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/* -*- 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 <sal/config.h>
#include <limits>
#include <string_view>
#include <ExponentialRegressionCurveCalculator.hxx>
#include <RegressionCalculationHelper.hxx>
#include <SpecialCharacters.hxx>
#include <rtl/math.hxx>
#include <rtl/ustrbuf.hxx>
using namespace ::com::sun::star;
namespace chart
{
ExponentialRegressionCurveCalculator::ExponentialRegressionCurveCalculator()
: m_fLogSlope(std::numeric_limits<double>::quiet_NaN())
, m_fLogIntercept(std::numeric_limits<double>::quiet_NaN())
, m_fSign(1.0)
{
}
ExponentialRegressionCurveCalculator::~ExponentialRegressionCurveCalculator()
{}
// ____ XRegressionCurveCalculator ____
void SAL_CALL ExponentialRegressionCurveCalculator::recalculateRegression(
const uno::Sequence< double >& aXValues,
const uno::Sequence< double >& aYValues )
{
RegressionCalculationHelper::tDoubleVectorPair aValues(
RegressionCalculationHelper::cleanup(
aXValues, aYValues,
RegressionCalculationHelper::isValidAndYPositive()));
m_fSign = 1.0;
size_t nMax = aValues.first.size();
if( nMax <= 1 ) // at least 2 points
{
aValues = RegressionCalculationHelper::cleanup(
aXValues, aYValues,
RegressionCalculationHelper::isValidAndYNegative());
nMax = aValues.first.size();
if( nMax <= 1 )
{
m_fLogSlope = std::numeric_limits<double>::quiet_NaN();
m_fLogIntercept = std::numeric_limits<double>::quiet_NaN();
m_fCorrelationCoefficient = std::numeric_limits<double>::quiet_NaN();// actual it is coefficient of determination
return;
}
m_fSign = -1.0;
}
double fAverageX = 0.0, fAverageY = 0.0;
double fLogIntercept = ( mForceIntercept && (m_fSign * mInterceptValue)>0 ) ? log(m_fSign * mInterceptValue) : 0.0;
std::vector<double> yVector;
yVector.resize(nMax, 0.0);
size_t i = 0;
for( i = 0; i < nMax; ++i )
{
double yValue = log( m_fSign *aValues.second[i] );
if (mForceIntercept)
{
yValue -= fLogIntercept;
}
else
{
fAverageX += aValues.first[i];
fAverageY += yValue;
}
yVector[i] = yValue;
}
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 = yVector[i] - fAverageY;
fQx += fDeltaX * fDeltaX;
fQy += fDeltaY * fDeltaY;
fQxy += fDeltaX * fDeltaY;
}
m_fLogSlope = fQxy / fQx;
m_fLogIntercept = mForceIntercept ? fLogIntercept : fAverageY - m_fLogSlope * fAverageX;
m_fCorrelationCoefficient = fQxy / sqrt( fQx * fQy );
}
double SAL_CALL ExponentialRegressionCurveCalculator::getCurveValue( double x )
{
if( ! ( std::isnan( m_fLogSlope ) ||
std::isnan( m_fLogIntercept )))
{
return m_fSign * exp(m_fLogIntercept + x * m_fLogSlope);
}
return std::numeric_limits<double>::quiet_NaN();
}
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 )
{
if( bMaySkipPointsInCalculation &&
isLinearScaling( xScalingX ) &&
isLogarithmicScaling( xScalingY ))
{
// optimize result
uno::Sequence< geometry::RealPoint2D > aResult{ { min, getCurveValue( min ) },
{ max, 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, sal_Int32* pFormulaMaxWidth /* = nullptr */ ) const
{
double fIntercept = exp(m_fLogIntercept);
bool bHasSlope = !rtl::math::approxEqual( exp(m_fLogSlope), 1.0 );
bool bHasLogSlope = !rtl::math::approxEqual( fabs(m_fLogSlope), 1.0 );
bool bHasIntercept = !rtl::math::approxEqual( fIntercept, 1.0 ) && fIntercept != 0.0;
OUStringBuffer aBuf( mYName + " = " );
sal_Int32 nLineLength = aBuf.getLength();
sal_Int32 nValueLength=0;
if ( pFormulaMaxWidth && *pFormulaMaxWidth > 0 )
{ // count characters different from coefficients
sal_Int32 nCharMin = nLineLength + 10 + mXName.getLength(); // 10 = "exp( ", " x )" + 2 extra characters
if ( m_fSign < 0.0 )
nCharMin += 2;
if ( fIntercept == 0.0 || ( !bHasSlope && m_fLogIntercept != 0.0 ) )
nCharMin += 3; // " + " special case where equation is written exp( a + b x )
if ( ( bHasIntercept || fIntercept == 0.0 || ( !bHasSlope && m_fLogIntercept != 0.0 ) ) &&
bHasLogSlope )
nValueLength = ( *pFormulaMaxWidth - nCharMin ) / 2;
else
nValueLength = *pFormulaMaxWidth - nCharMin;
if ( nValueLength <= 0 )
nValueLength = 1;
}
// temporary buffer
OUStringBuffer aTmpBuf("");
// if nValueLength not calculated then nullptr
sal_Int32* pValueLength = nValueLength ? &nValueLength : nullptr;
if ( m_fSign < 0.0 )
aTmpBuf.append( OUStringChar(aMinusSign) + " " );
if ( bHasIntercept )
{
OUString aValueString = getFormattedString( xNumFormatter, nNumberFormatKey, fIntercept, pValueLength );
if ( aValueString != "1" ) // aValueString may be rounded to 1 if nValueLength is small
{
aTmpBuf.append( aValueString + " " );
addStringToEquation( aBuf, nLineLength, aTmpBuf, pFormulaMaxWidth );
aTmpBuf.truncate();
}
}
aTmpBuf.append( "exp( " );
if ( !bHasIntercept )
{
if ( fIntercept == 0.0 || // underflow, a true zero is impossible
( !bHasSlope && m_fLogIntercept != 0.0 ) ) // show logarithmic output, if intercept and slope both are near one
{ // otherwise drop output of intercept, which is 1 here
OUString aValueString = getFormattedString( xNumFormatter, nNumberFormatKey, m_fLogIntercept, pValueLength );
if ( aValueString != "0" ) // aValueString may be rounded to 0 if nValueLength is small
{
aTmpBuf.append( aValueString ).append( (m_fLogSlope < 0.0) ? std::u16string_view(u" ") : std::u16string_view(u" + ") );
}
}
}
if ( m_fLogSlope < 0.0 )
aTmpBuf.append( OUStringChar(aMinusSign) + " " );
if ( bHasLogSlope )
{
OUString aValueString = getFormattedString( xNumFormatter, nNumberFormatKey, fabs(m_fLogSlope), pValueLength );
if ( aValueString != "1" ) // aValueString may be rounded to 1 if nValueLength is small
{
aTmpBuf.append( aValueString + " " );
}
}
aTmpBuf.append( mXName + " )");
addStringToEquation( aBuf, nLineLength, aTmpBuf, pFormulaMaxWidth );
return aBuf.makeStringAndClear();
}
} // namespace chart
/* vim:set shiftwidth=4 softtabstop=4 expandtab: */
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