chart2/source/tools/ExponentialRegressionCurveCalculator.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 <ExponentialRegressionCurveCalculator.hxx>
  21 #include <RegressionCalculationHelper.hxx>
  22 #include <SpecialCharacters.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 ExponentialRegressionCurveCalculator::ExponentialRegressionCurveCalculator()
  33     : m_fLogSlope(0.0)
  34     , m_fLogIntercept(0.0)
  35     , m_fSign(1.0)
  36 {
  37     ::rtl::math::setNan( & m_fLogSlope );
  38     ::rtl::math::setNan( & m_fLogIntercept );
  39 }
  40
  41 ExponentialRegressionCurveCalculator::~ExponentialRegressionCurveCalculator()
  42 {}
  43
  44 // ____ XRegressionCurveCalculator ____
  45 void SAL_CALL ExponentialRegressionCurveCalculator::recalculateRegression(
  46     const uno::Sequence< double >& aXValues,
  47     const uno::Sequence< double >& aYValues )
  48 {
  49     RegressionCalculationHelper::tDoubleVectorPair aValues(
  50         RegressionCalculationHelper::cleanup(
  51             aXValues, aYValues,
  52             RegressionCalculationHelper::isValidAndYPositive()));
  53     m_fSign = 1.0;
  54
  55     size_t nMax = aValues.first.size();
  56     if( nMax <= 1 ) // at least 2 points
  57     {
  58         aValues = RegressionCalculationHelper::cleanup(
  59                     aXValues, aYValues,
  60                     RegressionCalculationHelper::isValidAndYNegative());
  61         nMax = aValues.first.size();
  62         if( nMax <= 1 )
  63         {
  64             ::rtl::math::setNan( & m_fLogSlope );
  65             ::rtl::math::setNan( & m_fLogIntercept );
  66             ::rtl::math::setNan( & m_fCorrelationCoeffitient );// actual it is coefficient of determination
  67             return;
  68         }
  69         m_fSign = -1.0;
  70     }
  71
  72     double fAverageX = 0.0, fAverageY = 0.0;
  73     double fLogIntercept = ( mForceIntercept && (m_fSign * mInterceptValue)>0 ) ? log(m_fSign * mInterceptValue) : 0.0;
  74     std::vector<double> yVector;
  75     yVector.resize(nMax, 0.0);
  76
  77     size_t i = 0;
  78     for( i = 0; i < nMax; ++i )
  79     {
  80         double yValue = log( m_fSign *aValues.second[i] );
  81         if (mForceIntercept)
  82         {
  83             yValue -= fLogIntercept;
  84         }
  85         else
  86         {
  87             fAverageX += aValues.first[i];
  88             fAverageY += yValue;
  89         }
  90         yVector[i] = yValue;
  91     }
  92
  93     const double fN = static_cast< double >( nMax );
  94     fAverageX /= fN;
  95     fAverageY /= fN;
  96
  97     double fQx = 0.0, fQy = 0.0, fQxy = 0.0;
  98     for( i = 0; i < nMax; ++i )
  99     {
 100         double fDeltaX = aValues.first[i] - fAverageX;
 101         double fDeltaY = yVector[i] - fAverageY;
 102
 103         fQx  += fDeltaX * fDeltaX;
 104         fQy  += fDeltaY * fDeltaY;
 105         fQxy += fDeltaX * fDeltaY;
 106     }
 107
 108     m_fLogSlope = fQxy / fQx;
 109     m_fLogIntercept = mForceIntercept ? fLogIntercept : fAverageY - m_fLogSlope * fAverageX;
 110     m_fCorrelationCoeffitient = fQxy / sqrt( fQx * fQy );
 111 }
 112
 113 double SAL_CALL ExponentialRegressionCurveCalculator::getCurveValue( double x )
 114 {
 115     double fResult;
 116     ::rtl::math::setNan( & fResult );
 117
 118     if( ! ( ::rtl::math::isNan( m_fLogSlope ) ||
 119             ::rtl::math::isNan( m_fLogIntercept )))
 120     {
 121         fResult = m_fSign * exp(m_fLogIntercept + x * m_fLogSlope);
 122     }
 123
 124     return fResult;
 125 }
 126
 127 uno::Sequence< geometry::RealPoint2D > SAL_CALL ExponentialRegressionCurveCalculator::getCurveValues(
 128     double min, double max, ::sal_Int32 nPointCount,
 129     const uno::Reference< chart2::XScaling >& xScalingX,
 130     const uno::Reference< chart2::XScaling >& xScalingY,
 131     sal_Bool bMaySkipPointsInCalculation )
 132 {
 133     if( bMaySkipPointsInCalculation &&
 134         isLinearScaling( xScalingX ) &&
 135         isLogarithmicScaling( xScalingY ))
 136     {
 137         // optimize result
 138         uno::Sequence< geometry::RealPoint2D > aResult( 2 );
 139         aResult[0].X = min;
