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/*=========================================================================
*
* Copyright NumFOCUS
*
* 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
*
* https://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 itkUniformRandomSpatialNeighborSubsampler_h
#define itkUniformRandomSpatialNeighborSubsampler_h
#include "itkSpatialNeighborSubsampler.h"
#include "itkMersenneTwisterRandomVariateGenerator.h"
namespace itk
{
namespace Statistics
{
/**
* \class UniformRandomSpatialNeighborSubsampler
* \brief A subsampler that uniformly randomly selects points
* within the specified radius of the query point.
*
* This class derives from SpatialNeighborSubsampler and
* randomly selects points according to a uniform distribution
* within the Radius given by SetRadius(radius)
* as long as that point is also within the RegionConstraint.
*
* This class assumes that the instance identifiers in the input
* sample correspond to the result of ComputeOffset() of the index
* of the corresponding point in the image region.
*
* \sa SubsamplerBase, RegionConstrainedSubsampler
* \sa SpatialNeighborSubsampler
* \sa GaussianRandomSpatialNeighborSubsampler
* \ingroup ITKStatistics
*/
template <typename TSample, typename TRegion>
class ITK_TEMPLATE_EXPORT UniformRandomSpatialNeighborSubsampler : public SpatialNeighborSubsampler<TSample, TRegion>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(UniformRandomSpatialNeighborSubsampler);
/** Standard class type aliases */
using Self = UniformRandomSpatialNeighborSubsampler<TSample, TRegion>;
using Superclass = SpatialNeighborSubsampler<TSample, TRegion>;
using Baseclass = typename Superclass::Baseclass;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(UniformRandomSpatialNeighborSubsampler);
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** type alias alias for the source data container */
using typename Superclass::SampleType;
using typename Superclass::SampleConstPointer;
using typename Superclass::MeasurementVectorType;
using typename Superclass::InstanceIdentifier;
using typename Superclass::SubsampleType;
using typename Superclass::SubsamplePointer;
using typename Superclass::SubsampleConstIterator;
using typename Superclass::InstanceIdentifierHolder;
using SeedType = typename Baseclass::SeedType;
using SearchSizeType = unsigned long;
using RandomIntType = unsigned int;
/** type alias related to image region */
using typename Superclass::RadiusType;
using typename Superclass::RegionType;
using typename Superclass::IndexType;
using typename Superclass::IndexValueType;
using typename Superclass::SizeType;
using typename Superclass::ImageHelperType;
/** type alias related to random variate generator */
using RandomGeneratorType = Statistics::MersenneTwisterRandomVariateGenerator;
void
SetSeed(const SeedType seed) override
{
Superclass::SetSeed(seed);
this->m_RandomNumberGenerator->SetSeed(this->m_Seed);
}
virtual void
SetUseClockForSeed(const bool & useClock)
{
if (useClock != this->m_UseClockForSeed)
{
this->m_UseClockForSeed = useClock;
if (this->m_UseClockForSeed)
{
this->m_RandomNumberGenerator->SetSeed();
}
this->Modified();
}
}
itkBooleanMacro(UseClockForSeed);
itkGetConstMacro(UseClockForSeed, bool);
virtual void
SetNumberOfResultsRequested(const SearchSizeType & numberRequested)
{
itkDebugMacro("setting NumberOfResultsRequested to " << numberRequested);
if (this->m_RequestMaximumNumberOfResults || this->m_NumberOfResultsRequested != numberRequested)
{
this->m_NumberOfResultsRequested = numberRequested;
this->m_RequestMaximumNumberOfResults = false;
this->Modified();
}
}
itkGetConstMacro(NumberOfResultsRequested, SearchSizeType);
/** Main Search method that MUST be implemented by each subclass
* The Search method will find all points similar to query and return
* them as a Subsample. The definition of similar will be subclass-
* specific. And could mean spatial similarity or feature similarity
* etc. */
void
Search(const InstanceIdentifier & query, SubsamplePointer & results) override;
protected:
/**
* Clone the current subsampler.
* This does a complete copy of the subsampler state
* to the new subsampler
*/
typename LightObject::Pointer
InternalClone() const override;
UniformRandomSpatialNeighborSubsampler();
~UniformRandomSpatialNeighborSubsampler() override = default;
void
PrintSelf(std::ostream & os, Indent indent) const override;
/** method to randomly generate an integer in the closed range
* [lowerBound, upperBound]
* using a uniform sampling selection method.
* override this method to do gaussian selection */
virtual RandomIntType
GetIntegerVariate(RandomIntType lowerBound, RandomIntType upperBound, RandomIntType itkNotUsed(mean));
SearchSizeType m_NumberOfResultsRequested{};
RandomGeneratorType::Pointer m_RandomNumberGenerator{};
bool m_UseClockForSeed{};
}; // end of class UniformRandomSpatialNeighborSubsampler
} // end of namespace Statistics
} // end of namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
# include "itkUniformRandomSpatialNeighborSubsampler.hxx"
#endif
#endif
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