diff --git a/Main.R b/Main.R
index fcd6362ddd33652947d5aab25f8e27ad0e92e5db..a5f9614c4e86533614c50b30139a4e1254dcdf54 100644
--- a/Main.R
+++ b/Main.R
@@ -24,12 +24,6 @@ inputFolder <- paste(path, "input_data", sep = "/")
outputFolder <- paste(path, "output", sep = "/")
-### load some parameter
-# Management regimes and their abbreviation, they are merged to the data by the branching group (script loadDB.R)
-regime <- read.csv(paste0(path, "/params/regimes.csv"),
- sep = ",",
- stringsAsFactors = FALSE)
-
### Simulation variant that will be load
### The corresponding db files need to be stored in folder "input_data"
@@ -65,36 +59,24 @@ regime <- read.csv(paste0(path, "/params/regimes.csv"),
# Select the variation
+# !!! no needed if query based on the file name
#sim_variant <- "CC0_p_canesm"
-sim_variant <- "without"
+#sim_variant <- "without"
# Vector to keep all variants for future use:
-all.variants <- c("CC45",
- "CC85",
- "without",
- "CC45_p",
- "CC85_p",
- "CC26_p",
- "CC0_p",
- "CC45_p_canesm",
- "CC85_p_canesm",
- "CC26_p_canesm",
- "CC0_p_canesm")
-
-
-### Define the names of the databases (SIMO-output for 10 watersheds) that will be imported
-# It is used in the skripts "structure_SIMO_rslDB_FBE.R" and "loadDB.R"
-#db_names <- c(#"MV_Hartola",
- #"MV_Kitee",
- # "MV_Korsnas" #,
- #"MV_Parikkala",
- #"MV_Pori",
- #"MV_Pyhtaa",
- #"MV_Raasepori",
- #"MV_Simo",
- #"MV_Vaala",
- #"MV_Voyri"
- # )
+#all.variants <- c("CC45",
+ # "CC85",
+ # "without",
+ # "CC45_p",
+ # "CC85_p",
+ # "CC26_p",
+ # "CC0_p",
+ # "CC45_p_canesm",
+ # "CC85_p_canesm",
+ # "CC26_p_canesm",
+ # "CC0_p_canesm")
+
+
# List all .db in 'input'
db_input <- list.files(inputFolder,
@@ -105,46 +87,12 @@ db_input <- list.files(inputFolder,
db_names <- gsub(".db", "", db_input)
-### Restructure the SQL database.
-# The query creates a table called UNIT, which contains indicators over time and under management regimes
-#
-# !!! Only needed if the DB is loaded for the first time (this may take some time): "first_load = TRUE"
-# !!! For the downloaded watershed data this is already done: "first_load = FALSE"
-
-
-first_load = FALSE
-if (sim_variant %in% all.variants ){
- print("YES")
-} else {
- print("NO")
-}
-
-### the following lines do not need any changes ###
-
-
-# If one of the follwing simulation variants is read ...
-if(sim_variant %in% all.variants ) {
- print("sim_varian is in all variants")
-
- # Run the script with the SQL query for all management regimes
- source(paste0(path, "/structure_SIMO_rslDB_FBE.R"))
-
- } else {
- print("!!!else")
- # Otherwise, run the script witht the SQL query for Set aside without deadwood extraction (...SA)
- # This needs a different SQL query, since the database does not contain harvest information
- source(paste0(path, "/structure_SIMO_rslDB_SA.R")) # Query
-
-}
-
-
-###
-
-
-### Import the restructured SIMO data (from UNIT table) in the R-environment
-# It gives a single dataframe for each database named by "rsl_db_names.csv" AND an overall dataframe called "rslt_all.csv"
-# Select columns that should be importat from the SQL table UNIT (created before by script structure_SIMO_rslDB)
+# Identify columns from UNIT table to export to .cvs
+# -----------------------------------------
+# different columns are stored in stratum or in comp_unit
+# if more variables are required, need to update the SQL
+# created script 'structure_SIMO_rslDB.R'
# An overview on all available SIMO outcomes can be found under: params/Overview_outcomes_SIMO.xlsx
columns <- paste0("id,
@@ -158,21 +106,91 @@ columns <- paste0("id,
V_total_deadwood,
BA,
V,
- N,
SC,
+ N,
H_dom,
D_gm,
Harvested_V,
Biomass,
income_biomass,
- CARBON_STORAGE")
+ CARBON_STORAGE,
+ MAIN_SP")
+
+
+
+# If the _SA is included in the .db name
+# use specific query
-# Create the final CSV
-# -------------------------
+# CHeck for matching character string
+# !!!!!! this needs to be fixed!
+# what is the correct order of teh queries?
+# need to include OPER2 & OPER3 in SA scenario???
+# error: op_res.income - in SA and NO SA scenarios
+
+# TRy to add THIN value to SA_scenario???
+# NEED to fix final export of csv tables: simplify the output name!!!
+# remove the 'simulated_'
+
+#
+for (name in db_names) {
+ print("Back in main!!")
+ # CHeck if the name contains "_SA" regime
+ # if YES - run SA query
+ # if NO - run normal query
+
+
+ if(grepl("_SA", name)){
+
+ print(name)
+ print("run SA query")
+ # This needs specific SQL, since the database does not contain harvest information
+ source(paste0(path, "/structure_SIMO_rslDB_SA.R"))
+
+ } else {
+ print(name)
+ print("run FBE query")
+
+ # Run the script with the SQL query for all management regimes besides SA
+ source(paste0(path, "/structure_SIMO_rslDB_FBE.R")) # Query
+
+ }
+ }
+
+
+
+
+###
+# Create the final CSV for each database
+# ----------------------------------
source(paste(path, "loadDB.R", sep = "/"))
+
+
+
+# If one of the follwing simulation variants is read ...
+# if(sim_variant %in% all.variants ) {
+# print("sim_varian is in all variants")
+#
+# # Run the script with the SQL query for all management regimes
+# source(paste0(path, "/structure_SIMO_rslDB_FBE.R"))
+#
+#
+# } else {
+
+# # Otherwise, run the script witht the SQL query for Set aside without deadwood extraction (...SA)
+# # This needs a different SQL query, since the database does not contain harvest information
+# source(paste0(path, "/structure_SIMO_rslDB_SA.R")) # Query
+# }
+
+
+
+
+
+
+
+
### !!! CSV files are stored unter output
#
# If data/columns have already been loaded and saved as csv file under ../output: csv_exist = TRUE