Uses of Interface
broadwick.montecarlo.MonteCarloResults

Packages that use MonteCarloResults

Package	Description
broadwick.montecarlo	Monte Carlo simulation package.
broadwick.montecarlo.acceptor	All Monte Carlo acceptance criteria can be found in this package.
broadwick.montecarlo.markovchain	This package contains classes for generating Monte Carlo Markov Chains.

Uses of MonteCarloResults in broadwick.montecarlo

Classes in broadwick.montecarlo that implement MonteCarloResults

Modifier and Type	Class and Description
class	MonteCarloDefaultResults A default implementation for the MonteCarloResults interface.
(package private) class	Poison Poison object that causes the consumer of the MonteCarlo results to stop looking for objects on the queue.

Fields in broadwick.montecarlo declared as MonteCarloResults

Modifier and Type	Field and Description
private MonteCarloResults	Consumer.joinedResults
private MonteCarloResults	MonteCarlo.resultsConsumer

Fields in broadwick.montecarlo with type parameters of type MonteCarloResults

Modifier and Type	Field and Description
private ArrayBlockingQueue<MonteCarloResults>	Producer.queue
private ArrayBlockingQueue<MonteCarloResults>	Consumer.queue

Methods in broadwick.montecarlo that return MonteCarloResults

Modifier and Type	Method and Description
MonteCarloResults	MonteCarlo.getResults() Get a copy of the results from the simulation.
MonteCarloResults	Poison.join(MonteCarloResults results)
MonteCarloResults	MonteCarloResults.join(MonteCarloResults results) Join another Monte Carlo results object to this one.
MonteCarloResults	MonteCarloDefaultResults.join(MonteCarloResults results)
abstract MonteCarloResults	MonteCarloScenario.run(int seed) Compute the value of the Monte Carlo model/simulation at the given set of coordinates.

Methods in broadwick.montecarlo with parameters of type MonteCarloResults

Modifier and Type	Method and Description
MonteCarloResults	Poison.join(MonteCarloResults results)
MonteCarloResults	MonteCarloResults.join(MonteCarloResults results) Join another Monte Carlo results object to this one.
MonteCarloResults	MonteCarloDefaultResults.join(MonteCarloResults results)
void	MonteCarlo.setResultsConsumer(MonteCarloResults consumer) Set the consumer object for this Monte Carlo simulation.

Constructors in broadwick.montecarlo with parameters of type MonteCarloResults

Constructor and Description
Consumer(ArrayBlockingQueue<MonteCarloResults> queue, MonteCarloResults joinedResults) Create the consumer object.

Constructor parameters in broadwick.montecarlo with type arguments of type MonteCarloResults

Constructor and Description
Consumer(ArrayBlockingQueue<MonteCarloResults> queue, MonteCarloResults joinedResults) Create the consumer object.
Producer(ArrayBlockingQueue<MonteCarloResults> queue, MonteCarloScenario simulation, int numSimulations) Create the producer object.

Uses of MonteCarloResults in broadwick.montecarlo.acceptor

Methods in broadwick.montecarlo.acceptor with parameters of type MonteCarloResults

Modifier and Type	Method and Description
boolean	MonteCarloAcceptor.accept(MonteCarloResults oldResult, MonteCarloResults newResult) Accept a step in a Monte Carlo path/chain based on the ratio of the results at each step.
boolean	MetropolisHastings.accept(MonteCarloResults oldResult, MonteCarloResults newResult)

Uses of MonteCarloResults in broadwick.montecarlo.markovchain

Fields in broadwick.montecarlo.markovchain declared as MonteCarloResults

Modifier and Type	Field and Description
private MonteCarloResults	MarkovChainMonteCarlo.consumer

Constructors in broadwick.montecarlo.markovchain with parameters of type MonteCarloResults

Constructor and Description
MarkovChainMonteCarlo(MonteCarloScenario model, int numSimulations, MonteCarloResults consumer, MarkovChainController controller, MarkovStepGenerator generator) Create a Monte Carlo instance.
MarkovChainMonteCarlo(MonteCarloScenario model, int numSimulations, MonteCarloResults consumer, MarkovStepGenerator generator) Create a Monte Carlo instance.