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 * 
 * 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
 * 
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
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// MARKER(update_precomp.py): autogen include statement, do not remove
#include "precompiled_chart2.hxx"
#include "PotentialRegressionCurveCalculator.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
{

PotentialRegressionCurveCalculator::PotentialRegressionCurveCalculator() :
        m_fSlope( 0.0 ),
        m_fIntercept( 0.0 )
{
    ::rtl::math::setNan( & m_fSlope );
    ::rtl::math::setNan( & m_fIntercept );
}

PotentialRegressionCurveCalculator::~PotentialRegressionCurveCalculator()
{}

// ____ XRegressionCurveCalculator ____
void SAL_CALL PotentialRegressionCurveCalculator::recalculateRegression(
    const uno::Sequence< double >& aXValues,
    const uno::Sequence< double >& aYValues )
    throw (uno::RuntimeException)
{
    RegressionCalculationHelper::tDoubleVectorPair aValues(
        RegressionCalculationHelper::cleanup(
            aXValues, aYValues,
            RegressionCalculationHelper::isValidAndBothPositive()));

    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;
    }

    double fAverageX = 0.0, fAverageY = 0.0;
    size_t i = 0;
    for( i = 0; i < nMax; ++i )
    {
        fAverageX += log( 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 = log( aValues.first[i] ) - fAverageX;
        double fDeltaY = log( aValues.second[i] ) - fAverageY;

        fQx  += fDeltaX * fDeltaX;
        fQy  += fDeltaY * fDeltaY;
        fQxy += fDeltaX * fDeltaY;
    }

    m_fSlope = fQxy / fQx;
    m_fIntercept = fAverageY - m_fSlope * fAverageX;
    m_fCorrelationCoeffitient = fQxy / sqrt( fQx * fQy );

    m_fIntercept = exp( m_fIntercept );
}

double SAL_CALL PotentialRegressionCurveCalculator::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_fIntercept * pow( x, m_fSlope );
    }

    return fResult;
}

uno::Sequence< geometry::RealPoint2D > SAL_CALL PotentialRegressionCurveCalculator::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 &&
        isLogarithmicScaling( 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 PotentialRegressionCurveCalculator::ImplGetRepresentation(
    const uno::Reference< util::XNumberFormatter >& xNumFormatter,
    ::sal_Int32 nNumberFormatKey ) const
{
    OUStringBuffer aBuf( C2U( "f(x) = " ));

    if( m_fIntercept == 0.0 )
    {
        aBuf.append( sal_Unicode( '0' ));
    }
    else if( m_fSlope == 0.0 )
    {
        aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fIntercept ));
    }
    else
    {
        if( ! rtl::math::approxEqual( m_fIntercept, 1.0 ) )
        {
            aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fIntercept ));
            aBuf.append( sal_Unicode( ' ' ));
        }
        if( m_fSlope != 0.0 )
        {
            aBuf.appendAscii( RTL_CONSTASCII_STRINGPARAM( "x^" ));
            aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fSlope ));
        }
    }

    return aBuf.makeStringAndClear();
}

} //  namespace chart