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

Example 1 with RunProfileLikelihoodGeneralOp

use of org.vcell.vmicro.op.RunProfileLikelihoodGeneralOp 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 2 with RunProfileLikelihoodGeneralOp

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

the class KenworthyParticleTest 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, RowColumnResultSet reducedData, 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 RowColumnResultSet(new String[] { reducedData.getColumnDescriptions()[0].getName(), reducedData.getColumnDescriptions()[1].getName() });
    for (int i = 0; i < reducedData.getRowCount(); i++) {
        double[] row = new double[] { reducedData.getRow(i)[0], Math.sqrt(reducedData.getRow(i)[1]) };
        measurementErrors.addRow(row);
    }
    new DisplayPlotOp().displayPlot(reducedData, "raw reduced data", null);
    new DisplayPlotOp().displayPlot(measurementErrors, "raw reduced noise", null);
    // 
    // find large drop and determine first post-bleach timepoint.
    // 
    double largestDrop = -1000000;
    int indexLargestDrop = -1;
    for (int i = 1; i < reducedData.getRowCount(); i++) {
        double drop = reducedData.getRow(i - 1)[1] - reducedData.getRow(i)[1];
        if (drop > largestDrop) {
            indexLargestDrop = i;
            largestDrop = drop;
        }
    }
    System.out.println("index of first postbleach is " + indexLargestDrop);
    // 
    // normalize data and noise and start with first post-bleach index;
    // 
    RowColumnResultSet normalizedReducedData = new RowColumnResultSet(new String[] { reducedData.getColumnDescriptions()[0].getName(), reducedData.getColumnDescriptions()[1].getName() });
    RowColumnResultSet normalizedNoiseData = new RowColumnResultSet(new String[] { reducedData.getColumnDescriptions()[0].getName(), reducedData.getColumnDescriptions()[1].getName() });
    for (int i = indexLargestDrop; i < reducedData.getRowCount(); i++) {
        double timeAfterBleach = reducedData.getRow(i)[0] - reducedData.getRow(indexLargestDrop)[0];
        double normalizedData = reducedData.getRow(i)[1] / reducedData.getRow(0)[1];
        double[] newDataRow = new double[] { timeAfterBleach, normalizedData };
        normalizedReducedData.addRow(newDataRow);
        double normalizedNoise = measurementErrors.getRow(i)[1] / reducedData.getRow(0)[1];
        double[] newNoiseRow = new double[] { timeAfterBleach, normalizedNoise };
        normalizedNoiseData.addRow(newNoiseRow);
    }
    new DisplayPlotOp().displayPlot(normalizedReducedData, "normalized reduced data", null);
    new DisplayPlotOp().displayPlot(normalizedNoiseData, "normalized reduced noise", null);
    NormalizedSampleFunction[] sampleFunctions = new NormalizedSampleFunction[] { NormalizedSampleFunction.createUniform("psf", null, null, new ISize(10, 10, 1)) };
    ErrorFunction errorFunction = new ErrorFunctionKenworthy(normalizedReducedData);
    // ErrorFunction errorFunction = new ErrorFunctionMeanSquared();
    double bleachRadius_ROI = 2;
    // 
    // 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, normalizedReducedData, normalizedNoiseData, 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, normalizedReducedData, normalizedNoiseData, errorFunction);
    String title_u3 = "Uniform Disk Model - 3 parameters, (Rn=" + bleachRadius_ROI + ")";
    new DisplayInteractiveModelOp().displayOptModel(uniformDisk3Context, sampleFunctions, localWorkspace, title_u3, null);
    ProfileData[] profileData = new RunProfileLikelihoodGeneralOp().runProfileLikihood(uniformDisk3Context, null);
    new DisplayProfileLikelihoodPlotsOp().displayProfileLikelihoodPlots(profileData, "3param model", null);
// 
// GaussianFit parameter uniform disk model
// 
// FloatImage prebleachBleachAreaImage = new FloatImage(prebleachAvg);
// prebleachBleachAreaImage.and(bleachROI.getRoiImages()[0]); // mask-out all but the bleach area
// 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);
}

Example 3 with RunProfileLikelihoodGeneralOp

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

the class RunProfileLikelihoodGeneral method compute0.

@Override
protected void compute0(TaskContext context, final ClientTaskStatusSupport clientTaskStatusSupport) throws Exception {
    // get input
    OptContext optContext = context.getData(this.optContext);
    // do op
    RunProfileLikelihoodGeneralOp op = new RunProfileLikelihoodGeneralOp();
    ProfileData[] profileData = op.runProfileLikihood(optContext, clientTaskStatusSupport);
    // set output
    context.setData(this.profileData, profileData);
}