na.rm = T))
    sb_downgrade_perc <- sb_downgrade$ValUSD / sum(sb_countries$ValueUSD,na.rm = T)
    sb_downgrade_perc <- if_else(is.nan(sb_downgrade_perc), 0, sb_downgrade_perc)
    sb_downgrade_perc <<- sb_downgrade_perc*100
    
    if(sb_downgrade_perc > 100){print("Greater than 100% for SB percent")}
    
  }
  
  SectorCheck <- test_list#[test_list$portfolio_name == portfolio_name_select,]
  
  if (data_check(SectorCheck)){
    HasPower <<- SectorCheck$Power.CB| SectorCheck$Power.EQ
    HasAuto <<- SectorCheck$Automotive.CB | SectorCheck$Automotive.EQ
    HasOG <<- SectorCheck$OilGas.CB | SectorCheck$OilGas.EQ
    HasCoal <<- SectorCheck$Coal.CB | SectorCheck$Coal.EQ
    HasPowerCB <<- SectorCheck$Power.CB
    HasAutoCB <<- SectorCheck$Automotive.CB
    HasOGCB <<- SectorCheck$OilGas.CB
    HasCoalCB <<- SectorCheck$Coal.CB
    HasPowerEQ <<- SectorCheck$Power.EQ
    HasAutoEQ <<- SectorCheck$Automotive.EQ
    HasOGEQ <<- SectorCheck$OilGas.EQ
    HasCoalEQ <<- SectorCheck$Coal.EQ
  }
  
  PeerGroupName <- gsub("([a-z])([A-Z])", "\\1 \\2", PeerGroupSelection)
  
  ProjectPeersRef = PeerGroupSelection
  
  PeerGroupName <- ifelse(EQPeersRef == CBPeersRef & EQPeersRef == "Project",ProjectPeersRef, PeerGroupName)
  
  
  # # Check Physical Risk
  # if(HasRISK())
  # if(data_check(EQPhysicalRisk)){
  #   EQPhysicalRiskCheck <- TRUE
  # }else{EQPhysicalRiskCheck <- FALSE}
  # 
  # if(data_check(CBPhysicalRisk)){
  #   CBPhysicalRiskCheck <-TRUE
  # }  else{CBPhysicalRiskCheck <- FALSE}
  
  # if (IsSample == T){     # Only necessary to print an unnamed report ie for sharing with interested partners. 
  #   investor_name_select <- "Investor"
  #   portfolio_name_select <- "Sample Portfolio"
  # }
  
  # Underscores break the report hence they are removed from names 
  portfolio_name_select <- gsub("_"," ", portfolio_name_select)
  
  
  ### MERGE ALL RESULTS ###
  reportdata <<- data.frame(
    c("InvestorName",investor_name_select),
    c("PortfolioName",portfolio_name_select),
    c("SizeofPortfolio",SizeofPortfolio),
    c("TodaysDate",TodaysDate),
    c("PeerGroup",PeerGroupName),
    c("scenarioText",scenarioText),
    c("scenarioName",scenarioName),
    c("scenarioValue",Scenariochoose),
    c("scenarioDescription",scenarioDescription),
    c("scenarioTemp", scenarioTemp),
    c("BenchmarkValue",BenchmarkValue),
    c("AnalysisCoverage",AnalysisCoverage),
    c("HasPower",HasPower),
    c("HasAuto",HasAuto),
    c("HasOG",HasOG),
    c("HasCoal",HasCoal),
    c("HasCarbonBudget",HasCarbonBudget),
    c("HasPowerCB",HasPowerCB),
    c("HasAutoCB",HasAutoCB),
    c("HasOGCB",HasOGCB),
    c("HasCoalCB",HasCoalCB),
    c("HasPowerEQ",HasPowerEQ),
    c("HasAutoEQ",HasAutoEQ),
    c("HasOGEQ",HasOGEQ),
    c("HasCoalEQ",HasCoalEQ),
    c("NoPeers",NoPeers),
    c("AssetClass", AssetClass)#,
    # c("SovBondCov", SovBondCov),
    # c("sbdowngradeperc",sb_downgrade_perc)
  )
  
  colnames(reportdata) <- as.character(unlist(reportdata[1,]))
  reportdata = reportdata[-1, ]
  
  
  return(reportdata)
  
}

ReportGeneration <- function(){
  
  over <- SectorDataAnalysis()
  
  AnalysisCoverage <<-  round(sum(over$valid_value_usd[over$financial_sector !="Not Included"])/sum(over$valid_value_usd)*100,1)
  
  
  reportdata <- ReportData()
  reportdata <- reportdata %>% filter(PortfolioName == portfolio_name_select)
  
  # Copy in the template for the report
  text <- as.data.frame(template,stringsAsFactors = FALSE)  
  colnames(text) <- "text"
  
  # Function removes text lines between 
  # "handlenameS" and "handlenameE" ie CBPowerS, CBPowerE
  # Need to add these handles into the final doc when ready. Also determine what will be kicked out/what will remain. 
  
