Changeset 1393 for applications

Timestamp:

09/19/11 13:43:58 (13 years ago)

Author:

sindj

Message:

 

Location:

applications/robust

Files:

• main.cpp (modified) (15 diffs)
• robustlib.h (modified) (1 diff)

applications/robust/main.cpp

@@ -27 +27 @@
 //const int utility_constant = 5;
 
-const int max_model_order = 2;
+const int max_model_order = 1;
 const double apriorno     = 0.01;
 
@@ -81 +81 @@
         mat* data_matrix;
         vec  predictions;
+        char name[80];
         
         model(set<pair<int,int>> ar_components, //funkcie treidz model-konstruktor
@@ -90 +91 @@
         {
                 this->ar_components.insert(ar_components.begin(),ar_components.end());
+
+                strcpy(name,"M");
+
+                for(set<pair<int,int>>::iterator ar_ref = ar_components.begin();ar_ref!=ar_components.end();ar_ref++)
+                {
+                        char buffer1[2];
+                        char buffer2[2];
+                        itoa((*ar_ref).first,buffer1,10);
+                        itoa((*ar_ref).second,buffer2,10);
+
+                        strcat(name,buffer1);
+                        strcat(name,buffer2);
+                        strcat(name,"_");
+                }
+
                 this->has_constant      = has_constant;
+
+                if(has_constant)
+                {
+                        strcat(name,"C");
+                }
+
                 this->window_size       = window_size;
                 this->predicted_channel = predicted_channel;
@@ -97 +119 @@
                 if(robust)
                 {
+                        strcat(name,"R");
+
                         if(has_constant)
                         {
@@ -168 +192 @@
                         pair<vec,mat> imp_samples = my_rarx->posterior->importance_sample(sample_size);
 
-                        //cout << imp_samples.first << endl;
+                        //cout << imp_samples.first << endl;                    
                         
                         vec sample_prediction;                  
@@ -180 +204 @@
                                 }
                                 
-                                lap_sample.ins(0,(*LapRNG)());
+                                lap_sample.ins(lap_sample.size(),(*LapRNG)());
 
                                 sample_prediction.ins(0,lap_sample*imp_samples.second.get_col(t));                              
@@ -186 +210 @@
 
                         return pair<vec,vec>(imp_samples.first,sample_prediction);
-                }
+                }       
                 else
                 {
@@ -274 +298 @@
         vector<vector<string>> strings;
 
-        char* file_string =  "C:\\dataADClosePercDiff"; // "C:\\ar_student_single"; // 
+        char* file_string =  "C:\\results\\ar_student_single"; // "C:\\dataADClosePercDiff"; //  
 
         char dfstring[80];
@@ -330 +354 @@
 
         ofstream myfilew;
-        char fstring[80];                                       
-        strcpy(fstring,file_string);
+        //char fstring[80];                                     
+        //strcpy(fstring,file_string);
         //strcat(fstring,"lognc.txt");
-        strcat(fstring,"preds.txt");
+        //strcat(fstring,"preds.txt");  
 
         for(int time = max_model_order;time<data_matrix.cols();time++) //time<data_matrix.cols() 
@@ -347 +371 @@
                         //if (time = max_model_order) nazvy.push_back(models.model_ref]);// ako by som mohol dostat nazov modelu?
 
-                        if((*model_ref)->my_rarx!=NULL) //vklada normalizacnz faktor do cur_res_lognc
+                        if((*model_ref)->my_rarx!=NULL) //vklada normalizacni faktor do cur_res_lognc
                         {
                                 cur_res_lognc.ins(cur_res_lognc.size(),(*model_ref)->my_rarx->posterior->_ll());                                
@@ -356 +380 @@
                         }
 
+                        int sample_size = 10;
+                        pair<vec,mat> samples;
+                        if((*model_ref)->my_arx!=NULL)
+                        {
+                                mat samp_mat = (*model_ref)->my_arx->posterior().sample_mat(sample_size);
+                                samples = pair<vec,mat>(ones(samp_mat.rows()),samp_mat);
+                        }
+                        else
+                        {
+                                samples = (*model_ref)->my_rarx->posterior->importance_sample(sample_size);
+                        }
+                        
+                        for(int i=0;i<(*model_ref)->ar_components.size()+1;i++)
+                        {
+                                char fstring[80];                                       
+                                strcpy(fstring,file_string);
+                                strcat(fstring,(*model_ref)->name);
+                                strcat(fstring,".txt");
+                                
+                                cout << samples.first << endl;
+                                
+                                myfilew.open(fstring,ios::app);
+                                myfilew << samples.first << endl << samples.second << endl << zeros(samples.first.size()) << endl; 
+                                myfilew.close();
+                        }                       
+                        
+                        /* // PREDICTIONS
                         pair<vec,vec> predictions = (*model_ref)->predict(500,time,&LapRNG);
 
@@ -363 +414 @@
 
                         (*model_ref)->predictions.ins((*model_ref)->predictions.size(),avg_prediction);
-                        
-                        
+                                        
                         myfilew.open(fstring,ios::app);
-                        myfilew << avg_prediction << ",";
+                        myfilew << avg_prediction << ","; 
                         myfilew.close();
-                        
+                        */
 
                         //preds.ins(0,data_matrix.get(0,time+1));
@@ -374 +424 @@
 
                 
+                /* // REAL PRICE
                 myfilew.open(fstring,ios::app);
                 myfilew << data_matrix.get(0,time+1) << endl;
                 myfilew.close();
-                
+                */
 
                 result_lognc.ins_col(result_lognc.cols(),cur_res_lognc);
@@ -384 +435 @@
                 // cout << "Updated." << endl;  
                                                         
-
+                /*
                 myfilew.open(fstring,ios::app);
                 
@@ -424 +475 @@
                 }
                 
-                /*
-                for(int i = 0;i<cur_res_lognc.size();i++)
-                {
-                        myfilew << cur_res_lognc[i] << ' ';//zmenil som ciarku ze medzeru
-                }
+                
+                // for(int i = 0;i<cur_res_lognc.size();i++)
+                // {
+                //         myfilew << cur_res_lognc[i] << ' ';//zmenil som ciarku ze medzeru
+                // }
+                
+
+                myfilew << endl;                                
+                
+                myfilew.close();
                 */
-
-                myfilew << endl;                                
-                
-                myfilew.close();
                 
 }

applications/robust/robustlib.h

@@ -2657 +2657 @@
                         sample_prob *= probability_and_sigma.first;
 
-                        sample_coords.ins(0,probability_and_sigma.second);
+                        sample_coords.ins(sample_coords.size(),probability_and_sigma.second);
 
                         samples.ins_col(0,sample_coords);