Structural Bioinformatics Library: problem< graph, dp_mat, lambda_mat, parameter > Class Template Reference

Structural Bioinformatics Library

Template C++ / Python API for developping structural bioinformatics applications.

#include <problem.h>

Public Member Functions
int	get_size ()
vector< int > &	get_up ()
vector< int > &	get_lo ()
vector< int > &	get_solution ()
float	get_ub ()
float	get_lb ()
float	get_lb_father ()
float	get_ub_father ()
int	get_status ()
bool	is_splitted ()
double	get_solve_time ()
int	get_iter ()
void	set_up (int col, int val)
void	set_lo (int col, int val)
void	lr_sgd_solve (parameter &params)
float	get_correct_value (vector< int > &sol)
int	get_nz_sub_gr (vector< int > &sol)
void	update_lambda (float step)
int	is_brk_cst_col_node (int col1, int col2, int row2, vector< int > &sol)
int	is_brk_cst_row_node (int row1, int col2, int row2, vector< int > &sol)
int	check_cst_col_node (int col1, int col2, int row2, vector< int > &sol)
int	check_cst_row_node (int row1, int col2, int row2, vector< int > &sol)
	problem (graph &g1, dp_mat &dp1, lambda_mat &lb1)
	problem (problem &p, vector< int > &lo1, vector< int > &up1)
lambda_mat &	get_lambda_mat ()
graph &	get_graph ()
dp_mat &	get_dp_mat_apurva ()
problem *	create_subproblem (vector< int > &lo1, vector< int > &up1)
void	split (vector< int > &lo1, vector< int > &up1, vector< int > &lo2, vector< int > &up2)

Detailed Description

template<class graph, class dp_mat, class lambda_mat, class parameter>
class problem< graph, dp_mat, lambda_mat, parameter >

Problem Class This is used to solve a Contact Map Overlap Maximisation problem, using the A_purva integer programming model and lagrangian relaxation approach.

Constructor & Destructor Documentation

◆ problem() [1/2]

template<class graph, class dp_mat, class lambda_mat, class parameter>

problem	(	graph &	g1,
		dp_mat &	dp1,
		lambda_mat &	lb1 )

inline

Constructors : create a root problem.

◆ problem() [2/2]

template<class graph, class dp_mat, class lambda_mat, class parameter>

problem	(	problem< graph, dp_mat, lambda_mat, parameter > &	p,
		vector< int > &	lo1,
		vector< int > &	up1 )

inline

Constructors: Build a sub-problem of problem p, using lo1 for lowerlimits and up1for upperlimits.

Member Function Documentation

◆ check_cst_col_node()

template<class graph, class dp_mat, class lambda_mat, class parameter>

int check_cst_col_node	(	int	col1,
		int	col2,
		int	row2,
		vector< int > &	sol )

inline

return the value of the X_{col2,row2} - SUM Y_{col1,row1,col2,row2} col / node constraint.

◆ check_cst_row_node()

template<class graph, class dp_mat, class lambda_mat, class parameter>

int check_cst_row_node	(	int	row1,
		int	col2,
		int	row2,
		vector< int > &	sol )

inline

return the value of the X_{col2,row2} - SUM Y_{col1,row1,col2,row2} row / node constraint.

◆ create_subproblem()

template<class graph, class dp_mat, class lambda_mat, class parameter>

problem * create_subproblem	(	vector< int > &	lo1,
		vector< int > &	up1 )

inline

Methods Being given a lower and an upper limits, create the corresponding sub-problem.

◆ get_correct_value()

template<class graph, class dp_mat, class lambda_mat, class parameter>

float get_correct_value ( vector< int > & sol )

inline

Return the value of the solution for the Primal problem.

◆ get_dp_mat_apurva()

template<class graph, class dp_mat, class lambda_mat, class parameter>

dp_mat & get_dp_mat_apurva ( )

inline

Return the Dynamic programming object.

◆ get_graph()

template<class graph, class dp_mat, class lambda_mat, class parameter>

graph & get_graph ( )

inline

Return the Contact Map alignment graph.

◆ get_iter()

template<class graph, class dp_mat, class lambda_mat, class parameter>

int get_iter ( )

inline

Return the number of iteration needed to solve the problem.