  # handlename <- "AutoSector_CB"
  
  
  removetextlines <- function(handlename){
    startpage <- which(grepl(paste0(handlename,"S"),text$text))
    endpage <- which(grepl(paste0(handlename,"E"),text$text))
    
    if (length(startpage) == 0|length(endpage) == 0){
      text <- text
    }else if (length(startpage) > 0){
      removelist <- lapply(1:length(startpage), function(x) c(startpage[c(x)]:endpage[c(x)]))
      removelist <- melt(removelist[1:length(startpage)])
      text <- as.data.frame(text[-removelist$value,],stringsAsFactors =FALSE)
      colnames(text) <- "text"
    }else{
      removeline <- which(grepl(handlename,text$text))
      text <- as.data.frame(text[-removeline,],stringsAsFactors =FALSE)
      colnames(text) <- "text"
    }
    return(text)
  }
  
  if (!has_equity){text <- removetextlines("EQSpecific")}
  
  if (!has_debt){text <- removetextlines("CBSpecific")}
  
  
  
  if(!HasAuto){
    text <- removetextlines("AutoSector_ALL")
  } else {
    if(!HasAutoCB){
      text <- removetextlines("AutoSector_CB")
    }
    if(!HasAutoEQ){
      text <- removetextlines("AutoSector_EQ")
    }
  }
  if(!HasPower){
    text <- removetextlines("PowerSector_ALL")
  } else {
    if(!HasPowerCB){
      text <- removetextlines("PowerSector_CB")
    }
    if(!HasPowerEQ){
      text <- removetextlines("PowerSector_EQ")
    }
  }
  
  if(!HasOG  & !HasCoal){
    text <- removetextlines("FossilFuelSector_ALL")
  } else {
    if(!HasOGCB & !HasCoalCB){
      text <- removetextlines("FossilFuelSector_CB")
    }
    if(!HasOGEQ & !HasCoalEQ){
      text <- removetextlines("FossilFuelSector_EQ")
    }
    if(!HasCarbonBudget){
      text <- removetextlines("CarbonBudget")
    }
  }
  
  if (!HasCoal){text <- removetextlines("CoalMiningChart")}
  
  if(HasOG){
    if(HasOGCB== F|HasOGEQ == F){
      text <- removetextlines("FossilFuelOneSector")
    }
  }
  
  if(!(HasCoalCapCB|HasCoalCapEQ)){
    text <- removetextlines("CoalCapChart")
  }
  
  if (!IncPeersChart){
    text <- removetextlines("PeerComparison")
  }
  
  # if(!(HasRenCapCB|HasRenCapEQ)){
  #   text <- removetextlines("RenewableCapChart")
  # }
  
  if(!WithCompanyCharts){
    text <- removetextlines("CompanyCharts")
  }
  
  if(WithCompanyCharts){
    a<-0
    if(has_debt){a <- a+1}
    if(has_equity){a <- a+1}
    
    b<-0
    if(a == 1){
      if(HasPower){b<-b+1}
      if(HasAuto){b<-b+1}
    }else if(a == 2){
      text <- removetextlines("PowerAutoTwoSectors")
    }
    
    if(b == 2){
      text <- removetextlines("PowerAutoOneSector")
    }else if(b == 1){
      text <- removetextlines("PowerAutoTwoSectors")
    }
  }
  
  if(IncAlignment){
    text <- removetextlines("ExposureExecSummary")
  }else{
    text <- removetextlines("AlignmentExecSummary")
  }
  
  if(!IncPhysicalRisk){
    text <- removetextlines("IncludePhysicalRisk")
  }
  
  if(!IncOtherSectors){
    text <- removetextlines("OtherSectors")
  }
  
  # text <- removetextlines("IncRanking")
  if(!IncPRI){text <- removetextlines("UNPRI_Text")}
  if(!IncWWF){text <- removetextlines("WWFSpecificInclude")}
  if(IncWWF){text <- removetextlines("WWFSpecificExclude")}
  
