R/validationSummary.R
In pik-piam/remind: The REMIND R Package
Defines functions
validationSummary
Documented in
validationSummary
#' @title validationSummary
#' @description Create validationSummary.pdf from REMIND output and corresponding historical.mif with most important variables
#'
#' @export
#'
#' @param gdx GDX file
#' @param hist Validation data.All formats allowed which can be converted to quitte (including characters containing the path to a mif file)
#' @param outfile file name of the output pdf
#' @param reportfile file name to which a backup of the magpie reporting should be written (file ending should be ".mif"). No report written if set to NULL.
#' @param ... additional arguments supplied to the validationpdf function
#' @author David Klein, Lavinia Baumstark
#' @examples
#'
#' \dontrun{
#' validationSummary(gdx="fulldata.gdx",hist="historical.mif")
#' }
#'
#' @importFrom lusweave swopen swlatex swclose swtable swfigure
#' @importFrom luplot plotcountrymap
#' @importFrom utils capture.output
#' @importFrom mip plotstyle mipArea
#' @importFrom ggplot2 theme
#' @importFrom magclass getYears
validationSummary <- function(gdx, hist, reportfile=NULL, outfile="validationSummary.pdf", ...) {
# ---- If not provided produce REMIND mif now ----
# if no reporting-mif-file is provided c reporting
if(is.null(reportfile)){
cat("No REMIND reporting file required for producing the validationSummary.pdf was provided. Calling convGDX2MIF to produce it.\n")
reportfile <- convGDX2MIF(gdx)
}
data <- read.report(reportfile,as.list=FALSE)
data <- collapseNames(data)
data <- data[,getYears(data)<="y2100",]
# ---- Start PDF ----
template <- c("\\documentclass[a4paper, portrait ]{article}",
"\\setlength{\\oddsidemargin}{-0.8in}",
"\\setlength{\\evensidemargin}{-0.5in}",
"\\setlength{\\topmargin}{-0.8in}",
"\\setlength{\\parindent}{0in}",
"\\setlength{\\headheight}{0in}",
"\\setlength{\\topskip}{0in}",
"\\setlength{\\headsep}{0in}",
"\\setlength{\\footskip}{0.2in}",
"\\setlength\\textheight{0.95\\paperheight}",
"\\setlength\\textwidth{0.95\\paperwidth}",
"\\setlength{\\parindent}{0in}",
"\\usepackage{float}",
"\\usepackage[bookmarksopenlevel=section,colorlinks=true,linkbordercolor={0.9882353 0.8352941 0.7098039}]{hyperref}",
"\\hypersetup{bookmarks=true,pdfauthor={GES group, PIK}}",
"\\usepackage{graphicx}",
"\\usepackage[strings]{underscore}",
"\\usepackage{Sweave}",
"\\begin{document}",
"<<echo=false>>=",
"options(width=110)",
"@")
sw <- swopen(outfile = outfile, template = template)
swlatex(sw,c("\\title{Summary of REMIND results}","\\maketitle","\\tableofcontents"))
#on.exit(swclose(sw, clean_output=FALSE, engine="knitr"))
# ---- ToDo ----
# - GLO-Figure zu gross: fig.width funktioniert nicht
### Area plots (including history if available)
### Seitenaufbau: oben: grosser Plot mit globalen Werten
### unten: Regionen (per automatischem facet_wrap in mipArea)
# - FE by sector
# - non-electric SE
# - Trade
# - CH4 and N2O by source
### Line plots
### Further information
# - Mitigation costs
### Wenn es Ampeln zur Bewertung der Uebereinstimmung mit der Historie gibt, die wichtigsten auf einer Seite sammeln
# ---- Overview ----
swlatex(sw,"\\section{Overview}")