 140         aResult[0].Y = getCurveValue( min );
 141         aResult[1].X = max;
 142         aResult[1].Y = getCurveValue( max );
 143
 144         return aResult;
 145     }
 146
 147     return RegressionCurveCalculator::getCurveValues( min, max, nPointCount, xScalingX, xScalingY, bMaySkipPointsInCalculation );
 148 }
 149
 150 OUString ExponentialRegressionCurveCalculator::ImplGetRepresentation(
 151     const uno::Reference< util::XNumberFormatter >& xNumFormatter,
 152     sal_Int32 nNumberFormatKey, sal_Int32* pFormulaMaxWidth /* = nullptr */ ) const
 153 {
 154     double fIntercept = exp(m_fLogIntercept);
 155     bool bHasSlope = !rtl::math::approxEqual( exp(m_fLogSlope), 1.0 );
 156     bool bHasLogSlope = !rtl::math::approxEqual( fabs(m_fLogSlope), 1.0 );
 157     bool bHasIntercept = !rtl::math::approxEqual( fIntercept, 1.0 ) && fIntercept != 0.0;
 158
 159     OUStringBuffer aBuf( mYName + " = " );
 160     sal_Int32 nLineLength = aBuf.getLength();
 161     sal_Int32 nValueLength=0;
 162     if ( pFormulaMaxWidth && *pFormulaMaxWidth > 0 )
 163     {          // count characters different from coefficients
 164         sal_Int32 nCharMin = nLineLength + 10 + mXName.getLength();  // 10 = "exp( ", " x )" + 2 extra characters
 165         if ( m_fSign < 0.0 )
 166             nCharMin += 2;
 167         if ( fIntercept == 0.0 || ( !bHasSlope && m_fLogIntercept != 0.0 ) )
 168             nCharMin += 3; // " + " special case where equation is written exp( a + b x )
 169         if ( ( bHasIntercept || fIntercept == 0.0 || ( !bHasSlope && m_fLogIntercept != 0.0 ) ) &&
 170                bHasLogSlope )
 171             nValueLength = ( *pFormulaMaxWidth - nCharMin ) / 2;
 172         else
 173             nValueLength = *pFormulaMaxWidth - nCharMin;
 174         if ( nValueLength <= 0 )
 175             nValueLength = 1;
 176     }
 177                     // temporary buffer
 178     OUStringBuffer aTmpBuf("");
 179         // if nValueLength not calculated then nullptr
 180     sal_Int32* pValueLength = nValueLength ? &nValueLength : nullptr;
 181     if ( m_fSign < 0.0 )
 182         aTmpBuf.append( OUStringChar(aMinusSign) ).append( " " );
 183     if ( bHasIntercept )
 184     {
 185         OUString aValueString = getFormattedString( xNumFormatter, nNumberFormatKey, fIntercept, pValueLength );
 186         if ( aValueString != "1" )  // aValueString may be rounded to 1 if nValueLength is small
 187         {
 188             aTmpBuf.append( aValueString ).append( " " );
 189             addStringToEquation( aBuf, nLineLength, aTmpBuf, pFormulaMaxWidth );
 190             aTmpBuf.truncate();
 191         }
 192     }
 193     aTmpBuf.append( "exp( " );
 194     if ( !bHasIntercept )
 195     {
 196         if ( fIntercept == 0.0 ||  // underflow, a true zero is impossible
 197            ( !bHasSlope && m_fLogIntercept != 0.0 ) )   // show logarithmic output, if intercept and slope both are near one
 198         {                                               // otherwise drop output of intercept, which is 1 here
 199             OUString aValueString = getFormattedString( xNumFormatter, nNumberFormatKey, m_fLogIntercept, pValueLength );
 200             if ( aValueString != "0" )  // aValueString may be rounded to 0 if nValueLength is small
 201             {
 202                 aTmpBuf.append( aValueString ).append( (m_fLogSlope < 0.0) ? OUStringLiteral(" ") : OUStringLiteral(" + ") );
 203             }
 204         }
 205     }
 206     if ( m_fLogSlope < 0.0 )
 207         aTmpBuf.append( OUStringChar(aMinusSign) ).append( " " );
 208     if ( bHasLogSlope )
 209     {
 210         OUString aValueString = getFormattedString( xNumFormatter, nNumberFormatKey, fabs(m_fLogSlope), pValueLength );
 211         if ( aValueString != "1" )  // aValueString may be rounded to 1 if nValueLength is small
 212         {
 213             aTmpBuf.append( aValueString ).append( " " );
 214         }
 215     }
 216     aTmpBuf.append( mXName ).append(" )");
 217     addStringToEquation( aBuf, nLineLength, aTmpBuf, pFormulaMaxWidth );
 218
 219     return aBuf.makeStringAndClear();
 220 }
 221
 222 } //  namespace chart
 223
 224 /* vim:set shiftwidth=4 softtabstop=4 expandtab: */