Unit tests for correlation calculation

ApplicationCode/Application/Tools/RiaStatisticsTools.cpp

@@ -57,9 +57,30 @@ const QString RiaStatisticsTools::replacePercentileByPValueText( const QString&
 //--------------------------------------------------------------------------------------------------
 double RiaStatisticsTools::pearsonCorrelation( const std::vector<double>& xValues, const std::vector<double>& yValues )
 {
+#ifdef USE_GSL
+    return pearsonCorrelationGSL( xValues, yValues );
+#else
+    return pearsonCorrelationOwn( xValues, yValues );
+#endif
+}
+
+//--------------------------------------------------------------------------------------------------
+///
+//--------------------------------------------------------------------------------------------------
+double RiaStatisticsTools::pearsonCorrelationGSL( const std::vector<double>& xValues, const std::vector<double>& yValues )
+{
 #ifdef USE_GSL
     return gsl_stats_correlation( xValues.data(), 1, yValues.data(), 1, xValues.size() );
 #else
+    return std::numeric_limits<double>::infinity();
+#endif
+}
+
+//--------------------------------------------------------------------------------------------------
+///
+//--------------------------------------------------------------------------------------------------
+double RiaStatisticsTools::pearsonCorrelationOwn( const std::vector<double>& xValues, const std::vector<double>& yValues )
+{
     const double eps = 1.0e-8;
     if ( xValues.size() != yValues.size() ) return 0.0;
     if ( xValues.empty() ) return 0.0;
@@ -90,7 +111,6 @@ double RiaStatisticsTools::pearsonCorrelation( const std::vector<double>& xValue
     if ( sumxDiffSquared < eps || sumyDiffSquared < eps ) return 0.0;
 
     return sumNumerator / ( std::sqrt( sumxDiffSquared ) * std::sqrt( sumyDiffSquared ) );
-#endif
 }
 
 //--------------------------------------------------------------------------------------------------

ApplicationCode/Application/Tools/RiaStatisticsTools.h

@@ -52,6 +52,7 @@ public:
     }
 
     static double pearsonCorrelation( const std::vector<double>& xValues, const std::vector<double>& yValues );
-
+    static double pearsonCorrelationGSL( const std::vector<double>& xValues, const std::vector<double>& yValues );
+    static double pearsonCorrelationOwn( const std::vector<double>& xValues, const std::vector<double>& yValues );
     static double spearmanCorrelation( const std::vector<double>& xValues, const std::vector<double>& yValues );
 };

ApplicationCode/UnitTests/CMakeLists_files.cmake

@@ -69,6 +69,7 @@ ${CMAKE_CURRENT_LIST_DIR}/RifSurfaceReader-Test.cpp
 ${CMAKE_CURRENT_LIST_DIR}/RifColorLegendData-Test.cpp
 ${CMAKE_CURRENT_LIST_DIR}/RifRoffReader-Test.cpp
 ${CMAKE_CURRENT_LIST_DIR}/RifFaciesPropertiesReader-Test.cpp
+${CMAKE_CURRENT_LIST_DIR}/RiaStatisticsTools-Test.cpp
 ${CMAKE_CURRENT_LIST_DIR}/RifStimPlanXmlReader-Test.cpp
 )
 

ApplicationCode/UnitTests/RiaStatisticsTools-Test.cpp

@@ -0,0 +1,111 @@
+/////////////////////////////////////////////////////////////////////////////////
+//
+//  Copyright (C) 2020- Equinor ASA
+//
+//  ResInsight is free software: you can redistribute it and/or modify
+//  it under the terms of the GNU General Public License as published by
+//  the Free Software Foundation, either version 3 of the License, or
+//  (at your option) any later version.
+//
+//  ResInsight is distributed in the hope that it will be useful, but WITHOUT ANY
+//  WARRANTY; without even the implied warranty of MERCHANTABILITY or
+//  FITNESS FOR A PARTICULAR PURPOSE.
+//
+//  See the GNU General Public License at <http://www.gnu.org/licenses/gpl.html>
+//  for more details.
+//
+/////////////////////////////////////////////////////////////////////////////////
+
+#include "gtest/gtest.h"
+
+#include "RiaStatisticsTools.h"
+
+#include <QDebug>
+//--------------------------------------------------------------------------------------------------
+///
+//--------------------------------------------------------------------------------------------------
+TEST( RiaStatisticsTools, NoCorrelation )
+{
+    const int           N = 1000;
+    std::vector<double> a, b;
+    a.reserve( N );
+    b.reserve( N );
+    for ( int i = 0; i < N; ++i )
+    {
+        a.push_back( (double)i );
+    }
+    for ( int i = 0; i < N; ++i )
+    {
+        b.push_back( (double)std::rand() );
+    }
+    double correlation = RiaStatisticsTools::pearsonCorrelation( a, b );
+    EXPECT_LE( correlation, 0.25 );
+}
+
+//--------------------------------------------------------------------------------------------------
+///
+//--------------------------------------------------------------------------------------------------
+TEST( RiaStatisticsTools, FullCorrelation )
+{
+    const int           N = 1000;
+    std::vector<double> a, b;
+    a.reserve( N );
+    b.reserve( N );
+    for ( int i = 0; i < N; ++i )
+    {
+        a.push_back( (double)i );
+    }
+    for ( int i = 0; i < N; ++i )
+    {
+        b.push_back( i * 2.0 + 1.0 );
+    }
+    double correlation = RiaStatisticsTools::pearsonCorrelation( a, b );
+    EXPECT_NEAR( correlation, 1.0, 1.0e-2 );
+}
+
+//--------------------------------------------------------------------------------------------------
+///
+//--------------------------------------------------------------------------------------------------
+TEST( RiaStatisticsTools, NegativeCorrelation )
+{
+    const int           N = 1000;
+    std::vector<double> a, b;
+    a.reserve( N );
+    b.reserve( N );
+    for ( int i = 0; i < N; ++i )
+    {
+        a.push_back( (double)i );
+    }
+    for ( int i = 0; i < N; ++i )
+    {
+        b.push_back( i * -2.0 + 1.0 );
+    }
+    double correlation = RiaStatisticsTools::pearsonCorrelation( a, b );
+    EXPECT_NEAR( correlation, -1.0, 1.0e-2 );
+}
+
+//--------------------------------------------------------------------------------------------------
+///
+//--------------------------------------------------------------------------------------------------
+#ifdef USE_GSL
+TEST( RiaStatisticsTools, ComparisonGSLAndOwn )
+{
+    const int           N = 1000;
+    std::vector<double> a, b;
+    a.reserve( N );
+    b.reserve( N );
+    for ( int i = 0; i < N; ++i )
+    {
+        a.push_back( (double)i );
+    }
+    for ( int i = 0; i < N; ++i )
+    {
+        b.push_back( (double)std::rand() );
+    }
+    double correlationGSL = RiaStatisticsTools::pearsonCorrelationGSL( a, b );
+    double correlationOwn = RiaStatisticsTools::pearsonCorrelationOwn( a, b );
+    qDebug() << "GSL Correlation: " << correlationGSL << ", "
+             << "Own Correlation: " << correlationOwn;
+    EXPECT_NEAR( correlationGSL, correlationOwn, 1.0e-3 );
+}
+#endif