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Commit 3987611b authored by Lavinia Baumstark's avatar Lavinia Baumstark
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remove start_functions.R, adapt start_bundle_climate.R

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1 merge request!34Refactoring start scripts (yeah!)
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# | (C) 2006-2019 Potsdam Institute for Climate Impact Research (PIK)
# | authors, and contributors see CITATION.cff file. This file is part
# | of REMIND and licensed under AGPL-3.0-or-later. Under Section 7 of
# | AGPL-3.0, you are granted additional permissions described in the
# | REMIND License Exception, version 1.0 (see LICENSE file).
# | Contact: remind@pik-potsdam.de
start_run <- function(cfg, scenario = NULL, report = NULL, sceninreport = NULL, coupled = F, force = FALSE) {
# Load libraries
require(lucode, quietly = TRUE,warn.conflicts =FALSE)
require(magclass, quietly = TRUE,warn.conflicts =FALSE)
require(tools, quietly = TRUE,warn.conflicts =FALSE)
require(remind, quietly = TRUE,warn.conflicts =FALSE)
require(moinput)
require(mrvalidation)
.copy.fromlist <- function(filelist,destfolder) {
if(is.null(names(filelist))) names(filelist) <- rep("",length(filelist))
for(i in 1:length(filelist)) {
if(!is.na(filelist[i])) {
to <- paste0(destfolder,"/",names(filelist)[i])
if(!file.copy(filelist[i],to=to,recursive=dir.exists(to),overwrite=T))
cat(paste0("Could not copy ",filelist[i]," to ",to,"\n"))
}
}
}
# Store REMIND-root directory
maindir <- getwd()
on.exit(setwd(maindir))
# Is the run performed on the cluster?
on_cluster <- file.exists('/p')
# Adapt configuration to predifined scenario, if given
if(!is.null(scenario))
cfg <- setScenario(cfg, scenario)
# Check configuration for consistency
cfg <- check_config(cfg, settings_config = "config/settings_config.csv")
###-------- do update of input files based on previous runs if applicable ------###
if(!is.null(cfg$gms$carbonprice) && (cfg$gms$carbonprice == "NDC2018")){
source("scripts/input/prepare_NDC2018.R")
prepare_NDC2018(as.character(cfg$files2export$start["input_ref.gdx"]))
}
## the following is outcommented because by now it has to be done by hand ( currently only one gdx is handed to the next run, so it is impossible to fix to one run and use the tax from another run)
## Update CO2 tax information for exogenous carbon price runs with the same CO2 price as a previous run
#if(!is.null(cfg$gms$carbonprice) && (cfg$gms$carbonprice == "ExogSameAsPrevious")){
# source("scripts/input/create_ExogSameAsPrevious_CO2price_file.R")
# create_ExogSameAsPrevious_CO2price_file(as.character(cfg$files2export$start["input_ref.gdx"]))
#}
#AJS
if ( (cfg$gms$optimization != 'nash') & (cfg$gms$subsidizeLearning == 'globallyOptimal') ) {
cat("Only optimization='nash' is compatible with subsudizeLearning='globallyOptimal'. Switching subsidizeLearning to 'off' now. \n")
cfg$gms$subsidizeLearning = 'off'
}
# reportCEScalib only works with the calibrate module
if ( cfg$gms$CES_parameters != "calibrate" ) cfg$output <- setdiff(cfg$output,"reportCEScalib")
#AJS quit if title is too long - GAMS can't handle that
if( nchar(cfg$title) > 75 | grepl("\\.",cfg$title) ) {
stop("This title is too long or the name contains dots - GAMS would not tolerate this, and quit working at a point where you least expect it. Stopping now. ")
}
# Calculate CES configuration string
cfg$gms$cm_CES_configuration <- paste0("stat_",cfg$gms$stationary,"-",
"indu_",cfg$gms$industry,"-",
"buil_",cfg$gms$buildings,"-",
"tran_",cfg$gms$transport,"-",
"POP_", cfg$gms$cm_POPscen, "-",
"GDP_", cfg$gms$cm_GDPscen, "-",
"Kap_", cfg$gms$capitalMarket, "-",
"Reg_", substr(regionscode(cfg$regionmapping),1,10))
# write name of corresponding CES file to datainput.gms
replace_in_file(file = "./modules/29_CES_parameters/load/datainput.gms",
content = paste0('$include "./modules/29_CES_parameters/load/input/',cfg$gms$cm_CES_configuration,'.inc"'),
subject = "CES INPUT")
# adjust GDPpcScen based on GDPscen
cfg$gms$c_GDPpcScen <- gsub("gdp_","",cfg$gms$cm_GDPscen)
