use of org.vcell.vmicro.op.display.DisplayTimeSeriesOp in project vcell by virtualcell.
the class BrownianDynamicsTest method main.
public static void main(String[] args) {
try {
Options commandOptions = new Options();
Option noiseOption = new Option(OPTION_NOISE, false, "sampled images use Poisson statistics for photons, default is to count particles");
commandOptions.addOption(noiseOption);
Option psfOption = new Option(OPTION_PSF, false, "sampled images are convolve with microscope psf, default is to bin");
commandOptions.addOption(psfOption);
Option imageFileOption = new Option(OPTION_IMAGEFILE, true, "file to store image time series");
imageFileOption.setArgName("filename");
imageFileOption.setValueSeparator('=');
commandOptions.addOption(imageFileOption);
Option plotFileOption = new Option(OPTION_PLOTFILE, true, "file to store CSV time series (reduced data for ROIs)");
plotFileOption.setArgName("filename");
plotFileOption.setValueSeparator('=');
commandOptions.addOption(plotFileOption);
Option displayImageOption = new Option(OPTION_DISPLAY_IMAGE, false, "display image time series");
commandOptions.addOption(displayImageOption);
Option displayPlotOption = new Option(OPTION_DISPLAY_PLOT, false, "display plot of bleach roi");
commandOptions.addOption(displayPlotOption);
Option extentOption = new Option(OPTION_EXTENT, true, "extent of entire domain (default " + DEFAULT_EXTENT_SCALE + ")");
extentOption.setArgName("extent");
extentOption.setValueSeparator('=');
commandOptions.addOption(extentOption);
Option imageSizeOption = new Option(OPTION_IMAGE_SIZE, true, "num pixels in x and y (default " + DEFAULT_IMAGE_SIZE + ")");
imageSizeOption.setArgName("numPixels");
imageSizeOption.setValueSeparator('=');
commandOptions.addOption(imageSizeOption);
Option numParticlesOption = new Option(OPTION_NUM_PARTICLES, true, "num particles (default " + DEFAULT_NUM_PARTICLES + ")");
numParticlesOption.setArgName("num");
numParticlesOption.setValueSeparator('=');
commandOptions.addOption(numParticlesOption);
Option diffusionOption = new Option(OPTION_DIFFUSION, true, "diffusion rate (default " + DEFAULT_DIFFUSION + ")");
diffusionOption.setArgName("rate");
diffusionOption.setValueSeparator('=');
commandOptions.addOption(diffusionOption);
Option bleachRadiusOption = new Option(OPTION_BLEACH_RADIUS, true, "bleach radius (default " + DEFAULT_BLEACH_RADIUS + ")");
bleachRadiusOption.setArgName("radius");
bleachRadiusOption.setValueSeparator('=');
commandOptions.addOption(bleachRadiusOption);
Option psfRadiusOption = new Option(OPTION_PSF_RADIUS, true, "psf radius (default " + DEFAULT_PSF_RADIUS + ")");
psfRadiusOption.setArgName("radius");
psfRadiusOption.setValueSeparator('=');
commandOptions.addOption(psfRadiusOption);
Option bleachDurationOption = new Option(OPTION_BLEACH_DURATION, true, "psf radius (default " + DEFAULT_BLEACH_DURATION + ")");
bleachDurationOption.setArgName("duration");
bleachDurationOption.setValueSeparator('=');
commandOptions.addOption(bleachDurationOption);
Option endTimeOption = new Option(OPTION_ENDTIME, true, "end time (default " + DEFAULT_ENDTIME + ")");
endTimeOption.setArgName("time");
endTimeOption.setValueSeparator('=');
commandOptions.addOption(endTimeOption);
CommandLine cmdLine = null;
try {
Parser parser = new BasicParser();
cmdLine = parser.parse(commandOptions, args);
} catch (ParseException e1) {
e1.printStackTrace();
HelpFormatter hf = new HelpFormatter();
hf.printHelp("BrownianDynamicsTest", commandOptions);
System.exit(2);
}
boolean bNoise = cmdLine.hasOption(OPTION_NOISE);
