public class LeastSquaresBuilder
extends java.lang.Object
LeastSquaresProblem
s.LeastSquaresFactory
Modifier and Type | Field and Description |
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private ConvergenceChecker<LeastSquaresProblem.Evaluation> |
checker
convergence checker
|
private boolean |
lazyEvaluation
Lazy evaluation.
|
private int |
maxEvaluations
max evaluations
|
private int |
maxIterations
max iterations
|
private MultivariateJacobianFunction |
model
model function
|
private ParameterValidator |
paramValidator
Validator.
|
private RealVector |
start
initial guess
|
private RealVector |
target
observed values
|
private RealMatrix |
weight
weight matrix
|
Constructor and Description |
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LeastSquaresBuilder() |
Modifier and Type | Method and Description |
---|---|
LeastSquaresProblem |
build()
Construct a
LeastSquaresProblem from the data in this builder. |
LeastSquaresBuilder |
checker(ConvergenceChecker<LeastSquaresProblem.Evaluation> newChecker)
Configure the convergence checker.
|
LeastSquaresBuilder |
checkerPair(ConvergenceChecker<PointVectorValuePair> newChecker)
Configure the convergence checker.
|
LeastSquaresBuilder |
lazyEvaluation(boolean newValue)
Configure whether evaluation will be lazy or not.
|
LeastSquaresBuilder |
maxEvaluations(int newMaxEvaluations)
Configure the max evaluations.
|
LeastSquaresBuilder |
maxIterations(int newMaxIterations)
Configure the max iterations.
|
LeastSquaresBuilder |
model(MultivariateJacobianFunction newModel)
Configure the model function.
|
LeastSquaresBuilder |
model(MultivariateVectorFunction value,
MultivariateMatrixFunction jacobian)
Configure the model function.
|
LeastSquaresBuilder |
parameterValidator(ParameterValidator newValidator)
Configure the validator of the model parameters.
|
LeastSquaresBuilder |
start(double[] newStart)
Configure the initial guess.
|
LeastSquaresBuilder |
start(RealVector newStart)
Configure the initial guess.
|
LeastSquaresBuilder |
target(double[] newTarget)
Configure the observed data.
|
LeastSquaresBuilder |
target(RealVector newTarget)
Configure the observed data.
|
LeastSquaresBuilder |
weight(RealMatrix newWeight)
Configure the weight matrix.
|
private int maxEvaluations
private int maxIterations
private ConvergenceChecker<LeastSquaresProblem.Evaluation> checker
private MultivariateJacobianFunction model
private RealVector target
private RealVector start
private RealMatrix weight
private boolean lazyEvaluation
private ParameterValidator paramValidator
public LeastSquaresProblem build()
LeastSquaresProblem
from the data in this builder.LeastSquaresProblem
.public LeastSquaresBuilder maxEvaluations(int newMaxEvaluations)
newMaxEvaluations
- the maximum number of evaluations permitted.public LeastSquaresBuilder maxIterations(int newMaxIterations)
newMaxIterations
- the maximum number of iterations permitted.public LeastSquaresBuilder checker(ConvergenceChecker<LeastSquaresProblem.Evaluation> newChecker)
newChecker
- the convergence checker.public LeastSquaresBuilder checkerPair(ConvergenceChecker<PointVectorValuePair> newChecker)
checker(ConvergenceChecker)
.newChecker
- the convergence checker.public LeastSquaresBuilder model(MultivariateVectorFunction value, MultivariateMatrixFunction jacobian)
value
- the model function valuejacobian
- the Jacobian of value
public LeastSquaresBuilder model(MultivariateJacobianFunction newModel)
newModel
- the model function value and Jacobianpublic LeastSquaresBuilder target(RealVector newTarget)
newTarget
- the observed data.public LeastSquaresBuilder target(double[] newTarget)
newTarget
- the observed data.public LeastSquaresBuilder start(RealVector newStart)
newStart
- the initial guess.public LeastSquaresBuilder start(double[] newStart)
newStart
- the initial guess.public LeastSquaresBuilder weight(RealMatrix newWeight)
newWeight
- the weight matrixpublic LeastSquaresBuilder lazyEvaluation(boolean newValue)
newValue
- Whether to perform lazy evaluation.public LeastSquaresBuilder parameterValidator(ParameterValidator newValidator)
newValidator
- Parameter validator.