try removing ThorsonUtilities

.github/workflows/R-CMD-check.yml

@@ -65,6 +65,7 @@ jobs:
         run: |
           remotes::install_deps(dependencies=TRUE)
           remotes::install_cran("rcmdcheck")
+          install.packages("INLA",repos=c(getOption("repos"),INLA="https://inla.r-inla-download.org/R/stable"), dep=TRUE)
         shell: Rscript {0}
 
       - name: Check Ubuntu

DESCRIPTION

@@ -23,7 +23,6 @@ Imports:
     abind,
     effects,
     stats,
-    ThorsonUtilities,
     utils,
     fmesher,
     remotes,
@@ -42,11 +41,10 @@ Suggests:
     lme4,
 Remotes:
     james-thorson-NOAA/FishStatsUtils,
-    james-thorson/utilities
 License: file LICENSE
 LazyData: true
 Encoding: UTF-8
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.2
 ByteCompile: true
 URL: http://github.com/James-Thorson-NOAA/VAST
 BugReports: http://github.com/James-Thorson-NOAA/VAST/issues

R/list_parameters.R

@@ -0,0 +1,35 @@
+
+
+#' List fixed and random effects
+#'
+#' \code{list_parameters} lists all fixed and random effects
+#'
+#' @param Obj Compiled TMB object
+#' @return Return Tagged-list of fixed and random effects (returned invisibly)
+
+#' @export
+list_parameters = function( Obj, verbose=TRUE ){
+  Return = list()
+  Table = data.frame()
+  if( length(Obj$env$random)>0 ){
+    Return[["Fixed_effects"]] = names(Obj$env$last.par[-Obj$env$random])
+    Return[["Random_effects"]] = names(Obj$env$last.par[Obj$env$random])
+    Table = data.frame( "Coefficient_name"=names(table(Return[["Fixed_effects"]])),
+                        "Number_of_coefficients"=as.numeric(table(Return[["Fixed_effects"]])),
+                        "Type"="Fixed")
+    Table = rbind( Table,
+                   data.frame("Coefficient_name"=names(table(Return[["Random_effects"]])),
+                              "Number_of_coefficients"=as.numeric(table(Return[["Random_effects"]])),
+                              "Type"="Random"))
+  }else{
+    Return[["Fixed_effects"]] = names(Obj$env$last.par)
+    Table = data.frame( "Coefficient_name"=names(table(Return[["Fixed_effects"]])),
+                        "Number_of_coefficients"=as.numeric(table(Return[["Fixed_effects"]])),
+                        "Type"="Fixed")
+  }
+  if( verbose==TRUE ){
+    message("List of estimated fixed and random effects:")
+    print(Table)
+  }
+  return( invisible(Table) )
+}

R/make_model.R

@@ -265,7 +265,7 @@ function( TmbData,
   Obj$env$inner.control$grad.tol <- c(1e-8,1e-12,1e-15)[ConvergeTol] # # Default : 1e-8  # Maximum gradient limit inner optimization
 
   # Print number of parameters
-  ThorsonUtilities::list_parameters( Obj )
+  list_parameters( Obj )
 
   # Return stuff
   Return = list("Obj"=Obj, "Upper"=Bounds[,'Upper'], "Lower"=Bounds[,'Lower'], "Parameters"=Parameters, "Map"=Map, "Random"=Random)

R/project_model.R

@@ -6,9 +6,10 @@
 #'
 #' The function specifically simulates new values for random effects occurring
 #'      during forecasted years.  This includes some combination of intercepts
-#'      {beta1/beta2} and spatio-temporal terms {epsilon1/epsilon2} depending on which
+#'      \code{beta1} or \code{beta2} and spatio-temporal terms
+#'      \code{epsilon1} or \code{epsilon2} depending on which
 #'      are treated as random during estimation.  It does *not* generate new values of
-#'      covariates or random-effects that are not indexed by time {omega1/omega2}
+#'      covariates or random-effects that are not indexed by time \code{omega1} or \code{omega2}
 #'
 #' Note that the model may behave poorly when \code{historical_uncertainty="both"}
 #'      and the estimation model includes an AR1 process for any component.