Package gov.nih.mipav.model.algorithms

Class GaussianMixtureModelsIncompleteSamples

java.lang.Object

java.lang.Thread

gov.nih.mipav.model.algorithms.AlgorithmBase

gov.nih.mipav.model.algorithms.GaussianMixtureModelsIncompleteSamples

All Implemented Interfaces:

ActionListener, WindowListener, Runnable, EventListener

public class GaussianMixtureModelsIncompleteSamples
extends AlgorithmBase

dirichletRnd ported from mixGaussRnd.m by Mo Chen Copyright (c) 2016, Mo Chen All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution Neither the name of nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
(package private) class	GaussianMixtureModelsIncompleteSamples.Background
(package private) class	GaussianMixtureModelsIncompleteSamples.GMM

Nested classes/interfaces inherited from class java.lang.Thread

Thread.Builder, Thread.State, Thread.UncaughtExceptionHandler

Field Summary

Fields

Modifier and Type	Field	Description
private double[][][]	covar_callback_default_arr
private int	D
private int	K

Fields inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

destFlag, destImage, image25D, mask, maxProgressValue, minProgressValue, multiThreadingEnabled, nthreads, progress, progressModulus, progressStep, runningInSeparateThread, separable, srcImage, threadStopped

Fields inherited from class java.lang.Thread

MAX_PRIORITY, MIN_PRIORITY, NORM_PRIORITY

Constructor Summary

Constructors

Constructor	Description
GaussianMixtureModelsIncompleteSamples()
GaussianMixtureModelsIncompleteSamples(int K, int D)

