ReFRACtor
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#include <rosenbrock2_nlls_problem.h>
Public Types | |
enum | message_t { NONE, SOLVED, ERROR } |
Enum type for the message generated by the problem. More... | |
Public Member Functions | |
Rosenbrock2NLLSProblem () | |
virtual | ~Rosenbrock2NLLSProblem () |
virtual void | assert_parameter_correct (const blitz::Array< double, 1 > &x) const |
Checks that the new input parameters are correct. More... | |
virtual void | assert_parameter_set_correctly () const |
Checks that the parameters are set correctly. More... | |
virtual void | clear () |
Deletes data contents. More... | |
virtual void | clear () |
Deletes data contents. More... | |
virtual double | cost () |
Read comments on CostFunc::cost() More... | |
virtual void | cost_gradient (double &c, blitz::Array< double, 1 > &g) |
The cost function and its gradient together. More... | |
virtual void | cost_gradient_x (const blitz::Array< double, 1 > &x, double &c, blitz::Array< double, 1 > &g) |
The cost function and its gradient with parameters. More... | |
virtual double | cost_x (const blitz::Array< double, 1 > &x) |
The cost function with parameters. More... | |
virtual int | expected_parameter_size () const |
Returns the expected size of the parameters. More... | |
virtual blitz::Array< double, 1 > | gradient () |
Read comments on CostFuncDiff::gradient() More... | |
virtual int | gradient_size () const |
Returns the size of the gradient vector. More... | |
virtual blitz::Array< double, 1 > | gradient_x (const blitz::Array< double, 1 > &x) |
The gradient function with parameters. More... | |
virtual blitz::Array< double, 2 > | jacobian () |
The Jacobian matrix function. More... | |
virtual blitz::Array< double, 2 > | jacobian_x (const blitz::Array< double, 1 > &x) |
The Jacobian function with parameters. More... | |
virtual message_t | message () const |
Returns a value of CostFunc::message_t type. More... | |
virtual const char *const | message_str () const |
Returns the string version of the problem message. More... | |
virtual int | num_cost_evaluations () const |
Returns the number of the times cost has been evaluated. More... | |
virtual int | num_der1_evaluations () const |
Returns the number of the times gradient has been evaluated. More... | |
virtual int | num_jacobian_evaluations () const |
Returns the number of the times Jacobian has been evaluated. More... | |
virtual int | num_residual_evaluations () const |
Returns the number of the times residual has been evaluated. More... | |
virtual int | parameter_size () const |
Returns the size of the parameters. More... | |
virtual void | parameters (const blitz::Array< double, 1 > &x) |
Sets the problem at a new point in the parameter space. More... | |
virtual blitz::Array< double, 1 > | parameters () const |
Returns the current parameters. More... | |
virtual bool | parameters_different (const blitz::Array< double, 1 > &x) const |
Checks whether or not new input parameters are different from the current ones. More... | |
virtual void | print (std::ostream &Os) const |
Prints description of object. More... | |
std::string | print_to_string () const |
Print to string. More... | |
virtual blitz::Array< double, 1 > | residual () |
The residual vector function. More... | |
virtual void | residual_jacobian (blitz::Array< double, 1 > &r, blitz::Array< double, 2 > &j) |
The residual function and its Jacobian together. More... | |
virtual void | residual_jacobian_x (const blitz::Array< double, 1 > &x, blitz::Array< double, 1 > &r, blitz::Array< double, 2 > &j) |
The residual and its Jacobian with parameters. More... | |
virtual int | residual_size () const |
The size of the residual returned by residual() More... | |
virtual blitz::Array< double, 1 > | residual_x (const blitz::Array< double, 1 > &x) |
The residual function with parameters. More... | |
virtual void | set (const NLLSProblemState &s) |
Makes self a copy of the input state. More... | |
virtual void | set (const ProblemState &s) |
Makes self a copy of the input state. More... | |
virtual void | zero_num_evaluations () |
Sets cost and gradient evaluation counters to zero. More... | |
Protected Member Functions | |
virtual void | increment_num_cost_evaluations () |
Increments (by 1) cost evaluation counter. More... | |
virtual void | increment_num_der1_evaluations () |
Increments (by 1) gradient evaluation counter. More... | |
virtual void | set_num_cost_evaluations (int count) |
Sets the cost evaluation counter to a desired value. More... | |
virtual void | set_num_der1_evaluations (int count) |
Sets the gradient evaluation counter to a desired value. More... | |
Protected Attributes | |
blitz::Array< double, 2 > | J |
message_t | mssg |
blitz::Array< double, 1 > | R |
blitz::Array< double, 1 > | X |
Definition at line 9 of file rosenbrock2_nlls_problem.h.
