remove calculateAndValidateImportA function

R/ValidateModel.R

@@ -520,75 +520,6 @@ compareOutputfromMakeandUse <- function(model, output_type = "Commodity") {
   return(rel_diff)
 }
 
-#' Create import direct requirements table based on import use and import y tables
-#' @param model, An EEIO model object with model specs and crosswalk table loaded
-#' @param y A final demand VECTOR used for calculating the conventional model results, L*Y
-#' @param y_d A final demand VECTOR used for validating the model results using the A_m calculation.
-#' @return A calculated direct requirements table
-calculateAndValidateImportA <- function(model, y = NULL, y_d = NULL){
-
-  U_n_m <- model$U_n_m
-  A_m <- model$A_m
-
-
-  # Calculate production demand vector
-  FD_columns <- unlist(sapply(list("HouseholdDemand", "InvestmentDemand", 
-                                   "ChangeInventories", "Export", "Import",
-                                   "GovernmentDemand"),
-                              getVectorOfCodes, ioschema = model$specs$BaseIOSchema,
-                              iolevel = model$specs$BaseIOLevel))
-  FD_columns <- model$FinalDemandMeta$Code_Loc[which(model$FinalDemandMeta$Code %in% FD_columns)] #get the right column names, with location ids
-
-  # calculate "standard" x
-  y <- rowSums(model$U[c(model$Commodities$Code_Loc),c(FD_columns)])
-  x <- model$L %*% y # if y = I, then x = model$L. I <- diag(nrow(model$A))
-
-  # Calculate x as domestic + import components
-  y_m <- rowSums(model$ImportFinalDemand[,c(FD_columns)])
-  y_d <- rowSums(model$DomesticFDWithITA[,c(FD_columns)])
-
-  x_d <- model$L_d %*% y_d
-  x_dm <- x_d + A_m%*%x_d + y_m
-
-
-  # Validate results
-  rel_dif_x <- (x-x_dm)/x_dm
-  failures <- compare2RVectorTotals(x_dm, x)
-
-
-
-  # TODO: Move this to new function - testing adding environmental import factors
-  # Including the environmental components, S^d and Q^t, of the Swedish equation for import factors: f^(d+m) = S^d*L^d*y^d + Q^t*A^m*L^d*y^d + Q^t*y^m + f^h
-  # Since f^h is not currently part of the useeior model calculations, we drop it:
-
-  # f^(d+m) = S^d*L^d*y^d + Q^t*A^m*L^d*y^d + Q^t*y^m (eq 1)
-
-  # Note that: 
-  # S^d = model$B, where model$B is used for both domestic and non-domestic calculations in the standard results calculations.
-  # L^d = model$L_d.
-  # y^d = y_d as defined in the code above
-  # Q^t = model$M. This is because the non-domestic L matrix in the M calculation (model$B %*% model$L) takes the place of the MRIO-based L matrix, 
-  # even though the satellite table of environmental coefficients (B) is equivalent in this case.
-  # A^m = A_m as defined in the code above
-  # y^m = y_m as defined in the code above
-
-  # Thus, Eq. 1 then becomes
-
-  # f^(d+m) = model$B %*% model$L_d %*% y_d + model$M %*% A_m %*% model$L_d %*% y_d + model$M %*% y_m (eq 2)
-
-  # "Standard" result calculation is model$B %*% model$L %*% y = model$M %*% y
-  cat("\n Calculating results (M matrix) using import A (A_m).\n")
-  standard_M <- model$M
-  result_Standard <- standard_M %*% y
-  M_m <- standard_M #Q^t = M_m = imported M matrix, which for validation purposes is equivalent to the current standard_M
-  result_M <- (model$B %*% model$L_d %*% y_d) + (M_m %*% A_m %*% model$L_d %*% y_d + M_m %*% y_m) # parentheses used to denote (domestic) and (import) components
-
-  rel_dif_result <- (result_Standard - result_M)/result_M
-  result_failures <- compare2RVectorTotals(result_M, result_Standard)
-
-}
-
-
 #' Validate the results of the model build using the Import Factor approach (i.e., coupled model approach)
 #' @param model, An EEIO model object with model specs and crosswalk table loaded
 #' @param y A final demand VECTOR used for calculating the conventional model results, L*Y
@@ -608,7 +539,7 @@ validateImportFactorsApproach <- function(model, y = NULL, y_d = NULL){
   # Calculate Import final demand, y_m
   y_m <- as.matrix(rowSums(model$ImportMatrix[,FD_col_index]))
 
-  print("Testing that production final demand vector is equivalent between standard and coupled model approaches. I.e.: y = y_m + y_d")
+  cat("Testing that production final demand vector is equivalent between standard and coupled model approaches. I.e.: y = y_m + y_d.\n")
   print(all.equal(y, y_d+y_m))
 
 
@@ -621,8 +552,8 @@ validateImportFactorsApproach <- function(model, y = NULL, y_d = NULL){
 
   x_dm <- (model$L_d %*% y_d) + (model$L %*% model$A_m %*% model$L_d %*% y_d + model$L %*% y_m)
 
-  print("Testing that economic throughput is equivalement between standard and coupled model approaches when using production final demand vector. 
-        I.e.,: x = x_dm")
+  cat("Testing that economic throughput is equivalement between standard and coupled model approaches when using production final demand vector.\n") 
+  cat("I.e.,: x = x_dm.\n")
   print(all.equal(x, x_dm))
 
 
@@ -636,8 +567,8 @@ validateImportFactorsApproach <- function(model, y = NULL, y_d = NULL){
 
   LCI_dm <- (model$M_d %*% y_d) + (model$M %*% model$A_m %*% model$L_d %*% y_d + model$M %*% y_m)
 
-  print("Testing that environmental results are equivalemnt between standard and coupled model approaches (i.e., LCI = LCI_dm) when:
-        1) using production final demand vector; 2) assuming model$M = model$M_m ")
+  cat("Testing that environmental results are equivalemnt between standard and coupled model approaches (i.e., LCI = LCI_dm) when:\n")
+  cat("1) using production final demand vector; 2) assuming model$M = model$M_m.\n")
   print(all.equal(LCI, LCI_dm))