boolean bConvolve = cmdLine.hasOption(OPTION_PSF);
File imageFile = null;
if (cmdLine.hasOption(OPTION_IMAGEFILE)) {
imageFile = new File(cmdLine.getOptionValue(OPTION_IMAGEFILE));
}
File plotFile = null;
if (cmdLine.hasOption(OPTION_PLOTFILE)) {
plotFile = new File(cmdLine.getOptionValue(OPTION_PLOTFILE));
}
boolean bDisplayImage = cmdLine.hasOption(OPTION_DISPLAY_IMAGE);
boolean bDisplayPlot = cmdLine.hasOption(OPTION_DISPLAY_PLOT);
double extentScale = DEFAULT_EXTENT_SCALE;
if (cmdLine.hasOption(OPTION_EXTENT)) {
extentScale = Double.parseDouble(cmdLine.getOptionValue(OPTION_EXTENT));
}
int imageSize = DEFAULT_IMAGE_SIZE;
if (cmdLine.hasOption(OPTION_IMAGE_SIZE)) {
imageSize = Integer.parseInt(cmdLine.getOptionValue(OPTION_IMAGE_SIZE));
}
int numParticles = DEFAULT_NUM_PARTICLES;
if (cmdLine.hasOption(OPTION_NUM_PARTICLES)) {
numParticles = Integer.parseInt(cmdLine.getOptionValue(OPTION_NUM_PARTICLES));
}
double diffusionRate = DEFAULT_DIFFUSION;
if (cmdLine.hasOption(OPTION_DIFFUSION)) {
diffusionRate = Double.parseDouble(cmdLine.getOptionValue(OPTION_DIFFUSION));
}
double bleachRadius = DEFAULT_BLEACH_RADIUS;
if (cmdLine.hasOption(OPTION_BLEACH_RADIUS)) {
bleachRadius = Double.parseDouble(cmdLine.getOptionValue(OPTION_BLEACH_RADIUS));
}
double psfRadius = DEFAULT_PSF_RADIUS;
if (cmdLine.hasOption(OPTION_PSF_RADIUS)) {
psfRadius = Double.parseDouble(cmdLine.getOptionValue(OPTION_PSF_RADIUS));
}
double bleachDuration = DEFAULT_BLEACH_DURATION;
if (cmdLine.hasOption(OPTION_BLEACH_DURATION)) {
bleachDuration = Double.parseDouble(cmdLine.getOptionValue(OPTION_BLEACH_DURATION));
}
double endTime = DEFAULT_ENDTIME;
if (cmdLine.hasOption(OPTION_ENDTIME)) {
endTime = Double.parseDouble(cmdLine.getOptionValue(OPTION_BLEACH_DURATION));
}
//
// hard coded parameters
//
Origin origin = new Origin(0, 0, 0);
Extent extent = new Extent(extentScale, extentScale, 1);
int numX = imageSize;
int numY = imageSize;
double psfVar = psfRadius * psfRadius;
BrownianDynamicsTest test = new BrownianDynamicsTest();
ImageTimeSeries<UShortImage> rawTimeSeries = test.generateTestData(origin, extent, numX, numY, numParticles, diffusionRate, psfVar, bleachRadius * bleachRadius, bNoise, bConvolve, bleachDuration, endTime);
//
if (imageFile != null) {
new ExportRawTimeSeriesToVFrapOp().exportToVFRAP(imageFile, rawTimeSeries, null);
}
//
if (bDisplayImage) {
new DisplayTimeSeriesOp().displayImageTimeSeries(rawTimeSeries, "time series", null);
}
//
// compute reduced data if needed for plotting or saving.
//
RowColumnResultSet reducedData = null;
if (bDisplayPlot || plotFile != null) {
double muX = origin.getX() + 0.5 * extent.getX();
double muY = origin.getY() + 0.5 * extent.getY();
double sigma = Math.sqrt(psfVar);
NormalizedSampleFunction gaussian = NormalizedSampleFunction.fromGaussian("psf", origin, extent, new ISize(numX, numY, 1), muX, muY, sigma);
reducedData = new GenerateReducedDataOp().generateReducedData(rawTimeSeries, new NormalizedSampleFunction[] { gaussian });
}
//
if (plotFile != null) {
FileOutputStream fos = new FileOutputStream(plotFile);
new CSV().exportTo(fos, reducedData);
}
if (bDisplayPlot) {
new DisplayPlotOp().displayPlot(reducedData, "bleached roi", null);
}
} catch (Exception e) {
e.printStackTrace();
}
}
use of org.vcell.vmicro.op.display.DisplayTimeSeriesOp in project vcell by virtualcell.
the class PhotoactivationExperimentTest method analyzePhotoactivation.
/**
* Fits raw image time series data to uniform disk models (with Guassian or Uniform fluorescence).
