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ConsensusSequenceLayer.hpp
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Fri, May 3, 14:11

ConsensusSequenceLayer.hpp
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#ifndef CONSENSUSSEQUENCELAYER_HPP
#define CONSENSUSSEQUENCELAYER_HPP
#include <SequenceLayer.hpp>
class ConsensusSequenceLayer : public SequenceLayer
{
public:
/*!
* \brief Constructs an object with the
* given data and an empty (0 values)
* model.
* \param data the data.
* \param n_class the number of classes
* of the model.
* \param n_shift the number of shift
* states of the model.
* \param flip whether flipping is allowed.
* \param bckg_class should the last class
* of the model is constant and models the
* background.
*/
ConsensusSequenceLayer(const Matrix3D<double>& data,
size_t n_class,
size_t n_shift,
bool flip,
bool bckg_class) ;
/*!
* \brief Constructs an object with the
* given data and an empty (0 values)
* model.
* \param data the data.
* \param n_class the number of classes
* of the model.
* \param n_shift the number of shift
* states of the model.
* \param flip whether flipping is allowed.
* \param bckg_class should the last class
* of the model is constant and models the
* background.
*/
ConsensusSequenceLayer(Matrix2D<int>&& data,
size_t n_class,
size_t n_shift,
bool flip,
bool bckg_class) ;
/*!
* \brief Destructor.
*/
virtual ~ConsensusSequenceLayer() ;
/*!
* \brief Computes the log likelihood of the data
* given the current model parameters.
* \param logliklihood a matrix to store the
* results. It should have the following dimensions :
* 1st : same as the data number of row
* 2nd : same as the model number of classes
* 3rd : same as the number of shifts
* 4th : same as the number of flip states
* \param loglikelihood_max a vector containing the
* max value for each row of loglikelihood.
* Its length should be equal to the data row number.
* \throw std::invalid_argument if the dimensions are
* incorrect.
*/
virtual void compute_loglikelihoods(Matrix4D<double>& loglikelihood,
vector_d& loglikelihood_max,
ThreadPool* threads=nullptr) const override ;
/*!
* \brief Updates the model given the posterior
* probabilities (the probabilities of each row
* in the data to be assigned to each class,
* for each shift and flip state).
* \param posterior_prob the data assignment probabilities to
* the different classes.
*/
virtual void update_model(const Matrix4D<double>& posterior_prob,
ThreadPool* threads=nullptr) override ;
protected:
} ;
#endif // CONSENSUSSEQUENCELAYER_HPP

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