Changeset 2226

Timestamp:

Mar 24, 2010, 3:40:02 PM (13 years ago)

Author:

Peter

Message:

remove usage of deprecated constructors also in templates and tests. (refs #543)

Location:

trunk

Files:

• test/matrix_lookup_test.cc (modified) (1 diff)
• yat/classifier/EnsembleBuilder.h (modified) (2 diffs)
• yat/classifier/SubsetGenerator.h (modified) (3 diffs)

trunk/test/matrix_lookup_test.cc

@@ -88 +88 @@
          << "                           const bool)...";
   std::vector<size_t> one(1,1);
-  classifier::MatrixLookup m3(gsl_m2,utility::Index(one),true);
+  classifier::MatrixLookup m3(gsl_m2,utility::Index(one), 
+                              utility::Index(gsl_m2.columns()));
   if (m3.rows()!=1 || m3.columns()!=gsl_m2.columns() || m3(0,0)!=gsl_m2(1,0) || 
       m3(0,1)!=gsl_m2(1,1) || m3(0,2)!=gsl_m2(1,2) || m3(0,3)!=gsl_m2(1,3)) {

trunk/yat/classifier/EnsembleBuilder.h

@@ -10 +10 @@
   Copyright (C) 2008 Jari Häkkinen, Peter Johansson, Markus Ringnér
   Copyright (C) 2009 Jari Häkkinen, Peter Johansson
+  Copyright (C) 2010 Peter Johansson
 
   This file is part of the yat library, http://dev.thep.lu.se/yat
@@ -221 +222 @@
                                                size_t k)
   {
-    return MatrixLookupWeighted(data, subset_->training_features(k), true);
+    return MatrixLookupWeighted(data, subset_->training_features(k), 
+                                utility::Index(data.columns()));
   }
   

trunk/yat/classifier/SubsetGenerator.h

@@ -7 +7 @@
   Copyright (C) 2006 Jari Häkkinen, Peter Johansson, Markus Ringnér
   Copyright (C) 2007, 2008 Jari Häkkinen, Peter Johansson
-  Copyright (C) 2009 Peter Johansson
+  Copyright (C) 2009, 2010 Peter Johansson
 
   This file is part of the yat library, http://dev.thep.lu.se/yat
@@ -302 +302 @@
         // training data with no feature selection
         const MatrixLookupWeighted* train_data_all_feat = 
-          new MatrixLookupWeighted(ml, training_index(k), false);
+          new MatrixLookupWeighted(ml, utility::Index(ml.rows()), 
+                                   training_index(k));
         // use these data to create feature selection
         f_selector_->update(*train_data_all_feat, training_target(k));
@@ -329 +330 @@
         if (kernel.weighted()){
           MatrixLookupWeighted ml = kernel.data_weighted();
-          f_selector_->update(MatrixLookupWeighted(ml,training_index(k),false), 
+          f_selector_->update(MatrixLookupWeighted(ml, 
+                                                   utility::Index(ml.rows()),
+                                                   training_index(k)), 
                               training_target(k));
         }