chart2/source/tools/RegressionCalculationHelper.hxx

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  30 #ifndef CHART2_REGRESSIONCALCULATIONHELPER_HXX
  31 #define CHART2_REGRESSIONCALCULATIONHELPER_HXX
  32
  33 #include <rtl/math.hxx>
  34
  35 #include <utility>
  36 #include <functional>
  37 #include <vector>
  38 #include <rtl/math.hxx>
  39
  40 #define NUMBER_TO_STR(number) (::rtl::OStringToOUString(::rtl::math::doubleToString( \
  41           number, rtl_math_StringFormat_G, 4, '.', true ),RTL_TEXTENCODING_ASCII_US ))
  42
  43 #define UC_SPACE (sal_Unicode(' '))
  44 #define UC_MINUS_SIGN (sal_Unicode('-'))
  45 // #define UC_MINUS_SIGN (sal_Unicode(0x2212))
  46
  47 namespace chart
  48 {
  49 namespace RegressionCalculationHelper
  50 {
  51
  52 typedef ::std::pair< ::std::vector< double >, ::std::vector< double > > tDoubleVectorPair;
  53
  54 /** takes the given x- and y-values and copyies them into the resulting pair,
  55     which contains x-values in the first element and the y-values in the second
  56     one.  All tuples for which aPred is false are not copied.
  57
  58     <p>The functors below provide a set of useful predicates that can be
  59     used to pass as parameter aPred.</p>
  60  */
  61 template< class Pred >
  62 tDoubleVectorPair
  63     cleanup( const ::com::sun::star::uno::Sequence< double > & rXValues,
  64              const ::com::sun::star::uno::Sequence< double > & rYValues,
  65              Pred aPred )
  66 {
  67     tDoubleVectorPair aResult;
  68     sal_Int32 nSize = ::std::min( rXValues.getLength(), rYValues.getLength());
  69     for( sal_Int32 i=0; i<nSize; ++i )
  70     {
  71         if( aPred( rXValues[i], rYValues[i] ))
  72         {
  73             aResult.first.push_back( rXValues[i] );
  74             aResult.second.push_back( rYValues[i] );
  75         }
  76     }
  77
  78     return aResult;
  79 }
  80
  81
  82 class isValid : public ::std::binary_function< double, double, bool >
  83 {
  84 public:
  85     inline bool operator()( double x, double y )
  86     { return ! ( ::rtl::math::isNan( x ) ||
  87                  ::rtl::math::isNan( y ) ||
  88                  ::rtl::math::isInf( x ) ||
  89                  ::rtl::math::isInf( y ) );
  90     }
  91 };
  92
  93 class isValidAndXPositive : public ::std::binary_function< double, double, bool >
  94 {
  95 public:
  96     inline bool operator()( double x, double y )
  97     { return ! ( ::rtl::math::isNan( x ) ||
  98                  ::rtl::math::isNan( y ) ||
  99                  ::rtl::math::isInf( x ) ||
 100                  ::rtl::math::isInf( y ) ||
 101                  x <= 0.0 );
 102     }
 103 };
 104
 105 class isValidAndYPositive : public ::std::binary_function< double, double, bool >
 106 {
 107 public:
 108     inline bool operator()( double x, double y )
 109     { return ! ( ::rtl::math::isNan( x ) ||
 110                  ::rtl::math::isNan( y ) ||
 111                  ::rtl::math::isInf( x ) ||
 112                  ::rtl::math::isInf( y ) ||
 113                  y <= 0.0 );
 114     }
 115 };
 116
 117 class isValidAndBothPositive : public ::std::binary_function< double, double, bool >
 118 {
 119 public:
 120     inline bool operator()( double x, double y )
 121     { return ! ( ::rtl::math::isNan( x ) ||
 122                  ::rtl::math::isNan( y ) ||
 123                  ::rtl::math::isInf( x ) ||
 124                  ::rtl::math::isInf( y ) ||
 125                  x <= 0.0 ||
 126                  y <= 0.0 );
 127     }
 128 };
 129
 130 } //  namespace RegressionCalculationHelper
 131 } //  namespace chart
 132
 133 // CHART2_REGRESSIONCALCULATIONHELPER_HXX
 134 #endif