itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree > Class Template Reference
fast k-means algorithm implementation using k-d tree structure More...
#include <itkKdTreeBasedKmeansEstimator.h>
Detailed Description
template<class TKdTree>
class itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >
fast k-means algorithm implementation using k-d tree structure
It returns k mean vectors that are centroids of k-clusters using pre-generated k-d tree. k-d tree generation is done by the WeightedCentroidKdTreeGenerator. The tree construction needs to be done only once. The resulting k-d tree's non-terminal nodes that have their children nodes have vector sums of measurement vectors that belong to the nodes and the number of measurement vectors in addition to the typical node boundary information and pointers to children nodes. Instead of reassigning every measurement vector to the nearest cluster centroid and recalculating centroid, it maintain a set of cluster centroid candidates and using pruning algorithm that utilizes k-d tree, it updates the means of only relevant candidates at each iterations. It would be faster than traditional implementation of k-means algorithm. However, the k-d tree consumes a large amount of memory. The tree construction time and pruning algorithm's performance are important factors to the whole process's performance. If users want to use k-d tree for some purpose other than k-means estimation, they can use the KdTreeGenerator instead of the WeightedCentroidKdTreeGenerator. It will save the tree construction time and memory usage.
Note: There is a second implementation of k-means algorithm in ITK under the While the Kd tree based implementation is more time efficient, the GLA/LBG based algorithm is more memory efficient.
Recent API changes: The static const macro to get the length of a measurement vector, MeasurementVectorSize has been removed to allow the length of a measurement vector to be specified at run time. It is now obtained from the KdTree set as input. You may query this length using the function GetMeasurementVectorSize().
Definition at line 67 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
Member Typedef Documentation
| typedef KdTreeNodeType::CentroidType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CentroidType |
Definition at line 92 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef KdTreeNodeType::CentroidType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CentroidType |
Definition at line 89 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef itk::hash_map< InstanceIdentifier, unsigned int > itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::ClusterLabelsType |
Definition at line 157 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef itk::hash_map< InstanceIdentifier, unsigned int > itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::ClusterLabelsType |
Definition at line 145 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef SmartPointer<const Self> itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::ConstPointer |
Reimplemented from itk::Object.
Definition at line 78 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef SmartPointer<const Self> itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::ConstPointer |
Reimplemented from itk::Object.
Definition at line 75 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef DistanceToCentroidMembershipFunctionType::Pointer itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::DistanceToCentroidMembershipFunctionPointer |
Definition at line 111 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef DistanceToCentroidMembershipFunction< MeasurementVectorType > itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::DistanceToCentroidMembershipFunctionType |
Typedef requried to generate dataobject decorated output that can be plugged into SampleClassifierFilter
Definition at line 108 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef TKdTree::InstanceIdentifier itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::InstanceIdentifier |
Definition at line 90 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef TKdTree::InstanceIdentifier itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::InstanceIdentifier |
Definition at line 87 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef std::vector< ParameterType > itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::InternalParametersType |
Definition at line 101 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef std::vector< ParameterType > itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::InternalParametersType |
Definition at line 98 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
typedef int itk::LightObject::InternalReferenceCountType [protected, inherited] |
Define the type of the reference count according to the target. This allows the use of atomic operations
Definition at line 139 of file itkLightObject.h.
