Uses of Class
uwcse.location.core.State

Packages that use State

uwcse.location.client
uwcse.location.core
uwcse.location.messaging
uwcse.location.objects
uwcse.location.objects.alien
uwcse.location.objects.cricket
uwcse.location.objects.mote
uwcse.location.objects.versus

Uses of State in uwcse.location.client

Constructors in uwcse.location.client with parameters of type State

MeasurementDisplay(Measurement measurement, State sensorState, String objectName, StateTransform worldToScreenTransform)
Create a new location report display.

Uses of State in uwcse.location.core

Fields in uwcse.location.core declared as State

protected State	TrueStateMeasurement.m_state
protected State[]	CentroidTracker.m_window
protected State[]	SmoothCentroidTracker.m_history
protected State	StaticTracker.m_state

Methods in uwcse.location.core that return State

State	State.transform(State s) Return a new State that is the given argument State transformed using the translation and rotation parameters of this state.
static State	State.computeMean(Collection states) Compute the mean State of the given collection of states.
static State	State.computeWeightedMean(Collection samples) Compute the weighted mean State of the given collection of samples.
static State	State.computeWeightedSD(State mean, Collection samples) Compute the weighted standard deviation State of the given collection of samples.
abstract State	LocationReport.getMostLikelyState() Get the most likely State of the object.
State	TrueStateMeasurement.getState() Get the truth state represented by this measurement.
State	StateLocationReport.getMostLikelyState() The most likely state of this report is just the state so this method simply returns the state.
State	StateLocationReport.getState() Get the state.
State	MeanLocationReport.getMostLikelyState() The mostlikely state of this report is just the mean state so this method simply returns the mean value.
State	MeanLocationReport.getMean() Get the mean location.
State	MeanLocationReport.getStandardDeviation() Get the standard deviation indicating the error in location.
State	Sample.getState() Access the State of this sample

Methods in uwcse.location.core with parameters of type State

void	State.set(State s) Set the this State using the given one.
State	State.transform(State s) Return a new State that is the given argument State transformed using the translation and rotation parameters of this state.
static double	State.distanceBetween(State s1, State s2) Returns the linear distance between the position of the State sm1 and that of the sm2 State.
static State	State.computeWeightedSD(State mean, Collection samples) Compute the weighted standard deviation State of the given collection of samples.
boolean	WorldMap.isConsistent(State s) Return true if the given State is consistent with this world map.
double	WorldMap.obstacleDistance(State s) Returns the maximum distance that can be traveled from the given State's position along its heading before leaving bounds of the world map or hitting an obstacle.
void	StateTransform.transform(State state) Transforms the State parameter with this transformation and place the result back into the State.
void	TrueStateMeasurement.setState(State state) Set the true state represented by this measurement.
abstract double	LocationSensor.likelihood(Measurement meas, LocationReport sensorLocation, State objectState) Determine the probabilistic likelihood [0...1] that this sensor generated this measurement about an object, given the State of this sensor and the State that object.
void	ParticleFilterTracker.initGaussianDistribution(State mean) Initialize the samples in this filter according to the given mean inside the bounding box and set all the weights to a uniform value (1/getNumberOfSamples()).
void	ParticleFilterTracker.initGaussianDistribution(State mean, Vector3d posSD, Vector3d rotSD) Initialize the samples in this filter according to the given mean and stdDev inside the bounding box and set all the weights to a uniform value (1/getNumberOfSamples()).
void	ParticleFilterTracker.initPartialGaussianDistribution(State mean, Vector3d posSD, Vector3d rotSD, double fractionOfUniformSamples) Initialize the samples in this filter according to the given mean and stdDev inside the WorldMap and set all the weights to a uniform value (1 / getNumberOfSamples()).
void	ParticleFilterTracker.initPartialGaussianDistribution(State mean, Vector3d posSD, Vector3d rotSD, double fractionOfUniformSamples, Point3d lowerCorner, Point3d upperCorner) Initialize the samples in this filter according to the given mean and stdDev inside specified min/max bounding box and set all the weights to a uniform value (1 / getNumberOfSamples()).
void	Sample.setState(State s) Set a new state for this sample.

Constructors in uwcse.location.core with parameters of type State

State(State s)
Constructs and initializes a State from the given State object.

StateTransform(State state)
Constructs and initializes a transform from the position and quaternion rotation in the given State.

TrueStateMeasurement(String objectName, String sensorName, State state)
Creates a map measurement.

