d7b8b752cb
2008/03/28 16:44:23 rt 1.7.60.1: #i87441# Change license header to LPGL v3.
182 lines
5.8 KiB
C++
182 lines
5.8 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: LinearRegressionCurveCalculator.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 "LinearRegressionCurveCalculator.hxx"
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#include "macros.hxx"
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#include "RegressionCalculationHelper.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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LinearRegressionCurveCalculator::LinearRegressionCurveCalculator() :
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m_fSlope( 0.0 ),
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m_fIntercept( 0.0 )
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{
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::rtl::math::setNan( & m_fSlope );
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::rtl::math::setNan( & m_fIntercept );
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}
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LinearRegressionCurveCalculator::~LinearRegressionCurveCalculator()
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{}
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// ____ XRegressionCurveCalculator ____
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void SAL_CALL LinearRegressionCurveCalculator::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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RegressionCalculationHelper::tDoubleVectorPair aValues(
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RegressionCalculationHelper::cleanup(
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aXValues, aYValues,
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RegressionCalculationHelper::isValid()));
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const size_t nMax = aValues.first.size();
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if( nMax == 0 )
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{
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::rtl::math::setNan( & m_fSlope );
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::rtl::math::setNan( & m_fIntercept );
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::rtl::math::setNan( & m_fCorrelationCoeffitient );
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return;
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}
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const double fN = static_cast< double >( nMax );
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double fSumX = 0.0, fSumY = 0.0, fSumXSq = 0.0, fSumYSq = 0.0, fSumXY = 0.0;
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for( size_t i = 0; i < nMax; ++i )
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{
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fSumX += aValues.first[i];
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fSumY += aValues.second[i];
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fSumXSq += aValues.first[i] * aValues.first[i];
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fSumYSq += aValues.second[i] * aValues.second[i];
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fSumXY += aValues.first[i] * aValues.second[i];
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}
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m_fSlope = (fN * fSumXY - fSumX * fSumY) / ( fN * fSumXSq - fSumX * fSumX );
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m_fIntercept = (fSumY - m_fSlope * fSumX) / fN;
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m_fCorrelationCoeffitient = ( fN * fSumXY - fSumX * fSumY ) /
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sqrt( ( fN * fSumXSq - fSumX * fSumX ) *
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( fN * fSumYSq - fSumY * fSumY ) );
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}
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double SAL_CALL LinearRegressionCurveCalculator::getCurveValue( double x )
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throw (lang::IllegalArgumentException,
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uno::RuntimeException)
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{
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double fResult;
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::rtl::math::setNan( & fResult );
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if( ! ( ::rtl::math::isNan( m_fSlope ) ||
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::rtl::math::isNan( m_fIntercept )))
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{
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fResult = m_fSlope * x + m_fIntercept;
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}
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return fResult;
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}
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uno::Sequence< geometry::RealPoint2D > SAL_CALL LinearRegressionCurveCalculator::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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isLinearScaling( xScalingX ) &&
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isLinearScaling( xScalingY ))
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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 = this->getCurveValue( min );
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aResult[1].X = max;
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aResult[1].Y = this->getCurveValue( max );
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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 LinearRegressionCurveCalculator::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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bool bHaveSlope = false;
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if( m_fSlope != 0.0 )
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{
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if( ::rtl::math::approxEqual( fabs( m_fSlope ), 1.0 ))
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{
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if( m_fSlope < 0 )
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aBuf.append( UC_MINUS_SIGN );
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}
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else
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aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fSlope ));
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aBuf.append( sal_Unicode( 'x' ));
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bHaveSlope = true;
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}
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if( bHaveSlope )
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{
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if( m_fIntercept < 0.0 )
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{
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aBuf.append( UC_SPACE );
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aBuf.append( UC_MINUS_SIGN );
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aBuf.append( UC_SPACE );
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aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, fabs( m_fIntercept )));
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}
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else if( m_fIntercept > 0.0 )
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{
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aBuf.appendAscii( RTL_CONSTASCII_STRINGPARAM( " + " ));
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aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fIntercept ));
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}
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}
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else
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{
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aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fIntercept ));
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}
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return aBuf.makeStringAndClear();
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}
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} // namespace chart
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