Method Summary

Modifier and Type	Method	Description
void	_drawGMM_BG(Vector<double[][]> data2Vec, Vector<double[][][]> covar2Vec, GaussianMixtureModelsIncompleteSamples.GMM gmm, double size, String covar_callback, GaussianMixtureModelsIncompleteSamples.Background background, Random rng)
void	_EM(double[] log_L, int[] N, double[] N2, GaussianMixtureModelsIncompleteSamples.GMM gmm, double[][] log_p, int[][] U, double[][][][] T_inv, double[] log_S, double[][] data, double[][][] covar, double[][][] R, String sel_callback, int oversampling, String covar_callback, GaussianMixtureModelsIncompleteSamples.Background background, double[][] p_bg, double w, double cutoff, int miniter, int maxiter, double tol, String prefix, boolean[] changeable_amp, boolean[] changeable_mean, boolean[] changeable_covar, Random rng)
void	_EMstep(double[] log_L, int[] N, double[] N2, double[] N0update, GaussianMixtureModelsIncompleteSamples.GMM gmm, double[][] log_p, int[][] U, double[][][][] T_inv, double[] log_S, double N0, double[][] data, double[][][] covar, double[][][] R, String sel_callback, double[] omega, int oversampling, String covar_callback, GaussianMixtureModelsIncompleteSamples.Background background, double[][] p_bg, double w, double cutoff, double tol, boolean[] changeable_amp, boolean[] changeable_mean, boolean[] changeable_covar, int it, Random rng)
double	_Estep(GaussianMixtureModelsIncompleteSamples.GMM gmm, double[][] log_p, int[][] U, double[][][][] T_inv, double[] log_S, double[][] data, double[][][] covar, double[][][] R, double[] omega, GaussianMixtureModelsIncompleteSamples.Background background, double[][] p_bg, double cutoff, int it, Random rng)
void	_Esum(double[][] log_p, double[][][][] T_inv, int k, int[][] U, GaussianMixtureModelsIncompleteSamples.GMM gmm, double[][] data, double[][][] covar, double[][][] R, double cutoff)
void	_findSNMComponents(int[] changing, boolean[] cleanup, GaussianMixtureModelsIncompleteSamples.GMM gmm, int[][] U, double[][] log_p, double[] log_S, double N)
double	_JS(int k, GaussianMixtureModelsIncompleteSamples.GMM gmm, double[][] log_p, double[] log_S, int[][] U, double[] A)
void	_Mstep(double[] A, double[][] M, double[][][] C, double[] B, GaussianMixtureModelsIncompleteSamples.GMM gmm, int[][] U, double[][] log_p, double[][][][] T_inv, double[] log_S, double[][] data, double[][][] covar, double[][][] R, double[][] p_bg)
void	_Msums(double[] A, double[][] M, double[][][] C, int k, int[][] U, double[][] log_p, double[][][][] T_inv, GaussianMixtureModelsIncompleteSamples.GMM gmm, double[][] data, double[][][] R, double[] log_S)
void	_update(GaussianMixtureModelsIncompleteSamples.GMM gmm, double[] A, double[][] M, double[][][] C, int[] N, double[] B, double[] A2, double[][] M2, double[][][] C2, double[] N2, double[] B2, double w, boolean[] changeable_amp, boolean[] changeable_mean, boolean[] changeable_covar, GaussianMixtureModelsIncompleteSamples.Background background)
void	_update_snm(GaussianMixtureModelsIncompleteSamples.GMM gmm, int[] changeable, int[][] U, double N, boolean cleanup)
(package private) double	asinh(double x)
int[]	bincount(int[] indices, int minlength)
int[][][]	binSample(double[][] coords, int C)
double	chi2_cutoff(int D, double cutoff)
double[][][]	covar_callback_default(double[][] coords)
double[]	dirichletRnd(double[] ain, double[] m)
void	draw(Vector<double[][]> dataVec, Vector<double[][][]> covarVec, double[] updated_orig_size, Vector<double[]> omegaVec, GaussianMixtureModelsIncompleteSamples.GMM gmm, int obs_size, String sel_callback, boolean invert_sel, int orig_size, String covar_callback, GaussianMixtureModelsIncompleteSamples.Background background, Random rng)
void	drawWithNbh(double[][] samples, int[][] nbh, GaussianMixtureModelsIncompleteSamples.GMM gmm, int size, Random rng)
private double	erf(double x)
double	fit(int[][] U, GaussianMixtureModelsIncompleteSamples.GMM gmm, double[][] data, double[][][] covar, double[][][] R, String init_method, double w, double cutoff, String sel_callback, int oversampling, String covar_callback, GaussianMixtureModelsIncompleteSamples.Background background, double tol, int miniter, int maxiter, int[] frozen_amp, int[] frozen_mean, int[] frozen_covar, int split_n_merge, Random rng)
double	gamrnd(double a, double b)
double[]	getAll(double[][] coords)
double[]	getBox(double[][] coords)
double[]	getBoxWithHole(double[][] coords)
double[]	getCut(double[][] coords)
double[]	getHalf(double[][] coords)
double[]	getHole(double[][] coords)
double[]	getNoSel(double[][] coords)
double[]	getSelection(String sel_type, double[][] noisy, Random rng)
double[]	getSlopeSel(double[][] coords, Random rng)
boolean[]	GMMSel(double[][] coords, double[][][] covar, GaussianMixtureModelsIncompleteSamples.GMM sel_gmm, double cutoff_nd, Random rng)
void	initCube(GaussianMixtureModelsIncompleteSamples.GMM gmm, double w, Random rng)
void	initFromDataAtRandom(GaussianMixtureModelsIncompleteSamples.GMM gmm, double[][] data, double[][][] covar, double s, int[] k, Random rng)
void	initFromDataMinMax(GaussianMixtureModelsIncompleteSamples.GMM gmm, double[][] data, double[][][] covar, double s, int[] k, Random rng)
void	initFromKMeans(GaussianMixtureModelsIncompleteSamples.GMM gmm, double[][] data, Random rng)
boolean[]	insideComponent(int k, GaussianMixtureModelsIncompleteSamples.GMM gmm, double[][] coords, double[][][] covar, double cutoff)
double	logsum(double[] input)
double[]	logsum(double[][] input)
void	match1d(Vector<Integer> sub1Vec, Vector<Integer> sub2Vec, int[] arr1Input, int[] arr2, boolean presorted)
void	plotDifferences(double[][] orig, double[][] data, GaussianMixtureModelsIncompleteSamples.GMM[] gmms, GaussianMixtureModelsIncompleteSamples.GMM avg, double[] l)
void	plotResults(double[][] orig, double[][] data, GaussianMixtureModelsIncompleteSamples.GMM gmm, String description, double disp)
void	printResults(GaussianMixtureModelsIncompleteSamples.GMM gmm, String description)
void	runAlgorithm()	Actually runs the algorithm.
GaussianMixtureModelsIncompleteSamples.GMM	stack(GaussianMixtureModelsIncompleteSamples.GMM[] gmms, double[] weights)
GaussianMixtureModelsIncompleteSamples.GMM	stack_fit(GaussianMixtureModelsIncompleteSamples.GMM[] gmms, double[][] data, double[][][] covar, String init_callback, double w, double cutoff, String sel_callback, String covar_callack, GaussianMixtureModelsIncompleteSamples.Background bg, int L, double tol, Random rng)
void	test()
void	test_3D()