  # investor_name_select <- clean_punctuation(investor_name_select)
  # portfolio_name_select <- clean_punctuation(portfolio_name_select)
  portfolio_name_select <- gsub("_"," ",portfolio_name_select)
  
  if (IsSample == T){     # Only necessary to print an unnamed report ie for sharing with interested partners. 
    investor_name_select <- "Investor"
    portfolio_name_select <- "Sample Portfolio"
  }
  
  reportdata$AssetClass <- BondReference
  reportdata$ReportDate <- if(financial_timestamp == "2017Q4"){"31.12.2017"}else 
    if(financial_timestamp == "2018Q4"){"31.12.2018"}else 
      if(financial_timestamp == "2019Q4"){"31.12.2019"}else{
        financial_timestamp}
  
  investor_name_selectClean <- gsub("_"," ",investor_name_select)
  # investor_name_selectClean <- gsub("\("," ",investor_name_selectClean)
  # investor_name_selectClean <- gsub("/)"," ",investor_name_selectClean)
  investor_name_selectClean <- wrap_labels(investor_name_selectClean, 20)
  investor_name_selectClean <- gsub("'","",investor_name_selectClean)
  
  portfolio_name_selectClean <- gsub("_"," ",portfolio_name_select)  
  portfolio_name_selectClean <- wrap_labels(portfolio_name_selectClean, 20)
  portfolio_name_selectClean <- gsub("#","",portfolio_name_selectClean)
  portfolio_name_selectClean <- gsub("'","",portfolio_name_selectClean)
  
  
  text$text <- gsub("start_year+10",start_year+10,text$text,fixed=T)
  text$text <- gsub("start_year+5",start_year+5,text$text,fixed=T)
  text$text <- gsub("start_year",start_year,text$text)
  text$text <- gsub("investor_name_select",investor_name_selectClean,text$text)
  text$text <- gsub("portfolio_name_select",portfolio_name_selectClean,text$text)
  text$text <- gsub("SizeofPortfolio",paste0("\\\\$",reportdata$SizeofPortfolio),text$text)
  text$text <- gsub("TodaysDate",reportdata$TodaysDate,text$text)
  text$text <- gsub("ReportDate",reportdata$ReportDate,text$text)
  text$text <- gsub("PeerGroup",reportdata$PeerGroup,text$text)
  text$text <- gsub("AssetClass",reportdata$AssetClass,text$text)
  text$text <- gsub("AnalysisCoverage",reportdata$AnalysisCoverage,text$text)
  text$text <- gsub("scenarioText",reportdata$scenarioText,text$text)
  text$text <- gsub("scenarioName",reportdata$scenarioName,text$text)
  text$text <- gsub("scenarioValue",reportdata$scenarioValue,text$text)
  text$text <- gsub("scenarioDescription",reportdata$scenarioDescription,text$text)
  text$text <- gsub("scenarioTemp",reportdata$scenarioTemp,text$text)
  text$text <- gsub("BenchmarkValue",reportdata$BenchmarkValue,text$text)
  text$text <- gsub("EQMarketRef",eq_market_ref, text$text)
  text$text <- gsub("CBMarketRef",cb_market_ref, text$text)
  
  
  if (has_sb){
    text$text <- gsub("SovBondCov",SovBondCov, text$text)
    text$text <- gsub("sbdowngradeperc",sb_downgrade_perc, text$text)
  }
  
  
  if (data_check(text) == FALSE){
    NoReport <- paste0( "There is no data to print in a report")
    cat(NoReport,file="NoReport.txt",sep="\n")
  }else{
    
    
    
    # Figures
    namestring <- graph_name("00",ParameterFile)
    namestring <- basename(namestring)
    namestring <- gsub("00_","",namestring)
    FigNames <- as.data.frame(list.files(paste0(report_path), pattern = paste0(namestring)))
    colnames(FigNames) <- "Name"
    FigNames$Fig <- substring(FigNames$Name,1,2)
    
    FigureLocation <- "ReportOutputs"
    FigNames$Fig <- paste0(FigureLocation,"/Fig",FigNames$Fig)  
    
