diff options
author | Harpreet | 2016-08-04 15:25:44 +0530 |
---|---|---|
committer | Harpreet | 2016-08-04 15:25:44 +0530 |
commit | 9fd2976931c088dc523974afb901e96bad20f73c (patch) | |
tree | 22502de6e6988d5cd595290d11266f8432ad825b /build/Bonmin/include/coin/IpIpoptData.hpp | |
download | FOSSEE-Optim-toolbox-development-9fd2976931c088dc523974afb901e96bad20f73c.tar.gz FOSSEE-Optim-toolbox-development-9fd2976931c088dc523974afb901e96bad20f73c.tar.bz2 FOSSEE-Optim-toolbox-development-9fd2976931c088dc523974afb901e96bad20f73c.zip |
initial add
Diffstat (limited to 'build/Bonmin/include/coin/IpIpoptData.hpp')
-rw-r--r-- | build/Bonmin/include/coin/IpIpoptData.hpp | 819 |
1 files changed, 819 insertions, 0 deletions
diff --git a/build/Bonmin/include/coin/IpIpoptData.hpp b/build/Bonmin/include/coin/IpIpoptData.hpp new file mode 100644 index 0000000..6973bab --- /dev/null +++ b/build/Bonmin/include/coin/IpIpoptData.hpp @@ -0,0 +1,819 @@ +// Copyright (C) 2004, 2009 International Business Machines and others. +// All Rights Reserved. +// This code is published under the Eclipse Public License. +// +// $Id: IpIpoptData.hpp 2472 2014-04-05 17:47:20Z stefan $ +// +// Authors: Carl Laird, Andreas Waechter IBM 2004-08-13 + +#ifndef __IPIPOPTDATA_HPP__ +#define __IPIPOPTDATA_HPP__ + +#include "IpSymMatrix.hpp" +#include "IpOptionsList.hpp" +#include "IpIteratesVector.hpp" +#include "IpRegOptions.hpp" +#include "IpTimingStatistics.hpp" + +namespace Ipopt +{ + + /* Forward declaration */ + class IpoptNLP; + + /** Base class for additional data that is special to a particular + * type of algorithm, such as the CG penalty function, or using + * iterative linear solvers. The regular IpoptData object should + * be given a derivation of this base class when it is created. */ + class IpoptAdditionalData : public ReferencedObject + { + public: + /**@name Constructors/Destructors */ + //@{ + /** Default Constructor */ + IpoptAdditionalData() + {} + + /** Default destructor */ + virtual ~IpoptAdditionalData() + {} + //@} + + /** This method is called to initialize the global algorithmic + * parameters. The parameters are taken from the OptionsList + * object. */ + virtual bool Initialize(const Journalist& jnlst, + const OptionsList& options, + const std::string& prefix) = 0; + + /** Initialize Data Structures at the beginning. */ + virtual bool InitializeDataStructures() = 0; + + /** Do whatever is necessary to accept a trial point as current + * iterate. This is also used to finish an iteration, i.e., to + * release memory, and to reset any flags for a new iteration. */ + virtual void AcceptTrialPoint() = 0; + + private: + /**@name Default Compiler Generated Methods + * (Hidden to avoid implicit creation/calling). + * These methods are not implemented and + * we do not want the compiler to implement + * them for us, so we declare them private + * and do not define them. This ensures that + * they will not be implicitly created/called. */ + //@{ + /** Copy Constructor */ + IpoptAdditionalData(const IpoptAdditionalData&); + + /** Overloaded Equals Operator */ + void operator=(const IpoptAdditionalData&); + //@} + }; + + /** Class to organize all the data required by the algorithm. + * Internally, once this Data object has been initialized, all + * internal curr_ vectors must always be set (so that prototyes are + * available). The current values can only be set from the trial + * values. The trial values can be set by copying from a vector or + * by adding some fraction of a step to the current values. This + * object also stores steps, which allows to easily communicate the + * step from the step computation object to the line search object. + */ + class IpoptData : public ReferencedObject + { + public: + /**@name Constructors/Destructors */ + //@{ + /** Constructor */ + IpoptData(SmartPtr<IpoptAdditionalData> add_data = NULL, + Number cpu_time_start = -1.); + + /** Default