00001 // This is mul/pdf1d/pdf1d_flat_sampler.h 00002 #ifndef pdf1d_flat_sampler_h 00003 #define pdf1d_flat_sampler_h 00004 00005 //: 00006 // \file 00007 // \author Tim Cootes 00008 // \brief Sampler class for Univariate flat distributions 00009 00010 #include <vcl_string.h> 00011 #include <vnl/vnl_random.h> 00012 #include <pdf1d/pdf1d_sampler.h> 00013 class pdf1d_flat; 00014 00015 //======================================================================= 00016 00017 //: Samples from Univariate flat distributions 00018 class pdf1d_flat_sampler :public pdf1d_sampler 00019 { 00020 protected: 00021 //: The random number generator 00022 vnl_random rng_; 00023 public: 00024 00025 //: Dflt ctor 00026 pdf1d_flat_sampler(); 00027 00028 //: Destructor 00029 virtual ~pdf1d_flat_sampler(); 00030 00031 //: Set model for which this is an instance 00032 // Error check that it is an axis flat. 00033 virtual void set_model(const pdf1d_pdf&); 00034 00035 //: Draw random sample from Gaussian distribution 00036 virtual double sample(); 00037 00038 //: Fill x with samples possibly chosen so as to represent the distribution 00039 // 5 or fewer samples requested, they are spaced out equally. 00040 virtual void regular_samples(vnl_vector<double>& x); 00041 00042 //: Reseeds the internal random number generator 00043 // To achieve quasi-random initialisation use; 00044 // \code 00045 // #include <vcl_ctime.h> 00046 // .. 00047 // sampler.reseed(vcl_time(0)); 00048 // \endcode 00049 virtual void reseed(unsigned long); 00050 00051 00052 //: Return a reference to the pdf model 00053 // This is properly cast. 00054 const pdf1d_flat& flat() const; 00055 00056 //: Name of the class 00057 virtual vcl_string is_a() const; 00058 00059 //: Does the name of the class match the argument? 00060 virtual bool is_class(vcl_string const& s) const; 00061 00062 //: Create a copy on the heap and return base class pointer 00063 virtual pdf1d_sampler* clone() const; 00064 }; 00065 00066 #endif // pdf1d_flat_sampler_h