Methods inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

actionPerformed, addListener, addProgressChangeListener, calculateImageSize, calculatePrincipleAxis, computeElapsedTime, computeElapsedTime, convertIntoFloat, delinkProgressToAlgorithm, delinkProgressToAlgorithmMulti, displayError, errorCleanUp, finalize, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, generateProgressValues, getDestImage, getElapsedTime, getMask, getMaxProgressValue, getMinProgressValue, getNumberOfThreads, getProgress, getProgressChangeListener, getProgressChangeListeners, getProgressModulus, getProgressStep, getProgressValues, getSrcImage, isCompleted, isImage25D, isMultiThreadingEnabled, isRunningInSeparateThread, isThreadStopped, linkProgressToAlgorithm, linkProgressToAlgorithm, makeProgress, notifyListeners, removeListener, removeProgressChangeListener, run, setCompleted, setImage25D, setMask, setMaxProgressValue, setMinProgressValue, setMultiThreadingEnabled, setNumberOfThreads, setProgress, setProgressModulus, setProgressStep, setProgressValues, setProgressValues, setRunningInSeparateThread, setSrcImage, setStartTime, setThreadStopped, startMethod, windowActivated, windowClosed, windowClosing, windowDeactivated, windowDeiconified, windowIconified, windowOpened

Methods inherited from class java.lang.Thread

activeCount, checkAccess, clone, countStackFrames, currentThread, dumpStack, enumerate, getAllStackTraces, getContextClassLoader, getDefaultUncaughtExceptionHandler, getId, getName, getPriority, getStackTrace, getState, getThreadGroup, getUncaughtExceptionHandler, holdsLock, interrupt, interrupted, isAlive, isDaemon, isInterrupted, isVirtual, join, join, join, join, ofPlatform, ofVirtual, onSpinWait, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, sleep, start, startVirtualThread, stop, suspend, threadId, toString, yield

Methods inherited from class java.lang.Object

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

Field Details

K

private int K

D

private int D

covar_callback_default_arr

private double[][][] covar_callback_default_arr

Constructor Details

GaussianMixtureModelsIncompleteSamples

public GaussianMixtureModelsIncompleteSamples()

GaussianMixtureModelsIncompleteSamples

public GaussianMixtureModelsIncompleteSamples(int K,
 int D)

Method Details

test

public void test()

test_3D

public void test_3D()