# ---- CO2 price (log) ----
swlatex(sw,"\\subsection{CO2 prices}")
swfigure(sw,mipLineHistorical,data["GLO",,"Price|Carbon (US$2005/t CO2)"],x_hist=NULL,
ylab='Price|Carbon_log [US$2005/t CO2]',ybreaks=c(20,30,40,50,60,75,100,200,500,1000,2000,3000),
ylim=c(20,3000),ylog=TRUE,sw_option="height=10,width=9")
# ---- CO2 emissions ----
swlatex(sw,"\\subsection{CO2 emissions}")
# calculate new variables - now moved to reportCrossVariables.R
var.tot <-"Emi|CO2 (Mt CO2/yr)"
vars <- c("Emi|CO2|Energy|Supply|Non-Elec (Mt CO2/yr)",
"Emi|CO2|Energy|Supply|Electricity|Gross (Mt CO2/yr)",
"Emi|CO2|Energy|Demand|Industry|Gross (Mt CO2/yr)",
"Emi|CO2|FFaI|Industry|Process (Mt CO2/yr)",
# "Emi|CO2|Industrial Processes (Mt CO2/yr)",
"Emi|CO2|Buildings|Direct (Mt CO2/yr)",
"Emi|CO2|Transport|Demand (Mt CO2/yr)",
"Emi|CO2|Carbon Capture and Storage|Biomass|Neg (Mt CO2/yr)",
"Emi|CO2|Land-Use Change (Mt CO2/yr)",
NULL)
p <- mipArea(data["GLO",,vars], total = data["GLO",,var.tot]) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = data[,,var.tot]["GLO",,invert=TRUE])
swfigure(sw,print,p,fig.width=1)
# ---- PE ----
swlatex(sw,"\\subsection{PE}")
#var.tot <-"PE (EJ/yr)"
vars <- c("PE|Coal|w/ CCS (EJ/yr)",
"PE|Coal|w/o CCS (EJ/yr)",
"PE|+|Oil (EJ/yr)",
"PE|Gas|w/ CCS (EJ/yr)",
"PE|Gas|w/o CCS (EJ/yr)",
"PE|Biomass|w/ CCS (EJ/yr)",
"PE|Biomass|w/o CCS (EJ/yr)",
"PE|+|Nuclear (EJ/yr)",
"PE|+|Hydro (EJ/yr)",
"PE|+|Geothermal (EJ/yr)",
"PE|+|Solar (EJ/yr)",
"PE|+|Wind (EJ/yr)")
p <- mipArea(data["GLO",,vars], total = FALSE) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = FALSE)
swfigure(sw,print,p,fig.width=1)
# ---- SE Electricity ----
swlatex(sw,"\\subsection{SE Electricity}")
var.tot <-"SE|Electricity (EJ/yr)"
vars <- c("SE|Electricity|Coal|w/ CCS (EJ/yr)",
"SE|Electricity|Coal|w/o CCS (EJ/yr)",
"SE|Electricity|Oil (EJ/yr)",
"SE|Electricity|Gas|w/ CCS (EJ/yr)",
"SE|Electricity|Gas|w/o CCS (EJ/yr)",
"SE|Electricity|Biomass|w/ CCS (EJ/yr)",
"SE|Electricity|Biomass|w/o CCS (EJ/yr)",
"SE|Electricity|Nuclear (EJ/yr)",
"SE|Electricity|Hydrogen (EJ/yr)",
"SE|Electricity|Solar (EJ/yr)",
"SE|Electricity|Wind (EJ/yr)",
"SE|Electricity|Geothermal (EJ/yr)",
"SE|Electricity|Hydro (EJ/yr)"
)
p <- mipArea(data["GLO",,vars], total = data["GLO",,var.tot]) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = data[,,var.tot]["GLO",,invert=TRUE])
swfigure(sw,print,p,fig.width=1)
# ---- FE ----
swlatex(sw,"\\subsection{FE}")
#var.tot <-"FE (EJ/yr)"
vars <- c("FE|+|Solids (EJ/yr)",
"FE|+|Liquids (EJ/yr)",
"FE|+|Gases (EJ/yr)",
"FE|+|Heat (EJ/yr)",
"FE|+|Electricity (EJ/yr)",
"FE|+|Hydrogen (EJ/yr)"#,
#"FE|Solar (EJ/yr)",
#"FE|Other (EJ/yr)"
)
p <- mipArea(data["GLO",,vars], total = FALSE) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = FALSE)
swfigure(sw,print,p,fig.width=1)
# ---- FE Transport ----
swlatex(sw,"\\subsection{FE Transport}")
