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// Copyright (C) 2016 - IIT Bombay - FOSSEE
//
// This file must be used under the terms of the CeCILL.
// This source file is licensed as described in the file COPYING, which
// you should have received as part of this distribution. The terms
// are also available at
// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
// Author: Harpreet Singh, Pranav Deshpande and Akshay Miterani
// Organization: FOSSEE, IIT Bombay
// Email: toolbox@scilab.in
#ifndef minconTMINLP_HPP
#define minconTMINLP_HPP
#include "BonTMINLP.hpp"
#include "IpTNLP.hpp"
#include "call_scilab.h"
using namespace Ipopt;
using namespace Bonmin;
class minconTMINLP : public TMINLP
{
private:
Index numVars_; //Number of variables
Index numCons_; //Number of constraints
Index numLC_; //Number of Linear constraints
Index intconSize_;
Number *x0_= NULL; //lb_ is a pointer to a matrix of size of 1*numVars_ with lower bound of all variables.
Number *lb_= NULL; //lb_ is a pointer to a matrix of size of 1*numVars_ with lower bound of all variables.
Number *ub_= NULL; //ub_ is a pointer to a matrix of size of 1*numVars_ with upper bound of all variables.
Number *conLb_= NULL; //conLb_ is a pointer to a matrix of size of numCon_*1 with lower bound of all constraints.
Number *conUb_= NULL; //conUb_ is a pointer to a matrix of size of numCon_*1 with upper bound of all constraints.
Number *finalX_= NULL; //finalX_ is a pointer to a matrix of size of 1*numVars_ with final value for the primal variables.
Number finalObjVal_; //finalObjVal_ is a scalar with the final value of the objective.
Number *intcon_ = NULL;
int status_; //Solver return status
minconTMINLP(const minconTMINLP&);
minconTMINLP& operator=(const minconTMINLP&);
public:
// Constructor
minconTMINLP(Index nV, Number *x0, Number *lb, Number *ub, Index nLC, Index nCons, Number *conlb, Number *conub, Index intconSize, Number *intcon):numVars_(nV),x0_(x0),lb_(lb),ub_(ub),numLC_(nLC),numCons_(nCons),conLb_(conlb),conUb_(conub),intconSize_(intconSize),intcon_(intcon),finalX_(0),finalObjVal_(1e20){ }
/** default destructor */
virtual ~minconTMINLP();
virtual bool get_variables_types(Index n, VariableType* var_types);
virtual bool get_variables_linearity(Index n, Ipopt::TNLP::LinearityType* var_types);
virtual bool get_constraints_linearity(Index m, Ipopt::TNLP::LinearityType* const_types);
/** Method to return some info about the nlp */
virtual bool get_nlp_info(Index& n, Index& m, Index& nnz_jac_g,
Index& nnz_h_lag, TNLP::IndexStyleEnum& index_style);
/** Method to return the bounds for my problem */
virtual bool get_bounds_info(Index n, Number* x_l, Number* x_u,
Index m, Number* g_l, Number* g_u);
/** Method to return the starting point for the algorithm */
virtual bool get_starting_point(Index n, bool init_x, Number* x,
bool init_z, Number* z_L, Number* z_U,
Index m, bool init_lambda,
Number* lambda);
/** Method to return the objective value */
virtual bool eval_f(Index n, const Number* x, bool new_x, Number& obj_value);
/** Method to return the gradient of the objective */
virtual bool eval_grad_f(Index n, const Number* x, bool new_x, Number* grad_f);
/** Method to return the constraint residuals */
virtual bool eval_g(Index n, const Number* x, bool new_x, Index m, Number* g);
/** Method to return:
* 1) The structure of the jacobian (if "values" is NULL)
* 2) The values of the jacobian (if "values" is not NULL)
*/
virtual bool eval_jac_g(Index n, const Number* x, bool new_x,Index m, Index nele_jac, Index* iRow, Index *jCol,Number* values);
/** Method to return:
* 1) The structure of the hessian of the lagrangian (if "values" is NULL)
* 2) The values of the hessian of the lagrangian (if "values" is not NULL)
*/
virtual bool eval_h(Index n, const Number* x, bool new_x,Number obj_factor, Index m, const Number* lambda,bool new_lambda, Index nele_hess, Index* iRow,Index* jCol, Number* values);
/** This method is called when the algorithm is complete so the TNLP can store/write the solution */
virtual void finalize_solution(SolverReturn status,Index n, const Number* x, Number obj_value);
virtual const SosInfo * sosConstraints() const{return NULL;}
virtual const BranchingInfo* branchingInfo() const{return NULL;}
const double * getX(); //Returns a pointer to a matrix of size of 1*numVars_
//with final value for the primal variables.
const double * getGrad(); //Returns a pointer to a matrix of size of 1*numVars_
//with final value of gradient for the primal variables.
const double * getHess(); //Returns a pointer to a matrix of size of numVars_*numVars_
//with final value of hessian for the primal variables.
double getObjVal(); //Returns the output of the final value of the objective.
double iterCount(); //Returns the iteration count
int returnStatus(); //Returns the status count
};
#endif
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