Changeset 1582

Timestamp:

Oct 15, 2008, 7:59:21 PM (15 years ago)

Author:

Peter

Message:

refs #396 - fixing distance_test

File:

• trunk/test/distance_test.cc (modified) (11 diffs)

trunk/test/distance_test.cc

@@ -26 +26 @@
 #include "yat/statistics/EuclideanDistance.h"
 #include "yat/statistics/PearsonDistance.h"
+#include "yat/utility/DataIterator.h"
 #include "yat/utility/Matrix.h"
 #include "yat/utility/MatrixWeighted.h"
 #include "yat/utility/Vector.h"
+#include "yat/utility/WeightIterator.h"
 
 #include <cassert>
@@ -43 +45 @@
                     unsigned long int N=1);
 utility::Matrix data(void);
+utility::MatrixWeighted data_weighted(void);
 
 template<class Distance>
@@ -85 +88 @@
   test_distance(eucl_dist, suite, 100);
   double dist=eucl_dist(a.begin(),a.end(),b.begin());
-  if(std::abs(dist-2.23607)>tolerance) {
+  if (!suite.equal(dist, 2.23606797749978988178)) {
     suite.err() << "Error in unweighted Euclidean distance " << std::endl;
     suite.add(false);
@@ -94 +97 @@
   test_distance(pear_dist, suite, 1000);
   dist=pear_dist(a.begin(),a.end(),b.begin());
-  if(std::abs(dist-1.5)>tolerance) {
+  if (!suite.equal(dist, 1.5)) {
     suite.err() << "Error in unweighted Pearson distance " << std::endl;
     suite.add(false);
@@ -105 +108 @@
   m(1,0)=0;
   m(1,1)=0;
-  utility::Matrix w(2,3,1);
-  w(0,0)=0;
-  classifier::MatrixLookupWeighted mw(m,w);
+  utility::MatrixWeighted m_w(m);
+  m_w(0,0).weight()=0;
+  classifier::MatrixLookupWeighted mw(m_w);
   classifier::DataLookupWeighted1D aw(mw,0,true);
   classifier::DataLookupWeighted1D bw(mw,1,true);
@@ -113 +116 @@
   dist=eucl_dist(aw.begin(),aw.end(),bw.begin());
   
-  if(std::abs(dist-sqrt(6))>tolerance) {
+  if (!suite.equal_sqrt(dist, sqrt(6))) {
     suite.err() << "Error in weighted Euclidean distance " << std::endl;
     suite.add(false);
@@ -120 +123 @@
   dist=pear_dist(aw.begin(),aw.end(),bw.begin());
   
-  if(std::abs(dist-2)>tolerance) {
+  if (!suite.equal(dist, 2)) {
     suite.err() << "Error in weighted Pearson distance " << std::endl;
     suite.add(false);
@@ -172 +175 @@
 }
 
+utility::MatrixWeighted data_weighted(void)
+{
+  utility::Matrix x = data();
+  utility::Matrix w = weight();
+  utility::MatrixWeighted res(x.rows(), x.columns());
+  std::copy(x.begin(), x.end(), utility::data_iterator(res.begin()));
+  std::copy(w.begin(), w.end(), utility::weight_iterator(res.begin()));
+  return res;
+}
+
 template<class Distance>
 void test_distance(Distance dist, theplu::yat::test::Suite& suite,
@@ -188 +201 @@
                     unsigned long int N)
 {
-  utility::Matrix x(data());
-  utility::Matrix x2(x.rows(), 2*x.columns());
+  utility::MatrixWeighted x(data_weighted());
+  utility::MatrixWeighted mw(x.rows(), 2*x.columns());
   for (size_t i=0; i<x.rows(); ++i){
-    std::copy(x.begin_row(i), x.end_row(i), x2.begin_row(i));
-    std::copy(x.begin_row(i), x.end_row(i), x2.begin_row(i)+x.columns());
-  }
-  utility::Matrix w(weight());
-  utility::Matrix w2(w.rows(), 2*w.columns());
-  for (size_t i=0; i<w.rows(); ++i){
-    std::copy(w.begin_row(i), w.end_row(i), w2.begin_row(i));
-    std::copy(w.begin_row(i), w.end_row(i), w2.begin_row(i)+w.columns());
-  }
-  classifier::MatrixLookupWeighted ml(x2, w2);
-  double dist1 = dist(ml.begin_row(0), ml.end_row(0), ml.begin_row(1));
-  for (size_t i=0; i<w.columns(); ++i)
-    w2(0,i)=0.0;
-  double dist2 = dist(ml.begin_row(0), ml.end_row(0), ml.begin_row(1));
+    std::copy(x.begin_row(i), x.end_row(i), mw.begin_row(i));
+    std::copy(x.begin_row(i), x.end_row(i), mw.begin_row(i)+x.columns());
+  }
+  double dist1 = dist(mw.begin_row(0), mw.end_row(0), mw.begin_row(1));
+  for (size_t i=0; i<x.columns(); ++i)
+    mw(0,i).weight()=0.0;
+  double dist2 = dist(mw.begin_row(0), mw.end_row(0), mw.begin_row(1));
   check_equality(dist1, dist2, suite, "duplicate property", N);
 }
@@ -212 +218 @@
                     unsigned long int N)
 {
-  utility::Matrix x=data();
-  utility::Matrix w=weight();
-  classifier::MatrixLookupWeighted ml(x,w);
-  double dist1 = dist(ml.begin_row(0), ml.end_row(0), ml.begin_row(1));
-  w *= 2.13;
-  double dist2 = dist(ml.begin_row(0), ml.end_row(0), ml.begin_row(1));
+  utility::MatrixWeighted wx=data_weighted();
+  double dist1 = dist(wx.begin_row(0), wx.end_row(0), wx.begin_row(1));
+  // rescale weights 
+  for (size_t i=0; i<wx.rows(); ++i)
+    for (size_t j=0; j<wx.columns(); ++j)
+      wx(i,j).weight() *= 2.13;
+  double dist2 = dist(wx.begin_row(0), wx.end_row(0), wx.begin_row(1));
   check_equality(dist1, dist2, suite, "rescaling", N);
 }
@@ -261 +268 @@
                       unsigned long int N)
 {
-  utility::Matrix x=data();
-  utility::Matrix w=weight();
-  classifier::MatrixLookupWeighted ml(x,w);
-  w(0,0) = 0.0;
-  double dist1 = dist(ml.begin_row(0), ml.end_row(0), ml.begin_row(1));
-  w(0,0) = 100*std::numeric_limits<double>().epsilon();
-  double dist2 = dist(ml.begin_row(0), ml.end_row(0), ml.begin_row(1));
+  utility::MatrixWeighted wx=data_weighted();
+  wx(0,0).weight() = 0.0;
+  double dist1 = dist(wx.begin_row(0), wx.end_row(0), wx.begin_row(1));
+  wx(0,0).weight() = 100*std::numeric_limits<double>().epsilon();
+  double dist2 = dist(wx.begin_row(0), wx.end_row(0), wx.begin_row(1));
   check_equality(dist1, dist2, suite, "zero weight", N);
 }