# install devtools
install.packages("devtools")
library(devtools)

# install tidykml
devtools::install_github("briatte/tidykml")
library(tidykml)

# install gdxrrw
# 1: download from website: https://support.gams.com/gdxrrw:interfacing_gams_and_r
# 2: install package
install.packages("D:/public/yang/CAPRIR_Project/gdxrrw_1.0.5.zip", repos = NULL, type="source")
# or install from github
devtools::install_github("GAMS-dev/gdxrrw/gdxrrw")
library(gdxrrw)

# install capriR package
# remotes::install_github("trialsolution/caprir", force = TRUE)
devtools::install_git("https://git-dmz.thuenen.de/mindstep/caprir.git")
library(caprir)

devtools::install_git("https://git-dmz.thuenen.de/mindstep/capriv.git")
library(capriv)

# load packages
requiredPackages = c('caprir','capriv','gdxrrw', 'usethis','hablar', 'tibble',
                     'networkD3','readxl','tidyr','dplyr','reshape2',
                     'data.table','plotly', 'gt', 'ggtext', 'rlang', 'Hmisc')
for(p in requiredPackages){
  if(!require(p,character.only = TRUE)) install.packages(p)
  library(p,character.only = TRUE)}

map_data_use <- caprir::map_data %>%

  filter(!grepl("TR.*", CAPRI_NUTS_ID)) %>% # TR: Tuerkiye
  filter(!grepl("UK.*", CAPRI_NUTS_ID))  %>%# UK:
  filter(!grepl("PT20.*", CAPRI_NUTS_ID)) %>% # PT20/PT30
  filter(!grepl("PT30.*", CAPRI_NUTS_ID)) %>%# PT20/PT30
  filter(!grepl("ES70.*", CAPRI_NUTS_ID))  # ES70

setwd("D:/public/yang/CAPRIR_Project/capriv")

file1 <- "res_2_1230cap_after_2014_refdefaultA" # refdefautA
file2 <- "res_2_1230fta_import_bandefaultA" # bandefaultA
gamsPath <- "D://gams//win64//24.9"
igdx(gamsPath)

# CERE RAPE SOYA PULS
prod1 = c("CERE","RAPE","SOYA","PULS")

# MAIF OFAR GRAI GRAE
prod2 = c("MAIF", "OFAR","GRAI","GRAE")

prods = c(prod1,prod2)

gdx.dir <- paste0(getwd(), "/inst/extdata/gdx")

# products %>% filter(key %in% prod_list)
outdata.dir <- paste0(getwd(), "/inst/outdata")

# load baseline
benchmark <- capri_data(filename = paste0(gdx.dir,"/",file1),

                          selregion = "all",
                          seldim5 = "",

                          selcols = prods,

                          selrows = "LEVL" ,
                          simyear = "2030",
                          scenarioname = "benchmark")

# load scenario
scenario <- capri_data(filename = paste0(gdx.dir,"/",file2),

                         selregion = "all",
                         seldim5 = "",

                         selcols = prods,

                         selrows = "LEVL" ,
                         simyear = "2030",
                         scenarioname = "scenario")

# prod 1, percent change

p1 <- map_capri(baseline = benchmark, scenario = scenario, prods = prod1, comparison = TRUE, percent_change = TRUE, 11)

# prod 2, percent change

p2 <- map_capri(baseline = benchmark, scenario = scenario, prods = prod2, comparison = TRUE, percent_change = TRUE, 11)