# Make sure all MAGICC files have LF line endings, so Fortran won't crash
if (on_cluster)
system("find ./core/magicc/ -type f | xargs dos2unix -q")
# Set source_include so that loaded scripts know they are included as
# source (instead a load from command line)
source_include <- TRUE
################## M O D E L L O C K ###################################
# Lock the directory for other instances of the start scritps
lock_id <- model_lock(timeout1 = 1, oncluster=on_cluster)
on.exit(model_unlock(lock_id, oncluster=on_cluster))
################## M O D E L L O C K ###################################
# If report and scenname are supplied the data of this scenario in the report will be converted to REMIND input
# Used for REMIND-MAgPIE coupling
if (!is.null(report) && !is.null(sceninreport)) {
getReportData(report,sceninreport,inputpath_mag=cfg$gms$biomass,inputpath_acc=cfg$gms$agCosts)
}
# Update module paths in GAMS code
update_modules_embedding()
# configure main model gms file (cfg$model) based on settings of cfg file
cfg$gms$c_expname <- cfg$title
# run main.gms if not further specified
if(is.null(cfg$model)) cfg$model <- "main.gms"
manipulateConfig(cfg$model, cfg$gms)
# Check all setglobal settings for consistency
settingsCheck()
###########################################################################################################
############# PROCESSING INPUT DATA ###################### START ##########################################
###########################################################################################################
########## declare functions for updating information ################
update_info <- function(regionscode,revision) {
subject <- 'VERSION INFO'
content <- c('',
paste('Regionscode:',regionscode),
'',
paste('Input data revision:',revision),
'',
paste('Last modification (input data):',date()),
'')
replace_in_file(cfg$model,paste('*',content),subject)
}
update_sets <- function(map) {
.tmp <- function(x,prefix="", suffix1="", suffix2=" /", collapse=",", n=10) {
content <- NULL
tmp <- lapply(split(x, ceiling(seq_along(x)/n)),paste,collapse=collapse)
end <- suffix1
for(i in 1:length(tmp)) {
if(i==length(tmp)) end <- suffix2
content <- c(content,paste0(' ',prefix,tmp[[i]],end))
}
return(content)
}
modification_warning <- c(
'*** THIS CODE IS CREATED AUTOMATICALLY, DO NOT MODIFY THESE LINES DIRECTLY',
'*** ANY DIRECT MODIFICATION WILL BE LOST AFTER NEXT INPUT DOWNLOAD',
'*** CHANGES CAN BE DONE USING THE RESPECTIVE LINES IN scripts/start_functions.R')
content <- c(modification_warning,'','sets')
# write iso set with nice formatting (10 countries per line)
tmp <- lapply(split(map$CountryCode, ceiling(seq_along(map$CountryCode)/10)),paste,collapse=",")
regions <- levels(map$RegionCode)
content <- c(content, '',paste(' all_regi "all regions" /',paste(regions,collapse=','),'/',sep=''),'')
# Creating sets for H12 subregions
subsets <- toolRegionSubsets(map=cfg$regionmapping)
if(is.null(subsets[["EUR"]]))
subsets[["EUR"]] <- c("EUR")
content <- c(content, paste(' ext_regi "extended regions list (includes subsets of H12 regions)" / ', paste(c(paste0(names(subsets),"_regi"),regions),collapse=','),' /',sep=''),'')
content <- c(content, ' regi_group(ext_regi,all_regi) "region groups (regions that together corresponds to a H12 region)"')
content <- c(content, ' /')
for (i in 1:length(subsets)){
content <- c(content, paste0(' ', paste(c(paste0(names(subsets)[i],"_regi"))), ' .(',paste(subsets[[i]],collapse=','), ')'))
}
content <- c(content, ' /')
content <- c(content, ' ')
# iso countries set
content <- c(content,' iso "list of iso countries" /')
content <- c(content, .tmp(map$CountryCode, suffix1=",", suffix2=" /"),'')
content <- c(content,' regi2iso(all_regi,iso) "mapping regions to iso countries"',' /')
for(i in levels(map$RegionCode)) {
content <- c(content, .tmp(map$CountryCode[map$RegionCode==i], prefix=paste0(i," . ("), suffix1=")", suffix2=")"))
}
content <- c(content,' /')
content <- c(content, 'iso_regi "all iso countries and EU and greater China region" / EUR,CHA,')
content <- c(content, .tmp(map$CountryCode, suffix1=",", suffix2=" /"),'')
