Changeset 477 for library/tests/arx_test.cpp

Timestamp:

08/05/09 14:40:03 (15 years ago)

Author:

mido

Message:

panove, vite, jak jsem peclivej na upravu kodu.. snad se vam bude libit:) konfigurace je v souboru /system/astylerc

Files:

• library/tests/arx_test.cpp (modified) (4 diffs)

library/tests/arx_test.cpp

@@ -1 +1 @@
 /*!
-\file 
+\file
 \brief Test of basic elements of the ARX class
 
@@ -17 +17 @@
         // Setup model
         vec th ( "0.8 -0.3 0.4 0.01" );
-        int ord=th.length(); //auxiliary variable
-        double sqr=0.1;
+        int ord = th.length(); //auxiliary variable
+        double sqr = 0.1;
 
         //Test constructor
-        mat V0 = 0.00001*eye ( ord+1 ); V0 ( 0.0 ) = 1; //
-        double nu0 = ord+5.0;
+        mat V0 = 0.00001 * eye ( ord + 1 );
+        V0 ( 0.0 ) = 1; //
+        double nu0 = ord + 5.0;
 
         ARX Ar;
-        Ar.set_statistics(1, V0, nu0 );                 // Estimator
+        Ar.set_statistics ( 1, V0, nu0 );               // Estimator
         const epdf& f_thr = Ar.posterior();          // refrence to posterior of the estimator
 
@@ -31 +32 @@
         int ndat = 100;                 // number of data records
         vec Yt ( ndat );                // Store generated data
-        Yt.set_subvector ( 0,randn ( ord ) ); //initial values
+        Yt.set_subvector ( 0, randn ( ord ) ); //initial values
         vec rgr ( ord );                // regressor
-        vec Psi ( ord+1 );              // extended regressor
+        vec Psi ( ord + 1 );            // extended regressor
 
         //print moments of the prior distribution
-        cout << "prior mean: " << f_thr.mean() <<endl;
-        cout << "prior variance: " << f_thr.variance() <<endl;
+        cout << "prior mean: " << f_thr.mean() << endl;
+        cout << "prior variance: " << f_thr.variance() << endl;
 
         // cycle over time:
-        for ( int t=ord; t<ndat; t++ ) {
+        for ( int t = ord; t < ndat; t++ ) {
                 //Generate regressor
-                for ( int j=0;j< ( ord );j++ ) {rgr ( j ) =Yt ( t-j-1 );}
+                for ( int j = 0; j < ( ord ); j++ ) {
+                        rgr ( j ) = Yt ( t - j - 1 );
+                }
                 //model
-                Yt ( t ) = th*rgr + sqr * NorRNG();
+                Yt ( t ) = th * rgr + sqr * NorRNG();
 
                 Psi = concat ( Yt ( t ), rgr ); // Inefficient! Used for compatibility with Matlab!
@@ -53 +56 @@
                 // Test similarity of likelihoods from the Bayes rule and the predictor
                 cout << "BR log-lik: " << Ar._ll();
-                cout <<" , predictor ll: " <<  Pr->evallogcond ( vec_1 ( Yt ( t ) ),rgr )  <<endl;
+                cout << " , predictor ll: " <<  Pr->evallogcond ( vec_1 ( Yt ( t ) ), rgr )  << endl;
                 delete Pr;
         }
         //print posterior moments
-        cout << "posterior mean: " << f_thr.mean() <<endl;
-        cout << "posterior variance: " << f_thr.variance() <<endl;
+        cout << "posterior mean: " << f_thr.mean() << endl;
+        cout << "posterior variance: " << f_thr.variance() << endl;
 
         // Test brute-froce structure estimation
-        
-        cout << "Structure estimation: " <<endl;
-        cout <<Ar.structure_est ( egiw ( 1,V0,nu0 ) ) <<endl;
+
+        cout << "Structure estimation: " << endl;
+        cout << Ar.structure_est ( egiw ( 1, V0, nu0 ) ) << endl;
 }