destructor */ + virtual ~IpoptData(); + //@} + + /** Initialize Data Structures */ + bool InitializeDataStructures(IpoptNLP& ip_nlp, + bool want_x, + bool want_y_c, + bool want_y_d, + bool want_z_L, + bool want_z_U); + + /** This method must be called to initialize the global + * algorithmic parameters. The parameters are taken from the + * OptionsList object. */ + bool Initialize(const Journalist& jnlst, + const OptionsList& options, + const std::string& prefix); + + /** @name Get Methods for Iterates */ + //@{ + /** Current point */ + inline + SmartPtr<const IteratesVector> curr() const; + + /** Get the current point in a copied container that is non-const. + The entries in the container cannot be modified, but + the container can be modified to point to new entries. + */ + // SmartPtr<IteratesVector> curr_container() const; + + /** Get Trial point */ + inline + SmartPtr<const IteratesVector> trial() const; + + /** Get Trial point in a copied container that is non-const. + * The entries in the container can not be modified, but + * the container can be modified to point to new entries. + */ + //SmartPtr<IteratesVector> trial_container() const; + + /** Set the trial point - this method copies the pointer for + * efficiency (no copy and to keep cache tags the same) so + * after you call set you cannot modify the data again + */ + inline + void set_trial(SmartPtr<IteratesVector>& trial); + + /** Set the values of the primal trial variables (x and s) from + * provided Step with step length alpha. + */ + void SetTrialPrimalVariablesFromStep(Number alpha, + const Vector& delta_x, + const Vector& delta_s); + /** Set the values of the trial values for the equality constraint + * multipliers (y_c and y_d) from provided step with step length + * alpha. + */ + void SetTrialEqMultipliersFromStep(Number alpha, + const Vector& delta_y_c, + const Vector& delta_y_d); + /** Set the value of the trial values for the bound multipliers + * (z_L, z_U, v_L, v_U) from provided step with step length + * alpha. + */ + void SetTrialBoundMultipliersFromStep(Number alpha, + const Vector& delta_z_L, + const Vector& delta_z_U, + const Vector& delta_v_L, + const Vector& delta_v_U); + + /** ToDo: I may need to add versions of set_trial like the + * following, but I am not sure + */ + // void set_trial(const SmartPtr<IteratesVector>& trial_iterates); + // void set_trial(SmartPtr<const IteratesVector>& trial_iterates); + + /** get the current delta */ + inline + SmartPtr<const IteratesVector> delta() const; + + /** Set the current delta - like the trial point, this method copies + * the pointer for efficiency (no copy and to keep cache tags the + * same) so after you call set, you cannot modify the data + */ + inline + void set_delta(SmartPtr<IteratesVector>& delta); + + /** Set the current delta - like the trial point, this method + * copies the pointer for efficiency (no copy and to keep cache + * tags the same) so after you call set, you cannot modify the + * data. This is the version that is happy with a pointer to + * const IteratesVector. + */ + inline + void set_delta(SmartPtr<const IteratesVector>& delta); + + /** Affine Delta */ + inline + SmartPtr<const IteratesVector> delta_aff() const; + + /** Set the affine delta - like the trial point, this method copies + * the pointer for efficiency (no copy and to keep cache tags the + * same) so after you call set, you cannot modify the data + */ + inline + void set_delta_aff(SmartPtr<IteratesVector>& delta_aff); + + /** Hessian or Hessian approximation (do not hold on to it, it might be changed) */ + SmartPtr<const SymMatrix> W() + { + DBG_ASSERT(IsValid(W_)); + return W_; + } + + /** Set Hessian approximation */ + void Set_W(SmartPtr<const SymMatrix> W) + { + W_ = W; + } + + /** @name ("Main") Primal-dual search direction. Those fields are + * used to store the search directions computed from solving the + * primal-dual system, and can