Changeset 916 for trunk/test

Timestamp:

Sep 30, 2007, 2:50:10 AM (15 years ago)

Author:

Peter

Message:

Sorry this commit is a bit to big.

Adding a yat_assert. The yat assert are turned on by providing a
'-DYAT_DEBUG' flag to preprocessor if normal cassert is turned
on. This flag is activated for developers running configure with
--enable-debug. The motivation is that we can use these yat_asserts in
header files and the yat_asserts will be invisible to the normal user
also if he uses C-asserts.

added output operator in DataLookup2D and removed output operator in
MatrixLookup?

Removed template function add_values in Averager and weighted version

Added function to AveragerWeighted? taking iterator to four ranges.

Location:

trunk/test

Files:

• Makefile.am (modified) (1 diff)
• averager_test.cc (modified) (2 diffs)
• knn_test.cc (modified) (2 diffs)
• ncc_test.cc (modified) (3 diffs)

trunk/test/Makefile.am

@@ -32 +32 @@
   distance_test \
   ensemble_test feature_selection_test fileutil_test inputranker_test \
-  iterator_test kernel_test kernel_lookup_test \ 
+  iterator_test kernel_test kernel_lookup_test \
   knn_test matrix_test matrix_lookup_test \
   nbc_test \

trunk/test/averager_test.cc

@@ -141 +141 @@
   theplu::yat::utility::vector w(3,1);
   theplu::yat::statistics::AveragerWeighted aw;
-  aw.add_values(x,w);
+  add(aw, x.begin(), x.end(), w.begin());
   a.reset();
-  a.add_values(x);
+  add(a, x.begin(), x.end());
   const double tol=std::numeric_limits<double>().round_error();
   if (!equal(a,aw,tol,error)){
@@ -166 +166 @@
   aw2->reset();
   w*=17;
-  aw2->add_values(x,w);
+  add(*aw2, x.begin(), x.end(), w.begin());
   if (!equal(aw,*aw2,tol,error)){
     *error << "error: AveragerWeighted rescaling weights " 

trunk/test/knn_test.cc

@@ -4 +4 @@
 #include "yat/classifier/MatrixLookupWeighted.h"
 #include "yat/statistics/euclidean_vector_distance.h"
+#include "yat/statistics/pearson_vector_distance.h"
 #include "yat/utility/matrix.h"
 
@@ -42 +43 @@
   utility::matrix weights(data.rows(),data.columns(),0.0);
   utility::nan(data,weights);
-      
+
   classifier::MatrixLookupWeighted dataviewweighted(data,weights);
-  classifier::KNN<statistics::euclidean_vector_distance_tag> knn(dataviewweighted,targets);
+  classifier::KNN<statistics::pearson_vector_distance_tag> knn(dataviewweighted,targets);
+  *error << "Training KNN" << std::endl;
   knn.train();
   

trunk/test/ncc_test.cc

@@ -56 +56 @@
   bool ok = true;
 
+  classifier::MatrixLookupWeighted ml(4,4);
+  std::vector<std::string> vec(4, "pos");
+  vec[3]="bjds";
+  classifier::Target target(vec);
+  statistics::vector_distance_lookup_weighted_ptr dist=
+    statistics::vector_distance<statistics::pearson_vector_distance_tag>;
+  classifier::NCC ncctmp(ml,target,dist);
+  *error << "training...\n";
+  ncctmp.train();
+  
   std::ifstream is("data/sorlie_centroid_data.txt");
   utility::matrix data(is,'\t');
@@ -72 +82 @@
     statistics::vector_distance<statistics::pearson_vector_distance_tag>;
   classifier::NCC ncc(dataviewweighted,targets,distance);
+  *error << "training...\n";
   ncc.train();
 
@@ -103 +114 @@
   }
 
+  *error << "prediction...\n";
   utility::matrix prediction;
   ncc.predict(dataviewweighted,prediction);