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*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkExpectationMaximizationMixtureModelEstimator_h
#define itkExpectationMaximizationMixtureModelEstimator_h
#include "itkMixtureModelComponentBase.h"
#include "itkGaussianMembershipFunction.h"
#include "itkSimpleDataObjectDecorator.h"
namespace itk
{
namespace Statistics
{
/** \class ExpectationMaximizationMixtureModelEstimator
* \brief This class generates the parameter estimates for a mixture
* model using expectation maximization strategy.
*
* The first template argument is the type of the target sample
* data. This estimator expects one or more mixture model component
* objects of the classes derived from the
* MixtureModelComponentBase. The actual component (or module)
* parameters are updated by each component. Users can think this
* class as a strategy or a integration point for the EM
* procedure. The initial proportion (SetInitialProportions), the
* input sample (SetSample), the mixture model components
* (AddComponent), and the maximum iteration (SetMaximumIteration) are
* required. The EM procedure terminates when the current iteration
* reaches the maximum iteration or the model parameters converge.
*
* <b>Recent API changes:</b>
* The static const macro to get the length of a measurement vector,
* \c MeasurementVectorSize has been removed to allow the length of a measurement
* vector to be specified at run time. It is now obtained at run time from the
* sample set as input. Please use the function
* GetMeasurementVectorSize() to get the length.
*
* \sa MixtureModelComponentBase, GaussianMixtureModelComponent
* \ingroup ITKStatistics
*
* \wiki
* \wikiexample{Statistics/ExpectationMaximizationMixtureModelEstimator_2D,2D Gaussian Mixture Model Expectation Maximization}
* \endwiki
*/
template< typename TSample >
class ExpectationMaximizationMixtureModelEstimator:public Object
{
public:
/** Standard class typedef */
typedef ExpectationMaximizationMixtureModelEstimator Self;
typedef Object Superclass;
typedef SmartPointer< Self > Pointer;
typedef SmartPointer< const Self > ConstPointer;
/** Standard macros */
itkTypeMacro(ExpectationMaximizationMixtureModelEstimator,
Object);
itkNewMacro(Self);
/** TSample template argument related typedefs */
typedef TSample SampleType;
typedef typename TSample::MeasurementType MeasurementType;
typedef typename TSample::MeasurementVectorType MeasurementVectorType;
/** Typedef requried to generate dataobject decorated output that can
* be plugged into SampleClassifierFilter */
typedef GaussianMembershipFunction< MeasurementVectorType >
GaussianMembershipFunctionType;
typedef typename GaussianMembershipFunctionType::Pointer
GaussianMembershipFunctionPointer;
typedef MembershipFunctionBase< MeasurementVectorType > MembershipFunctionType;
typedef typename MembershipFunctionType::ConstPointer MembershipFunctionPointer;
typedef std::vector< MembershipFunctionPointer > MembershipFunctionVectorType;
typedef SimpleDataObjectDecorator<
MembershipFunctionVectorType > MembershipFunctionVectorObjectType;
typedef typename
MembershipFunctionVectorObjectType::Pointer MembershipFunctionVectorObjectPointer;
/** Type of the mixture model component base class */
typedef MixtureModelComponentBase< TSample > ComponentType;
/** Type of the component pointer storage */
typedef std::vector< ComponentType * > ComponentVectorType;
/** Type of the membership function base class */
typedef MembershipFunctionBase< MeasurementVectorType >
ComponentMembershipFunctionType;
/** Type of the array of the proportion values */
typedef Array< double > ProportionVectorType;
/** Sets the target data that will be classified by this */
void SetSample(const TSample *sample);
/** Returns the target data */
const TSample * GetSample() const;
/** Set/Gets the initial proportion values. The size of proportion
* vector should be same as the number of component (or classes) */
void SetInitialProportions(ProportionVectorType & propotion);
const ProportionVectorType & GetInitialProportions() const;
/** Gets the result proportion values */
const ProportionVectorType & GetProportions() const;
/** typedef for decorated array of proportion */
typedef SimpleDataObjectDecorator<
ProportionVectorType > MembershipFunctionsWeightsArrayObjectType;
typedef typename
MembershipFunctionsWeightsArrayObjectType::Pointer MembershipFunctionsWeightsArrayPointer;
/** Get method for data decorated Membership functions weights array */
const MembershipFunctionsWeightsArrayObjectType * GetMembershipFunctionsWeightsArray() const;
/** Set/Gets the maximum number of iterations. When the optimization
* process reaches the maximum number of interations, even if the
* class parameters aren't converged, the optimization process
* stops. */
void SetMaximumIteration(int numberOfIterations);
int GetMaximumIteration() const;
/** Gets the current iteration. */
int GetCurrentIteration()
{
return m_CurrentIteration;
}
/** Adds a new component (or class). */
int AddComponent(ComponentType *component);
/** Gets the total number of classes currently plugged in. */
unsigned int GetNumberOfComponents() const;
/** Runs the optimization process. */
void Update();
/** Termination status after running optimization */
enum TERMINATION_CODE { CONVERGED = 0, NOT_CONVERGED = 1 };
/** Gets the termination status */
TERMINATION_CODE GetTerminationCode() const;
/** Gets the membership function specified by componentIndex
argument. */
ComponentMembershipFunctionType * GetComponentMembershipFunction(int componentIndex) const;
/** Output Membership function vector containing the membership functions with
* the final optimized parameters */
const MembershipFunctionVectorObjectType * GetOutput() const;
protected:
ExpectationMaximizationMixtureModelEstimator();
virtual ~ExpectationMaximizationMixtureModelEstimator() {}
virtual void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE;
bool CalculateDensities();
double CalculateExpectation() const;
bool UpdateComponentParameters();
bool UpdateProportions();
/** Starts the estimation process */
void GenerateData();
private:
/** Target data sample pointer*/
const TSample *m_Sample;
int m_MaxIteration;
int m_CurrentIteration;
TERMINATION_CODE m_TerminationCode;
ComponentVectorType m_ComponentVector;
ProportionVectorType m_InitialProportions;
ProportionVectorType m_Proportions;
MembershipFunctionVectorObjectPointer m_MembershipFunctionsObject;
MembershipFunctionsWeightsArrayPointer m_MembershipFunctionsWeightArrayObject;
}; // end of class
} // end of namespace Statistics
} // end of namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkExpectationMaximizationMixtureModelEstimator.hxx"
#endif
#endif
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