Added segregDa, testing

DESCRIPTION

@@ -6,7 +6,7 @@ Description: Projection of future population and fishery dynamics is carried
   (fleet) that will result in the required abundances, catches or fishing
   mortalities.
 X-schema.org-keywords: forecast, fisheries, flr, R
-Version: 0.7.1.9221
+Version: 0.7.1.9223
 Authors@R: c(
 	person(given = 'Iago', family = 'Mosqueira', role = c('aut', 'cre'),
     email = '[email protected]'),
@@ -26,7 +26,7 @@ Imports:
 LinkingTo: Rcpp
 SystemRequirements: C++11
 Byarch: false
-Additional_repositories: http://flr-project.org/R
+Additional_repositories: https://flr.r-universe.dev
 Suggests:
   testthat,
   knitr,

R/fwd.R

@@ -50,7 +50,7 @@ setMethod("fwd", signature(object="FLBiols", fishery="FLFisheries",
   control="fwdControl"),
     function(object, fishery, control, effort_max=rep(100, length(fishery)),
       deviances=residuals, residuals=lapply(lapply(object, spwn),
-      "[<-", value=1)) {
+      "[<-", value=1), verbose=FALSE) {
 
   # CHECK valid fwdControl
   if(!validObject(control))
@@ -301,8 +301,9 @@ setMethod("fwd", signature(object="FLBiols", fishery="FLFisheries",
 
     ids <- which(out$solver_codes != 1, arr.ind=TRUE)
 
-    warning(paste("Unsolved targets at control rows: ",
-      paste(unique(ids[,"row"]), collapse=", ")))
+    if(verbose)
+      warning(paste("Unsolved targets at control rows: ",
+        paste(unique(ids[,"row"]), collapse=", ")))
   }
 
   # STRUCTURE of out

inst/include/fwdSR.h

@@ -88,6 +88,9 @@ T cushing(const T srp, const std::vector<double> params);
 template <typename T>
 T segreg(const T srp, const std::vector<double> params);
 
+template <typename T>
+T segregDa(const T srp, const std::vector<double> params);
+
 template <typename T>
 T survsrr(const T srp, const std::vector<double> params);
 

src/fwdSR.cpp

@@ -34,6 +34,8 @@ void fwdSR_base<T>::init_model_map(){
     map_model_name_to_function["cushing"] = &cushing;
     map_model_name_to_function["Cushing"] = &cushing;
     map_model_name_to_function["Segreg"] = &segreg;
+    map_model_name_to_function["segregDa"] = &segregDa;
+    map_model_name_to_function["SegregDa"] = &segregDa;
     map_model_name_to_function["segreg"] = &segreg;
     map_model_name_to_function["survSRR"] = &survsrr;
     map_model_name_to_function["survsrr"] = &survsrr;
@@ -499,6 +501,21 @@ T segreg(const T srp, const std::vector<double> params){
     return rec;
 }
 
+template <typename T>
+T segregDa(const T srp, const std::vector<double> params){
+    T rec;
+    // rec = if(ssb < b) a * ssb else a * b
+    if(pow(srp, params[2]) <= params[1]) {
+      rec = params[0] * pow(srp, params[2]);
+    }
+    else {
+      rec = params[0] * params[1];
+    }
+    return rec;
+}
+
+
+
 template <typename T>
 T survsrr(const T ssf, const std::vector<double> params){
     T rec;

src/operating_model.cpp

@@ -500,7 +500,7 @@ std::vector<adouble> operatingModel::calc_rec(const unsigned int biol_no, const
  * Calculate the instantaneous fishing mortality 
  * This method is the workhorse fishing mortality method that is called by other fishing mortality methods that do make checks.
  * F = effort * selectivity * catchability.
- * F = effort * selectivity * alpha * biomass ^ -beta
+ * F = effort %*% selectivity * alpha * biomass ^ -beta
  * Selectivity and biomass are disaggregated across all the FLQ dimensions (biomass has length 1 in the quant dimension), i.e. they will have seasons and units.
  * Effort always has length 1 in the unit and quant dimension and is disaggregated across other dimensions.
  * The catchability parameters can be disaggreated across dimensions 2 to 6. If not, they are recycled.