*
* @param rawTimeSeriesImages
* @param localWorkspace
* @throws Exception
*/
private static void analyzePhotoactivation(ImageTimeSeries<UShortImage> rawTimeSeriesImages, LocalWorkspace localWorkspace) throws Exception {
//
// correct the timestamps (1 per second).
//
double[] timeStamps = rawTimeSeriesImages.getImageTimeStamps();
for (int i = 0; i < timeStamps.length; i++) {
timeStamps[i] = i;
}
new DisplayTimeSeriesOp().displayImageTimeSeries(rawTimeSeriesImages, "raw images", (WindowListener) null);
ImageTimeSeries<UShortImage> blurredRaw = blurTimeSeries(rawTimeSeriesImages);
new DisplayTimeSeriesOp().displayImageTimeSeries(blurredRaw, "blurred raw images", (WindowListener) null);
double cellThreshold = 0.4;
GeometryRoisAndActivationTiming cellROIresults = new GenerateCellROIsFromRawPhotoactivationTimeSeriesOp().generate(blurredRaw, cellThreshold);
ROI backgroundROI = cellROIresults.backgroundROI_2D;
ROI cellROI = cellROIresults.cellROI_2D;
int indexOfFirstPostactivation = cellROIresults.indexOfFirstPostactivation;
boolean backgroundSubtract = false;
boolean normalizeByPreActivation = false;
NormalizedPhotoactivationDataResults normResults = new GenerateNormalizedPhotoactivationDataOp().generate(rawTimeSeriesImages, backgroundROI, indexOfFirstPostactivation, backgroundSubtract, normalizeByPreActivation);
ImageTimeSeries<FloatImage> normalizedTimeSeries = normResults.normalizedPhotoactivationData;
FloatImage preactivationAvg = normResults.preactivationAverageImage;
FloatImage normalizedPostactivation = normalizedTimeSeries.getAllImages()[0];
new DisplayTimeSeriesOp().displayImageTimeSeries(normalizedTimeSeries, "normalized images", (WindowListener) null);
//
// create a single bleach ROI by thresholding
//
double activatedThreshold = 1000;
ROI activatedROI = new GenerateActivationRoiOp().generateActivatedRoi(blurredRaw.getAllImages()[indexOfFirstPostactivation], cellROI, activatedThreshold);
new DisplayImageOp().displayImage(activatedROI.getRoiImages()[0], "activated roi", null);
new DisplayImageOp().displayImage(cellROI.getRoiImages()[0], "cell roi", null);
new DisplayImageOp().displayImage(backgroundROI.getRoiImages()[0], "background roi", null);
{
//
// only use bleach ROI for fitting etc.
//
NormalizedSampleFunction[] dataROIs = new NormalizedSampleFunction[] { NormalizedSampleFunction.fromROI(activatedROI) };
//
// get reduced data and errors for each ROI
//
RowColumnResultSet reducedData = new GenerateReducedDataOp().generateReducedData(normalizedTimeSeries, dataROIs);
RowColumnResultSet measurementErrors = new ComputeMeasurementErrorOp().computeNormalizedMeasurementError(dataROIs, indexOfFirstPostactivation, rawTimeSeriesImages, preactivationAvg, null);
DisplayPlotOp displayReducedData = new DisplayPlotOp();
displayReducedData.displayPlot(reducedData, "reduced data", null);
DisplayPlotOp displayMeasurementError = new DisplayPlotOp();
displayMeasurementError.displayPlot(measurementErrors, "measurement error", null);
//
// 2 parameter uniform disk model
//
Parameter tau = new Parameter("tau", 0.001, 200.0, 1.0, 0.1);
Parameter f_init = new Parameter("f_init", 0.5, 4000, 1.0, 1.0);
Parameter f_final = new Parameter("f_final", 0.01, 4000, 1.0, 0.5);
Parameter[] parameters = new Parameter[] { tau, f_init, f_final };
OptModel optModel = new OptModel("photoactivation (activated roi)", parameters) {
@Override
public double[][] getSolution0(double[] newParams, double[] solutionTimePoints) {
double tau = newParams[0];
double max = newParams[1];
double offset = newParams[2];
double[][] solution = new double[1][solutionTimePoints.length];
for (int i = 0; i < solution[0].length; i++) {
double t = solutionTimePoints[i];
solution[0][i] = offset + (max - offset) * Math.exp(-t / tau);
}
return solution;
}
@Override
public double getPenalty(double[] parameters2) {
return 0;
}
};
ErrorFunction errorFunction = new ErrorFunctionNoiseWeightedL2();
OptContext uniformDisk2Context = new Generate2DOptContextOp().generate2DOptContext(optModel, reducedData, measurementErrors, errorFunction);
