cMHN/documentation_v1.2/externs__TT_8hpp_source.html

using T = pRC::Float<>;


using TTN =

    pRC::TensorTrain::Tensor<T, decltype(cMHN::TT::getModeSizes<EVENTS>()),

        decltype(cMHN::TT::getRanks<EVENTS, MAXRANKP, 2>())>;


using S = TTN::Subscripts;


extern template TTN cMHN::calculatePTheta<MAXRANKP>(

    cMHN::TT::MHNOperator<T, EVENTS> const &, TTN const &, T const &);


extern template T cMHN::calculateScore<MAXRANKP>(

    cMHN::TT::MHNOperator<T, EVENTS> const &, std::map<S, T> const &,

    cMHN::Score<T> const &, cMHN::Regulator<T, EVENTS> const &, T const &);


extern template std::tuple<T, pRC::Tensor<T, EVENTS, EVENTS>>

cMHN::calculateScoreAndGradient<MAXRANKP, MAXRANKQ>(

    cMHN::TT::MHNOperator<T, EVENTS> const &, std::map<S, T> const &,

    cMHN::Score<T> const &, cMHN::Regulator<T, EVENTS> const &, TTN &,

    T const &, T const &);


extern template std::tuple<pRC::Tensor<T, EVENTS, EVENTS>,

    std::map<std::string, std::string>, std::map<std::string, double>>

cMHN::TT::learnTheta<MAXRANKP, MAXRANKQ>(pRC::Tensor<T, EVENTS, EVENTS> const &,

    std::string const &, std::string const &, std::map<S, T> const &,

    cMHN::Score<T> const &, cMHN::Regulator<T, EVENTS> const &, T const &,

    T const &, T const &);

cMHN::Regulator
Class storing all relevant information for a regulator.
Definition regulator.hpp:30

cMHN::Score
Class storing all relevant information for a score.
Definition score.hpp:28

cMHN::TT::MHNOperator
Class storing an MHN operator represented by a theta matrix (for TT calculations)
Definition mhn_operator.hpp:24

pRC::Float
Definition value.hpp:12

pRC::TensorTrain::Tensor
Definition declarations.hpp:16

pRC::Tensor
Definition tensor.hpp:25

S
TN::Subscripts S
Definition externs_nonTT.hpp:9

cMHN::TT::learnTheta
std::tuple< pRC::Tensor< T, D, D >, std::map< std::string, std::string >, std::map< std::string, double > > learnTheta(pRC::Tensor< T, D, D > const &theta, std::string const &header, std::string const &output, std::map< S, T > const &pD, cMHN::Score< T > const &Score, cMHN::Regulator< T, D > const &Regulator, T const &toleranceOptimizer, T const &toleranceSolverP, T const &toleranceSolverQ)
Optimizes an MHN represented by a theta matrix to best describe a given data distribution using the T...
Definition learn_theta.hpp:59

cMHN::TT::getRanks
constexpr auto getRanks()
Definition utility.hpp:17

cMHN::calculateScore
T calculateScore(nonTT::MHNOperator< T, D > const &op, std::map< S, T > const &pD, cMHN::Score< T > const &Score, cMHN::Regulator< T, D > const &Regulator)
Calculate score of a theta matrix given some data distribution pD.
Definition calculate_score.hpp:31

cMHN::calculatePTheta
decltype(expand(pRC::makeConstantSequence< pRC::Size, D, 2 >(), [](auto const ... Ns) { return pRC::Tensor< T, Ns... >{};})) calculatePTheta(nonTT::MHNOperator< T, D > const &op)
Calculates the vector pTheta given a nonTT MHN Operator.
Definition calculate_pTheta.hpp:39

cMHN::calculateScoreAndGradient
std::tuple< T, pRC::Tensor< T, D, D > > calculateScoreAndGradient(nonTT::MHNOperator< T, D > const &op, std::map< S, T > const &pD, cMHN::Score< T > const &Score, cMHN::Regulator< T, D > const &Regulator, T const &toleranceSolverQ=1e-8)
Calculate score and gradient of a theta matrix given some data distribution pD.
Definition calculate_score_and_gradient.hpp:35

pRC::TensorTrain::Tensor
Tensor(TensorViews::View< T, N, Ranks, F > const &) -> Tensor< T, N, Ranks >