var.tot <-"FE|Transport (EJ/yr)"
vars <- c("FE|Transport|Liquids (EJ/yr)",
"FE|Transport|Gases (EJ/yr)",
"FE|Transport|Electricity (EJ/yr)",
"FE|Transport|Hydrogen (EJ/yr)"
)
p <- mipArea(data["GLO",,vars], total = data["GLO",,var.tot]) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = data[,,var.tot]["GLO",,invert=TRUE])
swfigure(sw,print,p,fig.width=1)
#---- FE Industry ----
swlatex(sw,"\\subsection{FE Industry}")
var.tot <-"FE|Industry (EJ/yr)"
vars <- c("FE|Industry|Electricity (EJ/yr)",
"FE|Industry|Heat (EJ/yr)",
"FE|Industry|Gases (EJ/yr)",
"FE|Industry|Hydrogen (EJ/yr)",
"FE|Industry|Liquids (EJ/yr)",
"FE|Industry|Solids|Coal (EJ/yr)",
"FE|Industry|Solids|Biomass (EJ/yr)"#,
#"FE|Industry|Other (EJ/yr)"
)
p <- mipArea(data["GLO",,vars], total = data["GLO",,var.tot]) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = data[,,var.tot]["GLO",,invert=TRUE])
swfigure(sw,print,p,fig.width=1)
#---- FE Residential and Commercial ----
swlatex(sw,"\\subsection{FE Buildings}")
var.tot <-"FE|Buildings (EJ/yr)"
vars <- c("FE|Buildings|Electricity (EJ/yr)",
"FE|Buildings|Heat (EJ/yr)",
"FE|Buildings|Gases (EJ/yr)",
"FE|Buildings|Hydrogen (EJ/yr)",
"FE|Buildings|Liquids (EJ/yr)",
"FE|Buildings|Solids|Coal (EJ/yr)",
"FE|Buildings|Solids|Biomass (EJ/yr)"
)
# Global plot, FE
p <- mipArea(data["GLO",,vars], total = data["GLO",,var.tot]) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
#Regional plots, FE
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = data[,,var.tot]["GLO",,invert=TRUE])
swfigure(sw,print,p,fig.width=1)
# ---- FE prices ----
swlatex(sw,"\\subsection{FE prices}")
vars_price <- c(grep("Price\\|Final Energy\\|(Transport|Buildings|Industry) \\(US\\$2005/GJ\\)$", getNames(data),value = T),
grep("Price\\|Final Energy\\|Electricity\\|(Transport|Buildings|Industry) \\(US\\$2005/GJ\\)$", getNames(data),value = T),
grep("Price\\|Final Energy\\|Liquids\\|(Transport|Buildings|Industry) \\(US\\$2005/GJ\\)$", getNames(data),value = T),
grep("Price\\|Final Energy\\|Heating Oil\\|(Transport|Buildings|Industry) \\(US\\$2005/GJ\\)$", getNames(data),value = T),
grep("Price\\|Final Energy\\|Gases\\|(Transport|Buildings|Industry) \\(US\\$2005/GJ\\)$", getNames(data),value = T)
)
for (var_price in vars_price){
if ( var_price %in% magclass::getNames(data))
var_price_title = gsub("\\(" , "[" , var_price)
var_price_title = gsub("\\)" , "]" , var_price_title)
swfigure(sw,mipLineHistorical, data[,,var_price],x_hist=NULL,
ylab = var_price_title, color.dim = "region", facet.dim = "scenario",
color.dim.name = "Region",
legend.ncol=8,plot.priority=c("x_hist","x","x_proj"),sw_option="height=10,width=9")
}
# ---- Meta Information ----
swlatex(sw,"\\section{Meta information}")
# ---- Region map ----
swlatex(sw,"\\subsection{World regions}")
regi2iso <- readGDX(gdx,"regi2iso", react="silent")
if(!is.null(regi2iso)) {
map <- as.magpie(regi2iso[2:1],spatial=1)
col <- plotstyle(levels(as.factor(regi2iso[[1]])))
tmpplot <- function(...) {
a <- capture.output(plotcountrymap(...))
