office-gobmx/chart2/source/tools/ExponentialRegressionCurveCalculator.cxx
Jelle van der Waa dd9c97d587 fdo#62475 removed pointless comments
Change-Id: I3f5e86dba2df950aeb12c895f52d99274c0959aa
Reviewed-on: https://gerrit.libreoffice.org/5148
Reviewed-by: Luboš Luňák <l.lunak@suse.cz>
Tested-by: Luboš Luňák <l.lunak@suse.cz>
2013-07-29 11:34:33 +00:00

186 lines
6.1 KiB
C++

/* -*- 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 "ExponentialRegressionCurveCalculator.hxx"
#include "macros.hxx"
#include "RegressionCalculationHelper.hxx"
#include <rtl/math.hxx>
#include <rtl/ustrbuf.hxx>
using namespace ::com::sun::star;
namespace chart
{
ExponentialRegressionCurveCalculator::ExponentialRegressionCurveCalculator() :
m_fLogSlope( 0.0 ),
m_fLogIntercept( 0.0 )
{
::rtl::math::setNan( & m_fLogSlope );
::rtl::math::setNan( & m_fLogIntercept );
}
ExponentialRegressionCurveCalculator::~ExponentialRegressionCurveCalculator()
{}
// ____ XRegressionCurveCalculator ____
void SAL_CALL ExponentialRegressionCurveCalculator::recalculateRegression(
const uno::Sequence< double >& aXValues,
const uno::Sequence< double >& aYValues )
throw (uno::RuntimeException)
{
RegressionCalculationHelper::tDoubleVectorPair aValues(
RegressionCalculationHelper::cleanup(
aXValues, aYValues,
RegressionCalculationHelper::isValidAndYPositive()));
const size_t nMax = aValues.first.size();
if( nMax == 0 )
{
::rtl::math::setNan( & m_fLogSlope );
::rtl::math::setNan( & m_fLogIntercept );
::rtl::math::setNan( & m_fCorrelationCoeffitient );// actual it is coefficient of determination
return;
}
double fAverageX = 0.0, fAverageY = 0.0;
size_t i = 0;
for( i = 0; i < nMax; ++i )
{
fAverageX += aValues.first[i];
fAverageY += log( aValues.second[i] );
}
const double fN = static_cast< double >( nMax );
fAverageX /= fN;
fAverageY /= fN;
double fQx = 0.0, fQy = 0.0, fQxy = 0.0;
for( i = 0; i < nMax; ++i )
{
double fDeltaX = aValues.first[i] - fAverageX;
double fDeltaY = log( aValues.second[i] ) - fAverageY;
fQx += fDeltaX * fDeltaX;
fQy += fDeltaY * fDeltaY;
fQxy += fDeltaX * fDeltaY;
}
m_fLogSlope = fQxy / fQx;
m_fLogIntercept = fAverageY - m_fLogSlope * fAverageX;
m_fCorrelationCoeffitient = fQxy / sqrt( fQx * fQy );
}
double SAL_CALL ExponentialRegressionCurveCalculator::getCurveValue( double x )
throw (lang::IllegalArgumentException,
uno::RuntimeException)
{
double fResult;
::rtl::math::setNan( & fResult );
if( ! ( ::rtl::math::isNan( m_fLogSlope ) ||
::rtl::math::isNan( m_fLogIntercept )))
{
fResult = exp(m_fLogIntercept + x * m_fLogSlope);
}
return fResult;
}
uno::Sequence< geometry::RealPoint2D > SAL_CALL ExponentialRegressionCurveCalculator::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)
{
if( bMaySkipPointsInCalculation &&
isLinearScaling( xScalingX ) &&
isLogarithmicScaling( 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 );
}
OUString ExponentialRegressionCurveCalculator::ImplGetRepresentation(
const uno::Reference< util::XNumberFormatter >& xNumFormatter,
::sal_Int32 nNumberFormatKey ) const
{
double fIntercept = exp(m_fLogIntercept);
double fSlope = exp(m_fLogSlope);
bool bHasSlope = !rtl::math::approxEqual( fSlope, 1.0 );
bool bHasIntercept = !rtl::math::approxEqual( fIntercept, 1.0 );
OUStringBuffer aBuf( "f(x) = ");
if ( fIntercept == 0.0)
{
// underflow, a true zero is impossible
aBuf.append( "exp( ");
aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fLogIntercept) );
aBuf.append( (m_fLogSlope < 0.0) ? " - " : " + ");
aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, fabs(m_fLogSlope)) );
aBuf.append( " x )");
}
else
{
if (bHasIntercept)
{
aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, fIntercept) );
aBuf.append( " exp( ");
aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fLogSlope) );
aBuf.append( " x )");
}
else
{
// show logarithmic output, if intercept and slope both are near one
// otherwise drop output of intercept, which is 1 here
aBuf.append( " exp( ");
if (!bHasSlope)
{
aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fLogIntercept) );
aBuf.append( (m_fLogSlope < 0.0) ? " - " : " + ");
aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, fabs(m_fLogSlope)) );
}
else
{
aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fLogSlope) );
}
aBuf.append( " x )");
}
}
return aBuf.makeStringAndClear();
}
} // namespace chart
/* vim:set shiftwidth=4 softtabstop=4 expandtab: */