diff --git a/.gitignore b/.gitignore
index 82f927558a3dff0ea8c20858856e70779fd02c93..ab5c6e5aefb7e5a0a9df03f57a39f018e2c7bc83 100644
--- a/.gitignore
+++ b/.gitignore
@@ -160,3 +160,4 @@ cython_debug/
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/
+.~lock.*#
diff --git a/scenarioProcessing/a1ProcessScenarioData.R b/scenarioProcessing/a1ProcessScenarioData.R
new file mode 100644
index 0000000000000000000000000000000000000000..928275c69e7b732a6b9733355dca1849ff9e793d
--- /dev/null
+++ b/scenarioProcessing/a1ProcessScenarioData.R
@@ -0,0 +1,10 @@
+#
+# script to perform all the processing on the scenarios we got from James
+#
+# Benjamin Blanz 2024
+#
+
+source('stockAggregation.R')
+source('sectorMappingNACE2GTAP.R')
+source('aggregateShocks.R')
+source('relativizeShocks.R')
diff --git a/scenarioProcessing/aggregateShocks.R b/scenarioProcessing/aggregateShocks.R
index bde754eefbcfd9f9a5a3edec2c760bc9bebc06fa..95b273d8ebad505d599b6e909769db386f4f9f5d 100644
--- a/scenarioProcessing/aggregateShocks.R
+++ b/scenarioProcessing/aggregateShocks.R
@@ -1,6 +1,8 @@
#
# aggregate the flood2010 and earthquake scenarios to country level
-#
+#
+# Benjamin Blanz 2024
+#
source('funAggregateNuts2CNT.R')
codes <- read.csv("helperData/nuts3fid4Codes.csv")
diff --git a/scenarioProcessing/funAggregateNuts2CNT.R b/scenarioProcessing/funAggregateNuts2CNT.R
index 90028f34278ab36201eb06f7657f93d9d44ea329..da9f1ee24d7b4b89eae28ce13b8ec65d74669e21 100644
--- a/scenarioProcessing/funAggregateNuts2CNT.R
+++ b/scenarioProcessing/funAggregateNuts2CNT.R
@@ -1,13 +1,28 @@
+#
+# Function to aggregate stocks or stock data to the country level from the NUTS3 level
+#
+# Parameters
+# data data to aggregate
+# codes country codes
+#
+# Returns
+# aggregated data
+#
aggregateNUTS3ToCountry <- function(data,codes){
- sectorCols <- grep('ALL|TOTAL|^[A-Z]$',names(data),perl = T)
+ sectorColPattern <- 'ALL|TOTAL|^[A-Z]$|AGR|MIN|MFG|EGW|CNS|TRD|OTP|WTP|CMN|OFI|OBS|REA|PUB|OSG'
+ # identify columns with data rather than identifiers
+ sectorCols <- grep(sectorColPattern,names(data),perl = T)
+ # convert data to numeric (deals with in import error)
for(s in sectorCols){
suppressWarnings(data[[s]] <- as.numeric(data[[s]]))
}
data[is.na(data)] <- 0
+ # combine the data and the codes datasets on the fid4 field if the data dataset
+ # does not already have a CNTR_CODE field that can be used for aggregation
if(!('CNTR_CODE'%in%names(data))){
data <- merge(codes,data,by = 'fid4')
}
- sectorCols <- grep('ALL|TOTAL|^[A-Z]$',names(data),perl = T)
+ sectorCols <- grep(sectorColPattern,names(data),perl = T)
data <- aggregate(data[,c(sectorCols)],
by = list(Category=data$CNTR_CODE),FUN=sum)
names(data)[1] <- 'CNTR_CODE'
diff --git a/scenarioProcessing/funRelData.R b/scenarioProcessing/funRelData.R
index 1b3cb75a4817a5e3abb3a20334ffb2b882615093..981c275b6433ca6d9a34f09f1010acf63443edf9 100644
--- a/scenarioProcessing/funRelData.R
+++ b/scenarioProcessing/funRelData.R
@@ -1,11 +1,34 @@
+#
+# Function to calculate the relative magnitude of shocks to capital stocks
+# relative to the size of the sectoral capital stocks.