}
swfigure(sw,tmpplot,map,colourPalette=col,catMethod="categorical", mapTitle="", fig.orientation="landscape")
} else {
swlatex(sw,"Could not find mapping (regi2iso) between countries and regions in gdx file!")
}
# ---- Modelstatus ----
swlatex(sw,"\\subsection{Modelstat}")
repy <- readGDX(gdx,"p80_repy", react="silent")
if(!is.null(repy)) {
modstat <- repy[,,"modelstat"]
swtable(sw,modstat,table.placement="H",caption.placement="top",transpose=TRUE,caption="main",vert.lines=1,align="c")
} else {
swlatex(sw,"Could not find p80_repy (only in Nash available) in gdx file!")
}
# ---- Objective function (global/regional welfare) ----
swlatex(sw,"\\subsection{Objective function value}")
welf <- readGDX(gdx,c("v02_welfare","v_welfare"), react="silent")
if(!is.null(welf)) {
welf <- welf[,,"l"]
swtable(sw,welf,table.placement="H",caption.placement="top",transpose=TRUE,caption="Welfare",vert.lines=1,align="c")
} else {
swlatex(sw,"Could not find welfare value (v02_welfare, v_welfare) in gdx file!")
}
swclose(sw, clean_output=FALSE, engine="knitr")
}
pik-piam/remind documentation built on Sept. 9, 2021, 1:09 p.m.
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Defines functions validationSummary
Documented in validationSummary
#' @title validationSummary
#' @description Create validationSummary.pdf from REMIND output and corresponding historical.mif with most important variables
#'
#' @export
#'
#' @param gdx GDX file
#' @param hist Validation data.All formats allowed which can be converted to quitte (including characters containing the path to a mif file)
#' @param outfile file name of the output pdf
#' @param reportfile file name to which a backup of the magpie reporting should be written (file ending should be ".mif"). No report written if set to NULL.
#' @param ... additional arguments supplied to the validationpdf function
#' @author David Klein, Lavinia Baumstark
#' @examples
#'
#' \dontrun{
#' validationSummary(gdx="fulldata.gdx",hist="historical.mif")
#' }
#'
#' @importFrom lusweave swopen swlatex swclose swtable swfigure
#' @importFrom luplot plotcountrymap
#' @importFrom utils capture.output
#' @importFrom mip plotstyle mipArea
#' @importFrom ggplot2 theme
#' @importFrom magclass getYears
validationSummary <- function(gdx, hist, reportfile=NULL, outfile="validationSummary.pdf", ...) {
# ---- If not provided produce REMIND mif now ----
# if no reporting-mif-file is provided c reporting
if(is.null(reportfile)){
cat("No REMIND reporting file required for producing the validationSummary.pdf was provided. Calling convGDX2MIF to produce it.\n")
reportfile <- convGDX2MIF(gdx)
}
data <- read.report(reportfile,as.list=FALSE)
data <- collapseNames(data)
data <- data[,getYears(data)<="y2100",]
# ---- Start PDF ----
template <- c("\\documentclass[a4paper, portrait ]{article}",
