LCOV - code coverage report
Current view: top level - chart2/source/tools - ExponentialRegressionCurveCalculator.cxx (source / functions) Hit Total Coverage
Test: commit c8344322a7af75b84dd3ca8f78b05543a976dfd5 Lines: 0 82 0.0 %
Date: 2015-06-13 12:38:46 Functions: 0 7 0.0 %
Legend: Lines: hit not hit

          Line data    Source code
       1             : /* -*- Mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
       2             : /*
       3             :  * This file is part of the LibreOffice project.
       4             :  *
       5             :  * This Source Code Form is subject to the terms of the Mozilla Public
       6             :  * License, v. 2.0. If a copy of the MPL was not distributed with this
       7             :  * file, You can obtain one at http://mozilla.org/MPL/2.0/.
       8             :  *
       9             :  * This file incorporates work covered by the following license notice:
      10             :  *
      11             :  *   Licensed to the Apache Software Foundation (ASF) under one or more
      12             :  *   contributor license agreements. See the NOTICE file distributed
      13             :  *   with this work for additional information regarding copyright
      14             :  *   ownership. The ASF licenses this file to you under the Apache
      15             :  *   License, Version 2.0 (the "License"); you may not use this file
      16             :  *   except in compliance with the License. You may obtain a copy of
      17             :  *   the License at http://www.apache.org/licenses/LICENSE-2.0 .
      18             :  */
      19             : 
      20             : #include "ExponentialRegressionCurveCalculator.hxx"
      21             : #include "macros.hxx"
      22             : #include "RegressionCalculationHelper.hxx"
      23             : 
      24             : #include <rtl/math.hxx>
      25             : #include <rtl/ustrbuf.hxx>
      26             : 
      27             : using namespace ::com::sun::star;
      28             : 
      29             : namespace chart
      30             : {
      31             : 
      32           0 : ExponentialRegressionCurveCalculator::ExponentialRegressionCurveCalculator() :
      33             :         m_fLogSlope( 0.0 ),
      34           0 :         m_fLogIntercept( 0.0 )
      35             : {
      36           0 :     ::rtl::math::setNan( & m_fLogSlope );
      37           0 :     ::rtl::math::setNan( & m_fLogIntercept );
      38           0 : }
      39             : 
      40           0 : ExponentialRegressionCurveCalculator::~ExponentialRegressionCurveCalculator()
      41           0 : {}
      42             : 
      43             : // ____ XRegressionCurveCalculator ____
      44           0 : void SAL_CALL ExponentialRegressionCurveCalculator::recalculateRegression(
      45             :     const uno::Sequence< double >& aXValues,
      46             :     const uno::Sequence< double >& aYValues )
      47             :     throw (uno::RuntimeException, std::exception)
      48             : {
      49             :     RegressionCalculationHelper::tDoubleVectorPair aValues(
      50             :         RegressionCalculationHelper::cleanup(
      51             :             aXValues, aYValues,
      52           0 :             RegressionCalculationHelper::isValidAndYPositive()));
      53             : 
      54           0 :     const size_t nMax = aValues.first.size();
      55           0 :     if( nMax == 0 )
      56             :     {
      57           0 :         ::rtl::math::setNan( & m_fLogSlope );
      58           0 :         ::rtl::math::setNan( & m_fLogIntercept );
      59           0 :         ::rtl::math::setNan( & m_fCorrelationCoeffitient );// actual it is coefficient of determination
      60           0 :         return;
      61             :     }
      62             : 
      63           0 :     double fAverageX = 0.0, fAverageY = 0.0;
      64           0 :     double fLogIntercept = mForceIntercept ? log(mInterceptValue) : 0.0;
      65           0 :     std::vector<double> yVector;
      66           0 :     yVector.resize(nMax, 0.0);
      67             : 
      68           0 :     size_t i = 0;
      69           0 :     for( i = 0; i < nMax; ++i )
      70             :     {
      71           0 :         double yValue = log(aValues.second[i]);
      72           0 :         if (mForceIntercept)
      73             :         {
      74           0 :             yValue -= fLogIntercept;
      75             :         }
      76             :         else
      77             :         {
      78           0 :             fAverageX += aValues.first[i];
      79           0 :             fAverageY += yValue;
      80             :         }
      81           0 :         yVector[i] = yValue;
      82             :     }
      83             : 
      84           0 :     const double fN = static_cast< double >( nMax );
      85           0 :     fAverageX /= fN;
      86           0 :     fAverageY /= fN;
      87             : 
      88           0 :     double fQx = 0.0, fQy = 0.0, fQxy = 0.0;
      89           0 :     for( i = 0; i < nMax; ++i )
      90             :     {
      91           0 :         double fDeltaX = aValues.first[i] - fAverageX;
      92           0 :         double fDeltaY = yVector[i] - fAverageY;
      93             : 
      94           0 :         fQx  += fDeltaX * fDeltaX;
      95           0 :         fQy  += fDeltaY * fDeltaY;
      96           0 :         fQxy += fDeltaX * fDeltaY;
      97             :     }
      98             : 
      99           0 :     m_fLogSlope = fQxy / fQx;
