org.hipparchus.fitting

Class AbstractCurveFitter

java.lang.Object

org.hipparchus.fitting.AbstractCurveFitter

Direct Known Subclasses:

GaussianCurveFitter, HarmonicCurveFitter, PolynomialCurveFitter, SimpleCurveFitter

public abstract class AbstractCurveFitter
extends Object

Base class that contains common code for fitting parametric univariate real functions y = f(pi;x), where x is the independent variable and the pi are the parameters.
A fitter will find the optimal values of the parameters by fitting the curve so it remains very close to a set of N observed points (xk, yk), 0 <= k < N.
An algorithm usually performs the fit by finding the parameter values that minimizes the objective function

  ∑yk - f(xk)2,
 

which is actually a least-squares problem. This class contains boilerplate code for calling the fit(Collection) method for obtaining the parameters. The problem setup, such as the choice of optimization algorithm for fitting a specific function is delegated to subclasses.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
protected static class	AbstractCurveFitter.TheoreticalValuesFunction Vector function for computing function theoretical values.

Constructor Summary

Constructors

Constructor and Description
AbstractCurveFitter()

Method Summary

Modifier and Type	Method and Description
double[]	fit(Collection<WeightedObservedPoint> points) Fits a curve.
protected LeastSquaresOptimizer	getOptimizer() Creates an optimizer set up to fit the appropriate curve.
protected abstract LeastSquaresProblem	getProblem(Collection<WeightedObservedPoint> points) Creates a least squares problem corresponding to the appropriate curve.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

AbstractCurveFitter

public AbstractCurveFitter()

Method Detail

fit

public double[] fit(Collection<WeightedObservedPoint> points)

Fits a curve. This method computes the coefficients of the curve that best fit the sample of observed points.

Parameters:

points - Observations.

Returns:

the fitted parameters.

getOptimizer

protected LeastSquaresOptimizer getOptimizer()

Creates an optimizer set up to fit the appropriate curve.

The default implementation uses a Levenberg-Marquardt optimizer.

Returns:

the optimizer to use for fitting the curve to the given points.

getProblem

protected abstract LeastSquaresProblem getProblem(Collection<WeightedObservedPoint> points)

Creates a least squares problem corresponding to the appropriate curve.

Parameters:

points - Sample points.

Returns:

the least squares problem to use for fitting the curve to the given points.