problem.cc
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29 
30 #include <ifopt/problem.h>
31 #include <iostream>
32 #include <iomanip>
33 
34 
35 namespace ifopt {
36 
38  :constraints_("constraint-sets", false),
39  costs_("cost-terms", true)
40 {
41  variables_ = std::make_shared<Composite>("variable-sets", false);
42 }
43 
44 void
46 {
47  variables_->AddComponent(variable_set);
48 }
49 
50 void
52 {
53  constraint_set->LinkWithVariables(variables_);
54  constraints_.AddComponent(constraint_set);
55 }
56 
57 void
59 {
60  cost_set->LinkWithVariables(variables_);
61  costs_.AddComponent(cost_set);
62 }
63 
64 int
66 {
67  return variables_->GetRows();
68 }
69 
72 {
73  return variables_->GetBounds();
74 }
75 
78 {
79  return variables_->GetValues();
80 }
81 
82 void
83 Problem::SetVariables (const double* x)
84 {
85  variables_->SetVariables(ConvertToEigen(x));
86 }
87 
88 double
90 {
91  VectorXd g = VectorXd::Zero(1);
92  if (HasCostTerms()) {
93  SetVariables(x);
94  g = costs_.GetValues();
95  }
96  return g(0);
97 }
98 
100 Problem::EvaluateCostFunctionGradient (const double* x, bool use_finite_difference_approximation, double epsilon)
101 {
103  Jacobian jac = Jacobian(1,n);
104  if (HasCostTerms()) {
105  if(use_finite_difference_approximation) {
106  double step_size = epsilon;
107 
108  // calculate forward difference by disturbing each optimization variable
109  double g = EvaluateCostFunction(x);
110  std::vector<double> x_new(x, x + n);
111  for (int i=0; i<n; ++i) {
112  x_new[i] += step_size; // disturb
113  double g_new = EvaluateCostFunction(x_new.data());
114  jac.coeffRef(0,i) = (g_new - g)/step_size;
115  x_new[i] = x[i]; // reset for next iteration
116  }
117  } else {
118  SetVariables(x);
119  jac = costs_.GetJacobian();
120  }
121  }
122 
123  return jac.row(0).transpose();
124 }
125 
128 {
129  return constraints_.GetBounds();
130 }
131 
132 int
134 {
135  return GetBoundsOnConstraints().size();
136 }
137 
140 {
141  SetVariables(x);
142  return constraints_.GetValues();
143 }
144 
145 bool
147 {
148  return costs_.GetRows()>0;
149 }
150 
151 void
152 Problem::EvalNonzerosOfJacobian (const double* x, double* values)
153 {
154  SetVariables(x);
156 
157  jac.makeCompressed(); // so the valuePtr() is dense and accurate
158  std::copy(jac.valuePtr(), jac.valuePtr() + jac.nonZeros(), values);
159 }
160 
163 {
164  return constraints_.GetJacobian();
165 }
166 
169 {
170  return costs_.GetJacobian();
171 }
172 
173 void
175 {
176  x_prev.push_back(variables_->GetValues());
177 }
178 
181 {
182  return variables_;
183 }
184 
185 void
187 {
188  variables_->SetVariables(x_prev.at(iter));
189 }
190 
191 void
193 {
194  variables_->SetVariables(x_prev.at(GetIterationCount()-1));
195 }
196 
197 void
199 {
200  using namespace std;
201  cout << "\n"
202  << "************************************************************\n"
203  << " IFOPT - Interface to Nonlinear Optimizers (v2.0)\n"
204  << " \u00a9 Alexander W. Winkler\n"
205  << " https://github.com/ethz-adrl/ifopt\n"
206  << "************************************************************"
207  << "\n"
208  << "Legend:\n"
209  << "c - number of variables, constraints or cost terms" << std::endl
210  << "i - indices of this set in overall problem" << std::endl
211  << "v - number of [violated variable- or constraint-bounds] or [cost term value]"
212  << "\n\n"
213  << std::right
214  << std::setw(33) << ""
215  << std::setw(5) << "c "
216  << std::setw(16) << "i "
217  << std::setw(11) << "v "
218  << std::left
219  << "\n";
220 
221  variables_->PrintAll();
223  costs_.PrintAll();
224 };
225 
227 Problem::ConvertToEigen(const double* x) const
228 {
229  return Eigen::Map<const VectorXd>(x,GetNumberOfOptimizationVariables());
230 }
231 
232 } /* namespace opt */
233 
std::vector< VectorXd > x_prev
the pure variables for every iteration.