| typedef TKdTree::KdTreeNodeType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::KdTreeNodeType |
Types for the KdTree data structure
Definition at line 84 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef TKdTree::KdTreeNodeType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::KdTreeNodeType |
Types for the KdTree data structure
Definition at line 81 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef TKdTree::MeasurementType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::MeasurementType |
Definition at line 88 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef TKdTree::MeasurementType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::MeasurementType |
Definition at line 85 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef unsigned int itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::MeasurementVectorSizeType |
Typedef for the length of a measurement vector
Definition at line 96 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef unsigned int itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::MeasurementVectorSizeType |
Typedef for the length of a measurement vector
Definition at line 93 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef TKdTree::MeasurementVectorType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::MeasurementVectorType |
Definition at line 89 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef TKdTree::MeasurementVectorType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::MeasurementVectorType |
Definition at line 86 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef MembershipFunctionType::ConstPointer itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::MembershipFunctionPointer |
Definition at line 114 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef MembershipFunctionBase< MeasurementVectorType > itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::MembershipFunctionType |
Definition at line 113 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef MembershipFunctionVectorObjectType::Pointer itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::MembershipFunctionVectorObjectPointer |
Definition at line 119 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef SimpleDataObjectDecorator< MembershipFunctionVectorType > itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::MembershipFunctionVectorObjectType |
Definition at line 117 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef std::vector< MembershipFunctionPointer > itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::MembershipFunctionVectorType |
Definition at line 115 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef Array< double > itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::ParametersType |
Definition at line 102 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef Array< double > itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::ParametersType |
Definition at line 99 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef Array< double > itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::ParameterType |
Parameters type. It defines a position in the optimization search space.
Definition at line 100 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef Array< double > itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::ParameterType |
Parameters type. It defines a position in the optimization search space.
Definition at line 97 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef SmartPointer<Self> itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::Pointer |
Reimplemented from itk::Object.
Definition at line 77 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef SmartPointer<Self> itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::Pointer |
Reimplemented from itk::Object.
Definition at line 74 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef TKdTree::SampleType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::SampleType |
Definition at line 91 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef TKdTree::SampleType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::SampleType |
Definition at line 88 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef KdTreeBasedKmeansEstimator itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::Self |
Standard Self typedef.
Reimplemented from itk::Object.
Definition at line 75 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef KdTreeBasedKmeansEstimator itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::Self |
Standard "Self" typedef.
Reimplemented from itk::Object.
Definition at line 72 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef Object itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::Superclass |
Reimplemented from itk::Object.
Definition at line 76 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
| typedef Object itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::Superclass |
Reimplemented from itk::Object.
Definition at line 73 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
Constructor & Destructor Documentation
| itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::KdTreeBasedKmeansEstimator | ( | ) | [protected] |
| virtual itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::~KdTreeBasedKmeansEstimator | ( | ) | [inline, protected, virtual] |
Definition at line 155 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::KdTreeBasedKmeansEstimator | ( | ) | [protected] |
| virtual itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::~KdTreeBasedKmeansEstimator | ( | ) | [inline, protected, virtual] |
Definition at line 164 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.
Member Function Documentation
| unsigned long itk::Object::AddObserver | ( | const EventObject & | event, | |
| Command * | ||||
| ) | const [inherited] |
This is a global flag that controls whether any debug, warning or error messages are displayed.
| unsigned long itk::Object::AddObserver | ( | const EventObject & | event, | |
| Command * | ||||
| ) | [inherited] |
Allow people to add/remove/invoke observers (callbacks) to any ITK object. This is an implementation of the subject/observer design pattern. An observer is added by specifying an event to respond to and an itk::Command to execute. It returns an unsigned long tag which can be used later to remove the event or retrieve the command. The memory for the Command becomes the responsibility of this object, so don't pass the same instance of a command to two different objects
| static void itk::LightObject::BreakOnError | ( | ) | [static, inherited] |
This method is called when itkExceptionMacro executes. It allows the debugger to break on error.
