Uses of Class
edu.cnu.mdi.splot.fit.FitResult

Packages that use FitResult

Package	Description
edu.cnu.mdi.splot.fit
edu.cnu.mdi.splot.pdata	Data-model classes for the splot plotting library.

Uses of FitResult in edu.cnu.mdi.splot.fit

Methods in edu.cnu.mdi.splot.fit that return FitResult

Modifier and Type	Method	Description
protected static FitResult	ALeastSquaresFitter.buildFitResult(IFitStringGetter stringGetter, double[] params, org.apache.commons.math3.linear.RealMatrix covariance, int nPoints, int nParams, org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum opt)	Build a FitResult from the given components.
final FitResult	ALeastSquaresFitter.fit(double[] x, double[] y)	Fit with no weights, no initial guess override, and no parameter validator override.
final FitResult	ALeastSquaresFitter.fit(double[] x, double[] y, double[] weights)	Fit with weights but no initial guess override and no parameter validator override.
final FitResult	ALeastSquaresFitter.fit(double[] x, double[] y, double[] weights, double[] initialGuessOverride, org.apache.commons.math3.fitting.leastsquares.ParameterValidator validatorOverride)	Full fit entry point.
FitResult	ErfcFitter.fit(double[] x, double[] y, double[] weights, ErfcFitter.ParameterBounds bounds, double[] initialGuess)	Expert overload: fit with optional weights, optional bounds, and optional initial guess.
FitResult	ErfFitter.fit(double[] x, double[] y, double[] weights, ErfFitter.ParameterBounds bounds, double[] initialGuess)	Expert overload: fit with optional weights, optional bounds, and optional initial guess.
FitResult	GaussianFitter.fit(double[] x, double[] y, double[] weights, GaussianFitter.ParameterBounds bounds, double[] initialGuess)	Expert overload: fit with optional weights, optional bounds, and optional initial guess.
FitResult	IFitter.fit(double[] x, double[] y)	Fits a curve to the given data points, returning the fit result.
FitResult	IFitter.fit(double[] x, double[] y, double[] weights)	Fits a curve to the given data points with weights, returning the fit result.
FitResult	MultiGaussianFitter.fit(double[] x, double[] y, double[] weights, MultiGaussianFitter.ParameterBounds bounds, double[] initialGuess)	Expert overload: fit with optional weights, optional bounds, and optional initial guess.
FitResult	PolynomialFitter.fit(double[] x, double[] y, double[] weights, PolynomialFitter.ParameterBounds bounds, double[] initialGuess)	Fit with optional weights, bounds, and explicit initial guess.
static FitResult	PolynomialFitter.fit(int degree, double[] x, double[] y)	Convenience: fit a polynomial of a given degree with unit weights.
static FitResult	PolynomialFitter.fit(int degree, double[] x, double[] y, double[] weights)	Convenience: fit a polynomial of a given degree with supplied weights.

Methods in edu.cnu.mdi.splot.fit with parameters of type FitResult

Modifier and Type	Method	Description
abstract Evaluator	ALeastSquaresFitter.asEvaluator(FitResult fit)	Create an evaluator for the fit result.
Evaluator	ErfcFitter.asEvaluator(FitResult fit)
Evaluator	ErfFitter.asEvaluator(FitResult fit)
Evaluator	ExponentialDecayFitter.asEvaluator(FitResult fit)	Returns an Evaluator that computes A * exp(-x / τ) + C from the supplied fit result.
Evaluator	GaussianFitter.asEvaluator(FitResult fit)	Build a value getter using the fitted parameters.
Evaluator	LorentzianFitter.asEvaluator(FitResult fit)	Returns an Evaluator that computes A * (Γ/2)² / [(x − x₀)² + (Γ/2)²] + B.
Evaluator	MultiGaussianFitter.asEvaluator(FitResult fit)
Evaluator	PolynomialFitter.asEvaluator(FitResult fit)	Create an Evaluator that evaluates this polynomial using Horner's method.
Evaluator	PowerLawFitter.asEvaluator(FitResult fit)	Returns an Evaluator that computes A * x^n + C.

Uses of FitResult in edu.cnu.mdi.splot.pdata

Methods in edu.cnu.mdi.splot.pdata that return FitResult

Modifier and Type	Method	Description
FitResult	ACurve.fitResult()
protected FitResult	ACurve.fitWithOptionalWeights(IFitter fitter, FitVectors v)	Common pattern: if weights exist, call the weighted fit overload; otherwise call fit(x,y).

Methods in edu.cnu.mdi.splot.pdata with parameters of type FitResult

Modifier and Type	Method	Description
final void	ACurve.setFitResult(FitResult fitResult)	Set the fit result and notify listeners that the fit has changed.