    
    
    for (f in 1:nrow(FigNames)){
      text$text <- gsub(FigNames$Fig[f],FigNames$Name[f],text$text,fixed = TRUE)
    }
    
    
    ReportName <- paste0("ClimateAlignmentReport_",strtrim(investor_name_select,20),"_",strtrim(portfolio_name_select,20))
    
    # if (InvestorType %in% c("InvestorSingle","InvestorMeta")){ReportName <- paste0("ClimateAlignmentReport_",investor_name_select)}
    
    ReportName <- gsub(" ","",ReportName)
    
    
    if(nchar(ReportName)>65){ReportName <- strtrim(ReportName, 65)}
    
    if (WithCompanyCharts == F){ReportName <- paste0(ReportName,"_WO_CC")}
    
    
    # Save the template file
    write_utf8_rnw(text, paste0(report_path,ReportName,".Rnw"))
    
    # write.table(text,paste0(report_path,ReportName,".Rnw"),col.names = FALSE,row.names = FALSE,quote=FALSE)  
    
    # Copy in Report Graphics
    originalloc <- paste0(getwd(),"/Templates/ReportGraphics/")  
    graphicsloc <- paste0(report_path,"ReportGraphics/")
    flist <- list.files(originalloc, full.names = TRUE)
    
    if(!dir.exists(file.path(graphicsloc))){
      dir.create(file.path(graphicsloc), showWarnings = TRUE, recursive = FALSE, mode = "0777")
      for (file in flist){file.copy(file, graphicsloc)}
    }  
    
    owd <- getwd()
    setwd(report_path)
    # Create the PDF
    knit2pdf(paste0(report_path,ReportName,".Rnw"),compiler = "xelatex")
    
    # Delete remaining files and ReportGraphics Folder
    excessfileendings <- c(".Rnw",".tex")
    file.remove(paste0(ReportName,excessfileendings))
    unlink(paste0(report_path,"ReportGraphics"),recursive = TRUE)
    
    setwd(owd)
  }
  return()
}

read_utf8_tex <-
  function(file) {
    opts <- options(encoding = "native.enc")
    on.exit(options(opts), add = TRUE)
    
    readLines(file, encoding = 'UTF-8')
  }

write_utf8_rnw <-
  function(text, file) {
    opts <- options(encoding = "native.enc")
    on.exit(options(opts), add = TRUE)
    
    con <- file(file, encoding = 'native.enc')
    writeLines(enc2utf8(text$text), con = con, useBytes = TRUE, sep = '\n')
    close(con)
  }


##############
### Charts ###
##############

SectorDataAnalysis <- function(){
  
  over <- subgroup_overview
  over <- subset(over, over$portfolio_name == portfolio_name_select & valid_input==1)
  
  over$financial_sector <-ifelse (over$financial_sector %in% c("Coal","Oil&Gas"),"Fossil Fuels",over$financial_sector)
  over$financial_sector <-ifelse (over$financial_sector %in% c("Aviation","Shipping"),"Aviation & Shipping",over$financial_sector)
  over$financial_sector <-ifelse (over$financial_sector %in% c("Steel","Cement", "Cement & Steel"),"Cement & Steel",over$financial_sector)
  over$financial_sector <-ifelse (over$financial_sector %in% c("Other"),"Not Included",over$financial_sector)
  
  
  return(over)
}


PercentageOfPortfolioAssessed <- function(plotnumber){
  
  
  over <- SectorDataAnalysis()
  
  over <- over[over$financial_sector != "Not Included",]
  #over$financial_sector <- factor(over$financial_sector, levels = c("Fossil Fuels","Power", "Automotive",
  #                                                     "Cement & Steel","Aviation & Shipping"), ordered=TRUE)
  
  over<- as.data.frame(over)
  
  if (data_check(over)){
    
    over$financial_sector <- if_else(over$financial_sector == "Cement&Steel","Cement & Steel", over$financial_sector)
    over <- over %>%  filter(!is.na(financial_sector)) 
    
    ## "steelblue" color below should be changed to whatever our Portfolio color is
    over1<- subset(over, portfolio_name == portfolio_name_select & asset_type %in% c("Equity","Bonds"))
    
    over1 <- over1 %>% group_by(investor_name,portfolio_name,asset_type,financial_sector) %>% summarise( ValueUSD = sum(valid_value_usd))
    
    
    over1$asset_type <- gsub("Bonds", BondReference,over1$asset_type)
    over1$asset_type <- gsub("Equity", "Equity",over1$asset_type)
    over1$asset_type <- factor(over1$asset_type,levels=c("Equity", BondReference)) 
    