content <- c(content,' map_iso_regi(iso_regi,all_regi) "mapping from iso countries to regions that represent country" ',' /')
for(i in regions[regions %in% c("EUR","CHA",levels(map$CountryCode))]) {
content <- c(content, .tmp(i, prefix=paste0(i," . "), suffix1="", suffix2=""))
}
content <- c(content,' /',';')
replace_in_file('core/sets.gms',content,"SETS",comment="***")
}
############### download and distribute input data ###################
# check wheather the regional resolution and input data revision are outdated and update data if needed
if(file.exists("input/source_files.log")) {
input_old <- readLines("input/source_files.log")[1]
} else {
input_old <- "no_data"
}
input_new <- paste0("rev",cfg$revision,"_", regionscode(cfg$regionmapping),"_", tolower(cfg$model_name),".tgz")
if(!setequal(input_new, input_old) | cfg$force_download) {
cat("Your input data are outdated or in a different regional resolution. New data are downloaded and distributed. \n")
download_distribute(files = input_new,
repositories = cfg$repositories, # defined in your local .Rprofile or on the cluster /p/projects/rd3mod/R/.Rprofile
modelfolder = ".",
debug = FALSE)
}
##################### update information #############################
# update_info, which regional resolution and input data revision in cfg$model
update_info(regionscode(cfg$regionmapping),cfg$revision)
# update_sets, which is updating the region-depending sets in core/sets.gms
#-- load new mapping information
map <- read.csv(cfg$regionmapping,sep=";")
update_sets(map)
###########################################################################################################
############# PROCESSING INPUT DATA ###################### END ############################################
###########################################################################################################
############# ADD MODULE INFO IN SETS ###################### START ##########################################
content <- NULL
modification_warning <- c(
'*** THIS CODE IS CREATED AUTOMATICALLY, DO NOT MODIFY THESE LINES DIRECTLY',
'*** ANY DIRECT MODIFICATION WILL BE LOST AFTER NEXT MODEL START',
'*** CHANGES CAN BE DONE USING THE RESPECTIVE LINES IN scripts/start_functions.R')
content <- c(modification_warning,'','sets')
content <- c(content,'',' modules "all the available modules"')
content <- c(content,' /',paste0(" ",getModules("modules/")[,"name"]),' /')
content <- c(content,'','module2realisation(modules,*) "mapping of modules and active realisations" /')
content <- c(content,paste0(" ",getModules("modules/")[,"name"]," . %",getModules("modules/")[,"name"],"%"))
content <- c(content,' /',';')
replace_in_file('core/sets.gms',content,"MODULES",comment="***")
############# ADD MODULE INFO IN SETS ###################### END ############################################
# Replace load leveler-script with appropriate version
if (cfg$gms$optimization == "nash" && cfg$gms$cm_nash_mode == "parallel") {
if(length(unique(map$RegionCode)) <= 12) {
cfg$files2export$start[cfg$files2export$start == "scripts/run_submit/submit.cmd"] <-
"scripts/run_submit/submit_par.cmd"
} else { # use max amount of cores if regions number is greater than 12
cfg$files2export$start[cfg$files2export$start == "scripts/run_submit/submit.cmd"] <-
"scripts/run_submit/submit_par16.cmd"
}
} else if (cfg$gms$optimization == "testOneRegi") {
cfg$files2export$start[cfg$files2export$start == "scripts/run_submit/submit.cmd"] <-
"scripts/run_submit/submit_short.cmd"
}
# choose which conopt files to copy
cfg$files2export$start <- sub("conopt3",cfg$gms$cm_conoptv,cfg$files2export$start)
# Create name of output folder and output folder itself
date <- format(Sys.time(), "_%Y-%m-%d_%H.%M.%S")
cfg$results_folder <- gsub(":date:", date, cfg$results_folder, fixed = TRUE)
cfg$results_folder <- gsub(":title:", cfg$title, cfg$results_folder, fixed = TRUE)
# Create output folder
if (!file.exists(cfg$results_folder)) {
dir.create(cfg$results_folder, recursive = TRUE, showWarnings = FALSE)
} else if (!force) {
stop(paste0("Results folder ",cfg$results_folder," could not be created because it already exists."))
