org.bytedeco.javacpp

Class opencv_core.DownhillSolver

• All Implemented Interfaces:
AutoCloseable
Enclosing class:
opencv_core

@Namespace(value="cv")
public static class opencv_core.DownhillSolver
extends opencv_core.MinProblemSolver
\brief This class is used to perform the non-linear non-constrained minimization of a function,

defined on an n-dimensional Euclidean space, using the **Nelder-Mead method**, also known as downhill simplex method**. The basic idea about the method can be obtained from .

It should be noted, that this method, although deterministic, is rather a heuristic and therefore may converge to a local minima, not necessary a global one. It is iterative optimization technique, which at each step uses an information about the values of a function evaluated only at n+1 points, arranged as a *simplex* in n-dimensional space (hence the second name of the method). At each step new point is chosen to evaluate function at, obtained value is compared with previous ones and based on this information simplex changes it's shape , slowly moving to the local minimum. Thus this method is using *only* function values to make decision, on contrary to, say, Nonlinear Conjugate Gradient method (which is also implemented in optim).

Algorithm stops when the number of function evaluations done exceeds termcrit.maxCount, when the function values at the vertices of simplex are within termcrit.epsilon range or simplex becomes so small that it can enclosed in a box with termcrit.epsilon sides, whatever comes first, for some defined by user positive integer termcrit.maxCount and positive non-integer termcrit.epsilon.

\note DownhillSolver is a derivative of the abstract interface cv::MinProblemSolver, which in turn is derived from the Algorithm interface and is used to encapsulate the functionality, common to all non-linear optimization algorithms in the optim module.

\note term criteria should meet following condition:


termcrit.type == (TermCriteria::MAX_ITER + TermCriteria::EPS) && termcrit.epsilon > 0 && termcrit.maxCount > 0


• Nested classes/interfaces inherited from class org.bytedeco.javacpp.opencv_core.MinProblemSolver

opencv_core.MinProblemSolver.Function
• Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator

• Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position
• Constructor Summary

Constructors
Constructor and Description
DownhillSolver(Pointer p)
Pointer cast constructor.
• Method Summary

All Methods
Modifier and Type Method and Description
static opencv_core.DownhillSolver create()
static opencv_core.DownhillSolver create(opencv_core.MinProblemSolver.Function f, opencv_core.GpuMat initStep, opencv_core.TermCriteria termcrit)
static opencv_core.DownhillSolver create(opencv_core.MinProblemSolver.Function f, opencv_core.Mat initStep, opencv_core.TermCriteria termcrit)
\brief This function returns the reference to the ready-to-use DownhillSolver object.
static opencv_core.DownhillSolver create(opencv_core.MinProblemSolver.Function f, opencv_core.UMat initStep, opencv_core.TermCriteria termcrit)
void getInitStep(opencv_core.GpuMat step)
void getInitStep(opencv_core.Mat step)
\brief Returns the initial step that will be used in downhill simplex algorithm.
void getInitStep(opencv_core.UMat step)
void setInitStep(opencv_core.GpuMat step)
void setInitStep(opencv_core.Mat step)
\brief Sets the initial step that will be used in downhill simplex algorithm.
void setInitStep(opencv_core.UMat step)
• Methods inherited from class org.bytedeco.javacpp.opencv_core.MinProblemSolver

getFunction, getTermCriteria, minimize, minimize, minimize, setFunction, setTermCriteria
• Methods inherited from class org.bytedeco.javacpp.opencv_core.Algorithm

clear, empty, getDefaultName, position, read, save, save, write, write, write
• Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, put, realloc, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero
• Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait
• Method Detail

• getInitStep

public void getInitStep(@ByVal
opencv_core.Mat step)
\brief Returns the initial step that will be used in downhill simplex algorithm.