     100           0 :     m_fLogIntercept = mForceIntercept ? fLogIntercept : fAverageY - m_fLogSlope * fAverageX;
     101           0 :     m_fCorrelationCoeffitient = fQxy / sqrt( fQx * fQy );
     102             : }
     103             : 
     104           0 : double SAL_CALL ExponentialRegressionCurveCalculator::getCurveValue( double x )
     105             :     throw (lang::IllegalArgumentException,
     106             :            uno::RuntimeException, std::exception)
     107             : {
     108             :     double fResult;
     109           0 :     ::rtl::math::setNan( & fResult );
     110             : 
     111           0 :     if( ! ( ::rtl::math::isNan( m_fLogSlope ) ||
     112           0 :             ::rtl::math::isNan( m_fLogIntercept )))
     113             :     {
     114           0 :         fResult = exp(m_fLogIntercept + x * m_fLogSlope);
     115             :     }
     116             : 
     117           0 :     return fResult;
     118             : }
     119             : 
     120           0 : uno::Sequence< geometry::RealPoint2D > SAL_CALL ExponentialRegressionCurveCalculator::getCurveValues(
     121             :     double min, double max, ::sal_Int32 nPointCount,
     122             :     const uno::Reference< chart2::XScaling >& xScalingX,
     123             :     const uno::Reference< chart2::XScaling >& xScalingY,
     124             :     sal_Bool bMaySkipPointsInCalculation )
     125             :     throw (lang::IllegalArgumentException,
     126             :            uno::RuntimeException, std::exception)
     127             : {
     128           0 :     if( bMaySkipPointsInCalculation &&
     129           0 :         isLinearScaling( xScalingX ) &&
     130           0 :         isLogarithmicScaling( xScalingY ))
     131             :     {
     132             :         // optimize result
     133           0 :         uno::Sequence< geometry::RealPoint2D > aResult( 2 );
     134           0 :         aResult[0].X = min;
     135           0 :         aResult[0].Y = this->getCurveValue( min );
     136           0 :         aResult[1].X = max;
     137           0 :         aResult[1].Y = this->getCurveValue( max );
     138             : 
     139           0 :         return aResult;
     140             :     }
     141             : 
     142           0 :     return RegressionCurveCalculator::getCurveValues( min, max, nPointCount, xScalingX, xScalingY, bMaySkipPointsInCalculation );
     143             : }
     144             : 
     145           0 : OUString ExponentialRegressionCurveCalculator::ImplGetRepresentation(
     146             :     const uno::Reference< util::XNumberFormatter >& xNumFormatter,
     147             :     ::sal_Int32 nNumberFormatKey ) const
     148             : {
     149           0 :     double fIntercept = exp(m_fLogIntercept);
     150           0 :     double fSlope = exp(m_fLogSlope);
     151           0 :     bool bHasSlope = !rtl::math::approxEqual( fSlope, 1.0 );
     152           0 :     bool bHasIntercept = !rtl::math::approxEqual( fIntercept, 1.0 );
     153             : 
     154           0 :     OUStringBuffer aBuf( "f(x) = ");
     155             : 
     156           0 :     if ( fIntercept == 0.0)
     157             :     {
     158             :         // underflow, a true zero is impossible
     159           0 :         aBuf.append( "exp( ");
     160           0 :         aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fLogIntercept) );
     161           0 :         aBuf.append( (m_fLogSlope < 0.0) ? " - " : " + ");
     162           0 :         aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, fabs(m_fLogSlope)) );
     163           0 :         aBuf.append( " x )");
     164             :     }
     165             :     else
     166             :     {
     167           0 :         if (bHasIntercept)
     168             :         {
     169           0 :             aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, fIntercept) );
     170           0 :             aBuf.append( " exp( ");
     171           0 :             aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fLogSlope) );
     172           0 :             aBuf.append( " x )");
     173             :         }
     174             :         else
     175             :         {
     176             :             // show logarithmic output, if intercept and slope both are near one
     177             :             // otherwise drop output of intercept, which is 1 here
     178           0 :             aBuf.append( " exp( ");
     179           0 :             if (!bHasSlope)
     180             :             {
     181           0 :                 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fLogIntercept) );
     182           0 :                 aBuf.append( (m_fLogSlope < 0.0) ? " - " : " + ");
     183           0 :                 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, fabs(m_fLogSlope)) );
     184             :             }
     185             :             else
     186             :             {
     187           0 :                 aBuf.append( getFormattedString( xNumFormatter, nNumberFormatKey, m_fLogSlope) );
     188             :             }
     189           0 :             aBuf.append( " x )");
     190             :         }
     191             :     }
     192             : 
     193           0 :     return aBuf.makeStringAndClear();
     194             : }
     195             : 
     196             : } //  namespace chart
     197             : 
     198             : /* vim:set shiftwidth=4 softtabstop=4 expandtab: */

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