StateLocationReport(State state)
Create a state location report using the state.

StateLocationReport(Tracker tracker, State state)
Create a state location report using the given tracker and state.

MeanLocationReport(State mean, State standardDeviation)
Create a mean location report using the given mean and standard deviation.

MeanLocationReport(Tracker tracker, State mean, State standardDeviation)
Create a mean location report using the given tracker, mean, and standard deviation.

ParticleLocationReport(State mean, State standardDeviation, Collection samples)
Create a particle location report using the given mean, standard deviation, and list of samples.

ParticleLocationReport(Tracker tracker, State mean, State standardDeviation, Collection samples)
Create a particle location report using the given tracker, mean, standard deviation, and list of samples.

Sample(State state)
Create a new sample with the given State and weight of 1.

Sample(State state, double weight)
Create a new sample with the given State and weight.

Uses of State in uwcse.location.messaging

Fields in uwcse.location.messaging declared as State

State

AddObjectWithStateRpc.state

Uses of State in uwcse.location.objects

Methods in uwcse.location.objects with parameters of type State

double	FixedSensorObject.likelihood(Measurement meas, LocationReport sensorLocation, State objectState) This default likelihood method simply returns 1.0 having the effect of every measurement being equally and completely likely.
double	MobileSensorObject.likelihood(Measurement meas, LocationReport sensorLocation, State objectState) This default likelihood method simply returns 1.0 having the effect of every measurement being equally and completely likely.

Uses of State in uwcse.location.objects.alien

Methods in uwcse.location.objects.alien with parameters of type State

double	AlienReaderFixed.likelihood(Measurement meas, LocationReport sensorLocation, State objectState) Determine the probabilistic likelihood [0..1] that this Alien sensor generated this measurement about the object.
double	AlienReaderFixed.likelihood(Measurement proxMeas, LocationReport sensorLocation, State objectState) Determine the probabilistic likelihood [0..1] that this Alien sensor generated this proximity measurement about the object, given the location of this sensor and the State that object.
double	AlienReaderMobile.likelihood(Measurement meas, LocationReport sensorLocation, State objectState) Determine the probabilistic likelihood [0..1] that this Alien sensor generated this measurement about the object.
double	AlienReaderMobile.likelihood(Measurement proxMeas, LocationReport sensorLocation, State objectState) Determine the probabilistic likelihood [0..1] that this Alien sensor generated this proximity measurement about the object, given the location of this sensor and the State that object.
static double	AlienSensor.likelihood(ProximityMeasurement proxMeas, LocationReport sensorLocation, State objectState) Determine the probabilistic likelihood [0..1] that this Alien sensor generated this proximity measurement about the object, given the location of this sensor and the State that object.
double	AlienTagFixed.likelihood(Measurement meas, LocationReport sensorLocation, State objectState) Determine the probabilistic likelihood [0..1] that this Alien sensor generated this measurement about the object.
double	AlienTagFixed.likelihood(Measurement proxMeas, LocationReport sensorLocation, State objectState) Determine the probabilistic likelihood [0..1] that this Alien sensor generated this proximity measurement about the object, given the location of this sensor and the State that object.

Uses of State in uwcse.location.objects.cricket

Methods in uwcse.location.objects.cricket with parameters of type State

double

CricketListener.likelihood(Measurement distanceMeas, LocationReport sensorLocation, State objectState) Compute the probabilistic likelihood [0..1] that this listener heard the linear distance measurement from the given beacon object, given the State of this listener and the State the beacon.

Uses of State in uwcse.location.objects.mote

Methods in uwcse.location.objects.mote with parameters of type State

double

MoteSensor.likelihood(Measurement proxMeas, LocationReport sensorLocation, State objectState) Determine the probabilistic likelihood [0..1] that this Mote generated this proximity measurement about the object, given the location of this Mote and the objectState of the sensed Mote.

Uses of State in uwcse.location.objects.versus

Methods in uwcse.location.objects.versus with parameters of type State

double	VersusSensor.likelihood(Measurement proxMeas, LocationReport sensorLocation, State objectState) Determine the probabilistic likelihood [0..1] that this Versus sensor generated this proximity measurement about the object, given the location of this sensor and the State that object.
double	HoodedVersusSensor.likelihood(Measurement proxMeas, LocationReport sensorLocation, State objectState) Determine the probabilistic likelihood [0..1] that this Versus sensor generated this proximity measurement about the object, given the location of this sensor and the State that object.