chart2/source/tools/MeanValueRegressionCurveCalculator.cxx

   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 <MeanValueRegressionCurveCalculator.hxx>
  21
  22 #include <osl/diagnose.h>
  23 #include <rtl/math.hxx>
  24
  25 using namespace ::com::sun::star;
  26
  27 namespace chart
  28 {
  29
  30 MeanValueRegressionCurveCalculator::MeanValueRegressionCurveCalculator() :
  31         m_fMeanValue( 0.0 )
  32 {
  33     ::rtl::math::setNan( & m_fMeanValue );
  34 }
  35
  36 MeanValueRegressionCurveCalculator::~MeanValueRegressionCurveCalculator()
  37 {}
  38
  39 // ____ XRegressionCurveCalculator ____
  40 void SAL_CALL MeanValueRegressionCurveCalculator::recalculateRegression(
  41     const uno::Sequence< double >& /*aXValues*/,
  42     const uno::Sequence< double >& aYValues )
  43 {
  44     const sal_Int32 nDataLength = aYValues.getLength();
  45     sal_Int32 nMax = nDataLength;
  46     double fSumY = 0.0;
  47     const double * pY = aYValues.getConstArray();
  48
  49     for( sal_Int32 i = 0; i < nDataLength; ++i )
  50     {
  51         if( ::rtl::math::isNan( pY[i] ) ||
  52             ::rtl::math::isInf( pY[i] ))
  53             --nMax;
  54         else
  55             fSumY += pY[i];
  56     }
  57
  58     m_fCorrelationCoeffitient = 0.0;
  59
  60     if( nMax == 0 )
  61     {
  62         ::rtl::math::setNan( & m_fMeanValue );
  63     }
  64     else
  65     {
  66         m_fMeanValue = fSumY / static_cast< double >( nMax );
  67
  68         // correlation coefficient: standard deviation
  69         if( nMax > 1 )
  70         {
  71             double fErrorSum = 0.0;
  72             for( sal_Int32 i = 0; i < nDataLength; ++i )
  73             {
  74                 if( !::rtl::math::isNan( pY[i] ) &&
  75                     !::rtl::math::isInf( pY[i] ))
  76                 {
  77                     double v = m_fMeanValue - pY[i];
  78                     fErrorSum += (v*v);
  79                 }
  80             }
  81             OSL_ASSERT( fErrorSum >= 0.0 );
  82             m_fCorrelationCoeffitient = sqrt( fErrorSum / (nMax - 1 ));
  83         }
  84     }
  85 }
  86
  87 double SAL_CALL MeanValueRegressionCurveCalculator::getCurveValue( double /*x*/ )
  88 {
  89     return m_fMeanValue;
  90 }
  91
  92 uno::Sequence< geometry::RealPoint2D > SAL_CALL MeanValueRegressionCurveCalculator::getCurveValues(
  93     double min, double max, ::sal_Int32 nPointCount,
  94     const uno::Reference< chart2::XScaling >& xScalingX,
  95     const uno::Reference< chart2::XScaling >& xScalingY,
  96     sal_Bool bMaySkipPointsInCalculation )
  97 {
  98     if( bMaySkipPointsInCalculation )
  99     {
 100         // optimize result
 101         uno::Sequence< geometry::RealPoint2D > aResult( 2 );
 102         aResult[0].X = min;
 103         aResult[0].Y = m_fMeanValue;
 104         aResult[1].X = max;
 105         aResult[1].Y = m_fMeanValue;
 106
 107         return aResult;
 108     }
 109     return RegressionCurveCalculator::getCurveValues( min, max, nPointCount, xScalingX, xScalingY, bMaySkipPointsInCalculation );
 110 }
 111
 112 OUString MeanValueRegressionCurveCalculator::ImplGetRepresentation(
 113     const uno::Reference< util::XNumberFormatter >& xNumFormatter,
 114     sal_Int32 nNumberFormatKey, sal_Int32* pFormulaLength /* = nullptr */ ) const
 115 {
 116     OUString aBuf(mYName + " = ");
 117     if ( pFormulaLength )
 118     {
 119         *pFormulaLength -= aBuf.getLength();
 120         if ( *pFormulaLength <= 0 )
 121             return "###";
 122     }
 123     return ( aBuf + getFormattedString( xNumFormatter, nNumberFormatKey, m_fMeanValue, pFormulaLength ) );
 124 }
 125
 126 } //  namespace chart
 127
 128 /* vim:set shiftwidth=4 softtabstop=4 expandtab: */