chart2/source/tools/RegressionCalculationHelper.hxx

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  27 #ifndef CHART2_REGRESSIONCALCULATIONHELPER_HXX
  28 #define CHART2_REGRESSIONCALCULATIONHELPER_HXX
  29
  30 #include <rtl/math.hxx>
  31
  32 #include <utility>
  33 #include <functional>
  34 #include <vector>
  35 #include <rtl/math.hxx>
  36
  37 #define NUMBER_TO_STR(number) (::rtl::OStringToOUString(::rtl::math::doubleToString( \
  38           number, rtl_math_StringFormat_G, 4, '.', true ),RTL_TEXTENCODING_ASCII_US ))
  39
  40 #define UC_SPACE (sal_Unicode(' '))
  41 #define UC_MINUS_SIGN (sal_Unicode('-'))
  42 // #define UC_MINUS_SIGN (sal_Unicode(0x2212))
  43
  44 namespace chart
  45 {
  46 namespace RegressionCalculationHelper
  47 {
  48
  49 typedef ::std::pair< ::std::vector< double >, ::std::vector< double > > tDoubleVectorPair;
  50
  51 /** takes the given x- and y-values and copyies them into the resulting pair,
  52     which contains x-values in the first element and the y-values in the second
  53     one.  All tuples for which aPred is false are not copied.
  54
  55     <p>The functors below provide a set of useful predicates that can be
  56     used to pass as parameter aPred.</p>
  57  */
  58 template< class Pred >
  59 tDoubleVectorPair
  60     cleanup( const ::com::sun::star::uno::Sequence< double > & rXValues,
  61              const ::com::sun::star::uno::Sequence< double > & rYValues,
  62              Pred aPred )
  63 {
  64     tDoubleVectorPair aResult;
  65     sal_Int32 nSize = ::std::min( rXValues.getLength(), rYValues.getLength());
  66     for( sal_Int32 i=0; i<nSize; ++i )
  67     {
  68         if( aPred( rXValues[i], rYValues[i] ))
  69         {
  70             aResult.first.push_back( rXValues[i] );
  71             aResult.second.push_back( rYValues[i] );
  72         }
  73     }
  74
  75     return aResult;
  76 }
  77
  78
  79 class isValid : public ::std::binary_function< double, double, bool >
  80 {
  81 public:
  82     inline bool operator()( double x, double y )
  83     { return ! ( ::rtl::math::isNan( x ) ||
  84                  ::rtl::math::isNan( y ) ||
  85                  ::rtl::math::isInf( x ) ||
  86                  ::rtl::math::isInf( y ) );
  87     }
  88 };
  89
  90 class isValidAndXPositive : public ::std::binary_function< double, double, bool >
  91 {
  92 public:
  93     inline bool operator()( double x, double y )
  94     { return ! ( ::rtl::math::isNan( x ) ||
  95                  ::rtl::math::isNan( y ) ||
  96                  ::rtl::math::isInf( x ) ||
  97                  ::rtl::math::isInf( y ) ||
  98                  x <= 0.0 );
  99     }
 100 };
 101
 102 class isValidAndYPositive : public ::std::binary_function< double, double, bool >
 103 {
 104 public:
 105     inline bool operator()( double x, double y )
 106     { return ! ( ::rtl::math::isNan( x ) ||
 107                  ::rtl::math::isNan( y ) ||
 108                  ::rtl::math::isInf( x ) ||
 109                  ::rtl::math::isInf( y ) ||
 110                  y <= 0.0 );
 111     }
 112 };
 113
 114 class isValidAndBothPositive : public ::std::binary_function< double, double, bool >
 115 {
 116 public:
 117     inline bool operator()( double x, double y )
 118     { return ! ( ::rtl::math::isNan( x ) ||
 119                  ::rtl::math::isNan( y ) ||
 120                  ::rtl::math::isInf( x ) ||
 121                  ::rtl::math::isInf( y ) ||
 122                  x <= 0.0 ||
 123                  y <= 0.0 );
 124     }
 125 };
 126
 127 } //  namespace RegressionCalculationHelper
 128 } //  namespace chart
 129
 130 // CHART2_REGRESSIONCALCULATIONHELPER_HXX
 131 #endif