Change nomenclature in model from M_m to Q_t to align with nomenclatu…

…re from Palm paper.

R/BuildModel.R

@@ -137,9 +137,9 @@ constructEEIOMatrices <- function(model, configpaths = NULL) {
     }
     logging::loginfo("Calculating N_d matrix (total environmental impacts per dollar from domestic activity)...")
     model$N_d <- model$C %*% model$M_d
-    if(!is.null(model$M_m)) {
+    if(!is.null(model$Q_t)) {
       logging::loginfo("Calculating N_m matrix (total environmental impacts per dollar from imported activity)...")
-      model$N_m <- model$C %*% model$M_m # I don't think this is correct. See ImportFactorsTests.rmd, "Calculate the N matrix for the standard model using coupled model approach" chunk.
+      model$N_m <- model$C %*% model$Q_t # I don't think this is correct. See ImportFactorsTests.rmd, "Calculate the N matrix for the standard model using coupled model approach" chunk.
     }
   }
 

R/CalculationFunctions.R

@@ -117,15 +117,15 @@ calculateResultsWithExternalFactors <- function(model, demand = "Consumption", u
   if (use_domestic_requirements) {
     result$LCI_f <- (model$B %*% model$L_d %*% y_d)
   } else {
-    result$LCI_f <- (model$B %*% model$L_d %*% y_d) + (model$M_m %*% model$A_m %*% model$L_d %*% y_d + model$M_m %*% y_m)
+    result$LCI_f <- (model$B %*% model$L_d %*% y_d) + (model$Q_t %*% model$A_m %*% model$L_d %*% y_d + model$Q_t %*% y_m)
   }
   result$LCIA_f <- model$C %*% result$LCI_f
 
   result$LCI_f <- t(result$LCI_f)
   result$LCIA_f <- t(result$LCIA_f)
 
-  colnames(result$LCI_f) <- rownames(model$M_m)
-  rownames(result$LCI_f) <- colnames(model$M_m)
+  colnames(result$LCI_f) <- rownames(model$Q_t)
+  rownames(result$LCI_f) <- colnames(model$Q_t)
 
   colnames(result$LCIA_f) <- rownames(model$N_m)
   rownames(result$LCIA_f) <- colnames(model$N_m)

R/IOFunctions.R

@@ -277,14 +277,14 @@ buildModelwithImportFactors <- function(model, configpaths = NULL) {
   logging::loginfo("Calculating M_d matrix (total emissions and resource use per dollar from domestic activity)...")
   model$M_d <- model$B %*% model$L_d 
 
-  logging::loginfo("Calculating M_m matrix (total emissions and resource use per dollar from imported activity)...")
-  M_m <- loadExternalImportFactors(model, configpaths)
+  logging::loginfo("Calculating Q_t matrix (total emissions and resource use per dollar from imported activity)...")
+  Q_t <- loadExternalImportFactors(model, configpaths)
 
-  # Fill in flows for M_m not found in Import Factors but that exist in model and align order
-  M_m <- rbind(M_m, model$M_d[setdiff(rownames(model$M_d), rownames(M_m)),])
-  M_m <- M_m[rownames(model$M_d), ]
+  # Fill in flows for Q_t not found in Import Factors but that exist in model and align order
+  Q_t <- rbind(Q_t, model$M_d[setdiff(rownames(model$M_d), rownames(Q_t)),])
+  Q_t <- Q_t[rownames(model$M_d), ]
 
-  model$M_m <- M_m
+  model$Q_t <- Q_t
 
   return(model)
 }

R/LoadExternalImportFactors.R

@@ -4,7 +4,7 @@
 #' @param model An EEIO form USEEIO model object with model specs loaded
 #' @param configpaths str vector, paths (including file name) of model configuration file
 #' and optional agg/disagg configuration file(s). If NULL, built-in config files are used.
-#' @return M_m, matrix of import coefficients (flow x sector).
+#' @return Q_t, matrix of import coefficients (flow x sector).
 loadExternalImportFactors <- function(model, configpaths = NULL) {
 
   # Read in file with Import factors
@@ -50,12 +50,12 @@ loadExternalImportFactors <- function(model, configpaths = NULL) {
     IFTable['Location'] <- "US"
   }
 
-  M_m <- standardizeandcastSatelliteTable(IFTable, model)
+  Q_t <- standardizeandcastSatelliteTable(IFTable, model)
   # standardizeandcast prepares df for industries, convert to commodities
-  M_m[, setdiff(model$Commodities$Code_Loc, colnames(M_m))] <- 0
+  Q_t[, setdiff(model$Commodities$Code_Loc, colnames(Q_t))] <- 0
   # Adjust column order to be the same with V_n rownames
-  M_m <- M_m[, model$Commodities$Code_Loc]
-  M_m <- as.matrix(M_m)
+  Q_t <- Q_t[, model$Commodities$Code_Loc]
+  Q_t <- as.matrix(Q_t)
 
-  return(M_m)
+  return(Q_t)
 }

R/ValidateModel.R

@@ -564,12 +564,12 @@ validateImportFactorsApproach <- function(model, demand = "Consumption"){
   # Calculate LCI using coupled model approach
   # Revised equation from RW email (2023-11-01):
   # LCI <- (s_d * L_d * Y_d) + (s*L*A_m*L_d*Y_d + s*L*Y_m). I.e., s in RW email is analogous to model$B
-  # For validation, model$M = model$M_m, whereas in normally we'd be using model$M_m instead of model$M
+  # For validation, model$M = model$Q_t, whereas in normally we'd be using model$Q_t instead of model$M
 
   LCI_dm <- (model$M_d %*% y_d) + (M %*% model$A_m %*% model$L_d %*% y_d + M %*% y_m)
 
   cat("\nTesting that LCI results are equivalent between standard and coupled model approaches (i.e., LCI = LCI_dm) when\n")
-  cat("assuming model$M = model$M_m.\n")
+  cat("assuming model$M = model$Q_t.\n")
   print(all.equal(LCI, LCI_dm))
 
   # Calculate LCIA using standard approach
@@ -588,7 +588,7 @@ validateImportFactorsApproach <- function(model, demand = "Consumption"){
   rownames(LCIA_dm) <- colnames(model$N_m)
 
   cat("\nTesting that LCIA results are equivalent between standard and coupled model approaches (i.e., LCIA = LCIA_dm) when\n")
-  cat("assuming model$M = model$M_m.\n")
+  cat("assuming model$M = model$Q_t.\n")
   all.equal(LCIA_dm, LCIA)
 
 }