Uses of Class
de.unihalle.informatik.MiToBo.tracking.multitarget.datatypes.abstracts.AbstractMultiState

Packages that use AbstractMultiState
de.unihalle.informatik.MiToBo.tracking.multitarget.algo   
de.unihalle.informatik.MiToBo.tracking.multitarget.datatypes.abstracts   
de.unihalle.informatik.MiToBo.tracking.multitarget.datatypes.impl   
de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.abstracts   
de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.impl   
 

Uses of AbstractMultiState in de.unihalle.informatik.MiToBo.tracking.multitarget.algo
 

Fields in de.unihalle.informatik.MiToBo.tracking.multitarget.algo declared as AbstractMultiState
protected  AbstractMultiState<MotionModelID> MultiTargetIMMFilter.meanX
           
 

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.algo that return AbstractMultiState
 AbstractMultiState<T> MultiTargetRBMCDA.getMean()
           
 AbstractMultiState<MotionModelID> MultiTargetIMMFilter.getMean()
           
 

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.algo that return types with arguments of type AbstractMultiState
 MultiTargetPredictionFilter<AbstractMultiState<T>> MultiTargetRBMCDA.copy()
          Not implemented, always returns null
 

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.algo with parameters of type AbstractMultiState
 void MultiTargetIMMFilter.update(AbstractMultiState<MotionModelID> observation, DataAssociation association)
           
 void MultiTargetRBMCDA.update(AbstractMultiState<T> observation, DataAssociation association)
          The DataAssociation object may be null and is interpreted as groundtruth if given.
 

Uses of AbstractMultiState in de.unihalle.informatik.MiToBo.tracking.multitarget.datatypes.abstracts
 

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.datatypes.abstracts that return AbstractMultiState
abstract  AbstractMultiState<T> AbstractMultiState.copy()
          Copy this multi-state
abstract  AbstractMultiState<T> AbstractMultiStateFactory.createEmptyMultiState()
          Create an empty multi state object
abstract  AbstractMultiState<T> AbstractMultiStateFactory.createMultiState(double[][] continuousStateVariables, T[] discreteStateVariables)
          Create a multi state object initialized by the specified data
abstract  AbstractMultiState<T> AbstractMultiStateFactory.createMultiState(Jama.Matrix[] continuousStateVariables, T[] discreteStateVariables)
          Create a multi state object initialized by the specified data
 

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.datatypes.abstracts with parameters of type AbstractMultiState
 boolean AbstractMultiStateFactory.validMultiState(AbstractMultiState<T> multistate)
          Test if the specified multistate is valid for this factory.
 

Uses of AbstractMultiState in de.unihalle.informatik.MiToBo.tracking.multitarget.datatypes.impl
 

Subclasses of AbstractMultiState in de.unihalle.informatik.MiToBo.tracking.multitarget.datatypes.impl
 class MultiState<T extends Copyable<?>>
          Multi-target state implementation.
 

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.datatypes.impl that return AbstractMultiState
 AbstractMultiState<T> MultiStateFactory.createEmptyMultiState()
           
 AbstractMultiState<T> MultiStateFactory.createMultiState(double[][] continuousStateVariables, T[] discreteStateVariables)
           
 AbstractMultiState<T> MultiStateFactory.createMultiState(Jama.Matrix[] continuousStateVariables, T[] discreteStateVariables)
           
 AbstractMultiState<T> RBMCDASampleInfo.getObservations(int t)
          Get the observations of time t.
 