    # if(BondReference == "Corporate bond") {
    over1$asset_type <- dplyr::recode(over1$asset_type,  "Bond" = wrap_labels(BondsTitle, 10), Equity = EquityTitle)   #
    # } else {
    # over1$asset_type <- dplyr::recode(over1$asset_type,  "Other Title" = " ", Equity = EquityTitle)  #
    # }
    
    over1$financial_sector <- factor(over1$financial_sector, levels=c("Aviation & Shipping", "Cement & Steel",
                                                                      "Automotive", "Power","Fossil Fuels"), ordered=TRUE) 
    over1$financial_sector <- dplyr::recode(over1$financial_sector, 
                                            'Fossil Fuels' = wrap_labels(S_FossilFuels, 15), 
                                            "Power" = wrap_labels(S_Power, 15), 
                                            "Automotive"  = wrap_labels(S_Automotive, 15), #
                                            'Cement & Steel' = wrap_labels(S_CementSteel, 15), 
                                            'Aviation & Shipping'= wrap_labels(S_AviationShipping, 15) ) #
    
    over_horizontal_perc <- over1 %>% group_by(asset_type) %>% 
      mutate(percfinancial_sector = ValueUSD/sum(ValueUSD)) 
    
    #ymax<-max(aggregate(over1["ValueUSD"],by=over1["asset_type"],FUN=sum)$ValueUSD)
    
    ## version horizontal percentage
    plot <- ggplot(over_horizontal_perc, aes(x = asset_type, y = percfinancial_sector, fill = financial_sector)) +
      geom_bar(position = "stack", stat = "identity",width = 0.9) +
      coord_flip() +
      scale_fill_manual(name = "", values = c(shipping, pow, trans, material, energy),drop = FALSE) + #
      #scale_x_discrete(name="Asset Type",drop=F, labels=c(BondsTitle, EquityTitle)) + #
      scale_y_continuous(name = SectorShare, labels = percent, expand = c(0,0)) +
      guides(fill = guide_legend(nrow = 2, reverse = TRUE))+
      theme_barcharts() +
      theme(plot.title = element_text(),
            legend.position = "bottom",
            legend.direction = "horizontal",
            legend.text=element_text(size=textsize),
            legend.spacing.y = unit(-22, "pt"),
            legend.box.margin = unit(c(-5, 40, -10, 10), "pt"),
            axis.line.x = element_blank(),
            axis.line.y = element_line(size = 0.5),
            axis.text.x=element_text(colour=textcolor,size=11),
            axis.text.y=element_text(colour=textcolor,size=11),
            axis.title.x = element_text(size = 11, margin = margin(3, 0, 0, 0, "pt")),
            axis.title.y = element_blank(),
            panel.grid.major.x = element_line(colour = "#989898", size = 0.2),
            plot.margin = unit(c(-2, 20, 10, 2), "pt")) +
      ggtitle("\n")
    
  }else{
    label <- Therearenoclimaterelevantequityorbondholdingsintheportfolios  #
    
    plot <- no_chart(label)
    
  }
  
  ggsave(plot, filename=graph_name(plotnumber,ParameterFile), bg = "white",height=2.3,width=4.5,dpi=ppi)   #linewidth_in*.9
}

ScopeOfAnalysis <- function(plotnumber){
  
  over <- SectorDataAnalysis()
  
  Bond_translation <- if (BondReference == "Corporate bond"){
    paste0(wrap_labels(BondsTitle, 10))            #
  }else {
    wrap_labels(Corporate_Bond_1, 10)       ## place for other category!!!
  }
  
  
  over$asset_type <- gsub("Funds", "Others", over$asset_type) #
  over$asset_type <- gsub("Bonds", Bond_translation, over$asset_type) #
  over$asset_type <- gsub("Equity", EquityTitle, over$asset_type)     #
  over$asset_type <- gsub("Others", OthersTitle, over$asset_type)     #
  
  
  over$Sector.All <- ifelse(over$financial_sector == "Not Included", "Sectors Not in Scope", "Scope of the Analysis")
  
  over <- over %>%
    ungroup() %>% 
    select(Sector.All,asset_type,valid_value_usd) %>%
    group_by(Sector.All,asset_type) %>%
    summarise(valid_value_usd = sum(valid_value_usd))
  
