Build a linear function from a vector and a matrix. More...
#include <roboptim/core/numeric-linear-function.hh>
Public Member Functions | |
NumericLinearFunction (const matrix_t &A, const vector_t &b) throw () | |
Build a linear function from a matrix and a vector. | |
~NumericLinearFunction () throw () | |
virtual std::ostream & | print (std::ostream &) const throw () |
Display the function on the specified output stream. | |
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LinearFunction (size_type inputSize, size_type outputSize=1, std::string name=std::string()) throw () | |
Concrete class constructor should call this constructor. | |
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QuadraticFunction (size_type inputSize, size_type outputSize=1, std::string name=std::string()) throw () | |
Concrete class constructor should call this constructor. | |
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hessianSize_t | hessianSize () const throw () |
Return the size of a hessian. | |
bool | isValidHessian (const hessian_t &hessian) const throw () |
Check if the hessian is valid (check sizes). | |
hessian_t | hessian (const argument_t &argument, size_type functionId=0) const throw () |
Compute the hessian at a given point. | |
void | hessian (hessian_t &hessian, const argument_t &argument, size_type functionId=0) const throw () |
Compute the hessian at a given point. | |
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size_type | gradientSize () const throw () |
Return the gradient size. | |
jacobianSize_t | jacobianSize () const throw () |
Return the jacobian size as a pair. | |
bool | isValidGradient (const gradient_t &gradient) const throw () |
Check if the gradient is valid (check size). | |
bool | isValidJacobian (const jacobian_t &jacobian) const throw () |
Check if the jacobian is valid (check sizes). | |
jacobian_t | jacobian (const argument_t &argument) const throw () |
Computes the jacobian. | |
void | jacobian (jacobian_t &jacobian, const argument_t &argument) const throw () |
Computes the jacobian. | |
gradient_t | gradient (const argument_t &argument, size_type functionId=0) const throw () |
Computes the gradient. | |
void | gradient (gradient_t &gradient, const argument_t &argument, size_type functionId=0) const throw () |
Computes the gradient. | |
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bool | isValidResult (const result_t &result) const throw () |
Check the given result size is valid. | |
size_type | inputSize () const throw () |
Return the input size (i.e. argument's vector size). | |
size_type | outputSize () const throw () |
Return the output size (i.e. result's vector size). | |
virtual | ~Function () throw () |
Trivial destructor. | |
result_t | operator() (const argument_t &argument) const throw () |
Evaluate the function at a specified point. | |
void | operator() (result_t &result, const argument_t &argument) const throw () |
Evaluate the function at a specified point. | |
const std::string & | getName () const throw () |
Get function name. |
Protected Member Functions | |
void | impl_compute (result_t &, const argument_t &) const throw () |
Function evaluation. | |
void | impl_gradient (gradient_t &, const argument_t &, size_type=0) const throw () |
Gradient evaluation. | |
void | impl_jacobian (jacobian_t &, const argument_t &) const throw () |
Jacobian evaluation. | |
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void | impl_hessian (hessian_t &hessian, const argument_t &argument, size_type functionId=0) const throw () |
Hessian evaluation. |
Build a linear function from a vector and a matrix.
Implement a linear function using the general formula:
where and
are set when the class is instantiated.
roboptim::NumericLinearFunction::NumericLinearFunction | ( | const matrix_t & | A, |
const vector_t & | b | ||
) | throw () |
Build a linear function from a matrix and a vector.
See class documentation for A and b definition.
A | A matrix |
b | b vector |
roboptim::NumericLinearFunction::~NumericLinearFunction | ( | ) | throw () |
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protectedvirtual |
Function evaluation.
Evaluate the function, has to be implemented in concrete classes.
result | result will be stored in this vector |
argument | point at which the function will be evaluated |
Implements roboptim::Function.
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protectedvirtual |
Gradient evaluation.
Compute the gradient, has to be implemented in concrete classes. The gradient is computed for a specific sub-function which id is passed through the functionId argument.
gradient | gradient will be store in this argument |
argument | point where the gradient will be computed |
functionId | evaluated function id in the split representation |
Implements roboptim::DerivableFunction.
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protectedvirtual |
Jacobian evaluation.
Computes the jacobian, can be overridden by concrete classes. The default behavior is to compute the jacobian from the gradient.
jacobian | jacobian will be store in this argument |
arg | point where the jacobian will be computed |
Reimplemented from roboptim::DerivableFunction.
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virtual |
Display the function on the specified output stream.
o | output stream used for display |
Reimplemented from roboptim::LinearFunction.
References roboptim::decindent(), roboptim::iendl(), and roboptim::incindent().