new DisplayInteractiveModelOp().displayOptModel(uniformDisk2Context, dataROIs, localWorkspace, "nonspatial photoactivation - activated ROI only", null);
}
{
//
// only activation ROI for chemistry, cellROI for bleaching
//
NormalizedSampleFunction[] dataROIs = new NormalizedSampleFunction[] { NormalizedSampleFunction.fromROI(activatedROI), NormalizedSampleFunction.fromROI(cellROI) };
//
// get reduced data and errors for each ROI
//
RowColumnResultSet reducedData = new GenerateReducedDataOp().generateReducedData(normalizedTimeSeries, dataROIs);
RowColumnResultSet measurementErrors = new ComputeMeasurementErrorOp().computeNormalizedMeasurementError(dataROIs, indexOfFirstPostactivation, rawTimeSeriesImages, preactivationAvg, null);
DisplayPlotOp displayReducedData = new DisplayPlotOp();
displayReducedData.displayPlot(reducedData, "reduced data (2)", null);
DisplayPlotOp displayMeasurementError = new DisplayPlotOp();
displayMeasurementError.displayPlot(measurementErrors, "measurement error (2)", null);
//
// 2 parameter uniform disk model
//
Parameter tau_active = new Parameter("tau_active", 0.001, 200.0, 1.0, 0.1);
Parameter f_active_init = new Parameter("f_active_init", 0.5, 4000, 1.0, 1.0);
Parameter f_active_amplitude = new Parameter("f_active_amplitude", 0.01, 4000, 1.0, 0.5);
Parameter f_cell_init = new Parameter("f_cell_init", 0.01, 4000, 1.0, 0.1);
Parameter f_cell_amplitude = new Parameter("f_cell_amplitude", 0.01, 4000, 1.0, 0.1);
Parameter tau_cell = new Parameter("tau_cell", 0.00001, 200, 1.0, 1);
Parameter[] parameters = new Parameter[] { tau_active, f_active_init, f_active_amplitude, tau_cell, f_cell_init, f_cell_amplitude };
OptModel optModel = new OptModel("photoactivation (activated and cell rois)", parameters) {
@Override
public double[][] getSolution0(double[] newParams, double[] solutionTimePoints) {
double tau_active = newParams[0];
double max_active = newParams[1];
double amplitude_active = newParams[2];
double tau_cell = newParams[3];
double max_cell = newParams[4];
double amplitude_cell = newParams[5];
final int ACTIVE_ROI = 0;
final int CELL_ROI = 1;
final int NUM_ROIS = 2;
double[][] solution = new double[NUM_ROIS][solutionTimePoints.length];
for (int i = 0; i < solution[0].length; i++) {
double t = solutionTimePoints[i];
solution[ACTIVE_ROI][i] = (max_active - amplitude_active) + (amplitude_active) * Math.exp(-t / tau_active) * Math.exp(-t / tau_cell);
solution[CELL_ROI][i] = (max_cell - amplitude_cell) + (amplitude_cell) * Math.exp(-t / tau_cell);
}
return solution;
}
@Override
public double getPenalty(double[] parameters2) {
return 0;
}
};
ErrorFunctionNoiseWeightedL2 errorFunction = new ErrorFunctionNoiseWeightedL2();
OptContext uniformDisk2Context = new Generate2DOptContextOp().generate2DOptContext(optModel, reducedData, measurementErrors, errorFunction);
new DisplayInteractiveModelOp().displayOptModel(uniformDisk2Context, dataROIs, localWorkspace, "nonspatial photoactivation - activated and cell ROIs", null);
}
}
use of org.vcell.vmicro.op.display.DisplayTimeSeriesOp in project vcell by virtualcell.
the class VFrapProcess method main.
public static void main(String[] args) {
try {
File baseDir = new File(".");
// File baseDir = new File("/Users/schaff/Documents/workspace/VCell_5.4");
// initialize computing environment
//
File workingDirectory = new File(baseDir, "workingDir");
LocalWorkspace localWorkspace = new LocalWorkspace(workingDirectory);
//
// import raw image time series data from VFRAP file format (can have noise, background, etc ... can be actual microscopy data)
//
ClientTaskStatusSupport progressListener = new ClientTaskStatusSupport() {
String message = "";
int progress = 0;
@Override
public void setProgress(int progress) {
this.progress = progress;
}
@Override
public void setMessage(String message) {
this.message = message;
}
@Override
public boolean isInterrupted() {
return false;
}
@Override
public int getProgress() {
return progress;
}
@Override
public void addProgressDialogListener(ProgressDialogListener progressDialogListener) {
}
};
//
// generate fake data (and save?)