GMMSel

public boolean[] GMMSel(double[][] coords,
 double[][][] covar,
 GaussianMixtureModelsIncompleteSamples.GMM sel_gmm,
 double cutoff_nd,
 Random rng)

insideComponent

public boolean[] insideComponent(int k,
 GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double[][] coords,
 double[][][] covar,
 double cutoff)

binSample

public int[][][] binSample(double[][] coords,
 int C)

drawWithNbh

public void drawWithNbh(double[][] samples,
 int[][] nbh,
 GaussianMixtureModelsIncompleteSamples.GMM gmm,
 int size,
 Random rng)

bincount

public int[] bincount(int[] indices,
 int minlength)

initCube

public void initCube(GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double w,
 Random rng)

dirichletRnd

public double[] dirichletRnd(double[] ain,
 double[] m)

gamrnd

public double gamrnd(double a,
 double b)

getSlopeSel

public double[] getSlopeSel(double[][] coords,
 Random rng)

getNoSel

public double[] getNoSel(double[][] coords)

printResults

public void printResults(GaussianMixtureModelsIncompleteSamples.GMM gmm,
 String description)

stack_fit

public GaussianMixtureModelsIncompleteSamples.GMM stack_fit(GaussianMixtureModelsIncompleteSamples.GMM[] gmms,
 double[][] data,
 double[][][] covar,
 String init_callback,
 double w,
 double cutoff,
 String sel_callback,
 String covar_callack,
 GaussianMixtureModelsIncompleteSamples.Background bg,
 int L,
 double tol,
 Random rng)

stack

public GaussianMixtureModelsIncompleteSamples.GMM stack(GaussianMixtureModelsIncompleteSamples.GMM[] gmms,
 double[] weights)

getSelection

public double[] getSelection(String sel_type,
 double[][] noisy,
 Random rng)

runAlgorithm

public void runAlgorithm()

Description copied from class: AlgorithmBase

Actually runs the algorithm. Implemented by inheriting algorithms.

Specified by:

runAlgorithm in class AlgorithmBase

logsum

public double logsum(double[] input)

logsum

public double[] logsum(double[][] input)

getBox

public double[] getBox(double[][] coords)

getHole

public double[] getHole(double[][] coords)

getBoxWithHole

public double[] getBoxWithHole(double[][] coords)

getCut

public double[] getCut(double[][] coords)

getAll

public double[] getAll(double[][] coords)

getHalf

public double[] getHalf(double[][] coords)

plotDifferences

public void plotDifferences(double[][] orig,
 double[][] data,
 GaussianMixtureModelsIncompleteSamples.GMM[] gmms,
 GaussianMixtureModelsIncompleteSamples.GMM avg,
 double[] l)

plotResults

public void plotResults(double[][] orig,
 double[][] data,
 GaussianMixtureModelsIncompleteSamples.GMM gmm,
 String description,
 double disp)

asinh

double asinh(double x)

fit

public double fit(int[][] U,
 GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double[][] data,
 double[][][] covar,
 double[][][] R,
 String init_method,
 double w,
 double cutoff,
 String sel_callback,
 int oversampling,
 String covar_callback,
 GaussianMixtureModelsIncompleteSamples.Background background,
 double tol,
 int miniter,
 int maxiter,
 int[] frozen_amp,
 int[] frozen_mean,
 int[] frozen_covar,
 int split_n_merge,
 Random rng)

_update_snm

public void _update_snm(GaussianMixtureModelsIncompleteSamples.GMM gmm,
 int[] changeable,
 int[][] U,
 double N,
 boolean cleanup)

_findSNMComponents

public void _findSNMComponents(int[] changing,
 boolean[] cleanup,
 GaussianMixtureModelsIncompleteSamples.GMM gmm,
 int[][] U,
 double[][] log_p,
 double[] log_S,
 double N)

_JS

public double _JS(int k,
 GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double[][] log_p,
 double[] log_S,
 int[][] U,
 double[] A)

match1d

public void match1d(Vector<Integer> sub1Vec,
 Vector<Integer> sub2Vec,
 int[] arr1Input,
 int[] arr2,
 boolean presorted)