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CopyParameters | ( | InternalParametersType & | source, | |
| ParametersType & | target | |||
| ) | [protected] |
copies the source parameters (k-means) to the target
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CopyParameters | ( | ParametersType & | source, | |
| InternalParametersType & | target | |||
| ) | [protected] |
copies the source parameters (k-means) to the target
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CopyParameters | ( | InternalParametersType & | source, | |
| InternalParametersType & | target | |||
| ) | [protected] |
copies the source parameters (k-means) to the target
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CopyParameters | ( | InternalParametersType & | source, | |
| ParametersType & | target | |||
| ) | [protected] |
copies the source parameters (k-means) to the target
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CopyParameters | ( | ParametersType & | source, | |
| InternalParametersType & | target | |||
| ) | [protected] |
copies the source parameters (k-means) to the target
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CopyParameters | ( | InternalParametersType & | source, | |
| InternalParametersType & | target | |||
| ) | [protected] |
copies the source parameters (k-means) to the target
| virtual LightObject::Pointer itk::Object::CreateAnother | ( | ) | const [virtual, inherited] |
Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.
Reimplemented from itk::LightObject.
Reimplemented in itk::BSplineDeformableTransform< TScalarType, NDimensions, VSplineOrder >, itk::CreateObjectFunction< T >, itk::TransformFactoryBase, itk::AnalyzeImageIOFactory, itk::BioRadImageIOFactory, itk::BMPImageIOFactory, itk::Brains2MaskImageIOFactory, itk::DICOMImageIO2Factory, itk::DicomImageIOFactory, itk::GDCMImageIOFactory, itk::GE4ImageIOFactory, itk::GE5ImageIOFactory, itk::GEAdwImageIOFactory, itk::GiplImageIOFactory, itk::JPEGImageIOFactory, itk::LSMImageIOFactory, itk::MetaImageIOFactory, itk::NiftiImageIOFactory, itk::NrrdImageIOFactory, itk::PNGImageIOFactory, itk::RawImageIOFactory< TPixel, VImageDimension >, itk::SiemensVisionImageIOFactory, itk::StimulateImageIOFactory, itk::TIFFImageIOFactory, itk::VTKImageIOFactory, itk::Bruker2DSEQImageIOFactory, itk::MatlabTransformIOFactory, itk::MINC2ImageIOFactory, itk::PhilipsRECImageIOFactory, itk::TxtTransformIOFactory, itk::VoxBoCUBImageIOFactory, and itk::SpatialObjectFactoryBase.
| virtual void itk::Object::DebugOff | ( | ) | const [virtual, inherited] |
Turn debugging output off.
| virtual void itk::Object::DebugOn | ( | ) | const [virtual, inherited] |
Turn debugging output on.
| virtual void itk::LightObject::Delete | ( | ) | [virtual, inherited] |
Delete an itk object. This method should always be used to delete an object when the new operator was used to create it. Using the C delete method will not work with reference counting.
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::FillClusterLabels | ( | KdTreeNodeType * | node, | |
| int | closestIndex | |||
| ) | [protected] |
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::FillClusterLabels | ( | KdTreeNodeType * | node, | |
| int | closestIndex | |||
| ) | [protected] |
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::Filter | ( | KdTreeNodeType * | node, | |
| std::vector< int > | validIndexes, | |||
| MeasurementVectorType & | lowerBound, | |||
| MeasurementVectorType & | upperBound | |||
| ) | [protected] |
recursive pruning algorithm. the validIndexes vector contains only the indexes of the surviving candidates for the node
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::Filter | ( | KdTreeNodeType * | node, | |
| std::vector< int > | validIndexes, | |||
| MeasurementVectorType & | lowerBound, | |||
| MeasurementVectorType & | upperBound | |||
| ) | [protected] |
recursive pruning algorithm. the "validIndexes" vector contains only the indexes of the surviving candidates for the "node"
| virtual double itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetCentroidPositionChanges | ( | ) | const [virtual] |
| virtual const double& itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetCentroidPositionChanges | ( | ) | [virtual] |
| virtual double itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetCentroidPositionChangesThreshold | ( | ) | const [virtual] |
| virtual const double& itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetCentroidPositionChangesThreshold | ( | ) | [virtual] |
Set/Get the termination threshold for the squared sum of changes in centroid postions after one iteration
| int itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetClosestCandidate | ( | ParameterType & | measurements, | |
| std::vector< int > & | validIndexes | |||
| ) | [protected] |
get the index of the closest candidate to the measurements measurement vector
| int itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetClosestCandidate | ( | ParameterType & | measurements, | |
| std::vector< int > & | validIndexes | |||
| ) | [protected] |
get the index of the closest candidate to the "measurements" measurement vector
| ClusterLabelsType* itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetClusterLabels | ( | ) | [inline] |
Definition at line 150 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| Command* itk::Object::GetCommand | ( | unsigned long | tag | ) | [inherited] |
Get the command associated with the given tag. NOTE: This returns a pointer to a Command, but it is safe to asign this to a Command::Pointer. Since Command inherits from LightObject, at this point in the code, only a pointer or a reference to the Command can be used.
