Package etomica.math.numerical

Class PolynomialFit

java.lang.Object

etomica.math.numerical.PolynomialFit

public class PolynomialFit
extends java.lang.Object

Class that performs a polynomial fit to x,y data, optionally taking weights associated with each data point.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	PolynomialFit.FitResult

Constructor Summary

Constructors

Constructor	Description
PolynomialFit()

Method Summary

Modifier and Type	Method	Description
static double[]	doFit(int order, double[] x, double[] y)	Perform polynomial fit of the given order.
static double[]	doFit(int order, double[] x, double[] y, double[] w)	Perform polynomial fit of the given order with the given weights (w).
static PolynomialFit.FitResult	doFit(int order, double[] x, double[] y, double[] w, boolean doFitErr)
static double	getChi(double[] x, double[] y, double[] w, double[] poly)	Returns average relative deviation (relative to the uncertainty) of the given fit from the given data.
static double[][]	getFit(double[] x, PolynomialFit.FitResult fr)
static void	main(java.lang.String[] args)

Methods inherited from class java.lang.Object

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

Constructor Detail

PolynomialFit

public PolynomialFit()

Method Detail

doFit

public static double[] doFit(int order,
                             double[] x,
                             double[] y)

Perform polynomial fit of the given order. order=2 would fit y = a*x^2 + b*x + c The polynomial coefficients are returned as a double array in order of increasing power of x. So, double[] r = doFit(); r[i] is the coefficient for x^i

doFit

public static double[] doFit(int order,
                             double[] x,
                             double[] y,
                             double[] w)

Perform polynomial fit of the given order with the given weights (w). order=2 would fit y = a*x^2 + b*x + c The polynomial coefficients are returned as a double array in order of increasing power of x. So, double[] r = doFit(); r[i] is the coefficient for x^i

doFit

public static PolynomialFit.FitResult doFit(int order,
                                            double[] x,
                                            double[] y,
                                            double[] w,
                                            boolean doFitErr)

getFit

public static double[][] getFit(double[] x,
                                PolynomialFit.FitResult fr)

getChi

public static double getChi(double[] x,
                            double[] y,
                            double[] w,
                            double[] poly)

Returns average relative deviation (relative to the uncertainty) of the given fit from the given data.

chi = (<(diff/error)^2>/N)^.5

main

public static void main(java.lang.String[] args)