"\\setlength{\\oddsidemargin}{-0.8in}",
"\\setlength{\\evensidemargin}{-0.5in}",
"\\setlength{\\topmargin}{-0.8in}",
"\\setlength{\\parindent}{0in}",
"\\setlength{\\headheight}{0in}",
"\\setlength{\\topskip}{0in}",
"\\setlength{\\headsep}{0in}",
"\\setlength{\\footskip}{0.2in}",
"\\setlength\\textheight{0.95\\paperheight}",
"\\setlength\\textwidth{0.95\\paperwidth}",
"\\setlength{\\parindent}{0in}",
"\\usepackage{float}",
"\\usepackage[bookmarksopenlevel=section,colorlinks=true,linkbordercolor={0.9882353 0.8352941 0.7098039}]{hyperref}",
"\\hypersetup{bookmarks=true,pdfauthor={GES group, PIK}}",
"\\usepackage{graphicx}",
"\\usepackage[strings]{underscore}",
"\\usepackage{Sweave}",
"\\begin{document}",
"<<echo=false>>=",
"options(width=110)",
"@")
sw <- swopen(outfile = outfile, template = template)
swlatex(sw,c("\\title{Summary of REMIND results}","\\maketitle","\\tableofcontents"))
#on.exit(swclose(sw, clean_output=FALSE, engine="knitr"))
# ---- ToDo ----
# - GLO-Figure zu gross: fig.width funktioniert nicht
### Area plots (including history if available)
### Seitenaufbau: oben: grosser Plot mit globalen Werten
### unten: Regionen (per automatischem facet_wrap in mipArea)
# - FE by sector
# - non-electric SE
# - Trade
# - CH4 and N2O by source
### Line plots
### Further information
# - Mitigation costs
### Wenn es Ampeln zur Bewertung der Uebereinstimmung mit der Historie gibt, die wichtigsten auf einer Seite sammeln
# ---- Overview ----
swlatex(sw,"\\section{Overview}")
# ---- CO2 price (log) ----
swlatex(sw,"\\subsection{CO2 prices}")
swfigure(sw,mipLineHistorical,data["GLO",,"Price|Carbon (US$2005/t CO2)"],x_hist=NULL,
ylab='Price|Carbon_log [US$2005/t CO2]',ybreaks=c(20,30,40,50,60,75,100,200,500,1000,2000,3000),
ylim=c(20,3000),ylog=TRUE,sw_option="height=10,width=9")
# ---- CO2 emissions ----
swlatex(sw,"\\subsection{CO2 emissions}")
# calculate new variables - now moved to reportCrossVariables.R
var.tot <-"Emi|CO2 (Mt CO2/yr)"
vars <- c("Emi|CO2|Energy|Supply|Non-Elec (Mt CO2/yr)",
"Emi|CO2|Energy|Supply|Electricity|Gross (Mt CO2/yr)",
"Emi|CO2|Energy|Demand|Industry|Gross (Mt CO2/yr)",
"Emi|CO2|FFaI|Industry|Process (Mt CO2/yr)",
# "Emi|CO2|Industrial Processes (Mt CO2/yr)",
"Emi|CO2|Buildings|Direct (Mt CO2/yr)",
"Emi|CO2|Transport|Demand (Mt CO2/yr)",
"Emi|CO2|Carbon Capture and Storage|Biomass|Neg (Mt CO2/yr)",
"Emi|CO2|Land-Use Change (Mt CO2/yr)",
NULL)
p <- mipArea(data["GLO",,vars], total = data["GLO",,var.tot]) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = data[,,var.tot]["GLO",,invert=TRUE])
swfigure(sw,print,p,fig.width=1)
# ---- PE ----
swlatex(sw,"\\subsection{PE}")
#var.tot <-"PE (EJ/yr)"
vars <- c("PE|Coal|w/ CCS (EJ/yr)",
"PE|Coal|w/o CCS (EJ/yr)",
"PE|+|Oil (EJ/yr)",
"PE|Gas|w/ CCS (EJ/yr)",
"PE|Gas|w/o CCS (EJ/yr)",
"PE|Biomass|w/ CCS (EJ/yr)",