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inherited |
Enum type for the message generated by the problem.
In general it is very difficult (probably not possible) to develop a general purpose stopping criterion for a general purpose optimization or curve fitting iterative algorithm. The stopping criterion could be very problem dependent. This enumerated type is used to send a message to the solver of a problem, and the iterative solver can optionally take the message into account in deciding how to proceed.
Enumerator | |
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NONE | There are no messages. |
SOLVED | The problem is solved. |
ERROR | There is an error in the problem. |
Definition at line 38 of file cost_func.h.
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inline |
Definition at line 11 of file rosenbrock2_nlls_problem.h.
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inlinevirtual |
Definition at line 14 of file rosenbrock2_nlls_problem.h.
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virtualinherited |
Checks that the new input parameters are correct.
This method checks to see whether or not the new input parameters are correct. If the parameters are not correct then it throws an exception.
Definition at line 44 of file problem_state.cc.
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inlinevirtualinherited |
Checks that the parameters are set correctly.
This method checks to see whether or not the parameters are set correctly. If the parameters are not set correctly then it throws an exception.
Definition at line 197 of file problem_state.h.
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inlinevirtualinherited |
Deletes data contents.
This method deletes state. If needed, it must be reimplemented by other classes derived from this class to delete other saved components associated with the state as well.
Reimplemented from FullPhysics::ProblemState.
Definition at line 96 of file nlls_problem_state.h.
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inlinevirtualinherited |
Deletes data contents.
This method deletes state. It must be reimplemented by other classes derived from this class to delete other saved components associated with the state as well.
Reimplemented in FullPhysics::NLLSProblemState, FullPhysics::ModelState, FullPhysics::CostFuncDiffState, and FullPhysics::CostFuncState.
Definition at line 100 of file problem_state.h.
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virtualinherited |
Read comments on CostFunc::cost()
Implements FullPhysics::CostFunc.
Definition at line 24 of file nlls_problem.cc.
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virtualinherited |
The cost function and its gradient together.
This method passes to the caller the evaluated cost function and its gradient at the current set point.
The parameters (the point in the parameter space) must have already been set before calling this method. The parameters are already set if one of the following methods is already called successfully:
[out] | c | The cost function value |
[out] | g | The gradient vector with size gradient_size() |
Definition at line 17 of file cost_func_diff.cc.
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inlinevirtualinherited |
The cost function and its gradient with parameters.
This method passes to the caller the evaluated cost function and its gradient after setting the problem at the input new point.
[in] | x | New set of parameters |
[out] | c | The cost function value |
[out] | g | The gradient vector with size gradient_size() |
Definition at line 128 of file cost_func_diff.h.
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inlinevirtualinherited |
The cost function with parameters.
This method also evaluates the cost function; however, it sets the problem at the input new point and then evaluates the cost function.
[in] | x | New set of parameters |
Definition at line 89 of file cost_func.h.
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inlinevirtual |
Returns the expected size of the parameters.
This method must be reimplemented by the problem class the inherits ProblemState. It is only in the context of an optimization problem that one knows what the size of the parameters (number of the dimensions of the parameter space) is.
This method is intentionally implemented here instead of being left as a pure virtual method. The intention is that the user to be able to create an object of this class or its derived classes for the purpose of preserving an older state of a problem if needed.
Reimplemented from FullPhysics::ProblemState.
Definition at line 16 of file rosenbrock2_nlls_problem.h.
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virtualinherited |
Read comments on CostFuncDiff::gradient()
Implements FullPhysics::CostFuncDiff.
Definition at line 29 of file nlls_problem.cc.
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inlinevirtualinherited |
Returns the size of the gradient vector.
Definition at line 157 of file cost_func_diff.h.
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inlinevirtualinherited |
The gradient function with parameters.
This method also evaluates the gradient of the cost function; however, it sets the problem at the input new point and then evaluates the gradient.
The size of the gradient vector can be obtained in advance by calling gradient_size().
[in] | x | New set of parameters |
Definition at line 82 of file cost_func_diff.h.
