Changeset 1704 for trunk

Timestamp:

Jan 8, 2009, 6:17:44 PM (12 years ago)

Author:

Peter

Message:

avoid using abs in tests and use test::Suite instead

Location:

trunk/test

Files:

• averager_test.cc (modified) (8 diffs)
• distance_test.cc (modified) (5 diffs)
• feature_selection_test.cc (modified) (2 diffs)
• kernel_test.cc (modified) (3 diffs)
• kolmogorov_smirnov_test.cc (modified) (2 diffs)

trunk/test/averager_test.cc

@@ -5 +5 @@
   Copyright (C) 2006 Jari Häkkinen, Peter Johansson, Markus Ringnér
   Copyright (C) 2007, 2008 Jari Häkkinen, Peter Johansson
+  Copyright (C) 2009 Peter Johansson
 
   This file is part of the yat library, http://dev.thep.lu.se/yat
@@ -99 +100 @@
 
   a.add(3,5);
-  if (std::abs(a.standard_error()-sqrt(a.variance()/a.n()))>
-      std::numeric_limits<double>().round_error() ){
+  if (!suite.equal_sqrt(a.standard_error(), sqrt(a.variance()/a.n()),1)) {
     suite.add(false);
     suite.err() << "error: standard_error\n";
@@ -185 +185 @@
   for (int i=0; i<10; i++)
     ap.add(static_cast<double>(i),i);
-  if (std::abs(ap.correlation()-1)>tol){
+  if (!suite.equal(ap.correlation(),1,tol)){
     suite.add(false);
     suite.err() << "correlation: " << ap.correlation() << std::endl;
@@ -191 +191 @@
            << std::endl;
   }
-  if (ap.x_averager().variance()!=ap.covariance()){
+  if (!suite.equal(ap.x_averager().variance(),ap.covariance())) {
     suite.add(false);
     suite.err() << "error: covariance of identical vectors should equal to variance" 
@@ -201 +201 @@
   for (int i=0; i<8; i++)
     ap.add(static_cast<double>(i),i,-1);
-  if (std::abs(ap.correlation()-1)>tol) {
+  if (!suite.equal(ap.correlation(),1, tol)) {
     suite.add(false);
     suite.err() << "correlation after removal of data: " << ap.correlation()
@@ -253 +253 @@
            Suite& suite)
 {
-//  std::cout << (a.n()==b.n()) << std::endl;
-//  std::cout << (a.mean()==b.mean()) << std::endl;
-//  std::cout << (std::abs(a.variance()-b.variance()<1e-15)) << std::endl;
   return (a.n()==b.n() && suite.equal(a.mean(),b.mean(),tol) &&
           suite.equal(a.variance(),b.variance(),tol));
@@ -305 +302 @@
 {
   bool ok = true;
-  if  ( std::abs(a.covariance()-b.covariance())>tol){
+  if (!suite.equal(a.covariance(), b.covariance(), tol)) {
     suite.add(false);
     suite.err() << "error covariance: " << a.covariance() << "\t" 
            << b.covariance() << std::endl;
   }
-  if ( std::abs(a.correlation()-b.correlation())>tol ) {
+  if ( !suite.equal(a.correlation(),b.correlation(), tol)) {
     suite.add(false);
     suite.err() << "error correlation" << std::endl;
@@ -321 +318 @@
 {
   bool ok = true;
-  if  ( std::abs(a.covariance()-b.covariance())>tol){
+  if (!suite.equal(a.covariance(), b.covariance(), tol) ) {
     suite.add(false);
     suite.err() << "error covariance: " << a.covariance() << "\t" 
            << b.covariance() << std::endl;
   }
-  if ( std::abs(a.correlation()-b.correlation())>tol ) {
+  if ( !suite.equal(a.correlation(),b.correlation(), tol) ) {
     suite.add(false);
     suite.err() << "error correlation" << std::endl;

trunk/test/distance_test.cc

@@ -3 +3 @@
 /*
   Copyright (C) 2007, 2008 Jari Häkkinen, Peter Johansson, Markus Ringnér
+  Copyright (C) 2009 Peter Johansson
 
   This file is part of the yat library, http://dev.thep.lu.se/yat
@@ -83 +84 @@
   b(2) = 1;
   