| virtual int itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetCurrentIteration | ( | ) | const [virtual] |
| virtual const int& itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetCurrentIteration | ( | ) | [virtual] |
| bool itk::Object::GetDebug | ( | ) | const [inherited] |
Get the value of the debug flag.
| static bool itk::Object::GetGlobalWarningDisplay | ( | ) | [static, inherited] |
This is a global flag that controls whether any debug, warning or error messages are displayed.
| const TKdTree* itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetKdTree | ( | ) | const |
Set/Get the termination threshold for the squared sum of changes in centroid postions after one iteration
| TKdTree* itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetKdTree | ( | ) | [inline] |
Definition at line 130 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| virtual int itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetMaximumIteration | ( | ) | const [virtual] |
Set/Get the termination threshold for the squared sum of changes in centroid postions after one iteration
| virtual const int& itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetMaximumIteration | ( | ) | [virtual] |
Set/Get the termination threshold for the squared sum of changes in centroid postions after one iteration
| virtual MeasurementVectorSizeType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetMeasurementVectorSize | ( | ) | const [virtual] |
Get the length of measurement vectors in the KdTree
| virtual const MeasurementVectorSizeType& itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetMeasurementVectorSize | ( | ) | [virtual] |
Get the length of measurement vectors in the KdTree
| const MetaDataDictionary& itk::Object::GetMetaDataDictionary | ( | void | ) | const [inherited] |
- Returns:
- A constant reference to this objects MetaDataDictionary.
| MetaDataDictionary& itk::Object::GetMetaDataDictionary | ( | void | ) | [inherited] |
- Returns:
- A reference to this objects MetaDataDictionary.
- Warning:
- This reference may be changed.
| virtual unsigned long itk::Object::GetMTime | ( | ) | const [virtual, inherited] |
Return this objects modified time.
Reimplemented in itk::ImageRegistrationMethod< TFixedImage, TMovingImage >, itk::ImageToSpatialObjectRegistrationMethod< TFixedImage, TMovingSpatialObject >, itk::MultiResolutionImageRegistrationMethod< TFixedImage, TMovingImage >, itk::PointSetToImageRegistrationMethod< TFixedPointSet, TMovingImage >, itk::PointSetToPointSetRegistrationMethod< TFixedPointSet, TMovingPointSet >, itk::DeformationFieldSource< TOutputImage >, itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::VectorResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::BoundingBox< TPointIdentifier, VPointDimension, TCoordRep, TPointsContainer >, itk::ImageAdaptor< TImage, TAccessor >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::TransformToDeformationFieldSource< TOutputImage, TTransformPrecisionType >, itk::ImageSpatialObject< TDimension, TPixelType >, itk::MeshSpatialObject< TMesh >, itk::SceneSpatialObject< TSpaceDimension >, itk::SpatialObject< TDimension >, itk::ImageAdaptor< TImage, Accessor::AsinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SqrtPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::TanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::CosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::VectorToRGBPixelAccessor< TImage::PixelType::ValueType > >, itk::ImageAdaptor< TImage, Accessor::RGBToVectorPixelAccessor< TImage::PixelType::ComponentType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToModulusPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AbsPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, PixelAccessor >, itk::ImageAdaptor< TImage, Accessor::LogPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToPhasePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< VectorImage< TPixelType, Dimension >, Accessor::VectorImageToImagePixelAccessor< TPixelType > >, itk::ImageAdaptor< TImage, Accessor::Log10PixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AtanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToRealPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToImaginaryPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpNegativePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AcosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::RGBToLuminancePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AddPixelAccessor< TImage::PixelType > >, itk::ImageSpatialObject< TDimension, unsigned char >, itk::SpatialObject< 3 >, and itk::SpatialObject< ::itk::GetMeshDimension< TMesh >::PointDimension >.
