org.apache.commons.math3.optimization.fitting Class CurveFitter<T extends ParametricUnivariateFunction>

java.lang.Object org.apache.commons.math3.optimization.fitting.CurveFitter<T>
Type Parameters:
T - Function to use for the fit.
Direct Known Subclasses:
GaussianFitter, HarmonicFitter, PolynomialFitter

Deprecated. As of 3.1 (to be removed in 4.0).

@Deprecated
public class CurveFitter<T extends ParametricUnivariateFunction>
extends Object

Fitter for parametric univariate real functions y = f(x).
When a univariate real function y = f(x) does depend on some unknown parameters p0, p1 ... pn-1, this class can be used to find these parameters. It does this by fitting the curve so it remains very close to a set of observed points (x0, y0), (x1, y1) ... (xk-1, yk-1). This fitting is done by finding the parameters values that minimizes the objective function ∑(yi-f(xi))2. This is really a least squares problem.

Since:
2.0
Version:
\$Id: CurveFitter.java 1422230 2012-12-15 12:11:13Z erans \$

Constructor Summary
CurveFitter(DifferentiableMultivariateVectorOptimizer optimizer)
Deprecated. as of 3.1 replaced by CurveFitter(MultivariateDifferentiableVectorOptimizer)
CurveFitter(MultivariateDifferentiableVectorOptimizer optimizer)
Deprecated. Simple constructor.

Method Summary
Deprecated. Add an observed (x,y) point to the sample with unit weight.
void addObservedPoint(double weight, double x, double y)
Deprecated. Add an observed weighted (x,y) point to the sample.
Deprecated. Add an observed weighted (x,y) point to the sample.
void clearObservations()
Deprecated. Remove all observations.
double[] fit(int maxEval, T f, double[] initialGuess)
Deprecated. Fit a curve.
double[] fit(T f, double[] initialGuess)
Deprecated. Fit a curve.
WeightedObservedPoint[] getObservations()
Deprecated. Get the observed points.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

CurveFitter

public CurveFitter(DifferentiableMultivariateVectorOptimizer optimizer)
Deprecated. as of 3.1 replaced by CurveFitter(MultivariateDifferentiableVectorOptimizer)

Simple constructor.

Parameters:
optimizer - optimizer to use for the fitting

CurveFitter

public CurveFitter(MultivariateDifferentiableVectorOptimizer optimizer)
Deprecated.
Simple constructor.

Parameters:
optimizer - optimizer to use for the fitting
Since:
3.1
Method Detail

double y)
Deprecated.
Add an observed (x,y) point to the sample with unit weight.

Calling this method is equivalent to call addObservedPoint(1.0, x, y).

Parameters:
x - abscissa of the point
y - observed value of the point at x, after fitting we should have f(x) as close as possible to this value

double x,
double y)
Deprecated.
Add an observed weighted (x,y) point to the sample.

Parameters:
weight - weight of the observed point in the fit
x - abscissa of the point
y - observed value of the point at x, after fitting we should have f(x) as close as possible to this value

Deprecated.
Add an observed weighted (x,y) point to the sample.

Parameters:
observed - observed point to add

getObservations

public WeightedObservedPoint[] getObservations()
Deprecated.
Get the observed points.

Returns:
observed points

clearObservations

public void clearObservations()
Deprecated.
Remove all observations.

fit

public double[] fit(T f,
double[] initialGuess)
Deprecated.
Fit a curve. This method compute the coefficients of the curve that best fit the sample of observed points previously given through calls to the addObservedPoint method.

Parameters:
f - parametric function to fit.
initialGuess - first guess of the function parameters.
Returns:
the fitted parameters.
Throws:
DimensionMismatchException - if the start point dimension is wrong.

fit

public double[] fit(int maxEval,
T f,
double[] initialGuess)
Deprecated.
Fit a curve. This method compute the coefficients of the curve that best fit the sample of observed points previously given through calls to the addObservedPoint method.

Parameters:
f - parametric function to fit.
initialGuess - first guess of the function parameters.
maxEval - Maximum number of function evaluations.
Returns:
the fitted parameters.
Throws:
TooManyEvaluationsException - if the number of allowed evaluations is exceeded.
DimensionMismatchException - if the start point dimension is wrong.
Since:
3.0