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/* -*- Mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
* This file is part of the LibreOffice project.
*
* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
* file, You can obtain one at http://mozilla.org/MPL/2.0/.
*
* This file incorporates work covered by the following license notice:
*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed
* with this work for additional information regarding copyright
* ownership. The ASF licenses this file to you under the Apache
* License, Version 2.0 (the "License"); you may not use this file
* except in compliance with the License. You may obtain a copy of
* the License at http://www.apache.org/licenses/LICENSE-2.0 .
*/
#include <MeanValueRegressionCurveCalculator.hxx>
#include <osl/diagnose.h>
#include <rtl/math.hxx>
using namespace ::com::sun::star;
namespace chart
{
MeanValueRegressionCurveCalculator::MeanValueRegressionCurveCalculator() :
m_fMeanValue( 0.0 )
{
::rtl::math::setNan( & m_fMeanValue );
}
MeanValueRegressionCurveCalculator::~MeanValueRegressionCurveCalculator()
{}
// ____ XRegressionCurveCalculator ____
void SAL_CALL MeanValueRegressionCurveCalculator::recalculateRegression(
const uno::Sequence< double >& /*aXValues*/,
const uno::Sequence< double >& aYValues )
{
const sal_Int32 nDataLength = aYValues.getLength();
sal_Int32 nMax = nDataLength;
double fSumY = 0.0;
const double * pY = aYValues.getConstArray();
for( sal_Int32 i = 0; i < nDataLength; ++i )
{
if( std::isnan( pY[i] ) ||
std::isinf( pY[i] ))
--nMax;
else
fSumY += pY[i];
}
m_fCorrelationCoeffitient = 0.0;
if( nMax == 0 )
{
::rtl::math::setNan( & m_fMeanValue );
}
else
{
m_fMeanValue = fSumY / static_cast< double >( nMax );
// correlation coefficient: standard deviation
if( nMax > 1 )
{
double fErrorSum = 0.0;
for( sal_Int32 i = 0; i < nDataLength; ++i )
{
if( !std::isnan( pY[i] ) &&
!std::isinf( pY[i] ))
{
double v = m_fMeanValue - pY[i];
fErrorSum += (v*v);
}
}
OSL_ASSERT( fErrorSum >= 0.0 );
m_fCorrelationCoeffitient = sqrt( fErrorSum / (nMax - 1 ));
}
}
}
double SAL_CALL MeanValueRegressionCurveCalculator::getCurveValue( double /*x*/ )
{
return m_fMeanValue;
}
uno::Sequence< geometry::RealPoint2D > SAL_CALL MeanValueRegressionCurveCalculator::getCurveValues(
double min, double max, ::sal_Int32 nPointCount,
const uno::Reference< chart2::XScaling >& xScalingX,
const uno::Reference< chart2::XScaling >& xScalingY,
sal_Bool bMaySkipPointsInCalculation )
{
if( bMaySkipPointsInCalculation )
{
// optimize result
uno::Sequence< geometry::RealPoint2D > aResult( 2 );
aResult[0].X = min;
aResult[0].Y = m_fMeanValue;
aResult[1].X = max;
aResult[1].Y = m_fMeanValue;
return aResult;
}
return RegressionCurveCalculator::getCurveValues( min, max, nPointCount, xScalingX, xScalingY, bMaySkipPointsInCalculation );
}
OUString MeanValueRegressionCurveCalculator::ImplGetRepresentation(
const uno::Reference< util::XNumberFormatter >& xNumFormatter,
sal_Int32 nNumberFormatKey, sal_Int32* pFormulaLength /* = nullptr */ ) const
{
OUString aBuf(mYName + " = ");
if ( pFormulaLength )
{
*pFormulaLength -= aBuf.getLength();
if ( *pFormulaLength <= 0 )
return "###";
}
return ( aBuf + getFormattedString( xNumFormatter, nNumberFormatKey, m_fMeanValue, pFormulaLength ) );
}
} // namespace chart
/* vim:set shiftwidth=4 softtabstop=4 expandtab: */
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