Referenced by itk::SpatialObject< ::itk::GetMeshDimension< TMesh >::PointDimension >::GetObjectMTime().
| virtual const char* itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetNameOfClass | ( | ) | const [virtual] |
Run-time type information (and related methods).
Reimplemented from itk::Object.
| virtual const char* itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetNameOfClass | ( | ) | const [virtual] |
Run-time type information (and related methods).
Reimplemented from itk::Object.
| const MembershipFunctionVectorObjectType* itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetOutput | ( | ) | const |
Output Membership function vector containing the membership functions with the final optimized paramters
| virtual ParametersType itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetParameters | ( | ) | const [virtual] |
Set/Get the termination threshold for the squared sum of changes in centroid postions after one iteration
| ParametersType& itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetParameters | ( | void | ) | [inline] |
Get current position of the optimization.
Definition at line 106 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetPoint | ( | ParameterType & | point, | |
| MeasurementVectorType | measurements | |||
| ) | [protected] |
imports the measurements measurement vector data to the point
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetPoint | ( | ParameterType & | point, | |
| MeasurementVectorType | measurements | |||
| ) | [inline, protected] |
imports the "measurements" measurement vector data to the "point"
Definition at line 279 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| virtual int itk::LightObject::GetReferenceCount | ( | ) | const [inline, virtual, inherited] |
Gets the reference count on this object.
Definition at line 106 of file itkLightObject.h.
| double itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetSumOfSquaredPositionChanges | ( | InternalParametersType & | previous, | |
| InternalParametersType & | current | |||
| ) | [protected] |
gets the sum of squared difference between the previous position and current postion of all centroid. This is the primary termination condition for this algorithm. If the return value is less than the value that was set by the SetCentroidPositionChangesThreshold method.
| double itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetSumOfSquaredPositionChanges | ( | InternalParametersType & | previous, | |
| InternalParametersType & | current | |||
| ) | [protected] |
gets the sum of squared difference between the previous position and current postion of all centroid. This is the primary termination condition for this algorithm. If the return value is less than the value that was set by the SetCentroidPositionChangesThreshold method.
| virtual bool itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::GetUseClusterLabels | ( | ) | const [virtual] |
| static void itk::Object::GlobalWarningDisplayOff | ( | ) | [inline, static, inherited] |
This is a global flag that controls whether any debug, warning or error messages are displayed.
Definition at line 100 of file itkObject.h.
References itk::Object::SetGlobalWarningDisplay().
| static void itk::Object::GlobalWarningDisplayOn | ( | ) | [inline, static, inherited] |
This is a global flag that controls whether any debug, warning or error messages are displayed.
Definition at line 98 of file itkObject.h.