_EM

public void _EM(double[] log_L,
 int[] N,
 double[] N2,
 GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double[][] log_p,
 int[][] U,
 double[][][][] T_inv,
 double[] log_S,
 double[][] data,
 double[][][] covar,
 double[][][] R,
 String sel_callback,
 int oversampling,
 String covar_callback,
 GaussianMixtureModelsIncompleteSamples.Background background,
 double[][] p_bg,
 double w,
 double cutoff,
 int miniter,
 int maxiter,
 double tol,
 String prefix,
 boolean[] changeable_amp,
 boolean[] changeable_mean,
 boolean[] changeable_covar,
 Random rng)

_EMstep

public void _EMstep(double[] log_L,
 int[] N,
 double[] N2,
 double[] N0update,
 GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double[][] log_p,
 int[][] U,
 double[][][][] T_inv,
 double[] log_S,
 double N0,
 double[][] data,
 double[][][] covar,
 double[][][] R,
 String sel_callback,
 double[] omega,
 int oversampling,
 String covar_callback,
 GaussianMixtureModelsIncompleteSamples.Background background,
 double[][] p_bg,
 double w,
 double cutoff,
 double tol,
 boolean[] changeable_amp,
 boolean[] changeable_mean,
 boolean[] changeable_covar,
 int it,
 Random rng)

_update

public void _update(GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double[] A,
 double[][] M,
 double[][][] C,
 int[] N,
 double[] B,
 double[] A2,
 double[][] M2,
 double[][][] C2,
 double[] N2,
 double[] B2,
 double w,
 boolean[] changeable_amp,
 boolean[] changeable_mean,
 boolean[] changeable_covar,
 GaussianMixtureModelsIncompleteSamples.Background background)

draw

public void draw(Vector<double[][]> dataVec,
 Vector<double[][][]> covarVec,
 double[] updated_orig_size,
 Vector<double[]> omegaVec,
 GaussianMixtureModelsIncompleteSamples.GMM gmm,
 int obs_size,
 String sel_callback,
 boolean invert_sel,
 int orig_size,
 String covar_callback,
 GaussianMixtureModelsIncompleteSamples.Background background,
 Random rng)

_drawGMM_BG

public void _drawGMM_BG(Vector<double[][]> data2Vec,
 Vector<double[][][]> covar2Vec,
 GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double size,
 String covar_callback,
 GaussianMixtureModelsIncompleteSamples.Background background,
 Random rng)

_Mstep

public void _Mstep(double[] A,
 double[][] M,
 double[][][] C,
 double[] B,
 GaussianMixtureModelsIncompleteSamples.GMM gmm,
 int[][] U,
 double[][] log_p,
 double[][][][] T_inv,
 double[] log_S,
 double[][] data,
 double[][][] covar,
 double[][][] R,
 double[][] p_bg)

_Msums

public void _Msums(double[] A,
 double[][] M,
 double[][][] C,
 int k,
 int[][] U,
 double[][] log_p,
 double[][][][] T_inv,
 GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double[][] data,
 double[][][] R,
 double[] log_S)

_Estep

public double _Estep(GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double[][] log_p,
 int[][] U,
 double[][][][] T_inv,
 double[] log_S,
 double[][] data,
 double[][][] covar,
 double[][][] R,
 double[] omega,
 GaussianMixtureModelsIncompleteSamples.Background background,
 double[][] p_bg,
 double cutoff,
 int it,
 Random rng)

erf

private double erf(double x)

_Esum

public void _Esum(double[][] log_p,
 double[][][][] T_inv,
 int k,
 int[][] U,
 GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double[][] data,
 double[][][] covar,
 double[][][] R,
 double cutoff)

chi2_cutoff

public double chi2_cutoff(int D,
 double cutoff)

covar_callback_default

public double[][][] covar_callback_default(double[][] coords)

initFromDataAtRandom

public void initFromDataAtRandom(GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double[][] data,
 double[][][] covar,
 double s,
 int[] k,
 Random rng)

initFromKMeans

public void initFromKMeans(GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double[][] data,
 Random rng)

initFromDataMinMax

public void initFromDataMinMax(GaussianMixtureModelsIncompleteSamples.GMM gmm,
 double[][] data,
 double[][][] covar,
 double s,
 int[] k,
 Random rng)