org.ddogleg.optimization.functions

Interface FunctionNtoMxN

All Known Implementing Classes:

CalibPoseAndPointRodriguesJacobian, CallCounterNtoMxN, CylinderToPointSignedDistanceJacobian_F32, CylinderToPointSignedDistanceJacobian_F64, EvalFuncBadlyScaledBrown.Deriv, EvalFuncCurveFit.Deriv, EvalFuncHelicalValley.Deriv, EvalFuncPowell.Deriv, EvalFuncRosenbrock.Deriv, EvalFuncRosenbrockMod.Deriv, NumericalJacobianFB, NumericalJacobianForward, PnPJacobianRodrigues, PnPStereoJacobianRodrigues, RefineEllipseEuclideanLeastSquares.Jacobian, SphereToPointSignedDistanceJacobian_F32, SphereToPointSignedDistanceJacobian_F64, TestLsToNonLinearDeriv.DerivLS, Zhang99OptimizationJacobian

public interface FunctionNtoMxN

Function that takes in a vector of length N and outputs a matrix with dimension M x N.

Method Summary

Modifier and Type	Method and Description
int	getNumOfInputsN() Number of input parameters and columns in output matrix.
int	getNumOfOutputsM() Number of rows in output matrix.
void	process(double[] input, double[] output) Processes the input vector to output a 2D a matrix.

Method Detail

getNumOfInputsN

int getNumOfInputsN()

Number of input parameters and columns in output matrix. Typically the parameters you are optimizing.

Returns:

Number of input parameters

getNumOfOutputsM

int getNumOfOutputsM()

Number of rows in output matrix. Typically the functions that are being optimized.

Returns:

Number of rows in output matrix.

process

void process(double[] input,
             double[] output)

Processes the input vector to output a 2D a matrix. The matrix has a dimension of M rows and N columns and is formatted as a row major 1D-array. EJML can be used to provide a matrix wrapper around the output array: DenseMatrix J = DenseMatrix.wrap(m,n,output);

The user can modify the input parameters here and the optimizer must use those changes.

Parameters:

input - Vector with input parameters.

output - Row major array with M rows and N columns.