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EMBase.hpp
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EMBase.hpp
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#ifndef EMBASE_HPP
#define EMBASE_HPP
#include <iostream>
#include <vector>
#include <future> // std::promise
#include <Matrix2D.hpp>
#include <Matrix3D.hpp>
#include <Matrix4D.hpp>
#include <ThreadPool.hpp>
typedef std::vector<double> vector_d ;
/*!
* \brief The EMBase class is a base class
* providing the basic support for classes
* in implementing read density, sequence
* and both at the time classification
* procedures.
*/
class EMBase
{ public:
/*!
* \brief The possible exit codes for the classification
* method.
* 0 the classification procedure converged, 1 the
* classification procedure ended by reaching the maximum
* number of iterations, 2 the classification procedure
* encountered an error.
*/
enum exit_codes {CONVERGENCE=0, ITER_MAX, FAILURE} ;
public:
/*!
* \brief Constructs an EMBase object.
* \param n_row the number of rows in the data matrix.
* \param n_col the number of columns in the data matrix.
* \param n_iter the number of optimization iterations.
* \param n_shift the number of shift states allowed.
* \param flip whether flipping is allowed.
* \param n_threads the number of parallel threads
* to run the computations. 0 means no parallel
* computing, everything is run on the main thread.
* \throw std::invalid_argument if the shifting freedom
* is bigger than the number of columns.
*/
EMBase(size_t n_row,
size_t n_col,
size_t n_class,
size_t n_iter,
size_t n_shift,
bool flip,
size_t n_threads) ;
EMBase(const EMBase& other) = delete ;
/*!
* \brief Destructor.
*/
virtual ~EMBase() ;
/*!
* \brief Returns the posterior probability
* of each point belonging to each class, for
* each possible shift and flip state.
* \return the posterior probability matrix,
* with the following dimensions :
* 1st dim : the data points
* 2nd dim : the classes
* 3rd dim : the shift states
* 4th dim : the flip states
*/
virtual Matrix4D<double> get_post_prob() const ;
/*!
* \brief Returns the posterior class
* probabilities (the total class
* probability over all shift and
* flip states).
* \return the posterior class
* probabilities.
*/
virtual vector_d get_post_class_prob() const ;
/*!
* \brief Runs the models optimization and the
* data classification.
* \return a code indicating how the optimization
* ended.
*/
virtual EMBase::exit_codes classify() = 0 ;
protected:
/*!
* \brief Computes the data log likelihood given the
* current models, likelihood for each state.
*/
virtual void compute_loglikelihood() = 0 ;
/*!
* \brief Computes the data posterior probabilties.
*/
virtual void compute_post_prob() = 0 ;
/*!
* \brief Update the data models for all layers, given
* the current posterior and class probabilities.
*/
virtual void update_models() = 0;
/*!
* \brief Sets all the state probabilities
* (all shift and flip states in all classes)
* to a uniform probability.
*/
void set_state_prob_uniform() ;
/*!
* \brief Sets the posterior
* probabilities randomly (by
* sampling them from a beta
* distribution) and update all
* other probabilities accordingly.
* \param seed a seed to set the initial
* state of the random number generator.
*/
void set_post_prob_random(const std::string& seed) ;
/*!
* \brief The routine that effectively
* sets the posterior probabilities randomly
* (by sampling them from a beta
* distribution).
* \param from the index of the first row
* in the data to consider.
* \param to the index of the past last row
* in the data to consider.
* \param done the partial column (over the classes)
* sum of posterior probabilities. If several routines
* are running together, the colsums are retrieved by
* summing up the vectors together.
* \param seed a seed to set the initial
* state of the random number generator.
*/
void set_post_prob_random_routine(size_t from,
size_t to,
const std::string& seed,
std::promise<vector_d>& post_prob_colsum) ;
/*!
* \brief Computes the class/state probabilities from the
* posterior probabilities.
*/
void compute_class_prob() ;
/*!
* \brief Modifies the state probabilities in such a
* way that the state probabilities are then normaly
* distributed, centered on the middle shift state.
* However, the overall class probabilities remain
* unchanged.
*/
void center_post_state_prob() ;
/*!
* \brief the number of rows in data.
*/
size_t n_row ;
/*!
* \brief the number of columns in data.
*/
size_t n_col ;
/*!
* \brief the number of classes.
*/
size_t n_class ;
/*!
* \brief the number of shift states.
*/
size_t n_shift ;
/*!
* \brief whther flip is allowed.
*/
bool flip ;
/*!
* \brief zhe number of flip states.
*/
size_t n_flip ;
/*!
* \brief the number of iterations.
*/
size_t n_iter ;
/*!
* \brief the length of the models.
*/
size_t l_model ;
/*!
* \brief the joint loglikelihood for each data point,
* for each state (each class for each
* shift and flip state).
*/
Matrix4D<double> loglikelihood ;
/*!
* \brief the posterior probabilities.
*/
Matrix4D<double> post_prob ;
/*!
* \brief the states (shift and flip in each class)
* probabilities.
*/
Matrix3D<double> post_state_prob ;
/*!
* \brief the total prob per class.
*/
vector_d post_class_prob ;
/*!
* \brief the sum per row (data point) of post_prob.
*/
vector_d post_prob_rowsum ;
/*!
* \brief the sum per column (class) of post_prob.
*/
vector_d post_prob_colsum ;
/*!
* \brief the total of post_prob.
*/
double post_prob_tot ;
/*!
* \brief the threads.
*/
ThreadPool* threads ;
} ;
#endif // EMBASE_HPP

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