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116 lines
3.7 KiB
C++
116 lines
3.7 KiB
C++
/////////////////////////////////////////////////////////////////////////////////
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//
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// Copyright (C) 2020- Equinor ASA
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//
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// ResInsight is free software: you can redistribute it and/or modify
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// it under the terms of the GNU General Public License as published by
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// the Free Software Foundation, either version 3 of the License, or
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// (at your option) any later version.
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//
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// ResInsight is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or
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// FITNESS FOR A PARTICULAR PURPOSE.
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//
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// See the GNU General Public License at <http://www.gnu.org/licenses/gpl.html>
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// for more details.
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//
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/////////////////////////////////////////////////////////////////////////////////
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#include "gtest/gtest.h"
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#include "RiaStatisticsTools.h"
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#include <QDebug>
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//--------------------------------------------------------------------------------------------------
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///
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//--------------------------------------------------------------------------------------------------
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TEST( RiaStatisticsTools, NoCorrelation )
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{
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const int N = 1000;
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std::vector<double> a, b;
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a.reserve( N );
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b.reserve( N );
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for ( int i = 0; i < N; ++i )
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{
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a.push_back( (double)i );
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}
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for ( int i = 0; i < N; ++i )
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{
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b.push_back( (double)std::rand() );
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}
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double correlation = RiaStatisticsTools::pearsonCorrelation( a, b );
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EXPECT_LE( correlation, 0.25 );
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}
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//--------------------------------------------------------------------------------------------------
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///
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//--------------------------------------------------------------------------------------------------
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TEST( RiaStatisticsTools, FullCorrelation )
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{
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const int N = 1000;
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std::vector<double> a, b;
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a.reserve( N );
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b.reserve( N );
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for ( int i = 0; i < N; ++i )
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{
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a.push_back( (double)i );
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}
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for ( int i = 0; i < N; ++i )
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{
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b.push_back( i * 2.0 + 1.0 );
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}
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double correlation = RiaStatisticsTools::pearsonCorrelation( a, b );
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EXPECT_NEAR( correlation, 1.0, 1.0e-2 );
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}
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//--------------------------------------------------------------------------------------------------
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///
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//--------------------------------------------------------------------------------------------------
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TEST( RiaStatisticsTools, NegativeCorrelation )
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{
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const int N = 1000;
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std::vector<double> a, b;
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a.reserve( N );
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b.reserve( N );
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for ( int i = 0; i < N; ++i )
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{
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a.push_back( (double)i );
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}
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for ( int i = 0; i < N; ++i )
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{
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b.push_back( i * -2.0 + 1.0 );
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}
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double correlation = RiaStatisticsTools::pearsonCorrelation( a, b );
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EXPECT_NEAR( correlation, -1.0, 1.0e-2 );
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}
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//--------------------------------------------------------------------------------------------------
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///
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//--------------------------------------------------------------------------------------------------
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TEST( RiaStatisticsTools, MinValue )
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{
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const int N = 1000;
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std::vector<double> a;
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for ( int i = 10; i < N; ++i )
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{
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a.push_back( static_cast<double>( i ) );
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}
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double minValue = RiaStatisticsTools::minimumValue( a );
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EXPECT_EQ( minValue, 10.0 );
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}
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//--------------------------------------------------------------------------------------------------
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///
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//--------------------------------------------------------------------------------------------------
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TEST( RiaStatisticsTools, MaxValue )
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{
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const int N = 1000;
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std::vector<double> a;
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for ( int i = 10; i < N; ++i )
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{
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a.push_back( static_cast<double>( i ) );
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}
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double maxValue = RiaStatisticsTools::maximumValue( a );
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EXPECT_EQ( maxValue, 999.0 );
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}
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