} else {
cat("Deleting results folder because it alreay exists:",cfg$results_folder,"\n")
unlink(cfg$results_folder, recursive = TRUE)
dir.create(cfg$results_folder, recursive = TRUE, showWarnings = FALSE)
}
# Copy important files into output_folder (before REMIND execution)
.copy.fromlist(cfg$files2export$start,cfg$results_folder)
# Store main folder to make it accessible in submit.R
cfg$remind_folder <- getwd()
# Save configuration
save(cfg, file = path(cfg$results_folder, "config.Rdata"))
# Merge GAMS files
singleGAMSfile(mainfile=cfg$model,output = path(cfg$results_folder, "full.gms"))
# Collect run statistics (will be saved to central database in submit.R)
lucode::runstatistics(file = paste0(cfg$results_folder,"/runstatistics.rda"),
user = Sys.info()[["user"]],
date = Sys.time(),
version_management = "git",
revision = try(system("git rev-parse --short HEAD", intern=TRUE), silent=TRUE),
#revision_date = try(as.POSIXct(system("git show -s --format=%ci", intern=TRUE), silent=TRUE)),
status = try(system("git status", intern=TRUE), silent=TRUE))
################## M O D E L U N L O C K ###################################
# After full.gms was produced remind folders have to be unlocked to allow setting up the next run
model_unlock(lock_id, oncluster=on_cluster)
# Prevent model_unlock from being executed again at the end
on.exit()
# Repeat command since on.exit was cleared
on.exit(setwd(maindir))
################## M O D E L U N L O C K ###################################
setwd(cfg$results_folder)
# Decide whether the runs should be send to slurm (TRUE) or executed directly (FALSE)
if (is.na(cfg$sendToSlurm)) {
if (on_cluster) {
cfg$sendToSlurm <- TRUE
} else {
cfg$sendToSlurm <- FALSE
}
}
# "Compilation only" is always executed directly
if (cfg$action == "c") cfg$sendToSlurm <- FALSE
# Call appropriate submit script
if (cfg$sendToSlurm) {
# send to slurm
if(cfg$gms$optimization == "nash" && cfg$gms$cm_nash_mode == "parallel") {
if(length(unique(map$RegionCode)) <= 12) {
system(paste0("sed -i 's/__JOB_NAME__/pREMIND_", cfg$title,"/g' submit_par.cmd"))
system("sbatch submit_par.cmd")
} else { # use max amount of cores if regions number is greater than 12
system(paste0("sed -i 's/__JOB_NAME__/pREMIND_", cfg$title,"/g' submit_par16.cmd"))
system("sbatch submit_par16.cmd")
}
} else if (cfg$gms$optimization == "testOneRegi") {
system(paste0("sed -i 's/__JOB_NAME__/REMIND_", cfg$title,"/g' submit_short.cmd"))
system("sbatch submit_short.cmd")
} else {
system(paste0("sed -i 's/__JOB_NAME__/REMIND_", cfg$title,"/g' submit.cmd"))
if (cfg$gms$cm_startyear > 2030) {
system("sbatch --partition=ram_gpu submit.cmd")
} else {
system("sbatch submit.cmd")
}
}
} else {
# execute directly
system("Rscript submit.R")
}
# on.exit sets working directory back to REMIND main folder
return(cfg$results_folder)
}
getReportData <- function(rep,scen,inputpath_mag="magpie",inputpath_acc="costs") {
require(lucode, quietly = TRUE,warn.conflicts =FALSE)
require(magclass, quietly = TRUE,warn.conflicts =FALSE)
.bioenergy_price <- function(mag){
notGLO <- getRegions(mag)[!(getRegions(mag)=="GLO")]
if("Demand|Bioenergy|++|2nd generation (EJ/yr)" %in% getNames(mag)) {
# MAgPIE 4
out <- mag[,,"Prices|Bioenergy (US$05/GJ)"]*0.0315576 # with transformation factor from US$2005/GJ to US$2005/Wa
} else {
# MAgPIE 3
out <- mag[,,"Price|Primary Energy|Biomass (US$2005/GJ)"]*0.0315576 # with transformation factor from US$2005/GJ to US$2005/Wa
}
out["JPN",is.na(out["JPN",,]),] <- 0
