ITK
6.0.0
Insight Toolkit
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#include <itkCovarianceSampleFilter.h>
Calculates the covariance matrix of the target sample data.
The filter calculates first the sample mean and use it in the covariance calculation. The covariance is computed as follows Let \(\Sigma\) denotes covariance matrix for the sample, then: When \(x_{i}\) is \(i\)th component of a measurement vector \(\vec x\), \(\mu_{i}\) is the \(i\)th component of the \(\vec\mu\), and the \(\sigma_{ij}\) is the \(ij\)th component \(\Sigma\), \(\sigma_{ij} = (x_{i} - \mu_{i})(x_{j} - \mu_{j})\)
This estimator is an unbiased one, because it divisor in the covariance computation takes into account that one degree of freedom has been taken for computing the mean.
Without the plugged in mean vector, this calculator will perform the single pass mean and covariance calculation algorithm.
Definition at line 53 of file itkCovarianceSampleFilter.h.
Additional Inherited Members | |
Static Public Member Functions inherited from itk::Object | |
static bool | GetGlobalWarningDisplay () |
static void | GlobalWarningDisplayOff () |
static void | GlobalWarningDisplayOn () |
static Pointer | New () |
static void | SetGlobalWarningDisplay (bool val) |
Static Public Member Functions inherited from itk::LightObject | |
static void | BreakOnError () |
static Pointer | New () |
Static Protected Member Functions inherited from itk::ProcessObject | |
template<typename TSourceObject > | |
static void | MakeRequiredOutputs (TSourceObject &sourceObject, const DataObjectPointerArraySizeType numberOfRequiredOutputs) |
static constexpr float | progressFixedToFloat (uint32_t fixed) |
static uint32_t | progressFloatToFixed (float f) |
Protected Attributes inherited from itk::ProcessObject | |
TimeStamp | m_OutputInformationMTime {} |
bool | m_Updating {} |
Protected Attributes inherited from itk::LightObject | |
std::atomic< int > | m_ReferenceCount {} |
using itk::Statistics::CovarianceSampleFilter< TSample >::ConstPointer = SmartPointer<const Self> |
Definition at line 62 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::DataObjectPointer = DataObject::Pointer |
DataObject pointer
Definition at line 126 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::DataObjectPointerArraySizeType = ProcessObject::DataObjectPointerArraySizeType |
Definition at line 128 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::MatrixDecoratedType = SimpleDataObjectDecorator<MatrixType> |
VariableSizeMatrix is not a DataObject, we need to decorate it to push it down a ProcessObject's pipeline
Definition at line 105 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::MatrixType = VariableSizeMatrix<MeasurementRealType> |
Type of covariance matrix output
Definition at line 97 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::MeasurementRealType = typename NumericTraits<MeasurementType>::RealType |
Type of a floating point measurement component value
Definition at line 83 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::MeasurementType = typename SampleType::MeasurementType |
Type of measurement vector component value
Definition at line 77 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::MeasurementVectorDecoratedType = SimpleDataObjectDecorator<MeasurementVectorRealType> |
MeasurementVector is not a DataObject, we need to decorate it to push it down a ProcessObject's pipeline
Definition at line 116 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::MeasurementVectorRealType = typename NumericTraits<MeasurementVectorType>::RealType |
Type of a measurement vector, holding floating point values
Definition at line 80 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::MeasurementVectorSizeType = typename SampleType::MeasurementVectorSizeType |
Type of the length of each measurement vector
Definition at line 74 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::MeasurementVectorType = typename SampleType::MeasurementVectorType |
Type of each measurement vector in sample
Definition at line 71 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::OutputType = MeasurementVectorDecoratedType |
Definition at line 119 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::Pointer = SmartPointer<Self> |
Definition at line 61 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::SampleType = TSample |
Definition at line 63 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::Self = CovarianceSampleFilter |
Standard class type aliases.
Definition at line 59 of file itkCovarianceSampleFilter.h.
using itk::Statistics::CovarianceSampleFilter< TSample >::Superclass = ProcessObject |
Definition at line 60 of file itkCovarianceSampleFilter.h.
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protected |
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overrideprotecteddefault |
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overrideprotectedvirtual |
This method causes the filter to generate its output.
Reimplemented from itk::ProcessObject.
Reimplemented in itk::Statistics::WeightedCovarianceSampleFilter< TSample >.
const MatrixType itk::Statistics::CovarianceSampleFilter< TSample >::GetCovarianceMatrix | ( | ) | const |
Return the covariance matrix
const MatrixDecoratedType * itk::Statistics::CovarianceSampleFilter< TSample >::GetCovarianceMatrixOutput | ( | ) | const |
const SampleType * itk::Statistics::CovarianceSampleFilter< TSample >::GetInput | ( | ) | const |
Method to get the sample
const MeasurementVectorRealType itk::Statistics::CovarianceSampleFilter< TSample >::GetMean | ( | ) | const |
Return the mean vector
const MeasurementVectorDecoratedType * itk::Statistics::CovarianceSampleFilter< TSample >::GetMeanOutput | ( | ) | const |
MeasurementVectorSizeType itk::Statistics::CovarianceSampleFilter< TSample >::GetMeasurementVectorSize | ( | ) | const |
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overridevirtual |
Reimplemented from itk::ProcessObject.
Reimplemented in itk::Statistics::WeightedCovarianceSampleFilter< TSample >.
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overridevirtual |
Make a DataObject of the correct type to used as the specified output.
Every ProcessObject subclass must be able to create a DataObject that can be used as a specified output. This method is automatically called when DataObject::DisconnectPipeline() is called. DataObject::DisconnectPipeline, disconnects a data object from being an output of its current source. When the data object is disconnected, the ProcessObject needs to construct a replacement output data object so that the ProcessObject is in a valid state. So DataObject::DisconnectPipeline eventually calls ProcessObject::MakeOutput. Note that MakeOutput always returns a itkSmartPointer to a DataObject. ImageSource and MeshSource override this method to create the correct type of image and mesh respectively. If a filter has multiple outputs of different types, then that filter must provide an implementation of MakeOutput().
Reimplemented from itk::ProcessObject.
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static |
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overrideprotectedvirtual |
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::ProcessObject.
void itk::Statistics::CovarianceSampleFilter< TSample >::SetInput | ( | const SampleType * | sample | ) |