remove browser statements

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '3091608'
+ValidationKey: '3092076'
 AutocreateReadme: yes
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'

.github/workflows/check.yaml

@@ -23,7 +23,6 @@ jobs:
       - uses: r-lib/actions/setup-r-dependencies@v2
         with:
           extra-packages: |
-            gamstransfer=?ignore
             any::lucode2
             any::covr
             any::madrat

CITATION.cff

@@ -3,7 +3,7 @@ message: If you use this software, please cite it using the metadata from this f
 type: software
 title: 'edgeTransport: Prepare EDGE Transport Data for the REMIND model'
 version: 1.5.6
-date-released: '2024-04-05'
+date-released: '2024-04-08'
 abstract: EDGE-T is a fork of the GCAM transport module https://jgcri.github.io/gcam-doc/energy.html#transportation
   with a high level of detail in its representation of technological and modal options.
   It is a partial equilibrium model with a nested multinomial logit structure and

DESCRIPTION

@@ -15,7 +15,7 @@ Encoding: UTF-8
 LazyData: true
 RoxygenNote: 7.3.1
 VignetteBuilder: knitr
-Date: 2024-04-05
+Date: 2024-04-08
 Config/testthat/edition: 3
 Imports:
     rmndt,

R/generateEDGEdata.R

@@ -449,7 +449,6 @@ toolGenerateEDGEdata <- function(input_folder, output_folder, cache_folder = NUL
     if(nrow(nas) > 0) {
       print("NAs found in FV vintage shares.")
       nas
-      browser()
     }
     shares$FV_shares = vintages[["shares"]]$FV_shares
     prices = vintages[["prices"]]
@@ -474,7 +473,6 @@ toolGenerateEDGEdata <- function(input_folder, output_folder, cache_folder = NUL
     if(nrow(nas) > 0) {
       print("NAs found in final demand output.")
       nas
-      browser()
     }
 
     num_veh_stations = toolVehicleStations(

R/incotrend.R

@@ -93,7 +93,6 @@ toolPreftrend <- function(SWS, ptab, calibdem, incocost, years, GDP_POP_MER,
   nas <- FVtarget[is.na(sw)]
   if(nrow(nas) > 0){
     print("Warning: NAs in SWs found.")
-    browser()
   }
 
   setnames(FVtarget, "sw", "value")
@@ -221,31 +220,27 @@ toolPreftrend <- function(SWS, ptab, calibdem, incocost, years, GDP_POP_MER,
   nas <- S3target[is.na(sw)]
   if(nrow(nas) > 0){
     print("Warning: NAs in SWs found.")
-    browser()
   }
 
   S2target[, sw := sw/max(sw),
            by = c("region", "year", "subsector_L3")]
   nas <- S2target[is.na(sw)]
   if(nrow(nas) > 0){
     print("Warning: NAs in SWs found.")
-    browser()
   }
 
   S1target[, sw := sw/max(sw),
            by = c("region", "year", "subsector_L2")]
   nas <- S1target[is.na(sw)]
   if(nrow(nas) > 0){
     print("Warning: NAs in SWs found.")
-    browser()
   }
 
   VStarget[, sw := sw/max(sw),
            by = c("region", "year", "subsector_L1")]
   nas <- VStarget[is.na(sw)]
   if(nrow(nas) > 0){
     print("Warning: NAs in SWs found.")
-    browser()
   }
 
 
@@ -332,7 +327,6 @@ Hybrid Electric,Liquids")
     nas <- FVtarget[logit_type != "pchar" & is.na(value)]
     if(nrow(nas) > 0){
       print(sprintf("NAs found in FV shareweight trends for %s scenario.", tech_scen))
-      browser()
     }
     ## level S2: Bus vs LDV
     S2target[, regioncat := ifelse(region %in% richregions, "rich", "poor")]
@@ -350,7 +344,6 @@ Hybrid Electric,Liquids")
     nas <- S2target[is.na(sw)]
     if(nrow(nas) > 0){
       print(sprintf("NAs found in S2 shareweight trends for %s scenario.", tech_scen))
-      browser()
     }
 
     ## level S3: all other mode shares
@@ -369,7 +362,6 @@ Hybrid Electric,Liquids")
     nas <- S3target[is.na(sw)]
     if(nrow(nas) > 0){
       print(sprintf("NAs found in S3 shareweight trends for %s scenario.", tech_scen))
-      browser()
     }
 
   }else{

R/logit.R

@@ -66,7 +66,6 @@ toolCalculateLogitSW <- function(prices,
     nas <- df[is.na(share)]
     if(nrow(nas) > 0) {
       print("NAs found in SWs.")
-      browser()
     }
     MJ_km <- merge(df, mj_km_data, by=intersect(names(df),names(mj_km_data)), all = FALSE)
 
@@ -237,7 +236,6 @@ toolCalculateLogitSW <- function(prices,
   if(nrow(nas) > 0){
     print("NAs found in FV shares.")
     nas
-    browser()
   }
   # VS1
   VS1_all <- X2Xcalc(prices = FV,

R/reportEDGET.R

@@ -418,14 +418,12 @@ toolReportEDGET <- function(output_folder = ".",
 
     vars <- varlist[[aggrname]]
     #access the first element in vars
-    
+
 
     if (length(unique(datatable[variable %in% vars]$variable)) < length(vars)){
-      browser()
       print(paste0("Missing variables to aggregate data to ", aggrname))
       }
     else if (length(unique(datatable[variable %in% vars]$variable)) > length(vars)) {
-      browser()
       print(paste0('duplicates from: ', aggrname, 'not summed up'))
       }
     else {
@@ -992,11 +990,11 @@ toolReportEDGET <- function(output_folder = ".",
 
   #Calculate useful energy
   UE <- toMIF[grepl("FE", variable) & grepl("Electric|Liquids|Hydrogen", variable)] #select only FE for electricity, liquids and hydrogen
-  
-  
+
+
   #create new column named technology and assign values based on variables in UE.varialbe: if the variable contains "Electricity" then technology is "Electric", if the variable contains "Liquids" then technology is "Liquids", if the variable contains "Hydrogen" then technology is "Hydrogen"
   UE[, technology := ifelse(grepl("Electricity", variable), "Electric", ifelse(grepl("Liquids", variable), "Liquids", ifelse(grepl("Hydrogen", variable), "Hydrogen", NA)))]
-  
+
   UE <- merge(UE, Mapp_UE, technology) #merge with efficiencies
   UE[, value:= value*UE_efficiency][, c("variable", "technology", "UE_efficiency"):= list(gsub("FE","UE", variable), NULL, NULL)] #calculate useful energy
 

R/sharesIntensitiesDemand.R

@@ -140,7 +140,6 @@ toolSharesIntensityDemand <- function(logit_shares,
         nas <- dt[!complete.cases(dt)]
         if(nrow(nas) > 0){
             print("NAs found in REMIND output table")
-            browser()
         }
     }
     demand_list = list(demand = demand,