dimnames(out)[[3]] <- NULL #Delete variable name to prevent it from being written into output file
write.magpie(out[notGLO,,],paste0("./modules/30_biomass/",inputpath_mag,"/input/p30_pebiolc_pricemag_coupling.csv"),file_type="csvr")
}
.bioenergy_costs <- function(mag){
notGLO <- getRegions(mag)[!(getRegions(mag)=="GLO")]
if ("Production Cost|Agriculture|Biomass|Energy Crops (million US$2005/yr)" %in% getNames(mag)) {
out <- mag[,,"Production Cost|Agriculture|Biomass|Energy Crops (million US$2005/yr)"]/1000/1000 # with transformation factor from 10E6 US$2005 to 10E12 US$2005
}
else {
# in old MAgPIE reports the unit is reported to be "billion", however the values are in million
out <- mag[,,"Production Cost|Agriculture|Biomass|Energy Crops (billion US$2005/yr)"]/1000/1000 # with transformation factor from 10E6 US$2005 to 10E12 US$2005
}
out["JPN",is.na(out["JPN",,]),] <- 0
dimnames(out)[[3]] <- NULL
write.magpie(out[notGLO,,],paste0("./modules/30_biomass/",inputpath_mag,"/input/p30_pebiolc_costsmag.csv"),file_type="csvr")
}
.bioenergy_production <- function(mag){
notGLO <- getRegions(mag)[!(getRegions(mag)=="GLO")]
if("Demand|Bioenergy|2nd generation|++|Bioenergy crops (EJ/yr)" %in% getNames(mag)) {
# MAgPIE 4
out <- mag[,,"Demand|Bioenergy|2nd generation|++|Bioenergy crops (EJ/yr)"]/31.536 # EJ to TWa
} else {
# MAgPIE 3
out <- mag[,,"Primary Energy Production|Biomass|Energy Crops (EJ/yr)"]/31.536 # EJ to TWa
}
out[which(out<0)] <- 0 # set negative values to zero since they cause errors in GMAS power function
out["JPN",is.na(out["JPN",,]),] <- 0
dimnames(out)[[3]] <- NULL
write.magpie(out[notGLO,,],paste0("./modules/30_biomass/",inputpath_mag,"/input/p30_pebiolc_demandmag_coupling.csv"),file_type="csvr")
}
.emissions_mac <- function(mag) {
# define three columns of dataframe:
# emirem (remind emission names)
# emimag (magpie emission names)
# factor_mag2rem (factor for converting magpie to remind emissions)
# 1/1000*28/44, # kt N2O/yr -> Mt N2O/yr -> Mt N/yr
# 28/44, # Tg N2O/yr = Mt N2O/yr -> Mt N/yr
# 1/1000*12/44, # Mt CO2/yr -> Gt CO2/yr -> Gt C/yr
map <- data.frame(emirem=NULL,emimag=NULL,factor_mag2rem=NULL,stringsAsFactors=FALSE)
if("Emissions|N2O|Land|Agriculture|+|Animal Waste Management (Mt N2O/yr)" %in% getNames(mag)) {
# MAgPIE 4
map <- rbind(map,data.frame(emimag="Emissions|CO2|Land (Mt CO2/yr)", emirem="co2luc", factor_mag2rem=1/1000*12/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land|Agriculture|+|Animal Waste Management (Mt N2O/yr)", emirem="n2oanwstm", factor_mag2rem=28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land|Agriculture|Agricultural Soils|+|Inorganic Fertilizers (Mt N2O/yr)", emirem="n2ofertin", factor_mag2rem=28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land|Agriculture|Agricultural Soils|+|Manure applied to Croplands (Mt N2O/yr)", emirem="n2oanwstc", factor_mag2rem=28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land|Agriculture|Agricultural Soils|+|Decay of Crop Residues (Mt N2O/yr)", emirem="n2ofertcr", factor_mag2rem=28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land|Agriculture|Agricultural Soils|+|Soil Organic Matter Loss (Mt N2O/yr)", emirem="n2ofertsom",factor_mag2rem=28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land|Agriculture|Agricultural Soils|+|Pasture (Mt N2O/yr)", emirem="n2oanwstp", factor_mag2rem=28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|CH4|Land|Agriculture|+|Rice (Mt CH4/yr)", emirem="ch4rice", factor_mag2rem=1,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|CH4|Land|Agriculture|+|Animal waste management (Mt CH4/yr)", emirem="ch4anmlwst",factor_mag2rem=1,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|CH4|Land|Agriculture|+|Enteric fermentation (Mt CH4/yr)", emirem="ch4animals",factor_mag2rem=1,stringsAsFactors=FALSE))
