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/*
 * (c) Copyright Christian P. Fries, Germany. Contact: [email protected].
 *
 * Created on 29.02.2008
 */
package net.finmath.montecarlo.process;

import java.util.Map;

import net.finmath.montecarlo.IndependentIncrements;
import net.finmath.montecarlo.model.ProcessModel;

/**
 * The interface for a process (numerical scheme) of a stochastic process X where
 * X = f(Y) and Y is an Itô process

 * \[
 * dY_{j} = \mu_{j} dt + \lambda_{1,j} dW_{1} + \ldots + \lambda_{m,j} dW_{m}
 * \]
 *
 * The parameters are provided by a model implementing {@link net.finmath.montecarlo.model.ProcessModel}:
 * 
 * The value of Y(0) is provided by the method {@link net.finmath.montecarlo.model.ProcessModel#getInitialState}.
 * 
The value of μ is provided by the method {@link net.finmath.montecarlo.model.ProcessModel#getDrift}.
 * 
The value λ_j is provided by the method {@link net.finmath.montecarlo.model.ProcessModel#getFactorLoading}.
 * 
The function f is provided by the method {@link net.finmath.montecarlo.model.ProcessModel#applyStateSpaceTransform}.
 * 
 * Here, μ and λ_j may depend on X, which allows to implement stochastic drifts (like in a LIBOR market model)
 * of local volatility models.
 *
 * @author Christian Fries
 * @see net.finmath.montecarlo.model.ProcessModel The definition of the model.
 * @version 1.0
 */
public interface MonteCarloProcess extends Process {

	/**
	 * @return Returns the numberOfPaths.
	 */
	int getNumberOfPaths();

	/**
	 * @return Returns the numberOfFactors.
	 */
	int getNumberOfFactors();

	/**
	 * @return Returns the stochastic driver used to generate this process
	 */
	IndependentIncrements getStochasticDriver();

	/**
	 * Returns a clone of this model where the specified properties have been modified.
	 *
	 * Note that there is no guarantee that a model reacts on a specification of a properties in the
	 * parameter map dataModified. If data is provided which is ignored by the model
	 * no exception may be thrown.
	 *
	 * @param model The model to be used.
	 * @return A clone of this model (or this model if no parameter was modified).
	 */
	MonteCarloProcess getCloneWithModifiedModel(ProcessModel model);

	/**
	 * Returns a clone of this model where the specified properties have been modified.
	 *
	 * Note that there is no guarantee that a model reacts on a specification of a properties in the
	 * parameter map dataModified. If data is provided which is ignored by the model
	 * no exception may be thrown.
	 *
	 * @param dataModified Key-value-map of parameters to modify.
	 * @return A clone of this model (or this model if no parameter was modified).
	 */
	MonteCarloProcess getCloneWithModifiedData(Map dataModified);

	/**
	 * Create and return a clone of this process. The clone is not tied to any model, but has the same
	 * process specification, that is, if the model is the same, it would generate the same paths.
	 *
	 * @return Clone of the process
	 */
	@Override
	MonteCarloProcess clone();
}