refactor x as shared pointer

inst/include/common/data_object.hpp

@@ -45,7 +45,7 @@ namespace fims_data_object {
 template <typename Type>
 struct DataObject : public fims_model_object::FIMSObject<Type> {
   static uint32_t id_g;   /**< id of the Data Object >*/
-  std::vector<Type> data; /**< vector of the data >*/
+  std::shared_ptr<fims::Vector<Type>> data; /**< vector of the data >*/
   size_t dimensions;      /**< dimension of the Data object >*/
   size_t imax;            /**<1st dimension of data object >*/
   size_t jmax;            /**< 2nd dimension of data object>*/
@@ -57,7 +57,8 @@ struct DataObject : public fims_model_object::FIMSObject<Type> {
    * Constructs a one-dimensional data object.
    */
   DataObject(size_t imax) : dimensions(1), imax(imax) {
-    data.resize(imax);
+    this->data = std::make_shared<fims::Vector<Type> > (imax);
+    //data.resize(imax);
 
     this->id = DataObject<Type>::id_g++;
   }
@@ -66,7 +67,7 @@ struct DataObject : public fims_model_object::FIMSObject<Type> {
    * Constructs a two-dimensional data object.
    */
   DataObject(size_t imax, size_t jmax) : dimensions(2), imax(imax), jmax(jmax) {
-    data.resize(imax * jmax);
+    this->data = std::make_shared<fims::Vector<Type> > (imax * jmax);
     this->id = DataObject<Type>::id_g++;
   }
 
@@ -75,7 +76,7 @@ struct DataObject : public fims_model_object::FIMSObject<Type> {
    */
   DataObject(size_t imax, size_t jmax, size_t kmax)
       : dimensions(3), imax(imax), jmax(jmax), kmax(kmax) {
-    data.resize(imax * jmax * kmax);
+    this->data = std::make_shared<fims::Vector<Type> > (imax * jmax * kmax);
     this->id = DataObject<Type>::id_g++;
   }
 
@@ -84,7 +85,7 @@ struct DataObject : public fims_model_object::FIMSObject<Type> {
    */
   DataObject(size_t imax, size_t jmax, size_t kmax, size_t lmax)
       : dimensions(4), imax(imax), jmax(jmax), kmax(kmax), lmax(lmax) {
-    data.resize(imax * jmax * kmax * lmax);
+    this->data = std::make_shared<fims::Vector<Type> >(imax * jmax * kmax * lmax);
     this->id = DataObject<Type>::id_g++;
   }
 

inst/include/common/information.hpp

@@ -158,14 +158,14 @@ class Information {
 
   void setup_priors(){
     for(density_components_iterator it = density_components.begin(); it!= density_components.end(); ++it){
-      std::shared_ptr<fims_distributions::DensityComponentBase<Type> > n = (*it).second;
-      if(n->input_type == "prior"){
+      std::shared_ptr<fims_distributions::DensityComponentBase<Type> > d = (*it).second;
+      if(d->input_type == "prior"){
         variable_map_iterator vmit;
-        vmit = this->variable_map.find(n->key[0]); 
-        n->x = *(*vmit).second;
-        for(size_t i=1; i<n->key.size(); i++){
-          vmit = this->variable_map.find(n->key[i]); 
-          n->x.insert(std::end(n->x), 
+        vmit = this->variable_map.find(d->key[0]); 
+        d->x = *(*vmit).second;
+        for(size_t i=1; i<d->key.size(); i++){
+          vmit = this->variable_map.find(d->key[i]); 
+          d->x.insert(std::end(d->x), 
             std::begin(*(*vmit).second), std::end(*(*vmit).second));
         } 
       }
@@ -174,13 +174,13 @@ class Information {
   void setup_random_effects(){
     for(density_components_iterator it = this->density_components.begin(); it!= this->density_components.end(); ++it){
       std::shared_ptr<fims_distributions::DensityComponentBase<Type> > n = (*it).second;
-      if(n->input_type == "re"){
+      if(d->input_type == "re"){
         variable_map_iterator vmit;
-        vmit = this->variable_map.find(n->key[0]); 
-        n->x = *(*vmit).second;
-        for(size_t i=1; i<n->key.size(); i++){
-          vmit = this->variable_map.find(n->key[i]); 
-          n->x.insert(std::end(n->x), 
+        vmit = this->variable_map.find(d->key[0]); 
+        d->x = *(*vmit).second;
+        for(size_t i=1; i<d->key.size(); i++){
+          vmit = this->variable_map.find(d->key[i]); 
+          d->x.insert(std::end(d->x), 
                                     std::begin(*(*vmit).second), std::end(*(*vmit).second));
         } 
       }
@@ -189,14 +189,14 @@ class Information {
   void setup_data(){
     for(density_components_iterator it = this->density_components.begin(); it!= this->density_components.end(); ++it){
       std::shared_ptr<fims_distributions::DensityComponentBase<Type> > n = (*it).second;
-      if(n->input_type == "data"){
+      if(d->input_type == "data"){
         variable_map_iterator vmit;
-        vmit = this->variable_map.find(n->key[0]); 
-        n->expected_value = *(*vmit).second;
+        vmit = this->variable_map.find(d->key[0]); 
+        d->expected_values = *(*vmit).second;
 