◆ get_lambda_mat()

template<class graph, class dp_mat, class lambda_mat, class parameter>

lambda_mat & get_lambda_mat ( )

inline

Accessors Return the Lambda coeficients.

◆ get_lb()

template<class graph, class dp_mat, class lambda_mat, class parameter>

float get_lb ( )

inline

Return the current lowerbound of the problem.

◆ get_lb_father()

template<class graph, class dp_mat, class lambda_mat, class parameter>

float get_lb_father ( )

inline

Return the lowerbound of the father problem.

◆ get_lo()

template<class graph, class dp_mat, class lambda_mat, class parameter>

vector< int > & get_lo ( )

inline

Return the lower limits of the problem.

◆ get_nz_sub_gr()

template<class graph, class dp_mat, class lambda_mat, class parameter>

int get_nz_sub_gr ( vector< int > & sol )

inline

Return the nb of non-zero component of the subgradient vector, and the list of non-zero components is stored in nz_sgv

◆ get_size()

template<class graph, class dp_mat, class lambda_mat, class parameter>

int get_size ( )

inline

Accessors Return the size of the problem.

◆ get_solution()

template<class graph, class dp_mat, class lambda_mat, class parameter>

vector< int > & get_solution ( )

inline

Return the best feasible solution of the problem.

◆ get_solve_time()

template<class graph, class dp_mat, class lambda_mat, class parameter>

double get_solve_time ( )

inline

Return the time needed to solve the problem.

◆ get_status()

template<class graph, class dp_mat, class lambda_mat, class parameter>

int get_status ( )

inline

Return the status of the problem (see symbols.h).

◆ get_ub()

template<class graph, class dp_mat, class lambda_mat, class parameter>

float get_ub ( )

inline

Return the current upperbound of the problem.

◆ get_ub_father()

template<class graph, class dp_mat, class lambda_mat, class parameter>

float get_ub_father ( )

inline

Return the upperbound of the father problem.

◆ get_up()

template<class graph, class dp_mat, class lambda_mat, class parameter>

vector< int > & get_up ( )

inline

Return the upper limits of the problem.

◆ is_brk_cst_col_node()

template<class graph, class dp_mat, class lambda_mat, class parameter>

int is_brk_cst_col_node	(	int	col1,
		int	col2,
		int	row2,
		vector< int > &	sol )

inline

return the value of the X_{col2,row2} - SUM Y_{col1,row1,col2,row2} col / node constraint.

◆ is_brk_cst_row_node()

template<class graph, class dp_mat, class lambda_mat, class parameter>

int is_brk_cst_row_node	(	int	row1,
		int	col2,
		int	row2,
		vector< int > &	sol )

inline

return the value of the X_{col2,row2} - SUM Y_{col1,row1,col2,row2} row / node constraint.

◆ is_splitted()

template<class graph, class dp_mat, class lambda_mat, class parameter>

bool is_splitted ( )

inline

Boolean function, return 1 if the problem was successfully splitted, 0 else.

◆ lr_sgd_solve()

template<class graph, class dp_mat, class lambda_mat, class parameter>

void lr_sgd_solve ( parameter & params )

inline

Problem Solver, using Lagrangian Relaxation, with Dual problem solved using SubGradient Descent.

◆ set_lo()

template<class graph, class dp_mat, class lambda_mat, class parameter>

void set_lo	(	int	col,
		int	val )

inline

Set the lowerlimits of the problem.

◆ set_up()

template<class graph, class dp_mat, class lambda_mat, class parameter>

void set_up	(	int	col,
		int	val )

inline

Methods Set the upperlimits of the problem.

◆ split()

template<class graph, class dp_mat, class lambda_mat, class parameter>

void split	(	vector< int > &	lo1,
		vector< int > &	up1,
		vector< int > &	lo2,
		vector< int > &	up2 )

inline

This function split a problem into two subproblem. In fact it generate the two corresponding sets of upper and lower limits.

◆ update_lambda()

template<class graph, class dp_mat, class lambda_mat, class parameter>

void update_lambda ( float step )

inline

Update Lambda coeficients.

problem
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