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Add BinningMode (Linear/Logarithmic) and OutOfRangeHandling (Exclude/Include in Boundary Bins) to RigHistogramCalculator, with defaulted constructor arguments so existing callers are unaffected. All four histogram plot data sources get shared options for binning mode and an optional user-defined bin range through new PDM fields on RimHistogramDataSource. The grid statistics data source computes non-default histograms through a new non-caching RigStatisticsDataCache::computeHistogram() pass-through, leaving the cached statistics used by the 3D overlay and the P10/P90/mean annotation lines untouched. Selecting logarithmic binning enables logarithmic scale on the plot X axis once, via a new signal handled by RimHistogramCurve. Also fix the bin index computation to use uniform bins of width range/nBins, consistent with calculatePercentil() and the bin edges drawn by the plots. The previous divisor (nBins - 1) shifted counts by up to one bin width relative to the drawn bars and slightly biased histogram-based percentile estimates.
302 lines
8.0 KiB
C++
302 lines
8.0 KiB
C++
/////////////////////////////////////////////////////////////////////////////////
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//
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// Copyright (C) 2011-2012 Statoil ASA, Ceetron AS
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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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#pragma once
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#include "RigStatisticsTools.h"
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#include <cmath>
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#include <cstddef>
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#include <expected>
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#include <set>
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#include <string>
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#include <vector>
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class RigStatisticsMath
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{
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public:
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enum class PercentileStyle
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{
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REGULAR,
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SWITCHED
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};
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static void
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calculateBasicStatistics( const std::vector<double>& values, double* min, double* max, double* sum, double* range, double* mean, double* dev );
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static void calculateStatisticsCurves( const std::vector<double>& values,
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double* p10,
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double* p50,
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double* p90,
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double* mean,
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PercentileStyle percentileStyle );
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static std::expected<std::vector<double>, std::string>
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calculatePercentiles( const std::vector<double>& values, const std::vector<double>& quantiles, PercentileStyle percentileStyle );
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static std::expected<std::vector<double>, std::string> calculateNearestRankPercentiles( const std::vector<double>& inputValues,
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const std::vector<double>& percentiles,
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PercentileStyle percentileStyle );
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static std::expected<std::vector<double>, std::string> calculateInterpolatedPercentiles( const std::vector<double>& inputValues,
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const std::vector<double>& percentiles,
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PercentileStyle percentileStyle );
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static double calculateMean( const std::vector<double>& values );
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};
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//==================================================================================================
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/// Class to calculate a histogram, and histogram based p-value estimates
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//==================================================================================================
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class RigHistogramCalculator
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{
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public:
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enum class BinningMode
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{
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LINEAR,
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LOGARITHMIC
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};
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enum class OutOfRangeHandling
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{
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EXCLUDE,
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INCLUDE_IN_BOUNDARY_BINS
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};
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RigHistogramCalculator( double min,
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double max,
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size_t nBins,
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std::vector<size_t>* histogram,
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BinningMode binningMode = BinningMode::LINEAR,
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OutOfRangeHandling outOfRangeHandling = OutOfRangeHandling::EXCLUDE );
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void addData( const std::vector<double>& data );
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void addData( const std::vector<float>& data );
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void addValue( double value );
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/// Calculates the estimated percentile from the histogram.
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/// the percentile is the domain value at which pVal of the observations are below it.
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/// The estimate is only meaningful when the histogram covers the full range of the observed values.
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double calculatePercentil( double pVal, RigStatisticsMath::PercentileStyle percentileStyle );
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private:
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size_t m_maxIndex;
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double m_range;
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double m_min;
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double m_max;
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BinningMode m_binningMode;
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OutOfRangeHandling m_outOfRangeHandling;
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size_t m_observationCount;
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std::vector<size_t>* m_histogram;
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};
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class MinMaxAccumulator
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{
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public:
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MinMaxAccumulator( double initMin = HUGE_VAL, double initMax = -HUGE_VAL )
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: max( initMax )
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, min( initMin )
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{
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}
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void addData( const std::vector<double>& values )
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{
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for ( double val : values )
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{
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addValue( val );
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}
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}
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void addData( const std::vector<float>& values )
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{
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for ( float val : values )
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{
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addValue( val );
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}
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}
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void addValue( double value )
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{
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if ( RigStatisticsTools::isValidNumber<double>( value ) )
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{
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if ( value < min )
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{
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min = value;
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}
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if ( value > max )
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{
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max = value;
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}
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}
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}
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double max;
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double min;
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};
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class PercentilAccumulator
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{
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public:
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PercentilAccumulator() {}
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void addData( const std::vector<double>& values )
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{
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for ( double val : values )
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{
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addValue( val );
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}
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}
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void addData( const std::vector<float>& values )
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{
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for ( float val : values )
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{
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addValue( val );
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}
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}
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void addValue( double value ) { values.push_back( value ); }
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void computep10p90( double& p10, double& p90 )
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{
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double mean = HUGE_VAL;
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double p50 = HUGE_VAL;
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RigStatisticsMath::calculateStatisticsCurves( values, &p10, &p50, &p90, &mean, RigStatisticsMath::PercentileStyle::SWITCHED );
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}
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std::vector<double> values;
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};
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class PosNegAccumulator
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{
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public:
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PosNegAccumulator( double initPos = HUGE_VAL, double initNeg = -HUGE_VAL )
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: pos( initPos )
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, neg( initNeg )
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{
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}
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void addData( const std::vector<double>& values )
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{
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for ( double val : values )
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{
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addValue( val );
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}
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}
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void addData( const std::vector<float>& values )
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{
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for ( float val : values )
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{
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addValue( val );
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}
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}
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void addValue( double value )
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{
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if ( RigStatisticsTools::isValidNumber<double>( value ) )
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{
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if ( value < pos && value > 0 )
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{
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pos = value;
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}
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if ( value > neg && value < 0 )
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{
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neg = value;
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}
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}
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}
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double pos;
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double neg;
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};
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class SumCountAccumulator
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{
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public:
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SumCountAccumulator( double initSum = 0.0, size_t initCount = 0 )
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: valueSum( initSum )
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, sampleCount( initCount )
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{
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}
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void addData( const std::vector<double>& values )
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{
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for ( double val : values )
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{
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addValue( val );
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}
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}
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void addData( const std::vector<float>& values )
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{
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for ( float val : values )
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{
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addValue( val );
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}
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}
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void addValue( double value )
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{
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if ( RigStatisticsTools::isValidNumber<double>( value ) )
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{
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valueSum += value;
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++sampleCount;
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}
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}
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double valueSum;
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size_t sampleCount;
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};
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class UniqueValueAccumulator
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{
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public:
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UniqueValueAccumulator() {}
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void addData( const std::vector<double>& values )
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{
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for ( double val : values )
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{
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addValue( val );
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}
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}
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void addData( const std::vector<float>& values )
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{
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for ( float val : values )
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{
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addValue( val );
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}
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}
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void addValue( double value )
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{
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if ( RigStatisticsTools::isValidNumber<double>( value ) )
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{
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uniqueValues.insert( static_cast<int>( value ) );
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}
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}
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std::set<int> uniqueValues;
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};
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