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.datatypes.impl with parameters of type AbstractMultiState
 int RBMCDASampleInfo.addCurrentInfo(double logP_C, DataAssociation C, AbstractMultiState<T> observations, Set<Short> existingTargetIDs)
          Add sample info of the current time step
 

Uses of AbstractMultiState in de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.abstracts
 

Fields in de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.abstracts declared as AbstractMultiState
protected  AbstractMultiState<T> AbstractMultiStateTransitionDistribution.condX
          multi state condition on the density
protected  AbstractMultiState<T> AbstractMultiObservationDistribution.condX
          multi state condition on the density
protected  AbstractMultiState<S> AbstractAssociationDistribution.Z
          observations
 

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.abstracts that return AbstractMultiState
abstract  AbstractMultiState<T> AbstractMultiStateTransitionDistributionIndep.drawSample()
           
abstract  AbstractMultiState<T> AbstractMultiStateTransitionDistribution.drawSample()
           
abstract  AbstractMultiState<T> AbstractMultiStateTransitionDistributionIndep.drawSample(int i, AbstractMultiState<T> X)
           
 AbstractMultiState<T> AbstractMultiStateTransitionDistribution.getCondition()
           
 AbstractMultiState<T> AbstractMultiObservationDistribution.getCondition()
           
 

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.abstracts with parameters of type AbstractMultiState
abstract  AbstractMultiState<T> AbstractMultiStateTransitionDistributionIndep.drawSample(int i, AbstractMultiState<T> X)
           
abstract  double AbstractMultiObservationDistributionIndep.log_p(AbstractMultiState<S> Z)
           
abstract  double AbstractMultiObservationDistribution.log_p(AbstractMultiState<S> Z)
           
abstract  double AbstractMultiObservationDistributionIndep.log_p(AbstractMultiState<S> Z, int i)
          Evaluate the density independently for observation i in Z conditional on state i in X
abstract  double AbstractMultiObservationDistributionIndep.log_p(AbstractMultiState<S> Z, int i, int j)
          Evaluate the density independently for observation i in Z conditional on state j in X
abstract  double AbstractMultiObservationDistributionIndep.p(AbstractMultiState<S> Z)
           
abstract  double AbstractMultiObservationDistribution.p(AbstractMultiState<S> Z)
           
abstract  double AbstractMultiObservationDistributionIndep.p(AbstractMultiState<S> Z, int i)
          Evaluate the density independently for observation i in Z conditional on state i in X
abstract  double AbstractMultiObservationDistributionIndep.p(AbstractMultiState<S> Z, int i, int j)
          Evaluate the density independently for observation i in Z conditional on state j in X
 void AbstractMultiStateTransitionDistribution.setCondition(AbstractMultiState<T> X)
           
 void AbstractMultiObservationDistribution.setCondition(AbstractMultiState<T> X)
           
 void AbstractAssociationDistribution.setNewObservations(AbstractMultiState<S> Z, AbstractMultiObservationDistributionIndep<S,T> observationDistrib)
           
 

Constructors in de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.abstracts with parameters of type AbstractMultiState
AbstractAssociationDistribution(Random rand, AbstractMultiState<S> Z, AbstractMultiObservationDistributionIndep<S,T> observationDistrib, LogProbabilityDensityFunction spatialClutterDistrib, LogProbabilityDensityFunction spatialNewbornDistrib, DataAssociationFactory assocFactory)
          Constructor
AbstractMultiObservationDistribution(AbstractMultiState<T> conditionX, AbstractMultiStateFactory<T> factoryX, AbstractMultiStateFactory<S> factoryZ)
          Constructor to set the condition conditionX, and the factories of multi state and multi observation variables
AbstractMultiObservationDistributionIndep(AbstractMultiState<T> conditionX, AbstractMultiStateFactory<T> factoryX, AbstractMultiStateFactory<S> factoryZ)
          Constructor to set the condition conditionX, and the factories of multi state and multi observation variables
AbstractMultiStateTransitionDistribution(AbstractMultiState<T> X, AbstractMultiStateFactory<T> factoryX)
          Constructor to set the condition X, and the factories of multi state and multi observation variables
AbstractMultiStateTransitionDistributionIndep(AbstractMultiState<T> X, AbstractMultiStateFactory<T> factoryX)
           
 

Uses of AbstractMultiState in de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.impl
 