Parameters:
step - Initial step that will be used in algorithm. Note, that although corresponding setter accepts column-vectors as well as row-vectors, this method will return a row-vector.
DownhillSolver::setInitStep
• getInitStep

public void getInitStep(@ByVal
opencv_core.UMat step)
• getInitStep

public void getInitStep(@ByVal
opencv_core.GpuMat step)
• setInitStep

public void setInitStep(@ByVal
opencv_core.Mat step)
\brief Sets the initial step that will be used in downhill simplex algorithm.

Step, together with initial point (givin in DownhillSolver::minimize) are two n-dimensional vectors that are used to determine the shape of initial simplex. Roughly said, initial point determines the position of a simplex (it will become simplex's centroid), while step determines the spread (size in each dimension) of a simplex. To be more precise, if \f$s,x_0\in\mathbb{R}^n\f$ are the initial step and initial point respectively, the vertices of a simplex will be: \f$v_0:=x_0-\frac{1}{2} s\f$ and \f$v_i:=x_0+s_i\f$ for \f$i=1,2,\dots,n\f$ where \f$s_i\f$ denotes projections of the initial step of *n*-th coordinate (the result of projection is treated to be vector given by \f$s_i:=e_i\cdot\left\f$, where \f$e_i\f$ form canonical basis)

Parameters:
step - Initial step that will be used in algorithm. Roughly said, it determines the spread (size in each dimension) of an initial simplex.
• setInitStep

public void setInitStep(@ByVal
opencv_core.UMat step)
• setInitStep

public void setInitStep(@ByVal
opencv_core.GpuMat step)
• create

@opencv_core.Ptr
public static opencv_core.DownhillSolver create(@opencv_core.Ptr
opencv_core.MinProblemSolver.Function f,
@ByVal(nullValue="cv::InputArray(cv::Mat_<double>(1,1,0.0))")
opencv_core.Mat initStep,
@ByVal(nullValue="cv::TermCriteria(cv::TermCriteria::MAX_ITER+cv::TermCriteria::EPS,5000,0.000001)")
opencv_core.TermCriteria termcrit)
\brief This function returns the reference to the ready-to-use DownhillSolver object.

All the parameters are optional, so this procedure can be called even without parameters at all. In this case, the default values will be used. As default value for terminal criteria are the only sensible ones, MinProblemSolver::setFunction() and DownhillSolver::setInitStep() should be called upon the obtained object, if the respective parameters were not given to create(). Otherwise, the two ways (give parameters to createDownhillSolver() or miss them out and call the MinProblemSolver::setFunction() and DownhillSolver::setInitStep()) are absolutely equivalent (and will drop the same errors in the same way, should invalid input be detected).

Parameters:
f - Pointer to the function that will be minimized, similarly to the one you submit via MinProblemSolver::setFunction.
initStep - Initial step, that will be used to construct the initial simplex, similarly to the one you submit via MinProblemSolver::setInitStep.
termcrit - Terminal criteria to the algorithm, similarly to the one you submit via MinProblemSolver::setTermCriteria.
• create

@opencv_core.Ptr
public static opencv_core.DownhillSolver create()
• create

@opencv_core.Ptr
public static opencv_core.DownhillSolver create(@opencv_core.Ptr
opencv_core.MinProblemSolver.Function f,
@ByVal(nullValue="cv::InputArray(cv::Mat_<double>(1,1,0.0))")
opencv_core.UMat initStep,
@ByVal(nullValue="cv::TermCriteria(cv::TermCriteria::MAX_ITER+cv::TermCriteria::EPS,5000,0.000001)")
opencv_core.TermCriteria termcrit)
• create

@opencv_core.Ptr
public static opencv_core.DownhillSolver create(@opencv_core.Ptr
opencv_core.MinProblemSolver.Function f,
@ByVal(nullValue="cv::InputArray(cv::Mat_<double>(1,1,0.0))")
opencv_core.GpuMat initStep,
@ByVal(nullValue="cv::TermCriteria(cv::TermCriteria::MAX_ITER+cv::TermCriteria::EPS,5000,0.000001)")
opencv_core.TermCriteria termcrit)