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libreoffice/chart2/source/tools/LinearRegressionCurveCalculator.cxx

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/*************************************************************************
*
* OpenOffice.org - a multi-platform office productivity suite
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*
* $RCSfile: LinearRegressionCurveCalculator.cxx,v $
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*
* $Revision: 1.7 $
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*
* last change: $Author: ihi $ $Date: 2007-11-23 12:05:41 $
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*
* The Contents of this file are made available subject to
* the terms of GNU Lesser General Public License Version 2.1.
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*
*
* GNU Lesser General Public License Version 2.1
* =============================================
* Copyright 2005 by Sun Microsystems, Inc.
* 901 San Antonio Road, Palo Alto, CA 94303, USA
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*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License version 2.1, as published by the Free Software Foundation.
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*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
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*
* You should have received a copy of the GNU Lesser General Public
* License along with this library; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston,
* MA 02111-1307 USA
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*
************************************************************************/
// MARKER(update_precomp.py): autogen include statement, do not remove
#include "precompiled_chart2.hxx"
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#include "LinearRegressionCurveCalculator.hxx"
#include "macros.hxx"
#include "RegressionCalculationHelper.hxx"
#include <rtl/math.hxx>
#include <rtl/ustrbuf.hxx>
using namespace ::com::sun::star;
using ::rtl::OUString;
using ::rtl::OUStringBuffer;
namespace chart
{
LinearRegressionCurveCalculator::LinearRegressionCurveCalculator() :
m_fSlope( 0.0 ),
m_fIntercept( 0.0 )
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{
::rtl::math::setNan( & m_fSlope );
::rtl::math::setNan( & m_fIntercept );
}
LinearRegressionCurveCalculator::~LinearRegressionCurveCalculator()
{}
// ____ XRegressionCurveCalculator ____
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void SAL_CALL LinearRegressionCurveCalculator::recalculateRegression(
const uno::Sequence< double >& aXValues,
const uno::Sequence< double >& aYValues )
throw (uno::RuntimeException)
{
RegressionCalculationHelper::tDoubleVectorPair aValues(
RegressionCalculationHelper::cleanup(
aXValues, aYValues,
RegressionCalculationHelper::isValid()));
const size_t nMax = aValues.first.size();
if( nMax == 0 )
{
::rtl::math::setNan( & m_fSlope );
::rtl::math::setNan( & m_fIntercept );
::rtl::math::setNan( & m_fCorrelationCoeffitient );
return;
}
const double fN = static_cast< double >( nMax );
double fSumX = 0.0, fSumY = 0.0, fSumXSq = 0.0, fSumYSq = 0.0, fSumXY = 0.0;
for( size_t i = 0; i < nMax; ++i )
{
fSumX += aValues.first[i];
fSumY += aValues.second[i];
fSumXSq += aValues.first[i] * aValues.first[i];
fSumYSq += aValues.second[i] * aValues.second[i];
fSumXY += aValues.first[i] * aValues.second[i];
}
m_fSlope = (fN * fSumXY - fSumX * fSumY) / ( fN * fSumXSq - fSumX * fSumX );
m_fIntercept = (fSumY - m_fSlope * fSumX) / fN;
m_fCorrelationCoeffitient = ( fN * fSumXY - fSumX * fSumY ) /
sqrt( ( fN * fSumXSq - fSumX * fSumX ) *
( fN * fSumYSq - fSumY * fSumY ) );
}
double SAL_CALL LinearRegressionCurveCalculator::getCurveValue( double x )
throw (lang::IllegalArgumentException,
uno::RuntimeException)
{
double fResult;
::rtl::math::setNan( & fResult );
if( ! ( ::rtl::math::isNan( m_fSlope ) ||
::rtl::math::isNan( m_fIntercept )))
{
fResult = m_fSlope * x + m_fIntercept;
}
return fResult;
}
uno::Sequence< geometry::RealPoint2D > SAL_CALL LinearRegressionCurveCalculator::getCurveValues(
double min, double max, ::sal_Int32 nPointCount,
const uno::Reference< chart2::XScaling >& xScalingX,
const uno::Reference< chart2::XScaling >& xScalingY,
::sal_Bool bMaySkipPointsInCalculation )
throw (lang::IllegalArgumentException,
uno::RuntimeException)
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{
if( bMaySkipPointsInCalculation &&
isLinearScaling( xScalingX ) &&
isLinearScaling( xScalingY ))
{
// optimize result
uno::Sequence< geometry::RealPoint2D > aResult( 2 );
aResult[0].X = min;
aResult[0].Y = this->getCurveValue( min );
aResult[1].X = max;
aResult[1].Y = this->getCurveValue( max );
return aResult;
}
return RegressionCurveCalculator::getCurveValues( min, max, nPointCount, xScalingX, xScalingY, bMaySkipPointsInCalculation );
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}
OUString LinearRegressionCurveCalculator::ImplGetRepresentation(
const uno::Reference< util::XNumberFormatter >& xNumFormatter,
::sal_Int32 nNumberFormatKey ) const
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{
OUStringBuffer aBuf( C2U( "f(x) = " ));
bool bHaveSlope = false;
if( m_fSlope != 0.0 )
{
if( ::rtl::math::approxEqual( fabs( m_fSlope ), 1.0 ))
{
if( m_fSlope < 0 )
aBuf.append( UC_MINUS_SIGN );
}
else
aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fSlope ));
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aBuf.append( sal_Unicode( 'x' ));
bHaveSlope = true;
}
if( bHaveSlope )
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{
if( m_fIntercept < 0.0 )
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{
aBuf.append( UC_SPACE );
aBuf.append( UC_MINUS_SIGN );
aBuf.append( UC_SPACE );
aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, fabs( m_fIntercept )));
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}
else if( m_fIntercept > 0.0 )
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{
aBuf.appendAscii( RTL_CONSTASCII_STRINGPARAM( " + " ));
aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fIntercept ));
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}
}
else
{
aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fIntercept ));
}
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return aBuf.makeStringAndClear();
}
} // namespace chart