Fields in de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.impl declared as AbstractMultiState
protected  AbstractMultiState<T> MultiStateDistributionIndepGaussians.mean
           
 

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.impl that return AbstractMultiState
 AbstractMultiState<T> MultiStateLinTransDistributionIndepGaussians.drawSample()
           
 AbstractMultiState<T> MultiStateDistributionIndepGaussians.drawSample()
           
 AbstractMultiState<T> MultiObsDistributionIndepGaussians.drawSample()
           
 AbstractMultiState<T> MultiObsDistributionIndepGaussMix.drawSample()
           
 AbstractMultiState<T> MultiStateLinTransDistributionIndepGaussians.drawSample(int i, AbstractMultiState<T> X)
           
 AbstractMultiState<T> MultiStateDistributionIndepGaussians.drawSample(int i, AbstractMultiState<T> X)
           
 AbstractMultiState<T> MultiStateLinTransDistributionIndepGaussians.getMean()
           
 AbstractMultiState<T> MultiStateDistributionIndepGaussians.getMean()
           
 AbstractMultiState<T> MultiObsDistributionIndepGaussians.getMean()
           
 AbstractMultiState<T> MultiObsDistributionIndepGaussMix.getMean()
           
 

Methods in de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.impl with parameters of type AbstractMultiState
 AbstractMultiState<T> MultiStateLinTransDistributionIndepGaussians.drawSample(int i, AbstractMultiState<T> X)
           
 AbstractMultiState<T> MultiStateDistributionIndepGaussians.drawSample(int i, AbstractMultiState<T> X)
           
 double MultiObsDistributionIndepGaussians.log_p(AbstractMultiState<T> Z)
           
 double MultiObsDistributionIndepGaussMix.log_p(AbstractMultiState<T> Z)
           
 double MultiObsDistributionIndepGaussians.log_p(AbstractMultiState<T> Z, int i)
           
 double MultiObsDistributionIndepGaussMix.log_p(AbstractMultiState<T> Z, int i)
           
 double MultiObsDistributionIndepGaussians.log_p(AbstractMultiState<T> Z, int i, int j)
           
 double MultiObsDistributionIndepGaussMix.log_p(AbstractMultiState<T> Z, int i, int j)
           
 double MultiObsDistributionIndepGaussians.logp(AbstractMultiState<T> Z)
           
 double MultiStateLinTransDistributionIndepGaussians.p(AbstractMultiState<T> X)
           
 double MultiStateDistributionIndepGaussians.p(AbstractMultiState<T> X)
           
 double MultiObsDistributionIndepGaussians.p(AbstractMultiState<T> Z)
           
 double MultiObsDistributionIndepGaussMix.p(AbstractMultiState<T> Z)
           
 double MultiStateLinTransDistributionIndepGaussians.p(AbstractMultiState<T> X, int i)
           
 double MultiStateDistributionIndepGaussians.p(AbstractMultiState<T> X, int i)
           
 double MultiObsDistributionIndepGaussians.p(AbstractMultiState<T> Z, int i)
           
 double MultiObsDistributionIndepGaussMix.p(AbstractMultiState<T> Z, int i)
           
 double MultiObsDistributionIndepGaussians.p(AbstractMultiState<T> Z, int i, int j)
           
 double MultiObsDistributionIndepGaussMix.p(AbstractMultiState<T> Z, int i, int j)
           
 void MultiStateLinTransDistributionIndepGaussians.setCondition(AbstractMultiState<T> X)
           
 void MultiObsDistributionIndepGaussians.setCondition(AbstractMultiState<T> X)
           
 void AssociationDistributionNN.setNewObservations(AbstractMultiState<S> Z, AbstractMultiObservationDistributionIndep<S,T> observationDistrib)
           
 void AssociationDistribution.setNewObservations(AbstractMultiState<S> Z, AbstractMultiObservationDistributionIndep<S,T> observationDistrib)
           
 void MultiStateDistributionIndepGaussians.update(LinearTransformGaussNoise projector, AbstractMultiState<T> observations)
           
 void MultiStateDistributionIndepGaussians.updateIndep(int i, int j, LinearTransformGaussNoise projector, AbstractMultiState<T> observations)
          Update i-th Gaussian component with j-th observation
 void MultiStateDistributionIndepGaussians.updateIndep(int i, LinearTransformGaussNoise projector, AbstractMultiState<T> observations)
           