} else {
# MAgPIE 3
map <- rbind(map,data.frame(emimag="Emissions|CO2|Land Use (Mt CO2/yr)", emirem="co2luc", factor_mag2rem=1/1000*12/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land Use|Agriculture|AWM (kt N2O/yr)", emirem="n2oanwstm", factor_mag2rem=1/1000*28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land Use|Agriculture|Cropland Soils|Inorganic Fertilizers (kt N2O/yr)", emirem="n2ofertin", factor_mag2rem=1/1000*28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land Use|Agriculture|Cropland Soils|Manure applied to Croplands (kt N2O/yr)", emirem="n2oanwstc", factor_mag2rem=1/1000*28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land Use|Agriculture|Cropland Soils|Decay of crop residues (kt N2O/yr)", emirem="n2ofertcr", factor_mag2rem=1/1000*28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land Use|Agriculture|Cropland Soils|Soil organic matter loss (kt N2O/yr)", emirem="n2ofertsom",factor_mag2rem=1/1000*28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land Use|Agriculture|Cropland Soils|Lower N2O emissions of rice (kt N2O/yr)", emirem="n2ofertrb", factor_mag2rem=1/1000*28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land Use|Agriculture|Pasture (kt N2O/yr)", emirem="n2oanwstp", factor_mag2rem=1/1000*28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land Use|Biomass Burning|Forest Burning (kt N2O/yr)", emirem="n2oforest", factor_mag2rem=1/1000*28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land Use|Biomass Burning|Savannah Burning (kt N2O/yr)", emirem="n2osavan", factor_mag2rem=1/1000*28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|N2O|Land Use|Biomass Burning|Agricultural Waste Burning (kt N2O/yr)", emirem="n2oagwaste",factor_mag2rem=1/1000*28/44,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|CH4|Land Use|Agriculture|Rice (Mt CH4/yr)", emirem="ch4rice", factor_mag2rem=1,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|CH4|Land Use|Agriculture|AWM (Mt CH4/yr)", emirem="ch4anmlwst",factor_mag2rem=1,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|CH4|Land Use|Agriculture|Enteric Fermentation (Mt CH4/yr)", emirem="ch4animals",factor_mag2rem=1,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|CH4|Land Use|Biomass Burning|Forest Burning (Mt CH4/yr)", emirem="ch4forest", factor_mag2rem=1,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|CH4|Land Use|Biomass Burning|Savannah Burning (Mt CH4/yr)", emirem="ch4savan", factor_mag2rem=1,stringsAsFactors=FALSE))
map <- rbind(map,data.frame(emimag="Emissions|CH4|Land Use|Biomass Burning|Agricultural Waste Burning (Mt CH4/yr)", emirem="ch4agwaste",factor_mag2rem=1,stringsAsFactors=FALSE))
}
# Read data from MAgPIE report and convert to REMIND data, collect in 'out' object
out<-NULL
for (i in 1:nrow(map)) {
tmp<-setNames(mag[,,map[i,]$emimag],map[i,]$emirem)
tmp<-tmp*map[i,]$factor_mag2rem
#tmp["JPN",is.na(tmp["JPN",,]),] <- 0
# preliminary fix 20160111
#cat("Preliminary quick fix: filtering out NAs for all and negative values for almost all landuse emissions except for co2luc and n2ofertrb\n")
#tmp[is.na(tmp)] <- 0
# preliminary 20160114: filter out negative values except for co2luc and n2ofertrb
#if (map[i,]$emirem!="co2luc" && map[i,]$emirem!="n2ofertrb") {
