146 lines
4.4 KiB
C++
146 lines
4.4 KiB
C++
/*************************************************************************
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*
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* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
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*
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* Copyright 2008 by Sun Microsystems, Inc.
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*
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* OpenOffice.org - a multi-platform office productivity suite
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*
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* $RCSfile: MeanValueRegressionCurveCalculator.cxx,v $
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* $Revision: 1.8 $
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*
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* This file is part of OpenOffice.org.
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*
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* OpenOffice.org is free software: you can redistribute it and/or modify
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* it under the terms of the GNU Lesser General Public License version 3
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* only, as published by the Free Software Foundation.
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*
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* OpenOffice.org is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU Lesser General Public License version 3 for more details
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* (a copy is included in the LICENSE file that accompanied this code).
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*
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* You should have received a copy of the GNU Lesser General Public License
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* version 3 along with OpenOffice.org. If not, see
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* <http://www.openoffice.org/license.html>
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* for a copy of the LGPLv3 License.
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*
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************************************************************************/
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// MARKER(update_precomp.py): autogen include statement, do not remove
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#include "precompiled_chart2.hxx"
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#include "MeanValueRegressionCurveCalculator.hxx"
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#include "macros.hxx"
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#include <rtl/math.hxx>
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#include <rtl/ustrbuf.hxx>
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using namespace ::com::sun::star;
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using ::rtl::OUString;
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using ::rtl::OUStringBuffer;
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namespace chart
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{
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MeanValueRegressionCurveCalculator::MeanValueRegressionCurveCalculator() :
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m_fMeanValue( 0.0 )
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{
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::rtl::math::setNan( & m_fMeanValue );
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}
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MeanValueRegressionCurveCalculator::~MeanValueRegressionCurveCalculator()
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{}
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// ____ XRegressionCurveCalculator ____
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void SAL_CALL MeanValueRegressionCurveCalculator::recalculateRegression(
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const uno::Sequence< double >& /*aXValues*/,
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const uno::Sequence< double >& aYValues )
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throw (uno::RuntimeException)
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{
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const sal_Int32 nDataLength = aYValues.getLength();
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sal_Int32 nMax = nDataLength;
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double fSumY = 0.0;
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const double * pY = aYValues.getConstArray();
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for( sal_Int32 i = 0; i < nDataLength; ++i )
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{
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if( ::rtl::math::isNan( pY[i] ) ||
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::rtl::math::isInf( pY[i] ))
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--nMax;
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else
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fSumY += pY[i];
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}
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m_fCorrelationCoeffitient = 0.0;
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if( nMax == 0 )
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{
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::rtl::math::setNan( & m_fMeanValue );
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}
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else
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{
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m_fMeanValue = fSumY / static_cast< double >( nMax );
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// correlation coefficient: standard deviation
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if( nMax > 1 )
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{
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double fErrorSum = 0.0;
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for( sal_Int32 i = 0; i < nDataLength; ++i )
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{
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if( !::rtl::math::isNan( pY[i] ) &&
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!::rtl::math::isInf( pY[i] ))
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{
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double v = m_fMeanValue - pY[i];
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fErrorSum += (v*v);
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}
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}
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OSL_ASSERT( fErrorSum >= 0.0 );
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m_fCorrelationCoeffitient = sqrt( fErrorSum / (nMax - 1 ));
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}
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}
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}
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double SAL_CALL MeanValueRegressionCurveCalculator::getCurveValue( double /*x*/ )
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throw (lang::IllegalArgumentException,
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uno::RuntimeException)
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{
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return m_fMeanValue;
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}
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uno::Sequence< geometry::RealPoint2D > SAL_CALL MeanValueRegressionCurveCalculator::getCurveValues(
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double min, double max, ::sal_Int32 nPointCount,
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const uno::Reference< chart2::XScaling >& xScalingX,
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const uno::Reference< chart2::XScaling >& xScalingY,
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::sal_Bool bMaySkipPointsInCalculation )
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throw (lang::IllegalArgumentException,
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uno::RuntimeException)
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{
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if( bMaySkipPointsInCalculation )
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{
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// optimize result
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uno::Sequence< geometry::RealPoint2D > aResult( 2 );
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aResult[0].X = min;
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aResult[0].Y = m_fMeanValue;
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aResult[1].X = max;
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aResult[1].Y = m_fMeanValue;
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return aResult;
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}
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return RegressionCurveCalculator::getCurveValues( min, max, nPointCount, xScalingX, xScalingY, bMaySkipPointsInCalculation );
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}
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OUString MeanValueRegressionCurveCalculator::ImplGetRepresentation(
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const uno::Reference< util::XNumberFormatter >& xNumFormatter,
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::sal_Int32 nNumberFormatKey ) const
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{
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OUStringBuffer aBuf( C2U( "f(x) = " ));
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aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fMeanValue ));
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return aBuf.makeStringAndClear();
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}
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} // namespace chart
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