be used in the line search. They + * are overwritten in every iteration, so do not hold on to the + * pointers (make copies instead) */ + //@{ + + /** Returns true, if the primal-dual step have been already + * computed for the current iteration. This flag is reset after + * every call of AcceptTrialPoint(). If the search direction is + * computed during the computation of the barrier parameter, the + * method computing the barrier parameter should call + * SetHaveDeltas(true) to tell the IpoptAlgorithm object that it + * doesn't need to recompute the primal-dual step. */ + bool HaveDeltas() const + { + return have_deltas_; + } + + /** Method for setting the HaveDeltas flag. This method should be + * called if some method computes the primal-dual step (and + * stores it in the delta_ fields of IpoptData) at an early part + * of the iteration. If that flag is set to true, the + * IpoptAlgorithm object will not recompute the step. */ + void SetHaveDeltas(bool have_deltas) + { + have_deltas_ = have_deltas; + } + //@} + + /** @name Affine-scaling step. Those fields can be used to store + * the affine scaling step. For example, if the method for + * computing the current barrier parameter computes the affine + * scaling steps, then the corrector step in the line search does + * not have to recompute those solutions of the linear system. */ + //@{ + + /** Returns true, if the affine-scaling step have been already + * computed for the current iteration. This flag is reset after + * every call of AcceptTrialPoint(). If the search direction is + * computed during the computation of the barrier parameter, the + * method computing the barrier parameter should call + * SetHaveDeltas(true) to tell the line search does not have to + * recompute them in case it wants to do a corrector step. */ + bool HaveAffineDeltas() const + { + return have_affine_deltas_; + } + + /** Method for setting the HaveDeltas flag. This method should be + * called if some method computes the primal-dual step (and + * stores it in the delta_ fields of IpoptData) at an early part + * of the iteration. If that flag is set to true, the + * IpoptAlgorithm object will not recompute the step. */ + void SetHaveAffineDeltas(bool have_affine_deltas) + { + have_affine_deltas_ = have_affine_deltas; + } + //@} + + /** @name Public Methods for updating iterates */ + //@{ + /** Copy the trial values to the current values */ + inline + void CopyTrialToCurrent(); + + /** Set the current iterate values from the + * trial values. */ + void AcceptTrialPoint(); + //@} + + /** @name General algorithmic data */ + //@{ + Index iter_count() const + { + return iter_count_; + } + void Set_iter_count(Index iter_count) + { + iter_count_ = iter_count; + } + + Number curr_mu() const + { + DBG_ASSERT(mu_initialized_); + return curr_mu_; + } + void Set_mu(Number mu) + { + curr_mu_ = mu; + mu_initialized_ = true; + } + bool MuInitialized() const + { + return mu_initialized_; + } + + Number curr_tau() const + { + DBG_ASSERT(tau_initialized_); + return curr_tau_; + } + void Set_tau(Number tau) + { + curr_tau_ = tau; + tau_initialized_ = true; + } + bool TauInitialized() const + { + return tau_initialized_; + } + + void SetFreeMuMode(bool free_mu_mode) + { + free_mu_mode_ = free_mu_mode; + } + bool FreeMuMode() const + { + return free_mu_mode_; + } + + /** Setting the flag that indicates if a tiny step (below machine + * precision) has been detected */ + void Set_tiny_step_flag(bool flag) + { + tiny_step_flag_ = flag; + } + bool tiny_step_flag() + { + return tiny_step_flag_; + } + //@} + + /** Overall convergence tolerance. It is used in the convergence + * test, but also in some other parts of the algorithm that + * depend on the specified tolerance, such as the minimum value + * for the barrier parameter. */ + //@{ + /** Obtain the tolerance. */ + Number tol() const + { + DBG_ASSERT(initialize_called_); + return tol_; + } + /** Set