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inlineprotectedvirtualinherited |
Increments (by 1) cost evaluation counter.
The developer of a derived class, where the true cost function evaluation is implemented, must also call this method when the cost function is evaluated.
It is possible to call this method in cost_x() method; however, at this level we do not know when the cost function gets truly evaluated.
The developer of a derived class can save the expensive components of a cost function evaluation and reuse them when cost is inquired and the parameters have not changed. Therefore, she has the options of calling increment_num_cost_evaluations()
If X1 and X2 are two different sets of parameters, then after the sequence of method calls
with the first design option mentioned above num_cost_evaluations() will return 4, but with the second option mentioned above num_cost_evaluations() will return 2.
Therefore, in my opinion it was best not to decide when to call this method at this level in CostFunc class.
Definition at line 198 of file cost_func.h.
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inlineprotectedvirtualinherited |
Increments (by 1) gradient evaluation counter.
The developer of a derived class, where the true gradient evaluation is implemented, must also call this method when the gradient (first order derivatives) is evaluated.
It is possible to call this method in gradient_x() method; however, at this level we do not know when the gradient gets truly evaluated.
The developer of a derived class can save the expensive components of the gradient evaluation and reuse them when gradient is inquired and the parameters have not changed. Therefore, she has the options of calling increment_num_der1_evaluations()
If X1 and X2 are two different sets of parameters, then after the sequence of method calls
with the first design option mentioned above num_der1_evaluations() will return 4, but with the second option mentioned above num_der1_evaluations() will return 2.
Therefore, in my opinion it was best not to decide when to call this method at this level in CostFuncDiff class.
Definition at line 205 of file cost_func_diff.h.
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virtual |
The Jacobian matrix function.
This method must be implemented by the classes derived from this class.
The parameters (the point in the parameter space) must have already been set before calling this method. The parameters are already set if one of the following methods is already called successfully:
If the parameters are already set, then this method returns the Jacobian of the residual of the NLLS problem at the current set point.
The sizes of the Jacobian matrix can be obtained in advance:
Implements FullPhysics::NLLSProblem.
Definition at line 22 of file rosenbrock2_nlls_problem.cc.
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inlinevirtualinherited |
The Jacobian function with parameters.
This method also evaluates the Jacobian of the residual of the NLLS problem; however, it sets the problem at the input new point and then evaluates the Jacobian.
The sizes of the Jacobian matrix can be obtained in advance as mentioned in the comments on jacobian() method.
[in] | x | New set of parameters |
Definition at line 186 of file nlls_problem.h.
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inlinevirtualinherited |
Returns a value of CostFunc::message_t type.
This method returns a problem generated message. The message is initialized as CostFunc::NONE. The implementation of a problem can optionally set it to other values as needed, and the solver of the problem can optionally take different course of actions for different messages.
It is assumed that the solver will not take any different course of action if the returned value is CostFunc::NONE. For other possible values check the comments on CostFunc::message_t.
Definition at line 127 of file cost_func.h.
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virtualinherited |
Returns the string version of the problem message.
If the method status() returns
then message_str() will return
respectively.
Definition at line 14 of file cost_func.cc.
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inlinevirtualinherited |
Returns the number of the times cost has been evaluated.
Definition at line 99 of file cost_func.h.
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inlinevirtualinherited |
Returns the number of the times gradient has been evaluated.
Definition at line 139 of file cost_func_diff.h.
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inlinevirtualinherited |
Returns the number of the times Jacobian has been evaluated.
Definition at line 256 of file nlls_problem.h.
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inlinevirtualinherited |
Returns the number of the times residual has been evaluated.
Definition at line 246 of file nlls_problem.h.
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inlinevirtualinherited |
Returns the size of the parameters.
Definition at line 163 of file problem_state.h.
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virtualinherited |
Sets the problem at a new point in the parameter space.
The method calls parameters_different() to determine whether or not the new parameters are different:
[in] | x | New set of parameters |
Reimplemented in FullPhysics::NLLSProblemScaled, FullPhysics::NLLSMaxAPosteriori, FullPhysics::NLLSMaxLikelihood, and FullPhysics::ModelMeasureStandard.
Definition at line 36 of file problem_state.cc.
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inlinevirtualinherited |
Returns the current parameters.
Reimplemented in FullPhysics::NLLSProblemScaled, FullPhysics::NLLSMaxAPosteriori, FullPhysics::NLLSMaxLikelihood, and FullPhysics::ModelMeasureStandard.