//
// ImageTimeSeries<UShortImage> simulatedFluorescence = generateFakeData(localWorkspace, progressListener);
// new ExportRawTimeSeriesToVFrapOp().exportToVFRAP(vfrapFile, simulatedFluorescence, null);
//
// analyze raw data (from file?) using Keyworthy method.
//
File vfrapFile = new File(baseDir, "vfrapPaper/rawData/sim3/workflow.txt.save");
ImageTimeSeries<UShortImage> fluorTimeSeriesImages = new ImportRawTimeSeriesFromVFrapOp().importRawTimeSeriesFromVFrap(vfrapFile);
VFrapProcessResults results = compute(fluorTimeSeriesImages, 0.85, 0.4, localWorkspace, progressListener);
new DisplayTimeSeriesOp().displayImageTimeSeries(fluorTimeSeriesImages, "raw data", null);
new DisplayImageOp().displayImage(results.cellROI_2D.getRoiImages()[0], "cell ROI", null);
new DisplayImageOp().displayImage(results.bleachROI_2D.getRoiImages()[0], "bleach ROI", null);
new DisplayDependentROIsOp().displayDependentROIs(results.imageDataROIs, results.cellROI_2D, "data rois", null);
new DisplayTimeSeriesOp().displayImageTimeSeries(results.normalizedTimeSeries, "normalized data", null);
new DisplayProfileLikelihoodPlotsOp().displayProfileLikelihoodPlots(results.profileDataOne, "one fluorescent pool", null);
new DisplayProfileLikelihoodPlotsOp().displayProfileLikelihoodPlots(results.profileDataTwoWithPenalty, "too pools", null);
} catch (Exception e) {
e.printStackTrace(System.out);
}
}
use of org.vcell.vmicro.op.display.DisplayTimeSeriesOp in project vcell by virtualcell.
the class DisplayTimeSeries method compute0.
@Override
protected void compute0(TaskContext context, final ClientTaskStatusSupport clientTaskStatusSupport) throws Exception {
// set input
ImageTimeSeries<Image> imageDataset = context.getData(imageTimeSeries);
String titleString = "no title - not connected";
titleString = context.getDataWithDefault(title, "no title");
WindowListener listener = null;
// do op
DisplayTimeSeriesOp op = new DisplayTimeSeriesOp();
op.displayImageTimeSeries(imageDataset, titleString, listener);
// set output
context.setData(displayed, true);
}
use of org.vcell.vmicro.op.display.DisplayTimeSeriesOp in project vcell by virtualcell.
the class KenworthyWorkflowTest method analyzeKeyworthy.
/**
* Fits raw image time series data to uniform disk models (with Guassian or Uniform fluorescence).
*
* @param rawTimeSeriesImages
* @param localWorkspace
* @throws Exception
*/
private static void analyzeKeyworthy(ImageTimeSeries<UShortImage> rawTimeSeriesImages, LocalWorkspace localWorkspace) throws Exception {
new DisplayTimeSeriesOp().displayImageTimeSeries(rawTimeSeriesImages, "raw images", (WindowListener) null);
double cellThreshold = 0.5;
GeometryRoisAndBleachTiming cellROIresults = new GenerateCellROIsFromRawFrapTimeSeriesOp().generate(rawTimeSeriesImages, cellThreshold);
ROI backgroundROI = cellROIresults.backgroundROI_2D;
ROI cellROI = cellROIresults.cellROI_2D;
int indexOfFirstPostbleach = cellROIresults.indexOfFirstPostbleach;
new DisplayImageOp().displayImage(backgroundROI.getRoiImages()[0], "background ROI", null);
new DisplayImageOp().displayImage(cellROI.getRoiImages()[0], "cell ROI", null);
NormalizedFrapDataResults normResults = new GenerateNormalizedFrapDataOp().generate(rawTimeSeriesImages, backgroundROI, indexOfFirstPostbleach);
ImageTimeSeries<FloatImage> normalizedTimeSeries = normResults.normalizedFrapData;
FloatImage prebleachAvg = normResults.prebleachAverage;
FloatImage normalizedPostbleach = normalizedTimeSeries.getAllImages()[0];
new DisplayTimeSeriesOp().displayImageTimeSeries(normalizedTimeSeries, "normalized images", (WindowListener) null);
//
// create a single bleach ROI by thresholding
//
double bleachThreshold = 0.80;
ROI bleachROI = new GenerateBleachRoiOp().generateBleachRoi(normalizedPostbleach, cellROI, bleachThreshold);
//
// only use bleach ROI for fitting etc.