"PE|Biomass|w/o CCS (EJ/yr)",
"PE|+|Nuclear (EJ/yr)",
"PE|+|Hydro (EJ/yr)",
"PE|+|Geothermal (EJ/yr)",
"PE|+|Solar (EJ/yr)",
"PE|+|Wind (EJ/yr)")
p <- mipArea(data["GLO",,vars], total = FALSE) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = FALSE)
swfigure(sw,print,p,fig.width=1)
# ---- SE Electricity ----
swlatex(sw,"\\subsection{SE Electricity}")
var.tot <-"SE|Electricity (EJ/yr)"
vars <- c("SE|Electricity|Coal|w/ CCS (EJ/yr)",
"SE|Electricity|Coal|w/o CCS (EJ/yr)",
"SE|Electricity|Oil (EJ/yr)",
"SE|Electricity|Gas|w/ CCS (EJ/yr)",
"SE|Electricity|Gas|w/o CCS (EJ/yr)",
"SE|Electricity|Biomass|w/ CCS (EJ/yr)",
"SE|Electricity|Biomass|w/o CCS (EJ/yr)",
"SE|Electricity|Nuclear (EJ/yr)",
"SE|Electricity|Hydrogen (EJ/yr)",
"SE|Electricity|Solar (EJ/yr)",
"SE|Electricity|Wind (EJ/yr)",
"SE|Electricity|Geothermal (EJ/yr)",
"SE|Electricity|Hydro (EJ/yr)"
)
p <- mipArea(data["GLO",,vars], total = data["GLO",,var.tot]) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = data[,,var.tot]["GLO",,invert=TRUE])
swfigure(sw,print,p,fig.width=1)
# ---- FE ----
swlatex(sw,"\\subsection{FE}")
#var.tot <-"FE (EJ/yr)"
vars <- c("FE|+|Solids (EJ/yr)",
"FE|+|Liquids (EJ/yr)",
"FE|+|Gases (EJ/yr)",
"FE|+|Heat (EJ/yr)",
"FE|+|Electricity (EJ/yr)",
"FE|+|Hydrogen (EJ/yr)"#,
#"FE|Solar (EJ/yr)",
#"FE|Other (EJ/yr)"
)
p <- mipArea(data["GLO",,vars], total = FALSE) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = FALSE)
swfigure(sw,print,p,fig.width=1)
# ---- FE Transport ----
swlatex(sw,"\\subsection{FE Transport}")
var.tot <-"FE|Transport (EJ/yr)"
vars <- c("FE|Transport|Liquids (EJ/yr)",
"FE|Transport|Gases (EJ/yr)",
"FE|Transport|Electricity (EJ/yr)",
"FE|Transport|Hydrogen (EJ/yr)"
)
p <- mipArea(data["GLO",,vars], total = data["GLO",,var.tot]) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = data[,,var.tot]["GLO",,invert=TRUE])
swfigure(sw,print,p,fig.width=1)
#---- FE Industry ----
swlatex(sw,"\\subsection{FE Industry}")
var.tot <-"FE|Industry (EJ/yr)"
vars <- c("FE|Industry|Electricity (EJ/yr)",
"FE|Industry|Heat (EJ/yr)",
"FE|Industry|Gases (EJ/yr)",
"FE|Industry|Hydrogen (EJ/yr)",
"FE|Industry|Liquids (EJ/yr)",
"FE|Industry|Solids|Coal (EJ/yr)",
"FE|Industry|Solids|Biomass (EJ/yr)"#,
#"FE|Industry|Other (EJ/yr)"
)
p <- mipArea(data["GLO",,vars], total = data["GLO",,var.tot]) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = data[,,var.tot]["GLO",,invert=TRUE])
swfigure(sw,print,p,fig.width=1)
#---- FE Residential and Commercial ----
swlatex(sw,"\\subsection{FE Buildings}")
var.tot <-"FE|Buildings (EJ/yr)"
vars <- c("FE|Buildings|Electricity (EJ/yr)",
"FE|Buildings|Heat (EJ/yr)",
"FE|Buildings|Gases (EJ/yr)",
"FE|Buildings|Hydrogen (EJ/yr)",
"FE|Buildings|Liquids (EJ/yr)",
"FE|Buildings|Solids|Coal (EJ/yr)",
"FE|Buildings|Solids|Biomass (EJ/yr)"
)