 

Constructors in de.unihalle.informatik.MiToBo.tracking.multitarget.distributions.impl with parameters of type AbstractMultiState
AssociationDistribution(Random rand, AbstractMultiState<S> Z, AbstractMultiObservationDistributionIndep<S,T> observationDistrib, LogProbabilityDensityFunction spatialClutterDistrib, LogProbabilityDensityFunction spatialNewbornDistrib, LogProbabilityMassFunction mu, LogProbabilityMassFunction nu, double P_D)
          Constructor.
AssociationDistribution(Random rand, AbstractMultiState<S> Z, AbstractMultiObservationDistributionIndep<S,T> observationDistrib, LogProbabilityDensityFunction spatialClutterDistrib, LogProbabilityDensityFunction spatialNewbornDistrib, LogProbabilityMassFunction mu, LogProbabilityMassFunction nu, double P_D, int M_max)
          Constructor where the maximum number of observations in the time series is specified to avoid some re-computations.
AssociationDistributionNN(Random rand, AbstractMultiState<S> Z, AbstractMultiObservationDistributionIndep<S,T> observationDistrib, LogProbabilityDensityFunction spatialClutterDistrib, LogProbabilityDensityFunction spatialNewbornDistrib, LogProbabilityMassFunction mu, LogProbabilityMassFunction nu, double P_D, int maxNumNeighbors, double maxDistNeighbors)
          Constructor.
AssociationDistributionNN(Random rand, AbstractMultiState<S> Z, AbstractMultiObservationDistributionIndep<S,T> observationDistrib, LogProbabilityDensityFunction spatialClutterDistrib, LogProbabilityDensityFunction spatialNewbornDistrib, LogProbabilityMassFunction mu, LogProbabilityMassFunction nu, double P_D, int M_max, int maxNumNeighbors, double maxDistNeighbors)
          Constructor where the maximum number of observations in the time series is specified to avoid some re-computations.
MultiObsDistributionIndepGaussians(Random rand, Jama.Matrix[] H, Jama.Matrix[] R, AbstractMultiState<T> X, AbstractMultiStateFactory<T> factoryX, AbstractMultiStateFactory<T> factoryZ)
           
MultiObsDistributionIndepGaussians(Random rand, Jama.Matrix H, Jama.Matrix R, AbstractMultiState<T> X, AbstractMultiStateFactory<T> factoryX, AbstractMultiStateFactory<T> factoryZ)
           
MultiObsDistributionIndepGaussMix(Random rand, Jama.Matrix H, Vector<GaussMixDistribution> obsDistGaussMixtures, AbstractMultiState<T> X, AbstractMultiStateFactory<T> factoryX, AbstractMultiStateFactory<T> factoryZ)
           
MultiStateDistributionIndepGaussians(AbstractMultiState<T> mean, Jama.Matrix covariance, Random rand)
          Constructor with identical covariance matrices for all states
MultiStateDistributionIndepGaussians(AbstractMultiState<T> mean, Vector<Jama.Matrix> covariance, Random rand)
          Constructor with different covariance matrix for each state
MultiStateLinTransDistributionIndepGaussians(Random rand, Jama.Matrix[] F, Jama.Matrix[] Q, AbstractMultiState<T> X, AbstractMultiStateFactory<T> factoryX)
           
MultiStateLinTransDistributionIndepGaussians(Random rand, Jama.Matrix F, Jama.Matrix Q, AbstractMultiState<T> X, AbstractMultiStateFactory<T> factoryX)
           
 



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