BIE Overview Quick Start Theoretical overview Available methods Parallel chains Computation engine Command Line Interface Graphical User Interface Assigning Output Visualization tool Data handling Software technology Parallel debugging Results to date Recent developments Links User guide Future features Project goals Project Team Copyright and license

/home/weinberg/src/BIE/include/GaussTestLikelihoodFunctionMulti.h // This is -*- C++ -*- #ifndef GaussTestLikelihoodFunctionMulti_h #define GaussTestLikelihoodFunctionMulti_h #include "Serializable.h" #include "LikelihoodFunction.h" namespace BIE { //+ CLICLASS GaussTestLikelihoodFunctionMulti SUPER LikelihoodFunction class GaussTestLikelihoodFunctionMulti : public LikelihoodFunction { private: deque < vector<double> > fdata; deque <int> nbins; deque <double> dx; vector <double> pdata; vector <int> cdata; double xmin, xmax; unsigned nmix; int dim; int ptwo; int N; int levels; bool point; vector <double> centers, variance, weights; public: //+ CLICONSTR GaussTestLikelihoodFunctionMulti(); //+ CLICONSTR int int int GaussTestLikelihoodFunctionMulti(int Ptwo, int N0, int Levels); //+ CLICONSTR int int int clivectord* clivectord* clivectord* GaussTestLikelihoodFunctionMulti(int Ptwo, int N0, int Levels, vector<double>* cen0, vector<double>* var0, vector<double>* wgt0); //+ CLICONSTR int int GaussTestLikelihoodFunctionMulti(int N0, int Levels); //+ CLICONSTR int int clivectord* clivectord* clivectord* GaussTestLikelihoodFunctionMulti(int N0, int Levels, vector<double>* cen0, vector<double>* var0, vector<double>* wgt0); //+ CLIMETHOD void SetLevels int void SetLevels(int n); //+ CLIMETHOD void SetDim int void SetDim(int n); //+ CLIMETHOD void PrintData void PrintData(); double LikeProb(std::vector<double> &z, SampleDistribution* sd, double norm, Tile *t, State *s, int indx) { return LocalLikelihood(s); } string ParameterDescription(int i); protected: void makeSyntheticData(); void makeSyntheticPointData(); void makeArrays(); double LocalLikelihood(State* s); // AUTO GENERATED BY ../persistence/autopersist.py private: friend class boost::serialization::access; template<class Archive> void serialize(Archive & ar, const unsigned int version) { this->pre_serialize(ar, version); try { ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(LikelihoodFunction); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(fdata); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(nbins); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(dx); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(pdata); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(cdata); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(xmin); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(xmax); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(nmix); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(dim); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(ptwo); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(N); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(levels); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(point); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(centers); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(variance); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } try { ar & BOOST_SERIALIZATION_NVP(weights); BIE_CATCH_BOOST_SERIALIZATION_EXCEPTION; } this->post_serialize(ar, version); } }; } // namespace BIE BIE_CLASS_TYPE_INFO(BIE::GaussTestLikelihoodFunctionMulti) BIE_CLASS_EXPORT_KEY(BIE::GaussTestLikelihoodFunctionMulti) #endif