Examples with GenerateReducedDataOp org.vcell.vmicro.op.GenerateReducedDataOp used on opensource projects

Example 1 with GenerateReducedDataOp

use of org.vcell.vmicro.op.GenerateReducedDataOp in project vcell by virtualcell.

the class GenerateReducedData method compute0.

@Override
protected void compute0(TaskContext context, final ClientTaskStatusSupport clientTaskStatusSupport) throws Exception {
    // get input
    ROI[] rois = context.getData(imageDataROIs);
    ImageTimeSeries<? extends Image> simData = (ImageTimeSeries<? extends Image>) context.getData(imageTimeSeries);
    // do op
    GenerateReducedDataOp op = new GenerateReducedDataOp();
    RowColumnResultSet reducedData = op.generateReducedData(simData, rois);
    // set output
    context.setData(reducedROIData, reducedData);
}

Example 2 with GenerateReducedDataOp

use of org.vcell.vmicro.op.GenerateReducedDataOp 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();
    }
}

Example 3 with GenerateReducedDataOp

use of org.vcell.vmicro.op.GenerateReducedDataOp 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);
    }
}

Example 4 with GenerateReducedDataOp

use of org.vcell.vmicro.op.GenerateReducedDataOp in project vcell by virtualcell.

the class VFrapProcess method compute.