Definition: problem.h:274
Problem()
Creates a optimization problem with no variables, costs or constraints.
Definition: problem.cc:37
Composite::Ptr variables_
Definition: problem.h:267
VecBound GetBounds() const override
Returns the "bounds" of this component.
Definition: composite.cc:194
void SetOptVariables(int iter)
Sets the optimization variables to those at iteration iter.
Definition: problem.cc:186
Composite::Ptr GetOptVariables() const
Read/write access to the current optimization variables.
Definition: problem.cc:180
int GetNumberOfConstraints() const
The number of individual constraints.
Definition: problem.cc:133
void AddCostSet(CostTerm::Ptr cost_set)
Add a cost term to the optimization problem.
Definition: problem.cc:58
int GetIterationCount() const
The number of iterations it took to solve the problem.
Definition: problem.h:244
std::shared_ptr< Composite > Ptr
Definition: composite.h:164
Component::Jacobian Jacobian
Definition: problem.h:100
double EvaluateCostFunction(const double *x)
The scalar cost for current optimization variables x.
Definition: problem.cc:89
Composite constraints_
Definition: problem.h:271
VectorXd EvaluateCostFunctionGradient(const double *x, bool use_finite_difference_approximation=false, double epsilon=std::numeric_limits< double >::epsilon())
The column-vector of derivatives of the cost w.r.t. each variable.
Definition: problem.cc:100
VectorXd GetVariableValues() const
The current value of the optimization variables.
Definition: problem.cc:77
void PrintCurrent() const
Prints the variables, costs and constraints.
Definition: problem.cc:198
Component::VectorXd VectorXd
Definition: problem.h:101
int GetRows() const
Returns the number of rows of this component.
Definition: composite.cc:44
std::shared_ptr< Component > Ptr
Definition: composite.h:65
void SaveCurrent()
Saves the current values of the optimization variables in x_prev.
Definition: problem.cc:174
int GetNumberOfOptimizationVariables() const
The number of optimization variables.
Definition: problem.cc:65
VectorXd ConvertToEigen(const double *x) const
Definition: problem.cc:227
Component::VecBound VecBound
Definition: problem.h:99
VectorXd GetValues() const override
Returns the "values" of whatever this component represents.
Definition: composite.cc:136
void SetVariables(const double *x)
Updates the variables with the values of the raw pointer x.
Definition: problem.cc:83
Jacobian GetJacobianOfConstraints() const
The sparse-matrix representation of Jacobian of the constraints.
Definition: problem.cc:162
void AddComponent(const Component::Ptr &)
Adds a component to this composite.
Definition: composite.cc:104
std::shared_ptr< ConstraintSet > Ptr
void PrintAll() const
Definition: composite.cc:212
VecBound GetBoundsOnConstraints() const
The upper and lower bound of each individual constraint.
Definition: problem.cc:127
void SetOptVariablesFinal()
Sets the optimization variables to those of the final iteration.
Definition: problem.cc:192
bool HasCostTerms() const
True if the optimization problem includes a cost, false if merely a feasibility problem is defined...
Definition: problem.cc:146
common namespace for all elements in this library.
Definition: bounds.h:33
Jacobian GetJacobian() const override
Returns derivatives of each row w.r.t. the variables.
Definition: composite.cc:164
void EvalNonzerosOfJacobian(const double *x, double *values)
Extracts those entries from constraint Jacobian that are not zero.
Definition: problem.cc:152
void AddConstraintSet(ConstraintSet::Ptr constraint_set)
Add a set of multiple constraints to the optimization problem.
Definition: problem.cc:51
Jacobian GetJacobianOfCosts() const
The sparse-matrix representation of Jacobian of the costs.
Definition: problem.cc:168
VectorXd EvaluateConstraints(const double *x)
Each constraint value g(x) for current optimization variables x.
Definition: problem.cc:139
void AddVariableSet(VariableSet::Ptr variable_set)
Add one individual set of variables to the optimization problem.
Definition: problem.cc:45
Composite costs_
Definition: problem.h:272
VecBound GetBoundsOnOptimizationVariables() const
The maximum and minimum value each optimization variable is allowed to have.
Definition: problem.cc:71


ifopt
Author(s): Alexander W. Winkler
autogenerated on Fri Sep 16 2022 02:15:26