  
  if(data_check(over) == F){
    over <- over %>% ungroup() %>% add_row(Sector.All = "Power", asset_type =  Bond_translation, valid_value_usd = 0)
  }
  
  over <- over %>%
    complete(asset_type=c(Bond_translation,EquityTitle,OthersTitle),  #
             Sector.All = c("Sectors Not in Scope",
                            #"Other Climate Sectors",
                            "Scope of the Analysis"), 
             fill=list(valid_value_usd = 0)) %>%
    unique()
  
  over <- as.data.frame(over)
  orderofchart <- c(Bond_translation,EquityTitle,OthersTitle) #
  over$asset_type <- factor(over$asset_type,levels=orderofchart)
  over$Sector.All <- factor(over$Sector.All, levels=c("Sectors Not in Scope",
                                                      #"Other Climate Sectors",
                                                      "Scope of the Analysis"), ordered=TRUE)
  tot<- over %>%
    group_by(asset_type) %>%
    summarise(s=sum(valid_value_usd))
  
  # for NEW VERSION horizontal chart
  over_horizontal_chart <- over %>% filter(asset_type != OthersTitle)
  
  annotate.position <- over_horizontal_chart %>% group_by(asset_type) %>% summarize(sumValueUSD = sum(valid_value_usd)) %>% 
    summarize(maxsumValueUSD = max(sumValueUSD))
  
  annotate.label <- over_horizontal_chart %>% filter(Sector.All == "Scope of the Analysis")
  
  number_cifer <- nchar(round(annotate.position$maxsumValueUSD, digits = 0))
  
  breaks_by <- function(number_cifer){
    10^(number_cifer-1)
  }
  breaks_interval <- breaks_by(number_cifer)
  
  plot <- ggplot(over_horizontal_chart, aes(x = fct_rev(asset_type), y=valid_value_usd, fill=Sector.All)) +
    geom_bar(position="stack", stat="identity", width = 0.9) +
    coord_flip() +
    scale_fill_manual(name="", labels=c(SectorsNotinScope,
                                        # OtherClimateRelevantSectors,
                                        SectorsinScenarioAnalysis),
                      values=c("grey80", 
                               #"#deebf7",
                               "#265b9b"),drop = FALSE) + #
    #scale_x_discrete(name="Asset Type", labels = x_labels) +
    scale_y_continuous(name=MarketValue, labels=comprss, expand=c(0, 0, 0, 0), 
                       breaks = seq(0, annotate.position$maxsumValueUSD, by = breaks_interval*2)) + #breaks = scales::pretty_breaks(n = 3)) +   #
    # limits = c(0, annotate.position$maxsumValueUSD+0.3*annotate.position$maxsumValueUSD)) +     #
    guides(fill=guide_legend(nrow=1, byrow = TRUE, reverse = TRUE))+
    theme_barcharts() +
    theme(plot.title = element_text(colour="#265b9b",size=11, hjust = 1),
          legend.position = "bottom",
          legend.text=element_text(size=textsize),
          legend.box.margin = unit(c(-15, 60, -10, 0), "pt"),
          legend.spacing.y = unit(0, "pt"),
          axis.line.x = element_blank(),
          axis.line.y = element_line(size = 0.5),
          axis.text.x=element_text(colour=textcolor,size=11),
          axis.text.y=element_text(colour=textcolor,size=11),
          axis.title.x = element_text(colour=textcolor, size = 11, margin = margin(5, 0, 0, 0, "pt"), hjust = 0.3),
          axis.title.y = element_blank(),
          panel.grid.major.x = element_line(colour = "#989898", size = 0.2),
          plot.margin = unit(c(5, 10, 10, 2), "pt")) +
    annotate("text", x = annotate.label$asset_type, y = annotate.position$maxsumValueUSD + 0.35*annotate.position$maxsumValueUSD,
             # label = wrap_labels(paste0(comma(round(annotate.label$valid_value_usd, digits = 0))), 10),
             label = comprss(annotate.label$valid_value_usd), 
             family = textfont, colour="#265b9b", hjust = 1) +
    ggtitle(Climaterelevantsectors)
  
  
  ggsave(plot,filename=graph_name(plotnumber,ParameterFile), bg = "white",height=2.2,width=4.5,dpi=ppi)   #linewidth_in*.9
  
}