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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-27 16:51:28 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-27 16:51:28 +0000 |
commit | 940b4d1848e8c70ab7642901a68594e8016caffc (patch) | |
tree | eb72f344ee6c3d9b80a7ecc079ea79e9fba8676d /chart2/source/tools/MeanValueRegressionCurveCalculator.cxx | |
parent | Initial commit. (diff) | |
download | libreoffice-940b4d1848e8c70ab7642901a68594e8016caffc.tar.xz libreoffice-940b4d1848e8c70ab7642901a68594e8016caffc.zip |
Adding upstream version 1:7.0.4.upstream/1%7.0.4upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'chart2/source/tools/MeanValueRegressionCurveCalculator.cxx')
-rw-r--r-- | chart2/source/tools/MeanValueRegressionCurveCalculator.cxx | 128 |
1 files changed, 128 insertions, 0 deletions
diff --git a/chart2/source/tools/MeanValueRegressionCurveCalculator.cxx b/chart2/source/tools/MeanValueRegressionCurveCalculator.cxx new file mode 100644 index 000000000..c9821343b --- /dev/null +++ b/chart2/source/tools/MeanValueRegressionCurveCalculator.cxx @@ -0,0 +1,128 @@ +/* -*- 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_fCorrelationCoefficient = 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_fCorrelationCoefficient = 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: */ |