a new value for the tolerance. One should be very careful + * when using this, since changing the predefined tolerance might + * have unexpected consequences. This method is for example used + * in the restoration convergence checker to tighten the + * restoration phase convergence tolerance, if the restoration + * phase converged to a point that has not a large value for the + * constraint violation. */ + void Set_tol(Number tol) + { + tol_ = tol; + } + //@} + + /** Cpu time counter at the beginning of the optimization. This + * is useful to see how much CPU time has been spent in this + * optimization run. */ + Number cpu_time_start() const + { + return cpu_time_start_; + } + + /** @name Information gathered for iteration output */ + //@{ + Number info_regu_x() const + { + return info_regu_x_; + } + void Set_info_regu_x(Number regu_x) + { + info_regu_x_ = regu_x; + } + Number info_alpha_primal() const + { + return info_alpha_primal_; + } + void Set_info_alpha_primal(Number alpha_primal) + { + info_alpha_primal_ = alpha_primal; + } + char info_alpha_primal_char() const + { + return info_alpha_primal_char_; + } + void Set_info_alpha_primal_char(char info_alpha_primal_char) + { + info_alpha_primal_char_ = info_alpha_primal_char; + } + Number info_alpha_dual() const + { + return info_alpha_dual_; + } + void Set_info_alpha_dual(Number alpha_dual) + { + info_alpha_dual_ = alpha_dual; + } + Index info_ls_count() const + { + return info_ls_count_; + } + void Set_info_ls_count(Index ls_count) + { + info_ls_count_ = ls_count; + } + bool info_skip_output() const + { + return info_skip_output_; + } + void Append_info_string(const std::string& add_str) + { + info_string_ += add_str; + } + const std::string& info_string() const + { + return info_string_; + } + /** Set this to true, if the next time when output is written, the + * summary line should not be printed. */ + void Set_info_skip_output(bool info_skip_output) + { + info_skip_output_ = info_skip_output; + } + + /** gives time when the last summary output line was printed */ + Number info_last_output() + { + return info_last_output_; + } + /** sets time when the last summary output line was printed */ + void Set_info_last_output(Number info_last_output) + { + info_last_output_ = info_last_output; + } + + /** gives number of iteration summaries actually printed + * since last summary header was printed */ + int info_iters_since_header() + { + return info_iters_since_header_; + } + /** increases number of iteration summaries actually printed + * since last summary header was printed */ + void Inc_info_iters_since_header() + { + info_iters_since_header_++; + } + /** sets number of iteration summaries actually printed + * since last summary header was printed */ + void Set_info_iters_since_header(int info_iters_since_header) + { + info_iters_since_header_ = info_iters_since_header; + } + + /** Reset all info fields */ + void ResetInfo() + { + info_regu_x_ = 0; + info_alpha_primal_ = 0; + info_alpha_dual_ = 0.; + info_alpha_primal_char_ = ' '; + info_skip_output_ = false; + info_string_.erase(); + } + //@} + + /** Return Timing Statistics Object */ + TimingStatistics& TimingStats() + { + return timing_statistics_; + } + + /** Check if additional data has been set */ + bool HaveAddData() + { + return IsValid(add_data_); + } + + /** Get access to additional data object */ + IpoptAdditionalData& AdditionalData() + { + return *add_data_; + } + + /** Set a new pointer for additional Ipopt data */ + void SetAddData(SmartPtr<IpoptAdditionalData> add_data) + { + DBG_ASSERT(!HaveAddData()); + add_data_ = add_data; + } + + /** Set the perturbation of the primal-dual system */ + void setPDPert(Number pd_pert_x, Number pd_pert_s, + Number pd_pert_c, Number pd_pert_d) + { + pd_pert_x_ = pd_pert_x; + pd_pert_s_ = pd_pert_s; + pd_pert_c_ = pd_pert_c; + pd_pert_d_ = pd_pert_d; + } + + /** Get the current perturbation of