+#
+# Stocks can be provided either at the country or at the NUTS3 level. The regional
+# aggregation of data and stocks has to match.
+# The column names in data and stocks should match.
+#
+# Parameters
+# data The shock impacts specifying the capital destroyed
+# stocksNUTS3 The sectoral stocks of capital at NUTS3 level
+# stocksCNT The sectoral stocks of capital at country level
+#
+# Returns
+# shock data relative to the stocks
+#
+# Benjamin Blanz 2024
+#
relData <- function(data,stocksNUTS3=NULL,stocksCNT=NULL){
+ sectorColPattern <- 'ALL|TOTAL|^[A-Z]$|AGR|MIN|MFG|EGW|CNS|TRD|OTP|WTP|CMN|OFI|OBS|REA|PUB|OSG'
+ # Ensure the Total clumn is called TOTAL, not ALL as in some scenarios
names(data)[names(data)=='ALL'] <- 'TOTAL'
names(stocksNUTS3)[names(stocksNUTS3)=='ALL'] <- 'TOTAL'
names(stocksCNT)[names(stocksCNT)=='ALL'] <- 'TOTAL'
- sectorCols <- grep('ALL|TOTAL|^[A-Z]$',names(data),perl = T)
+ # Identify the columns with data (not the columns with country or idx).
+ sectorCols <- grep(sectorColPattern,names(data),perl = T)
+ # prepare an empty data set for the relative data, keeping the index columns
data.rel <- data
data.rel[,sectorCols] <- NA
for(i in 1:nrow(data)){
+ # identify the correct row in the stocks
if('fid4' %in% names(data)){
stocks <- stocksNUTS3
rowInStocks <- which(stocks$fid4 == data$fid4[i])
@@ -22,6 +45,7 @@ relData <- function(data,stocksNUTS3=NULL,stocksCNT=NULL){
if(length(rowInStocks)==0){
warning(paste('no region match for data row',i))
}
+ # calculate relative impact for all sectors of this row
for(s in names(data)[sectorCols]){
suppressWarnings(data.rel[i,s] <- as.numeric(data[i,s]) / as.numeric(stocks[rowInStocks,s]))
if (is.nan(data.rel[i,s])|is.na(data.rel[i,s])){
diff --git a/scenarioProcessing/helperData/GTAP_NACE_sector_mapping.xlsx b/scenarioProcessing/helperData/GTAP_NACE_sector_mapping.xlsx
new file mode 100644
index 0000000000000000000000000000000000000000..d2160144f58b37fd0c309d8698b79a23b824b104
Binary files /dev/null and b/scenarioProcessing/helperData/GTAP_NACE_sector_mapping.xlsx differ
diff --git a/scenarioProcessing/relativizeShocks.R b/scenarioProcessing/relativizeShocks.R
index 6a2fdc19e03e7cd49e962a0ce376fcd53ad7fdc0..e012ebd6fdaf1fa1280a1eecf90de0371c7a241e 100644