-        for(size_t i=1; i<n->key.size(); i++){
-          vmit = this->variable_map.find(n->key[i]); 
-          n->expected_value.insert(std::end(n->expected_value), 
+        for(size_t i=1; i<d->key.size(); i++){
+          vmit = this->variable_map.find(d->key[i]); 
+          d->expected_values.insert(std::end(d->expected_values), 
             std::begin(*(*vmit).second), std::end(*(*vmit).second));
         } 
       }

inst/include/common/model.hpp

@@ -92,7 +92,7 @@ class Model {  // may need singleton
 #endif
     // Loop over densities and evaluate joint negative log densities for priors
    size_t n_priors = 0;
-   typename density_components_iterator d_it;
+   density_components_iterator d_it;
     for(d_it = this->density_components.begin(); d_it!= this->density_components.end(); ++d_it){
       std::shared_ptr<fims_distributions::DensityComponentBase<Type> > d = (*d_it).second;
       #ifdef TMB_MODEL
@@ -148,7 +148,7 @@ class Model {  // may need singleton
               << this->fims_information->populations.size() << " populations."
               << std::endl;
     for (p_it = this->fims_information->populations.begin();
-         p_it != this->fims_information->populations.end(); ++it) {
+         p_it != this->fims_information->populations.end(); ++p_it) {
       //(*p_it).second points to the Population module
       std::shared_ptr<fims_popdy::Population<Type> > p = (*p_it).second;
       // link to TMB objective function
@@ -159,7 +159,7 @@ class Model {  // may need singleton
       p->Evaluate();
     }
 
-    typename fims_info::Information<Type>::population_iterator f_it;
+    typename fims_info::Information<Type>::fleet_iterator f_it;
     // Loop over fleets/surveys, and evaluate age comp and index expected values
      for (f_it = this->fims_information->fleets.begin();
         f_it != this->fims_information->fleets.end(); ++f_it) {
@@ -171,15 +171,15 @@ class Model {  // may need singleton
         MODEL_LOG << "Setting up pointer to fleet " << f->id << "."
                   << std::endl;
         f->evaluate_age_comp();
-        f->evaluate_index()
+        f->evaluate_index();
       }
 
     // Loop over and evaluate data joint negative log-likelihoods
     for(d_it = this->density_components.begin(); d_it!= this->density_components.end(); ++d_it){
       std::shared_ptr<fims_distributions::DensityComponentBase<Type> > d = (*d_it).second;
       #ifdef TMB_MODEL
         d->of = this->of;
-        d->keep = this->keep;
+        //d->keep = this->keep;
       #endif
       if(d->input_type == "data"){
         jnll -= d->evaluate();

