vec_math
Class MultipleFrequencyFit

java.lang.Object
  util.PropertyContainer
      util.PropertyResources
          util.PropertyBundles
              vec_math.AbstractAnalyser
                  vec_math.MultipleFrequencyFit

All Implemented Interfaces:

Cloneable, Initializable, LocalizedSupplying, PropertySupplying, ResourceSupplying, Analyser

public class MultipleFrequencyFit
extends AbstractAnalyser

This analyser recursively fits fourier series like

   F_M = ΣMA_k*cos(2πf·k·t)+B_k*sin(2πf·k·t)
   

for the given order number to the data the Fourier frequencies are estimated from the highest frequency from a CleanFourier periodogram on the residual data.

Nested Class Summary

static class	MultipleFrequencyFit.File Use the fourier least-squares on file data.
(package private) class	MultipleFrequencyFit.FourierComponents

Nested classes/interfaces inherited from class util.PropertyResources

PropertyResources.URLResource

Field Summary

private List<Vector1D>	alarms The false alarm probabilities of the solutions.
static double	DEFCONVERGENCE Default rms convergence criterium.
static double	DEFFALSEALARM Default rms convergence criterium.
private static boolean	DEFUSESIMPLEX Default use fast-convergent levenberg-marquardt.
private static boolean	DEFVISUALIZEALL Default visualize all
static String	KEY_CONVERGENCE If frequency is stable to this number, series stop.
static String	KEY_FALSEALARM The key for the maximum Fourier series order, no default
static String	KEY_KEEPFIXED On reiterations, these terms are kept fix.
static String	KEY_MAXFREQ If given, a maximum frequency to scan.
static String	KEY_MINFREQ If given, a minimum frequency to scan.
static String	KEY_ORDER The key for the maximum Fourier series order, no default
static String	KEY_REITERATE If true, the final solution is re-iterated if -p.
static String	KEY_USESIMPLEX On reiterations use the more robust simplex on improving.
static String	KEY_VISUALIZEALL If true return all residuals, not just highest order.
private List<VectorG>	valid The solutions, ordered for increasing order in the series.
private double	xav Intermittance storage for second-step improvement.
private double	yav Intermittance storage for second-step improvement.

Fields inherited from class util.PropertyBundles

KEY_LOCALECOUNTRY, KEY_LOCALELANGUAGE, KEY_RESOURCEBUNDLES

Fields inherited from class util.PropertyResources

KEY_NOINITONCREATE, localurl, locate, POSTFIX_DIR, POSTFIX_EXT, POSTFIX_FILE, POSTFIX_LIST, POSTFIX_URL, urlset

Fields inherited from class util.PropertyContainer

KEY_LISTSEPARATOR, KEY_MAPKEYVALUECHAR, KEY_MAPSEPARATOR

Fields inherited from interface util.ResourceSupplying

KEY_URLRESOURCES, KEY_URLUSECONFIG, KEY_URLUSECURRENT, KEY_URLUSEHOME

Fields inherited from interface util.PropertySupplying

CONFIG, KEY_CLASS

Constructor Summary

MultipleFrequencyFit(Map<String,String> prop)
Creates a new phase dispersion minimizer.

Method Summary

long[]	functionCalls(VectorG[] in) No estimate possible.
private VectorG	improve(VectorG[] in, List<VectorG> freqs, int[] fixorder) Improvement of multidimensional fourier fit means we take a vector of frequencies and amplitudes, construct single-order fourier series out of them and let all frequencies and amplitudes varry, except those stated in the fixed orders array.
Object[]	metadata(VectorG[] in, VectorG[] allfits, VectorG[] p) Metadata are the fitting Fouries with their false alarm probabilities.
VectorG[]	process(VectorG[] in) Processes the data until we reach either KEY_ORDER in the Fouriere series expansion, or the frequency is stable to KEY_CONVERGENCE.
double	significance(double f, VectorG[] data, VectorG[] fit, VectorG[] residual) No significance yet.
VectorG[]	visualize(VectorG[] in, VectorG[] allfits) Visualized data is the original data minus the highest-order Fourier fit.

Methods inherited from class vec_math.AbstractAnalyser

getBootstrapData, getBootstrapData, getDiminishedData, getDiminishedData, getSyntheticData, getSyntheticData, reset, runningAverage

Methods inherited from class util.PropertyBundles

clone, getLocalized, getLocalized, getLocalizedString, getLocalizedString, loadResource

Methods inherited from class util.PropertyResources

createFrom, createFrom, createFrom, getApplet, getAsResources, getLocalClassLoader, getPropertiesToKey, getPropertiesToKey, getResource, getResourceAsStream, getResourceFromKey, getResources, init, keyCreate, keyCreate, reload, setApplet

Methods inherited from class util.PropertyContainer

augment, augment, augment, defaultBoolean, defaultChar, defaultDouble, defaultFloat, defaultInt, defaultLong, defaultObject, defaultObject, defaultProperties, defaultProperty, getAsBoolean, getAsChar, getAsDouble, getAsEnums, getAsFloat, getAsInt, getAsList, getAsLong, getAsMap, getAsMap, getAsObject, getAsObject, getProperties, getProperty, has, isNew, parseObject, reload, removeProperty, rescanned, setObject, setProperties, setProperty, stringProperties, toString