public static VFrapProcessResults compute(ImageTimeSeries rawTimeSeriesImages, double bleachThreshold, double cellThreshold, LocalWorkspace localWorkspace, ClientTaskStatusSupport clientTaskStatusSupport) throws Exception {
    GenerateCellROIsFromRawFrapTimeSeriesOp generateCellROIs = new GenerateCellROIsFromRawFrapTimeSeriesOp();
    GeometryRoisAndBleachTiming geometryAndTiming = generateCellROIs.generate(rawTimeSeriesImages, cellThreshold);
    GenerateNormalizedFrapDataOp generateNormalizedFrapData = new GenerateNormalizedFrapDataOp();
    NormalizedFrapDataResults normalizedFrapResults = generateNormalizedFrapData.generate(rawTimeSeriesImages, geometryAndTiming.backgroundROI_2D, geometryAndTiming.indexOfFirstPostbleach);
    GenerateBleachRoiOp generateROIs = new GenerateBleachRoiOp();
    ROI bleachROI = generateROIs.generateBleachRoi(normalizedFrapResults.normalizedFrapData.getAllImages()[0], geometryAndTiming.cellROI_2D, bleachThreshold);
    GenerateDependentImageROIsOp generateDependentROIs = new GenerateDependentImageROIsOp();
    ROI[] dataROIs = generateDependentROIs.generate(geometryAndTiming.cellROI_2D, bleachROI);
    NormalizedSampleFunction[] roiSampleFunctions = new NormalizedSampleFunction[dataROIs.length];
    for (int i = 0; i < dataROIs.length; i++) {
        roiSampleFunctions[i] = NormalizedSampleFunction.fromROI(dataROIs[i]);
    }
    GenerateReducedDataOp generateReducedNormalizedData = new GenerateReducedDataOp();
    RowColumnResultSet reducedData = generateReducedNormalizedData.generateReducedData(normalizedFrapResults.normalizedFrapData, roiSampleFunctions);
    ComputeMeasurementErrorOp computeMeasurementError = new ComputeMeasurementErrorOp();
    RowColumnResultSet measurementError = computeMeasurementError.computeNormalizedMeasurementError(roiSampleFunctions, geometryAndTiming.indexOfFirstPostbleach, rawTimeSeriesImages, normalizedFrapResults.prebleachAverage, clientTaskStatusSupport);
    GenerateTrivial2DPsfOp psf_2D = new GenerateTrivial2DPsfOp();
    UShortImage psf = psf_2D.generateTrivial2D_Psf();
    // RunRefSimulationOp runRefSimulationFull = new RunRefSimulationOp();
    // GenerateReducedROIDataOp generateReducedRefSimData = new GenerateReducedROIDataOp();
    RunRefSimulationFastOp runRefSimulationFast = new RunRefSimulationFastOp();
    RowColumnResultSet refData = runRefSimulationFast.runRefSimFast(geometryAndTiming.cellROI_2D, normalizedFrapResults.normalizedFrapData, dataROIs, psf, localWorkspace, clientTaskStatusSupport);
    final double refDiffusionRate = 1.0;
    double[] refSimTimePoints = refData.extractColumn(0);
    int numRois = refData.getDataColumnCount() - 1;
    int numRefSimTimes = refData.getRowCount();
    double[][] refSimData = new double[numRois][numRefSimTimes];
    for (int roi = 0; roi < numRois; roi++) {
        double[] roiData = refData.extractColumn(roi + 1);
        for (int t = 0; t < numRefSimTimes; t++) {
            refSimData[roi][t] = roiData[t];
        }
    }
    ErrorFunction errorFunction = new ErrorFunctionNoiseWeightedL2();
    OptModelOneDiff optModelOneDiff = new OptModelOneDiff(refSimData, refSimTimePoints, refDiffusionRate);
    Generate2DOptContextOp generate2DOptContextOne = new Generate2DOptContextOp();
    OptContext optContextOneDiff = generate2DOptContextOne.generate2DOptContext(optModelOneDiff, reducedData, measurementError, errorFunction);
    RunProfileLikelihoodGeneralOp runProfileLikelihoodOne = new RunProfileLikelihoodGeneralOp();
    ProfileData[] profileDataOne = runProfileLikelihoodOne.runProfileLikihood(optContextOneDiff, clientTaskStatusSupport);
    // OptModelTwoDiffWithoutPenalty optModelTwoDiffWithoutPenalty = new OptModelTwoDiffWithoutPenalty(refSimData, refSimTimePoints, refDiffusionRate);
    // Generate2DOptContextOp generate2DOptContextTwoWithoutPenalty = new Generate2DOptContextOp();
    // OptContext optContextTwoDiffWithoutPenalty = generate2DOptContextTwoWithoutPenalty.generate2DOptContext(optModelTwoDiffWithoutPenalty, reducedData, measurementError);
    // RunProfileLikelihoodGeneralOp runProfileLikelihoodTwoWithoutPenalty = new RunProfileLikelihoodGeneralOp();
    // ProfileData[] profileDataTwoWithoutPenalty = runProfileLikelihoodTwoWithoutPenalty.runProfileLikihood(optContextTwoDiffWithoutPenalty, clientTaskStatusSupport);
    OptModelTwoDiffWithPenalty optModelTwoDiffWithPenalty = new OptModelTwoDiffWithPenalty(refSimData, refSimTimePoints, refDiffusionRate);
    Generate2DOptContextOp generate2DOptContextTwoWithPenalty = new Generate2DOptContextOp();
    OptContext optContextTwoDiffWithPenalty = generate2DOptContextTwoWithPenalty.generate2DOptContext(optModelTwoDiffWithPenalty, reducedData, measurementError, errorFunction);
    RunProfileLikelihoodGeneralOp runProfileLikelihoodTwoWithPenalty = new RunProfileLikelihoodGeneralOp();
    ProfileData[] profileDataTwoWithPenalty = runProfileLikelihoodTwoWithPenalty.runProfileLikihood(optContextTwoDiffWithPenalty, clientTaskStatusSupport);
    // 
    // SLOW WAY
    // 
    // runRefSimulationFull.cellROI_2D,generateCellROIs.cellROI_2D);
    // runRefSimulationFull.normalizedTimeSeries,generateNormalizedFrapData.normalizedFrapData);
    // workflow.addTask(runRefSimulationFull);
    // generateReducedRefSimData.imageTimeSeries,runRefSimulationFull.refSimTimeSeries);
    // generateReducedRefSimData.imageDataROIs,generateDependentROIs.imageDataROIs);
    // workflow.addTask(generateReducedRefSimData);
    // DataHolder<RowColumnResultSet> reducedROIData = generateReducedRefSimData.reducedROIData;
    // DataHolder<Double> refSimDiffusionRate = runRefSimulationFull.refSimDiffusionRate;
    VFrapProcessResults results = new VFrapProcessResults(dataROIs, geometryAndTiming.cellROI_2D, bleachROI, normalizedFrapResults.normalizedFrapData, reducedData, profileDataOne, profileDataTwoWithPenalty);
    return results;
}

Example 5 with GenerateReducedDataOp

use of org.vcell.vmicro.op.GenerateReducedDataOp 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);
}