inst/include/distributions/functors/density_components_base.hpp

@@ -34,13 +34,17 @@ struct DensityComponentBase : public fims_model_object::FIMSObject<Type> {
   // Assigning each one its own ID is a way to keep track of
   // all the instances of the DensityComponentBase class.
  static uint32_t id_g; /**< global unique identifier for distribution modules */
- fims::Vector<Type> x; /**< input value of distribution function */
+ std::shared_ptr<fims::Vector<Type> > x; /**< input value of distribution function */
  fims::Vector<Type> expected_values; /**< expected value of distribution function */
  fims::Vector<Type> lpdf_vec; /**< vector to record observation level negative log-likelihood values */
  std::string  input_type; /**< string classifies the type of the negative log-likelihood; options are: prior, re, data */
  bool osa_flag = false; /**< Boolean; if true, osa residuals are calculated */
  bool simulate_flag = false; /**< Boolean; if true, data are simulated from the distribution */
  std::vector<uint32_t> key; /**< unique id for variable map that points to a fims::Vector */
+ Type na_value = -999;   /**< specifying the NA value >*/
+  #ifdef TMB_MODEL
+    ::objective_function<Type> *of; /**< Pointer to the TMB objective function */
+  #endif
 
   /** @brief Constructor.
    */

inst/include/distributions/functors/lognormal_lpdf.hpp

@@ -28,10 +28,6 @@ namespace fims_distributions
         fims::Vector<Type> log_logsd; /**< log of the standard deviation of the distribution on the log scale; can be a vector or scalar */
         fims::Vector<Type> logmu; /**< mean of the distribution on the log scale; can be a vector or scalar */
         fims::Vector<Type> logsd; /**< standard deviation of the distribution on the log scale; can be a vector or scalar */
-        std::vector<bool> is_na; /**< Boolean; if true, data observation is NA and the likelihood contribution is skipped */
-        #ifdef TMB_MODEL
-        ::objective_function<Type> *of; /**< Pointer to the TMB objective function */
-        #endif
         Type lpdf = 0.0; /**< total log probability density contribution of the distribution */
         // data_indicator<tmbutils::vector<Type> , Type> keep; /**< Indicator used in TMB one-step-ahead residual calculations */
 
@@ -52,7 +48,6 @@ namespace fims_distributions
         {
             this->logmu.resize(this->x.size());
             this->logsd.resize(this->x.size());
-            is_na.resize(this->x.size());
             this->lpdf_vec.resize(this->x.size());
             for (size_t i = 0; i < this->x.size(); i++)
             {
@@ -83,14 +78,14 @@ namespace fims_distributions
 
                 #ifdef TMB_MODEL
                 if(this->input_type == "data"){
-                  if(this->x->at(i) != this->x->na_value){
+                  if(this->x->at(i) != this->na_value){
+                  // this->lpdf_vec[i] = this->keep[i] * -dnorm(this->x->at(i), logmu[i], logsd[i], true) - this->x->at(i);
                       this->lpdf_vec[i] = dnorm(this->x->at(i), logmu[i], logsd[i], true) - this->x->at(i);
                   } else {
                     this->lpdf_vec[i] = 0;
                   } 
                 } else {
-                  // this->lpdf_vec[i] = this->keep[i] * -dnorm(this->x[i], logmu[i], logsd[i], true);
-                  this->lpdf_vec[i] = dnorm(this->x[i], logmu[i], logsd[i], true);
+                  this->lpdf_vec[i] = dnorm(this->x->at(i), logmu[i], logsd[i], true);
                 }
 
                 lpdf += this->lpdf_vec[i];

inst/include/distributions/functors/multinomial_lpmf.hpp

@@ -28,10 +28,7 @@ namespace fims_distributions
     {
         Type lpmf = 0.0; /**< total negative log-likelihood contribution of the distribution */
         fims::Vector<size_t> dims; /**< Dimensions of the number of rows and columns of the multivariate dataset */
-        std::vector<bool> is_na; /**< Boolean; if true, data observation is NA and the likelihood contribution for the entire row is skipped */
-        #ifdef TMB_MODEL
-        ::objective_function<Type> *of; /**< Pointer to the TMB objective function */
-        #endif
+
         // data_indicator<tmbutils::vector<Type> , Type> keep;  /**< Indicator used in TMB one-step-ahead residual calculations */
 