References itk::Object::SetGlobalWarningDisplay().
| bool itk::Object::HasObserver | ( | const EventObject & | event | ) | const [inherited] |
Return true if an observer is registered for this event.
| void itk::Object::InvokeEvent | ( | const EventObject & | ) | const [inherited] |
Call Execute on all the Commands observing this event id. The actions triggered by this call doesn't modify this object.
| void itk::Object::InvokeEvent | ( | const EventObject & | ) | [inherited] |
Call Execute on all the Commands observing this event id.
| bool itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::IsFarther | ( | ParameterType & | pointA, | |
| ParameterType & | pointB, | |||
| MeasurementVectorType & | lowerBound, | |||
| MeasurementVectorType & | upperBound | |||
| ) | [protected] |
returns true if the pointA is farther than pointB to the boundary
| bool itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::IsFarther | ( | ParameterType & | pointA, | |
| ParameterType & | pointB, | |||
| MeasurementVectorType & | lowerBound, | |||
| MeasurementVectorType & | upperBound | |||
| ) | [protected] |
returns true if the pointA is farther than pointB to the boundary
| virtual void itk::Object::Modified | ( | ) | const [virtual, inherited] |
Update the modification time for this object. Many filters rely on the modification time to determine if they need to recompute their data.
Reimplemented in itk::NormalizeImageFilter< TInputImage, TOutputImage >, itk::ImageAdaptor< TImage, TAccessor >, itk::MiniPipelineSeparableImageFilter< TInputImage, TOutputImage, TFilter >, itk::GrayscaleDilateImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleErodeImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleMorphologicalClosingImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleMorphologicalOpeningImageFilter< TInputImage, TOutputImage, TKernel >, itk::MorphologicalGradientImageFilter< TInputImage, TOutputImage, TKernel >, itk::ImageAdaptor< TImage, Accessor::AsinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SqrtPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::TanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::CosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::VectorToRGBPixelAccessor< TImage::PixelType::ValueType > >, itk::ImageAdaptor< TImage, Accessor::RGBToVectorPixelAccessor< TImage::PixelType::ComponentType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToModulusPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AbsPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, PixelAccessor >, itk::ImageAdaptor< TImage, Accessor::LogPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToPhasePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< VectorImage< TPixelType, Dimension >, Accessor::VectorImageToImagePixelAccessor< TPixelType > >, itk::ImageAdaptor< TImage, Accessor::Log10PixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AtanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToRealPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToImaginaryPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpNegativePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AcosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::RGBToLuminancePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AddPixelAccessor< TImage::PixelType > >, and itk::MiniPipelineSeparableImageFilter< TInputImage, TOutputImage, RankImageFilter< TInputImage, TInputImage, FlatStructuringElement< ::itk::GetImageDimension< TInputImage >::ImageDimension > > >.
Referenced by itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::InsertNarrowBandNode(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetCenter(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetMatrix(), itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBand(), itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBandInnerRadius(), itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBandTotalRadius(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetOffset(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetRealThresholds(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetThresholds(), itk::Statistics::GoodnessOfFitFunctionBase< TInputHistogram >::SetTotalObservedScale(), and itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetTranslation().
| static Pointer itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::New | ( | ) | [static] |
Method for creation through the object factory.
Reimplemented from itk::Object.
| static Pointer itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::New | ( | ) | [static] |
Method for creation through the object factory.
Reimplemented from itk::Object.
| void itk::LightObject::Print | ( | std::ostream & | os, | |
| Indent | indent = 0 | |||
| ) | const [inherited] |
Cause the object to print itself out.
Referenced by itk::WeakPointer< ProcessObject >::Print().
| virtual void itk::LightObject::PrintHeader | ( | std::ostream & | os, | |
| Indent | indent | |||
| ) | const [protected, virtual, inherited] |
Define the type of the reference count according to the target. This allows the use of atomic operations
| bool itk::Object::PrintObservers | ( | std::ostream & | os, | |
| Indent | indent | |||
| ) | const [protected, inherited] |
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::PrintPoint | ( | ParameterType & | point | ) | [protected] |
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::PrintPoint | ( | ParameterType & | point | ) | [inline, protected] |
Definition at line 288 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::PrintSelf | ( | std::ostream & | os, | |
| Indent | indent | |||
| ) | const [protected, virtual] |
Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.
Reimplemented from itk::Object.
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::PrintSelf | ( | std::ostream & | os, | |
| Indent | indent | |||
| ) | const [protected, virtual] |
Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.