Definition at line 153 of file problem_state.h.
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virtualinherited |
Checks whether or not new input parameters are different from the current ones.
The methods checks to see whether or not the new input parameters (point in the parameter space) are different from the parameters maintained by the object for which the method is called.
If the size of the input parameters is not equal to the expected size of the parameters (check comments on expected_parameter_size), then the method will throw an exception.
If the object for which the method is called has currently no parameters set, then the method returns true. Otherwise, the method uses some algorithm to figure out when the difference is "big enough" to be considered different. If the method determines that the new input parameters are different from the current parameters, then it returns true, otherwise, it returns false.
[in] | x | New set of parameters |
Definition at line 9 of file problem_state.cc.
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inlinevirtual |
Prints description of object.
Reimplemented from FullPhysics::NLLSProblem.
Definition at line 19 of file rosenbrock2_nlls_problem.h.
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inlineinherited |
Print to string.
This is primarily useful for SWIG wrappers to this class, e.g. a to_s method in ruby.
Definition at line 31 of file printable.h.
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virtual |
The residual vector function.
This method must be implemented by the classes derived from this class.
The parameters (the point in the parameter space) must have already been set before calling this method. The parameters are already set if one of the following methods is already called successfully:
If the parameters are already set, then this method returns the residual of the NLLS problem at the current set point.
The size of the residual vector can be obtained in advance by calling residual_size().
Implements FullPhysics::NLLSProblem.
Definition at line 9 of file rosenbrock2_nlls_problem.cc.
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virtualinherited |
The residual function and its Jacobian together.
This method passes to the caller the evaluated residual function and its Jacobian at the current set point.
The parameters (the point in the parameter space) must have already been set before calling this method. The parameters are already set if one of the following methods is already called successfully:
[out] | r | The residual vector |
[out] | j | The Jacobian matrix |
Definition at line 18 of file nlls_problem.cc.
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inlinevirtualinherited |
The residual and its Jacobian with parameters.
This method passes to the caller the evaluated residual function and its Jacobian after setting the problem at the input new point.
[in] | x | New set of parameters |
[out] | r | The residual vector |
[out] | j | The Jacobian matrix |
Definition at line 235 of file nlls_problem.h.
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inlinevirtual |
The size of the residual returned by residual()
This method must be implemented by the classes derived from this class.
Implements FullPhysics::NLLSProblem.
Definition at line 15 of file rosenbrock2_nlls_problem.h.
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inlinevirtualinherited |
The residual function with parameters.
This method also evaluates the residual of the NLLS problem; however, it sets the problem at the input new point and then evaluates the residual.
The size of the residual vector can be obtained in advance by calling residual_size().
[in] | x | New set of parameters |
Definition at line 132 of file nlls_problem.h.
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virtualinherited |
Makes self a copy of the input state.
This method makes the object, for which it is called, a copy of the input state.
[in] | s | another NLLSProblemState |
Definition at line 7 of file nlls_problem_state.cc.
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inlinevirtualinherited |
Makes self a copy of the input state.
This method makes the object, for which it is called, a copy of the input state.
[in] | s | another ProblemState |
Definition at line 88 of file problem_state.h.
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inlineprotectedvirtualinherited |
Sets the cost evaluation counter to a desired value.
This method sets the cost evaluation counter to a desired value. It is just provided if the developers of the derived classes have any use for it
[in] | count | Desired value for cost evaluation counter setting |
Definition at line 213 of file cost_func.h.
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inlineprotectedvirtualinherited |
Sets the gradient evaluation counter to a desired value.
This method sets the gradient (first order derivatives) evaluation counter to a desired value. It is just provided if the developers of the derived classes have any use for it
[in] | count | Desired value for gradient evaluation counter setting |
Definition at line 220 of file cost_func_diff.h.
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inlinevirtualinherited |
Sets cost and gradient evaluation counters to zero.
Reimplemented from FullPhysics::CostFunc.
Definition at line 147 of file cost_func_diff.h.
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protectedinherited |
Definition at line 111 of file nlls_problem_state.h.
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protectedinherited |
Definition at line 163 of file cost_func.h.
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protectedinherited |
Definition at line 110 of file nlls_problem_state.h.
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protectedinherited |
Definition at line 222 of file problem_state.h.