Methods inherited from class java.lang.Object

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

Methods inherited from interface util.ResourceSupplying

getResource, getResourceAsStream, getResources

Methods inherited from interface util.PropertySupplying

defaultBoolean, defaultChar, defaultDouble, defaultFloat, defaultInt, defaultLong, defaultObject, defaultObject, defaultProperties, defaultProperty, getAsBoolean, getAsChar, getAsDouble, getAsFloat, getAsInt, getAsList, getAsLong, getAsMap, getAsObject, getAsObject, getProperties, getProperty, has, parseObject, removeProperty, setObject, setProperty, stringProperties

Methods inherited from interface util.Initializable

init

Field Detail

KEY_ORDER

public static final String KEY_ORDER

The key for the maximum Fourier series order, no default

See Also:

Constant Field Values

KEY_FALSEALARM

public static final String KEY_FALSEALARM

The key for the maximum Fourier series order, no default

See Also:

Constant Field Values

KEY_CONVERGENCE

public static final String KEY_CONVERGENCE

If frequency is stable to this number, series stop.

See Also:

Constant Field Values

KEY_VISUALIZEALL

public static final String KEY_VISUALIZEALL

If true return all residuals, not just highest order.

See Also:

Constant Field Values

KEY_MINFREQ

public static final String KEY_MINFREQ

If given, a minimum frequency to scan.

See Also:

Constant Field Values

KEY_MAXFREQ

public static final String KEY_MAXFREQ

If given, a maximum frequency to scan.

See Also:

Constant Field Values

KEY_REITERATE

public static final String KEY_REITERATE

If true, the final solution is re-iterated if -p.

See Also:

Constant Field Values

KEY_KEEPFIXED

public static final String KEY_KEEPFIXED

On reiterations, these terms are kept fix.

See Also:

Constant Field Values

KEY_USESIMPLEX

public static final String KEY_USESIMPLEX

On reiterations use the more robust simplex on improving.

See Also:

Constant Field Values

DEFCONVERGENCE

public static final double DEFCONVERGENCE

Default rms convergence criterium.

See Also:

Constant Field Values

DEFFALSEALARM

public static final double DEFFALSEALARM

Default rms convergence criterium.

See Also:

Constant Field Values

DEFVISUALIZEALL

private static final boolean DEFVISUALIZEALL

Default visualize all

See Also:

Constant Field Values

DEFUSESIMPLEX

private static final boolean DEFUSESIMPLEX

Default use fast-convergent levenberg-marquardt.

See Also:

Constant Field Values

valid

private List<VectorG> valid

The solutions, ordered for increasing order in the series.

alarms

private List<Vector1D> alarms

The false alarm probabilities of the solutions.

xav

private double xav

Intermittance storage for second-step improvement.

yav

private double yav

Intermittance storage for second-step improvement.

Constructor Detail

MultipleFrequencyFit

public MultipleFrequencyFit(Map<String,String> prop)

Creates a new phase dispersion minimizer.

Method Detail

process

public VectorG[] process(VectorG[] in)

Processes the data until we reach either KEY_ORDER in the Fouriere series expansion, or the frequency is stable to KEY_CONVERGENCE. Each iteration produces a fit in the resulting data vector, so the dimension of the processed VectorG is 1+order. The original data is not part of the processed data.

Parameters:

in - The measured data.

Returns:

Processed data of the same length as input data.

visualize

public VectorG[] visualize(VectorG[] in,
                           VectorG[] allfits)

Visualized data is the original data minus the highest-order Fourier fit. If the KEY_VISUALIZEALL is set to true, we return all fits. If KEY_REITERATE is set to true, the highest fit is re-entered to an amoeba, where all parameters, except those for order fixed by the comma-separated string in KEY_KEEPFIXED are allowed to change again.

Specified by:

visualize in interface Analyser

Overrides:

visualize in class AbstractAnalyser

Parameters:

in - The measured data.

allfits - The processed data from Analyser.process(vec_math.VectorG[]).

Returns:

Visualizable data derived from processed one.

functionCalls

public long[] functionCalls(VectorG[] in)

No estimate possible.

Returns:

null If unknown.

metadata

public Object[] metadata(VectorG[] in,
                         VectorG[] allfits,
                         VectorG[] p)

Metadata are the fitting Fouries with their false alarm probabilities.

Parameters:

in - The original data, before process.

allfits - The processed data from Analyser.process(vec_math.VectorG[]).

p - The visualized data from Analyser.visualize(vec_math.VectorG[], vec_math.VectorG[]).

significance

public double significance(double f,
                           VectorG[] data,
                           VectorG[] fit,
                           VectorG[] residual)

No significance yet.

Parameters:

f - The value whose significance is to be probed.

data - The original data, before process.

fit - The processed data from Analyser.process(vec_math.VectorG[]).

residual - The visualized data from Analyser.visualize(vec_math.VectorG[], vec_math.VectorG[]).

Returns:

A significance, 1-false-Alarm probability

improve

private VectorG improve(VectorG[] in,
                        List<VectorG> freqs,
                        int[] fixorder)

Improvement of multidimensional fourier fit means we take a vector of frequencies and amplitudes, construct single-order fourier series out of them and let all frequencies and amplitudes varry, except those stated in the fixed orders array. This array is sorted.