-  double tolerance=1e-4;
   statistics::EuclideanDistance eucl_dist;
   suite.err() << "testing EuclideanDistance" << std::endl;
@@ -135 +135 @@
   sb[2] = 1;
   
+  double tolerance=1e-4;
   dist=eucl_dist(sa.begin(),sa.end(),sb.begin()); 
-  if(std::abs(dist-2.23607)>tolerance) {
+  if(!suite.equal_fix(dist, 2.23607,tolerance)) {
     suite.err() << "Error in distance for std::vector " << std::endl;
     suite.add(false);
@@ -145 +146 @@
   std::copy(sa.begin(),sa.end(),std::back_inserter<std::list<double> >(la));
   dist=eucl_dist(la.begin(),la.end(),sb.begin());
-  if(std::abs(dist-2.23607)>tolerance) {
+  if(!suite.equal_fix(dist, 2.23607, tolerance) ) {
     suite.err() << "Error in distance for std::list " << std::endl;
     suite.add(false);
@@ -245 +246 @@
   utility::Matrix x = data();
   double self = dist(x.begin(), x.end(), x.begin());
-  if (!(std::abs(self) <= N*std::numeric_limits<double>().epsilon()) ){
+  if (!suite.equal_fix(self,0, N*std::numeric_limits<double>().epsilon()) ) {
     suite.err() << "error: self distance is " << self << "\n"
                 << "supposed to be zero.\n";

trunk/test/feature_selection_test.cc

@@ -4 +4 @@
   Copyright (C) 2006 Jari Häkkinen, Peter Johansson
   Copyright (C) 2007 Jari Häkkinen, Peter Johansson, Markus Ringnér
-  Copyright (C) 2008 Peter Johansson
+  Copyright (C) 2008, 2009 Peter Johansson
 
   This file is part of the yat library, http://dev.thep.lu.se/yat
@@ -88 +88 @@
 
   classifier::DataLookupWeighted1D row(dataviewweighted,best_feature,true);
-  double score_diff=std::abs(snr.score(targets,row)-1.47804);
-  if(score_diff>0.00001) {
+  if(!suite.equal_fix(snr.score(targets, row), 1.47804, 0.00001) ) {
     suite.err() << "\nERROR: Best score not what expected!\n" << std::endl;
     suite.add(false);

trunk/test/kernel_test.cc

@@ -5 +5 @@
   Copyright (C) 2006 Jari Häkkinen, Peter Johansson, Markus Ringnér
   Copyright (C) 2007, 2008 Jari Häkkinen, Peter Johansson
+  Copyright (C) 2009 Peter Johansson
 
   This file is part of the yat library, http://dev.thep.lu.se/yat
@@ -140 +141 @@
   for(size_t i=0;i<control.rows();i++)
     for(size_t j=0;j<control.columns();j++)
-      if (std::abs(kernel(i,j)-control(i,j))>error_bound){
+      if (!suite.equal_fix(kernel(i,j),control(i,j), error_bound) ){
         suite.err() << "ERROR: comparing kernel(" << i << "," << j << "): "
                     << kernel(i,j)
@@ -184 +185 @@
   for(size_t i=0;i<control.rows();i++)
     for(size_t j=0;j<control.columns();j++)
-      if (std::abs(kernel(i,j)-control(i,j))>error_bound){
+      if (!suite.equal_fix(kernel(i,j), control(i,j), error_bound) ){
         suite.err() << "ERROR: comparing kernel(" << i << "," << j << "): "
                     << kernel(i,j)

trunk/test/kolmogorov_smirnov_test.cc

@@ -107 +107 @@
   double p_correct = 0.2;
   double margin=10*std::sqrt(p_correct*(1-p_correct)/n);
-  if (std::abs(p-p_correct)>margin) {
+  if (!suite.equal_fix(p, p_correct, margin) ) {
     suite.add(false);
     suite.err() << "Error: p = " << p << "\n"
@@ -132 +132 @@
   double margin = 5 * a.standard_error(); 
   double p_approx = ks.p_value();
-  if (std::abs(a.mean()-p_approx)>margin) {
+  if (!suite.equal_fix(a.mean(), p_approx, margin) ) {
     suite.add(false);
     suite.err() << "Error: unexpected large deviation between p_values\n"