--- a/scenarioProcessing/relativizeShocks.R
+++ b/scenarioProcessing/relativizeShocks.R
@@ -2,11 +2,15 @@
# Uses the stocks in the flood scenario 2 and in the country level aggregate stocks derived
# from it to relativize the shocks in the earthquake and flood1 scenarios.
#
+# Benjamin Blanz 2024
+#
source('funRelData.R')
-nuts3LevelStocks <- read.csv("helperData/nuts3LevelStocks.csv", row.names=NULL)
-countryLevelStocks <- read.csv("helperData/countryLevelStocks.csv", row.names=NULL)
+nuts3LevelStocksNACE <- read.csv("helperData/nuts3LevelStocksNACE.csv", row.names=NULL)
+nuts3LevelStocksGTAP <- read.csv("helperData/nuts3LevelStocksGTAP.csv", row.names=NULL)
+countryLevelStocksNACE <- read.csv("helperData/countryLevelStocksNACE.csv", row.names=NULL)
+countryLevelStocksGTAP <- read.csv("helperData/countryLevelStocksGTAP.csv", row.names=NULL)
files <- list.files('scenarios',pattern = 'csv',recursive = T)
@@ -16,8 +20,13 @@ for(f.i in 1:length(files)){
file <- files[f.i]
cat(sprintf('%i of %i %s\n',f.i, length(files),file))
data <- read.csv(file,row.names=NULL)
- data.CNT <- relData(data,nuts3LevelStocks,countryLevelStocks)
- write.csv(data.CNT,gsub('.csv','-rel.csv',file),row.names = F)
+ if(grepl('GTAP',file)){
+ data.rel <- relData(data,nuts3LevelStocksGTAP,countryLevelStocksGTAP)
+ write.csv(data.rel,gsub('.csv','-rel.csv',file),row.names = F)
+ }else{
+ data.rel <- relData(data,nuts3LevelStocksNACE,countryLevelStocksNACE)
+ write.csv(data.rel,gsub('.csv','-rel.csv',file),row.names = F)
+ }
}
diff --git a/scenarioProcessing/stockAggregation.R b/scenarioProcessing/stockAggregation.R
index 9c7cdad179054bb1221f2a1caac7deccf11b0b22..37e4a4e5f1d3d01d134fd2e15099af84a0aef98f 100644
--- a/scenarioProcessing/stockAggregation.R
+++ b/scenarioProcessing/stockAggregation.R
@@ -1,8 +1,13 @@
#
-# Aggregate NUTS3 scenario data to country level
+# Aggregate NUTS3 scenario stock data to country level
#
# library(sf)
-# worldAdmin1 <- read_sf('scenarios/ne_10m_admin_1_states_provinces/ne_10m_admin_1_states_provinces.shp')
+# worldAdmin1 <- read_sf('scenarios/ne_10m_admin_1_states_provinces/ne_10m_admin_1_states_provinces.shp')
+#
+# Benjamin Blanz 2024
+#
+
+sectorColPattern <- 'ALL|TOTAL|^[A-Z]$|AGR|MIN|MFG|EGW|CNS|TRD|OTP|WTP|CMN|OFI|OBS|REA|PUB|OSG'
# read scenario file with NUTS3 data ####
library(readxl)
@@ -37,7 +42,7 @@ sink('helperData/nuts3LevelStocksMetadata.csv')
cat(sprintf('Unit %s,,\n',stockUnit))
cat(sprintf('Labels,, \n'))
cat(sprintf('Sector,Label,Type\n'))
-sectorCols <- grep('ALL|TOTAL|^[A-Z]$',names(stocksNUTS3),perl = T)
+sectorCols <- grep(sectorColPattern,names(stocksNUTS3),perl = T)
for(n in colnames(stocksNUTS3)[sectorCols]){
cat(sprintf('"%s", "%s", "%s"\n',n,stockLabels[n],stockTypes[n]))
}
@@ -45,7 +50,7 @@ sink()
# aggregate to country level
-sectorCols <- grep('ALL|TOTAL|^[A-Z]$',names(stocksNUTS3),perl = T)
+sectorCols <- grep(sectorColPattern,names(stocksNUTS3),perl = T)
stocksCNT <- aggregate(stocksNUTS3[,sectorCols],
by = list(Category=stocksNUTS3$CNTR_CODE),FUN=sum)
colnames(stocksCNT)[1] <- 'CNTR_CODE'
@@ -65,7 +70,7 @@ sink('helperData/countryLevelStocksMetadata.csv')
cat(sprintf('Unit %s,,\n',stockUnit))
cat(sprintf('Labels,, \n'))
cat(sprintf('Sector,Label,Type\n'))
-sectorCols <- grep('ALL|TOTAL|^[A-Z]$',names(stocksNUTS3),perl = T)
+sectorCols <- grep(sectorColPattern,names(stocksNUTS3),perl = T)
for(n in colnames(stocksNUTS3)[sectorCols]){
cat(sprintf('"%s", "%s", "%s"\n',n,stockLabels[n],stockTypes[n]))
}