Reimplemented from itk::Object.
| virtual void itk::LightObject::PrintTrailer | ( | std::ostream & | os, | |
| Indent | indent | |||
| ) | const [protected, virtual, inherited] |
Define the type of the reference count according to the target. This allows the use of atomic operations
| virtual void itk::Object::Register | ( | ) | const [virtual, inherited] |
Increase the reference count (mark as used by another object).
Reimplemented from itk::LightObject.
| void itk::Object::RemoveAllObservers | ( | ) | [inherited] |
Remove all observers .
| void itk::Object::RemoveObserver | ( | unsigned long | tag | ) | [inherited] |
Remove the observer with this tag value.
| virtual void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::SetCentroidPositionChangesThreshold | ( | double | _arg | ) | [virtual] |
Set/Get the termination threshold for the squared sum of changes in centroid postions after one iteration
| virtual void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::SetCentroidPositionChangesThreshold | ( | double | _arg | ) | [virtual] |
Set/Get the termination threshold for the squared sum of changes in centroid postions after one iteration
| void itk::Object::SetDebug | ( | bool | debugFlag | ) | const [inherited] |
Set the value of the debug flag. A non-zero value turns debugging on.
| static void itk::Object::SetGlobalWarningDisplay | ( | bool | flag | ) | [static, inherited] |
This is a global flag that controls whether any debug, warning or error messages are displayed.
Referenced by itk::Object::GlobalWarningDisplayOff(), and itk::Object::GlobalWarningDisplayOn().
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::SetKdTree | ( | TKdTree * | tree | ) |
Set/Get the pointer to the KdTree
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::SetKdTree | ( | TKdTree * | tree | ) | [inline] |
Set/Get the pointer to the KdTree
Definition at line 121 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
References itk::Statistics::MeasurementVectorTraits::SetLength().
| virtual void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::SetMaximumIteration | ( | int | _arg | ) | [virtual] |
Set/Get maximum iteration limit.
| virtual void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::SetMaximumIteration | ( | int | _arg | ) | [virtual] |
Set/Get maximum iteration limit.
| void itk::Object::SetMetaDataDictionary | ( | const MetaDataDictionary & | rhs | ) | [inherited] |
- Returns:
- Set the MetaDataDictionary
| virtual void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::SetParameters | ( | ParametersType | _arg | ) | [virtual] |
Set the position to initialize the optimization.
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::SetParameters | ( | ParametersType & | params | ) | [inline] |
Set the position to initialize the optimization.
Definition at line 102 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| virtual void itk::Object::SetReferenceCount | ( | int | ) | [virtual, inherited] |
Sets the reference count (use with care)
Reimplemented from itk::LightObject.
| virtual void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::SetUseClusterLabels | ( | bool | _arg | ) | [virtual] |
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::SetUseClusterLabels | ( | bool | flag | ) | [inline] |
Definition at line 147 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::StartOptimization | ( | ) |
Start optimization Optimization will stop when it meets either of two termination conditions, the maximum iteration limit or epsilon (minimal changes in squared sum of changes in centroid positions)
| void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::StartOptimization | ( | ) |
Start optimization Optimization will stop when it meets either of two termination conditions, the maximum iteration limit or epsilon (minimal changes in squared sum of changes in centroid positions)
| virtual void itk::Object::UnRegister | ( | ) | const [virtual, inherited] |
Decrease the reference count (release by another object).
Reimplemented from itk::LightObject.
Member Data Documentation
InternalReferenceCountType itk::LightObject::m_ReferenceCount [mutable, protected, inherited] |
Number of uses of this object by other objects.
Definition at line 144 of file itkLightObject.h.
SimpleFastMutexLock itk::LightObject::m_ReferenceCountLock [mutable, protected, inherited] |
Mutex lock to protect modification to the reference count
Definition at line 147 of file itkLightObject.h.
The documentation for this class was generated from the following files:
