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CLHEP/GenericFunctions/FourierFit.hh
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1 // -*- C++ -*-
2 // $Id:
3 //---------------------FourierFit-------------------------------------------//
4 // //
5 // Class FourierFit. This is a fitting function consisting of a super //
6 // position of N legendre polynomials. Cascading fractions and phases are //
7 // the input parameters. Function is normalized to one (on [0,2PI]) //
8 // Joe Boudreau, Petar Maksimovic, January 2000 //
9 // //
10 //--------------------------------------------------------------------------//
11 #ifndef FourierFit_h
12 #define FourierFit_h 1
15 namespace Genfun {
16 
21  class FourierFit : public AbsFunction {
22 
24 
25  public:
26 
27  // Constructor
28  FourierFit(unsigned int N);
29 
30  // Copy constructor
31  FourierFit(const FourierFit &right);
32 
33  // Destructor
34  virtual ~FourierFit();
35 
36  // Retreive function value
37  virtual double operator ()(double argument) const;
38  virtual double operator ()(const Argument & a) const {return operator() (a[0]);}
39 
40  unsigned int order() const;
41 
42  Parameter *getFraction(unsigned int i);
43  const Parameter *getFraction(unsigned int i) const;
44 
45  Parameter *getPhase(unsigned int i);
46  const Parameter *getPhase(unsigned int i) const;
47 
48 
49  private:
50 
51  // It is illegal to assign an adjustable constant
52  const FourierFit & operator=(const FourierFit &right);
53 
54  //
55  const unsigned int N;
56  std::vector <Genfun::Parameter *> fraction;
57  std::vector <Genfun::Parameter *> phase;
58 
59 
60  };
61 } // namespace Genfun
62 #include "CLHEP/GenericFunctions/FourierFit.icc"
63 #endif
a
@ a
Definition: testCategories.cc:125
Parameter.hh
Genfun::AbsFunction
Definition: CLHEP/GenericFunctions/AbsFunction.hh:48
Genfun::FourierFit
Definition: CLHEP/GenericFunctions/FourierFit.hh:21
AbsFunction.hh
Genfun::FourierFit::operator()
virtual double operator()(double argument) const
Genfun::FourierFit::getPhase
Parameter * getPhase(unsigned int i)
N
the goal is to keep the overall false rejection probability down at the to level For each validated we discuss which of course is by necessity relative timing We take the time for a single random via one of the fastest good and at any rate the ratios will vary by around depending on the processor and memory configuration used A timing for a distribution of units would mean no time used beyond the uniform random Summary Distribution Validated Validation Rejected Past N RandGauss N
Definition: validation.doc:48
Genfun::FourierFit::~FourierFit
virtual ~FourierFit()
Genfun::Argument
Definition: CLHEP/GenericFunctions/Argument.hh:17
i
long i
Definition: JamesRandomSeeding.txt:27
Genfun::FourierFit::FourierFit
FourierFit(unsigned int N)
Genfun::Parameter
Definition: CLHEP/GenericFunctions/Parameter.hh:35
Genfun::FourierFit::getFraction
Parameter * getFraction(unsigned int i)
Genfun::FourierFit::order
unsigned int order() const
FUNCTION_OBJECT_DEF
#define FUNCTION_OBJECT_DEF(classname)
Definition: CLHEP/GenericFunctions/AbsFunction.hh:144
Genfun
Definition: CLHEP/GenericFunctions/Abs.hh:14