# tmp[tmp<0] <- 0
#}
out<-mbind(out,tmp)
}
# Write REMIND input file
notGLO <- getRegions(mag)[!(getRegions(mag)=="GLO")]
filename <- paste0("./core/input/f_macBaseMagpie_coupling.cs4r")
write.magpie(out[notGLO],filename)
write(paste0("*** EOF ",filename," ***"),file=filename,append=TRUE)
}
.agriculture_costs <- function(mag){
notGLO <- getRegions(mag)[!(getRegions(mag)=="GLO")]
out <- mag[,,"Costs|MainSolve w/o GHG Emissions (million US$05/yr)"]/1000/1000 # with transformation factor from 10E6 US$2005 to 10E12 US$2005
out["JPN",is.na(out["JPN",,]),] <- 0
dimnames(out)[[3]] <- NULL #Delete variable name to prevent it from being written into output file
write.magpie(out[notGLO,,],paste0("./modules/26_agCosts/",inputpath_acc,"/input/p26_totLUcost_coupling.csv"),file_type="csvr")
}
.agriculture_tradebal <- function(mag){
notGLO <- getRegions(mag)[!(getRegions(mag)=="GLO")]
out <- mag[,,"Trade|Agriculture|Trade Balance (billion US$2005/yr)"]/1000 # with transformation factor from 10E9 US$2005 to 10E12 US$2005
out["JPN",is.na(out["JPN",,]),] <- 0
dimnames(out)[[3]] <- NULL
write.magpie(out[notGLO,,],paste0("./modules/26_agCosts/",inputpath_acc,"/input/trade_bal_reg.rem.csv"),file_type="csvr")
}
if (length(scen)!=1) stop("getReportData: 'scen' does not contain exactly one scenario:",scen)
if (length(intersect(scen,getNames(rep,dim="scenario")))!=1) stop("getReportData: 'scen'",scen," not contained in 'rep'.")
rep <- collapseNames(rep) # get rid of scenrio and model dimension if they exist
years <- 2000+5*(1:30)
mag <- time_interpolate(rep,years)
.bioenergy_price(mag)
#.bioenergy_costs(mag) # Obsolete since bioenergy costs are not calculated by MAgPIE anymore but by integrating the supplycurve
.bioenergy_production(mag)
.emissions_mac(mag)
.agriculture_costs(mag)
# need to be updated to MAgPIE 4 interface
#.agriculture_tradebal(mag)
}
start_reportrun <- function (cfg,path_report,sceninreport=NULL){
rep <- convert.report(path_report,outmodel="REMIND")
write.report(rep,"report.mif")
if (!is.null(sceninreport))
sceninreport <- intersect(sceninreport,names(rep))
else
sceninreport <- names(rep)
for(scen in sceninreport) {
cfg$title <- scen
# If REMIND had pre-defined scenarios like MAgPIE they must be set here according to the scenario read in from the MAgPIE reporting
# cfg <- setScenario(cfg,strsplit(scen,"_")[[1]][1])
start_run(cfg, report=rep, sceninreport=scen)
}
}
start_bundle_climate.R
+ 8
− 2
View file @ 3987611b
......@@ -4,10 +4,15 @@
# | AGPL-3.0, you are granted additional permissions described in the
# | REMIND License Exception, version 1.0 (see LICENSE file).
# | Contact: remind@pik-potsdam.de
source("scripts/start_functions.R")
require(lucode, quietly = TRUE, warn.conflicts = FALSE)
source("scripts/start/submit.R")
source("scripts/start/choose_slurmConfig.R")
# Choose submission type
slurmConfig <- choose_slurmConfig()
.setgdxcopy <- function(needle, stack, new) {
# delete entries in stack that contain needle and append new
out <- c(stack[-grep(needle, stack)], new)
......@@ -55,6 +60,7 @@ for (scen in rownames(scenarios)) {
source("config/default.cfg")
# Have the log output written in a file (not on the screen)
cfg$slurmConfig <- slurmConfig
cfg$logoption <- 2
cfg$sequential <- NA
......@@ -124,6 +130,6 @@ for (scen in rownames(scenarios)) {
| is.na(settings[scen,"path_gdx_ref"])){
cat("Starting: ",scen,"\n")
load(paste0(scen,".RData"))
start_run(cfg)
submit(cfg)
}
}
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