DESY ACOP Beans Home

de.desy.acop.video.analysis
Class FittingUtilities

java.lang.Object
  de.desy.acop.video.analysis.FittingUtilities

public class FittingUtilities
extends java.lang.Object

FittingUtilities provides a set of utilities to fit a gaussian function to a set of data

Author:

Jaka Bobnar

Constructor Summary

FittingUtilities()

Method Summary

static double[][]	FFT1D(double[][] x, boolean forward)
static double[]	fit(double[] y, double constY) Performs a linear fit of exponential function to the y data.
static boolean	isNaN(double[] values) Checks if any of the values in the arrays is NaN.
static double[]	lmGauss(double[] x, double[] y, double[] weights, double[] startValues) Fits a gauss with offset y = Ae^(-(x-C)^2/(2B^2)) to the given data.
static double[]	lmLinear(double[] x, double[] y, double[] weights, double[] startValues) Fits a gauss with offset y = Ae^(-(x-C)^2/(2B^2)) + D + E x to the given data.
static double[]	lmOffset(double[] x, double[] y, double[] weights, double[] startValues) Deprecated. ues lmLinear(double[], double[], double[], double[])
static void	main(java.lang.String[] args)
static double[]	smooth(double[] x) Smooths the data with averaging.
static double[]	smooth(double[] x, boolean lowPassFilterOn) Smooths the values in the array with averaging and applying a low pass filter.

Methods inherited from class java.lang.Object

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

Constructor Detail

FittingUtilities

public FittingUtilities()

Method Detail

lmOffset

@Deprecated
public static double[] lmOffset(double[] x,
                                           double[] y,
                                           double[] weights,
                                           double[] startValues)
                         throws OptimizationException,
                                FunctionEvaluationException,
                                java.lang.IllegalArgumentException

Deprecated. ues lmLinear(double[], double[], double[], double[])

Fits a gauss with offset y = Ae^(-(x-C)^2/(2B^2)) + D to the given data.

Parameters:

x - the independent variable data

y - the dependent variable data

weights - the weights of the measurements

startValues - starting values for the parameters

Returns:

array of calculated parameters ([A,B,C,D])

Throws:

OptimizationException

FunctionEvaluationException

java.lang.IllegalArgumentException

lmLinear

public static double[] lmLinear(double[] x,
                                double[] y,
                                double[] weights,
                                double[] startValues)
                         throws OptimizationException,
                                FunctionEvaluationException,
                                java.lang.IllegalArgumentException

Fits a gauss with offset y = Ae^(-(x-C)^2/(2B^2)) + D + E x to the given data.

Parameters:

x - the independent variable data

y - the dependent variable data

weights - the weights of the measurements

startValues - starting values for the parameters

Returns:

array of calculated parameters ([A,B,C,D,E])

Throws:

OptimizationException

FunctionEvaluationException

java.lang.IllegalArgumentException

lmGauss

public static double[] lmGauss(double[] x,
                               double[] y,
                               double[] weights,
                               double[] startValues)
                        throws OptimizationException,
                               FunctionEvaluationException,
                               java.lang.IllegalArgumentException

Fits a gauss with offset y = Ae^(-(x-C)^2/(2B^2)) to the given data.

Parameters:

x - the independent variable data

y - the dependent variable data

weights - the weights of the measurements

startValues - starting values for the parameters

Returns:

array of calculated parameters ([A,B,C])

Throws:

OptimizationException

FunctionEvaluationException

java.lang.IllegalArgumentException

main

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

Throws:

MathException

fit

public static double[] fit(double[] y,
                           double constY)
                    throws MathException

Performs a linear fit of exponential function to the y data.

Parameters:

y -

constY -

Returns:

Throws:

MathException

isNaN

public static boolean isNaN(double[] values)

Checks if any of the values in the arrays is NaN.

Parameters:

values -

Returns:

smooth

public static double[] smooth(double[] x)

Smooths the data with averaging.

Parameters:

x - data to be smoothed

Returns:

smoothed data

smooth

public static double[] smooth(double[] x,
                              boolean lowPassFilterOn)

Smooths the values in the array with averaging and applying a low pass filter.

Parameters:

x - the data to smooth

lowPassFilterOn - true if low pass filtering should be used

Returns:

smoothed array

FFT1D

public static double[][] FFT1D(double[][] x,
                               boolean forward)

Parameters:

x - array of values. First array are real values, second imaginary

forward - true for forward and false for inverse transform

Returns:

Fourier transform of x

Throws:

java.lang.Exception