the primal-dual system */ + void getPDPert(Number& pd_pert_x, Number& pd_pert_s, + Number& pd_pert_c, Number& pd_pert_d) + { + pd_pert_x = pd_pert_x_; + pd_pert_s = pd_pert_s_; + pd_pert_c = pd_pert_c_; + pd_pert_d = pd_pert_d_; + } + + /** Methods for IpoptType */ + //@{ + static void RegisterOptions(const SmartPtr<RegisteredOptions>& roptions); + //@} + + private: + /** @name Iterates */ + //@{ + /** Main iteration variables + * (current iteration) */ + SmartPtr<const IteratesVector> curr_; + + /** Main iteration variables + * (trial calculations) */ + SmartPtr<const IteratesVector> trial_; + + /** Hessian (approximation) - might be changed elsewhere! */ + SmartPtr<const SymMatrix> W_; + + /** @name Primal-dual Step */ + //@{ + SmartPtr<const IteratesVector> delta_; + /** The following flag is set to true, if some other part of the + * algorithm (like the method for computing the barrier + * parameter) has already computed the primal-dual search + * direction. This flag is reset when the AcceptTrialPoint + * method is called. + * ToDo: we could cue off of a null delta_; + */ + bool have_deltas_; + //@} + + /** @name Affine-scaling step. This used to transfer the + * information about the affine-scaling step from the computation + * of the barrier parameter to the corrector (in the line + * search). */ + //@{ + SmartPtr<const IteratesVector> delta_aff_; + /** The following flag is set to true, if some other part of the + * algorithm (like the method for computing the barrier + * parameter) has already computed the affine-scaling step. This + * flag is reset when the AcceptTrialPoint method is called. + * ToDo: we could cue off of a null delta_aff_; + */ + bool have_affine_deltas_; + //@} + + /** iteration count */ + Index iter_count_; + + /** current barrier parameter */ + Number curr_mu_; + bool mu_initialized_; + + /** current fraction to the boundary parameter */ + Number curr_tau_; + bool tau_initialized_; + + /** flag indicating if Initialize method has been called (for + * debugging) */ + bool initialize_called_; + + /** flag for debugging whether we have already curr_ values + * available (from which new Vectors can be generated */ + bool have_prototypes_; + + /** @name Global algorithm parameters. Those are options that can + * be modified by the user and appear at different places in the + * algorithm. They are set using an OptionsList object in the + * Initialize method. */ + //@{ + /** Overall convergence tolerance */ + Number tol_; + //@} + + /** @name Status data **/ + //@{ + /** flag indicating whether the algorithm is in the free mu mode */ + bool free_mu_mode_; + /** flag indicating if a tiny step has been detected */ + bool tiny_step_flag_; + //@} + + /** @name Gathered information for iteration output */ + //@{ + /** Size of regularization for the Hessian */ + Number info_regu_x_; + /** Primal step size */ + Number info_alpha_primal_; + /** Info character for primal step size */ + char info_alpha_primal_char_; + /** Dual step size */ + Number info_alpha_dual_; + /** Number of backtracking trial steps */ + Index info_ls_count_; + /** true, if next summary output line should not be printed (eg + * after restoration phase. */ + bool info_skip_output_; + /** any string of characters for the end of the output line */ + std::string info_string_; + /** time when the last summary output line was printed */ + Number info_last_output_; + /** number of iteration summaries actually printed since last + * summary header was printed */ + int info_iters_since_header_; + //@} + + /** VectorSpace for all the iterates */ + SmartPtr<IteratesVectorSpace> iterates_space_; + + /** TimingStatistics object collecting all Ipopt timing + * statistics */ + TimingStatistics timing_statistics_; + + /** CPU time counter at initialization. */ + Number cpu_time_start_; + + /** Object for the data specific for the Chen-Goldfarb penalty + * method algorithm */ + SmartPtr<IpoptAdditionalData> add_data_; + + /** @name Information about the perturbation of the primal-dual + * system */ + //@{ + Number pd_pert_x_; + Number pd_pert_s_; + Number pd_pert_c_; + Number pd_pert_d_; + //@} + + /**@name Default Compiler Generated Methods + * (Hidden to avoid implicit creation/calling). + * These methods are not implemented and + * we do not want the compiler to implement + * them for us, so we declare them private + * and do not define them. This ensures that + * they will not be implicitly created/called. */ + //@{ + /** Copy Constructor */ + IpoptData(const IpoptData&); + + /** Overloaded Equals Operator */ + void operator=(const IpoptData&); + //@} + +#if COIN_IPOPT_CHECKLEVEL > 0 + /** Some debug flags to make sure vectors are not changed + * behind the IpoptData's back + */ + //@{ + TaggedObject::Tag debug_curr_tag_; + TaggedObject::Tag debug_trial_tag_; + TaggedObject::Tag debug_delta_tag_; + TaggedObject::Tag debug_delta_aff_tag_; + TaggedObject::Tag debug_curr_tag_sum_; + TaggedObject::Tag debug_trial_tag_sum_; + TaggedObject::Tag debug_delta_tag_sum_; + TaggedObject::Tag debug_delta_aff_tag_sum_; + //@} +#endif + + }; + + inline + SmartPtr<const IteratesVector> IpoptData::curr() const + { + DBG_ASSERT(IsNull(curr_) || (curr_->GetTag() == debug_curr_tag_ && curr_->GetTagSum() == debug_curr_tag_sum_) ); + + return curr_; + } + + inline + SmartPtr<const IteratesVector> IpoptData::trial() const + { + DBG_ASSERT(IsNull(trial_) || (trial_->GetTag() == debug_trial_tag_ && trial_->GetTagSum() == debug_trial_tag_sum_) ); + + return trial_; + } + + inline + SmartPtr<const IteratesVector> IpoptData::delta() const + { + DBG_ASSERT(IsNull(delta_) || (delta_->GetTag() == debug_delta_tag_ && delta_->GetTagSum() == debug_delta_tag_sum_) ); + + return delta_; + } + + inline + SmartPtr<const IteratesVector> IpoptData::delta_aff() const + { + DBG_ASSERT(IsNull(delta_aff_) || (delta_aff_->GetTag() == debug_delta_aff_tag_ && delta_aff_->GetTagSum() == debug_delta_aff_tag_sum_) ); + + return delta_aff_; + } + + inline + void IpoptData::CopyTrialToCurrent() + { + curr_ = trial_; +#if COIN_IPOPT_CHECKLEVEL > 0 + + if (IsValid(curr_)) { + debug_curr_tag_ = curr_->GetTag(); + debug_curr_tag_sum_ = curr_->GetTagSum(); + } + else { + debug_curr_tag_ = 0; + debug_curr_tag_sum_ = 0; + } +#endif + + } + + inline + void IpoptData::set_trial(SmartPtr<IteratesVector>& trial) + { + trial_ = ConstPtr(trial); + +#if COIN_IPOPT_CHECKLEVEL > 0 + // verify the correct space + DBG_ASSERT(trial_->OwnerSpace() == (VectorSpace*)GetRawPtr(iterates_space_)); + if (IsValid(trial)) { + debug_trial_tag_ = trial->GetTag(); + debug_trial_tag_sum_ = trial->GetTagSum(); + } + else { + debug_trial_tag_ = 0; + debug_trial_tag_sum_ = 0; + } +#endif + + trial = NULL; + } + + inline + void IpoptData::set_delta(SmartPtr<IteratesVector>& delta) + { + delta_ = ConstPtr(delta); +#if COIN_IPOPT_CHECKLEVEL > 0 + + if (IsValid(delta)) { + debug_delta_tag_ = delta->GetTag(); + debug_delta_tag_sum_ = delta->GetTagSum(); + } + else { + debug_delta_tag_ = 0; + debug_delta_tag_sum_ = 0; + } +#endif + + delta = NULL; + } + + inline + void IpoptData::set_delta(SmartPtr<const IteratesVector>& delta) + { + delta_ = delta; +#if COIN_IPOPT_CHECKLEVEL > 0 + + if (IsValid(delta)) { + debug_delta_tag_ = delta->GetTag(); + debug_delta_tag_sum_ = delta->GetTagSum(); + } + else { + debug_delta_tag_ = 0; + debug_delta_tag_sum_ = 0; + } +#endif + + delta = NULL; + } + + inline + void IpoptData::set_delta_aff(SmartPtr<IteratesVector>& delta_aff) + { + delta_aff_ = ConstPtr(delta_aff); +#if COIN_IPOPT_CHECKLEVEL > 0 + + if (IsValid(delta_aff)) { + debug_delta_aff_tag_ = delta_aff->GetTag(); + debug_delta_aff_tag_sum_ = delta_aff->GetTagSum(); + } + else { + debug_delta_aff_tag_ = 0; + debug_delta_aff_tag_sum_ = delta_aff->GetTagSum(); + } +#endif + + delta_aff = NULL; + } + +} // namespace Ipopt + +#endif |