# Global plot, FE
p <- mipArea(data["GLO",,vars], total = data["GLO",,var.tot]) + theme(legend.position="none")
swfigure(sw,print,p,fig.width=0.5)
#Regional plots, FE
p <- mipArea(data[,,vars]["GLO",,invert=TRUE], total = data[,,var.tot]["GLO",,invert=TRUE])
swfigure(sw,print,p,fig.width=1)
# ---- FE prices ----
swlatex(sw,"\\subsection{FE prices}")
vars_price <- c(grep("Price\\|Final Energy\\|(Transport|Buildings|Industry) \\(US\\$2005/GJ\\)$", getNames(data),value = T),
grep("Price\\|Final Energy\\|Electricity\\|(Transport|Buildings|Industry) \\(US\\$2005/GJ\\)$", getNames(data),value = T),
grep("Price\\|Final Energy\\|Liquids\\|(Transport|Buildings|Industry) \\(US\\$2005/GJ\\)$", getNames(data),value = T),
grep("Price\\|Final Energy\\|Heating Oil\\|(Transport|Buildings|Industry) \\(US\\$2005/GJ\\)$", getNames(data),value = T),
grep("Price\\|Final Energy\\|Gases\\|(Transport|Buildings|Industry) \\(US\\$2005/GJ\\)$", getNames(data),value = T)
)
for (var_price in vars_price){
if ( var_price %in% magclass::getNames(data))
var_price_title = gsub("\\(" , "[" , var_price)
var_price_title = gsub("\\)" , "]" , var_price_title)
swfigure(sw,mipLineHistorical, data[,,var_price],x_hist=NULL,
ylab = var_price_title, color.dim = "region", facet.dim = "scenario",
color.dim.name = "Region",
legend.ncol=8,plot.priority=c("x_hist","x","x_proj"),sw_option="height=10,width=9")
}
# ---- Meta Information ----
swlatex(sw,"\\section{Meta information}")
# ---- Region map ----
swlatex(sw,"\\subsection{World regions}")
regi2iso <- readGDX(gdx,"regi2iso", react="silent")
if(!is.null(regi2iso)) {
map <- as.magpie(regi2iso[2:1],spatial=1)
col <- plotstyle(levels(as.factor(regi2iso[[1]])))
tmpplot <- function(...) {
a <- capture.output(plotcountrymap(...))
}
swfigure(sw,tmpplot,map,colourPalette=col,catMethod="categorical", mapTitle="", fig.orientation="landscape")
} else {
swlatex(sw,"Could not find mapping (regi2iso) between countries and regions in gdx file!")
}
# ---- Modelstatus ----
swlatex(sw,"\\subsection{Modelstat}")
repy <- readGDX(gdx,"p80_repy", react="silent")
if(!is.null(repy)) {
modstat <- repy[,,"modelstat"]
swtable(sw,modstat,table.placement="H",caption.placement="top",transpose=TRUE,caption="main",vert.lines=1,align="c")
} else {
swlatex(sw,"Could not find p80_repy (only in Nash available) in gdx file!")
}
# ---- Objective function (global/regional welfare) ----
swlatex(sw,"\\subsection{Objective function value}")
welf <- readGDX(gdx,c("v02_welfare","v_welfare"), react="silent")
if(!is.null(welf)) {
welf <- welf[,,"l"]
swtable(sw,welf,table.placement="H",caption.placement="top",transpose=TRUE,caption="Welfare",vert.lines=1,align="c")
} else {
swlatex(sw,"Could not find welfare value (v02_welfare, v_welfare) in gdx file!")
}
swclose(sw, clean_output=FALSE, engine="knitr")
}
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