//
// ROI[] dataROIs = new ROI[] { bleachROI };
//
// fit 2D Gaussian to normalized data to determine center, radius and K factor of bleach (assuming exp(-exp
//
FitBleachSpotOpResults fitSpotResults = new FitBleachSpotOp().fit(NormalizedSampleFunction.fromROI(bleachROI), normalizedTimeSeries.getAllImages()[0]);
double bleachFactorK_GaussianFit = fitSpotResults.bleachFactorK_GaussianFit;
double bleachRadius_GaussianFit = fitSpotResults.bleachRadius_GaussianFit;
double bleachRadius_ROI = fitSpotResults.bleachRadius_ROI;
double centerX_GaussianFit = fitSpotResults.centerX_GaussianFit;
double centerX_ROI = fitSpotResults.centerX_ROI;
double centerY_GaussianFit = fitSpotResults.centerY_GaussianFit;
double centerY_ROI = fitSpotResults.centerY_ROI;
NormalizedSampleFunction[] sampleFunctions = new NormalizedSampleFunction[] { NormalizedSampleFunction.fromROI(bleachROI) };
//
// get reduced data and errors for each ROI
//
RowColumnResultSet reducedData = new GenerateReducedDataOp().generateReducedData(normalizedTimeSeries, sampleFunctions);
RowColumnResultSet measurementErrors = new ComputeMeasurementErrorOp().computeNormalizedMeasurementError(sampleFunctions, indexOfFirstPostbleach, rawTimeSeriesImages, prebleachAvg, null);
ErrorFunction errorFunction = new ErrorFunctionKenworthy(reducedData);
//
// 2 parameter uniform disk model
//
OptModel uniformDisk2OptModel = new OptModelKenworthyUniformDisk2P(bleachRadius_ROI);
String title_u2 = "Uniform Disk Model - 2 parameters, (Rn=" + bleachRadius_ROI + ")";
OptContext uniformDisk2Context = new Generate2DOptContextOp().generate2DOptContext(uniformDisk2OptModel, reducedData, measurementErrors, errorFunction);
new DisplayInteractiveModelOp().displayOptModel(uniformDisk2Context, sampleFunctions, localWorkspace, title_u2, null);
//
// 3 parameter uniform disk model
//
OptModel uniformDisk3OptModel = new OptModelKenworthyUniformDisk3P(bleachRadius_ROI);
OptContext uniformDisk3Context = new Generate2DOptContextOp().generate2DOptContext(uniformDisk3OptModel, reducedData, measurementErrors, errorFunction);
String title_u3 = "Uniform Disk Model - 3 parameters, (Rn=" + bleachRadius_ROI + ")";
new DisplayInteractiveModelOp().displayOptModel(uniformDisk3Context, sampleFunctions, localWorkspace, title_u3, null);
//
// GaussianFit parameter uniform disk model
//
FloatImage prebleachBleachAreaImage = new FloatImage(prebleachAvg);
// mask-out all but the bleach area
prebleachBleachAreaImage.and(bleachROI.getRoiImages()[0]);
double prebleachAvgInROI = prebleachBleachAreaImage.getImageStatistics().meanValue;
OptModel gaussian2OptModel = new OptModelKenworthyGaussian(prebleachAvgInROI, bleachFactorK_GaussianFit, bleachRadius_GaussianFit, bleachRadius_ROI);
OptContext gaussianDisk2Context = new Generate2DOptContextOp().generate2DOptContext(gaussian2OptModel, reducedData, measurementErrors, errorFunction);
String title_g2 = "Gaussian Disk Model - 2 parameters (prebleach=" + prebleachAvgInROI + ",K=" + bleachFactorK_GaussianFit + ",Re=" + bleachRadius_GaussianFit + ",Rnom=" + bleachRadius_ROI + ")";
new DisplayInteractiveModelOp().displayOptModel(gaussianDisk2Context, sampleFunctions, localWorkspace, title_g2, null);
}
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