org.ddogleg.optimization

Interface OptimizationDerivative<State>

public interface OptimizationDerivative<State>

Interface for computing the gradient of a set of functions given a set of model parameters. Before computeDerivative(Object, double[][]) is called, the model must be set using setModel(double[]).

Method Summary

Modifier and Type	Method and Description
boolean	computeDerivative(State state, double[][] gradient) Computes the gradient for each function with respect to model parameters.
void	setModel(double[] model) Specifies the current model parameters around which the gradient is computed.

Method Detail

setModel

void setModel(double[] model)

Specifies the current model parameters around which the gradient is computed.

Parameters:

model - Model parameters.

computeDerivative

boolean computeDerivative(State state,
                          double[][] gradient)

Computes the gradient for each function with respect to model parameters. The derivative is a 2D array. The first axis is for each function and the second for each model parameter:

derivative[i][j] = &partial; f_i / &partial; p_j

Parameters:

state - State of the system being examined.

gradient - Gradient with respect to the current model parameters,

Returns:

true if successful or false if it failed.