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Diffstat (limited to 'build/cpp/minuncTMINLP.hpp')
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diff --git a/build/cpp/minuncTMINLP.hpp b/build/cpp/minuncTMINLP.hpp deleted file mode 100644 index 2b6e954..0000000 --- a/build/cpp/minuncTMINLP.hpp +++ /dev/null @@ -1,113 +0,0 @@ -// 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 - -#define __USE_DEPRECATED_STACK_FUNCTIONS__ -#ifndef minuncTMINLP_HPP -#define minuncTMINLP_HPP - -#include "BonTMINLP.hpp" -#include "IpTNLP.hpp" -#include "call_scilab.h" - -using namespace Ipopt; -using namespace Bonmin; - -class minuncTMINLP : public TMINLP -{ - private: - - Index numVars_; //Number of input variables - - Index intconSize_; - - const Number *varGuess_= NULL; //varGuess_ is a pointer to a matrix of size of 1*numVars_ with initial guess of all variables. - - 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 - minuncTMINLP(const minuncTMINLP&); - minuncTMINLP& operator=(const minuncTMINLP&); - -public: - // Constructor - minuncTMINLP(Index nV, Number *x0, Index intconSize, Number *intcon):numVars_(nV),varGuess_(x0),intconSize_(intconSize),intcon_(intcon),finalX_(0),finalObjVal_(1e20){ } - - /** default destructor */ - virtual ~minuncTMINLP(); - - 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 |