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21 
22 
23 #ifndef CHART2_REGRESSIONCALCULATIONHELPER_HXX
24 #define CHART2_REGRESSIONCALCULATIONHELPER_HXX
25 
26 #include <rtl/math.hxx>
27 
28 #include <utility>
29 #include <functional>
30 #include <vector>
31 #include <rtl/math.hxx>
32 
33 #define NUMBER_TO_STR(number) (::rtl::OStringToOUString(::rtl::math::doubleToString( \
34           number, rtl_math_StringFormat_G, 4, '.', true ),RTL_TEXTENCODING_ASCII_US ))
35 
36 #define UC_SPACE (sal_Unicode(' '))
37 #define UC_MINUS_SIGN (sal_Unicode('-'))
38 // #define UC_MINUS_SIGN (sal_Unicode(0x2212))
39 
40 namespace chart
41 {
42 namespace RegressionCalculationHelper
43 {
44 
45 typedef ::std::pair< ::std::vector< double >, ::std::vector< double > > tDoubleVectorPair;
46 
47 /** takes the given x- and y-values and copyies them into the resulting pair,
48     which contains x-values in the first element and the y-values in the second
49     one.  All tuples for which aPred is false are not copied.
50 
51     <p>The functors below provide a set of useful predicates that can be
52     used to pass as parameter aPred.</p>
53  */
54 template< class Pred >
55 tDoubleVectorPair
cleanup(const::com::sun::star::uno::Sequence<double> & rXValues,const::com::sun::star::uno::Sequence<double> & rYValues,Pred aPred)56     cleanup( const ::com::sun::star::uno::Sequence< double > & rXValues,
57              const ::com::sun::star::uno::Sequence< double > & rYValues,
58              Pred aPred )
59 {
60     tDoubleVectorPair aResult;
61     sal_Int32 nSize = ::std::min( rXValues.getLength(), rYValues.getLength());
62     for( sal_Int32 i=0; i<nSize; ++i )
63     {
64         if( aPred( rXValues[i], rYValues[i] ))
65         {
66             aResult.first.push_back( rXValues[i] );
67             aResult.second.push_back( rYValues[i] );
68         }
69     }
70 
71     return aResult;
72 }
73 
74 
75 class isValid : public ::std::binary_function< double, double, bool >
76 {
77 public:
operator ()(double x,double y)78     inline bool operator()( double x, double y )
79     { return ! ( ::rtl::math::isNan( x ) ||
80                  ::rtl::math::isNan( y ) ||
81                  ::rtl::math::isInf( x ) ||
82                  ::rtl::math::isInf( y ) );
83     }
84 };
85 
86 class isValidAndXPositive : public ::std::binary_function< double, double, bool >
87 {
88 public:
operator ()(double x,double y)89     inline bool operator()( double x, double y )
90     { return ! ( ::rtl::math::isNan( x ) ||
91                  ::rtl::math::isNan( y ) ||
92                  ::rtl::math::isInf( x ) ||
93                  ::rtl::math::isInf( y ) ||
94                  x <= 0.0 );
95     }
96 };
97 
98 class isValidAndYPositive : public ::std::binary_function< double, double, bool >
99 {
100 public:
operator ()(double x,double y)101     inline bool operator()( double x, double y )
102     { return ! ( ::rtl::math::isNan( x ) ||
103                  ::rtl::math::isNan( y ) ||
104                  ::rtl::math::isInf( x ) ||
105                  ::rtl::math::isInf( y ) ||
106                  y <= 0.0 );
107     }
108 };
109 
110 class isValidAndBothPositive : public ::std::binary_function< double, double, bool >
111 {
112 public:
operator ()(double x,double y)113     inline bool operator()( double x, double y )
114     { return ! ( ::rtl::math::isNan( x ) ||
115                  ::rtl::math::isNan( y ) ||
116                  ::rtl::math::isInf( x ) ||
117                  ::rtl::math::isInf( y ) ||
118                  x <= 0.0 ||
119                  y <= 0.0 );
120     }
121 };
122 
123 } //  namespace RegressionCalculationHelper
124 } //  namespace chart
125 
126 // CHART2_REGRESSIONCALCULATIONHELPER_HXX
127 #endif
128