         /** @brief Constructor.
@@ -75,7 +72,7 @@ namespace fims_distributions
 
                     #ifdef TMB_MODEL
                     for (size_t j = 0; j < dims[1]; j++){
-                        if (this->x->at(i,j) != this->x->na_value) {
+                        if (this->x->at(i)->at(j) != this->na_value) {
                             size_t idx = (i * dims[1]) + j;
                         } else {
                             containsNA - true;
@@ -85,8 +82,8 @@ namespace fims_distributions
                     if(!containsNA){
                         for (size_t j = 0; j < dims[1]; j++){
                             size_t idx = (i * dims[1]) + j;
-                            x_vector[j] = this->x->at(i, j);
-                            prob_vector[j] = this->expected_value[idx];
+                            x_vector[j] = this->x->at(i)->at(j);
+                            prob_vector[j] = this->expected_values[idx];
                         }
                     }
 

inst/include/distributions/functors/normal_lpdf.hpp

@@ -28,10 +28,7 @@ struct NormalLPDF : public DensityComponentBase<Type> {
     fims::Vector<Type> mu; /**< mean of the distribution; can be a vector or scalar */
     fims::Vector<Type> sd; /**< standard deviation of the distribution; can be a vector or scalar */
     Type lpdf = 0.0; /**< total log probability density contribution of the distribution */
-    std::vector<bool> is_na; /**< Boolean; if true, data observation is NA and the likelihood contribution is skipped */
-    #ifdef TMB_MODEL
-    ::objective_function<Type> *of; /**< Pointer to the TMB objective function */
-    #endif
+
     //data_indicator<tmbutils::vector<Type> , Type> keep; /**< Indicator used in TMB one-step-ahead residual calculations */
 
     /** @brief Constructor.
@@ -76,15 +73,15 @@ struct NormalLPDF : public DensityComponentBase<Type> {
             }
             #ifdef TMB_MODEL
             if(this->input_type == "data"){
-              if(this->x->at(i) != this->x->na_value){
+              if(this->x->at(i) != this->na_value){
+              // this->lpdf_vec[i] = this->keep[i] * -dnorm(this->x->at(i), mu[i], sd[i], true);
                   this->lpdf_vec[i] = dnorm(this->x->at(i), mu[i], sd[i], true);
               } else {
                 this->lpdf_vec[i] = 0;
               } 
 
             } else {
-              // this->lpdf_vec[i] = this->keep[i] * -dnorm(this->x[i], mu[i], sd[i], true);
-              this->lpdf_vec[i] = dnorm(this->x[i], mu[i], sd[i], true);
+              this->lpdf_vec[i] = dnorm(this->x->at(i), mu[i], sd[i], true);
             }
             lpdf += this->lpdf_vec[i];
             if(this->simulate_flag){

inst/include/interface/rcpp/rcpp_interface.hpp

@@ -432,8 +432,7 @@ RCPP_MODULE(fims) {
       .method("evaluate", &DnormDistributionsInterface::evaluate)
       .field("x", &DnormDistributionsInterface::x)
       .field("expected_values", &DnormDistributionsInterface::expected_values)
-      .field("log_sd", &DnormDistributionsInterface::log_sd)
-      .field("is_na", &DnormDistributionsInterface::is_na);
+      .field("log_sd", &DnormDistributionsInterface::log_sd);
 
   Rcpp::class_<LogisticMaturityInterface>("LogisticMaturity")
       .constructor()
@@ -475,16 +474,14 @@ RCPP_MODULE(fims) {
       .field("input_type", &DlnormDistributionsInterface::input_type)
       .field("x", &DlnormDistributionsInterface::x)
       .field("expected_values", &DlnormDistributionsInterface::expected_values)
-      .field("log_logsd", &DlnormDistributionsInterface::log_logsd)
-      .field("is_na", &DlnormDistributionsInterface::is_na);
+      .field("log_logsd", &DlnormDistributionsInterface::log_logsd);
 
   Rcpp::class_<DmultinomDistributionsInterface>("TMBDmultinomDistribution")
       .constructor()
       .method("evaluate", &DmultinomDistributionsInterface::evaluate)
       .method("get_id", &DmultinomDistributionsInterface::get_id)
       .field("x", &DmultinomDistributionsInterface::x)
       .field("expected_values", &DmultinomDistributionsInterface::expected_values)
-      .field("is_na", &DmultinomDistributionsInterface::is_na)
       .field("dims", &DmultinomDistributionsInterface::dims);
 }