Examples with DisplayProfileLikelihoodPlotsOp org.vcell.vmicro.op.display.DisplayProfileLikelihoodPlotsOp used on opensource projects

Example 1 with DisplayProfileLikelihoodPlotsOp

use of org.vcell.vmicro.op.display.DisplayProfileLikelihoodPlotsOp 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);
    }
}

Example 2 with DisplayProfileLikelihoodPlotsOp

use of org.vcell.vmicro.op.display.DisplayProfileLikelihoodPlotsOp in project vcell by virtualcell.

the class WorkflowObjectsPanel method displayData.

private void displayData(TaskContext taskContext, WorkflowObject workflowObject) {
    if (workflowObject instanceof DataInput || workflowObject instanceof DataOutput) {
        String title = parametersFunctionsTableModel.getName(workflowObject);
        WindowListener listener = new WindowAdapter() {
        };
        Object data = null;
        if (workflowObject instanceof WorkflowDataSource) {
            WorkflowDataSource dataHolder = (WorkflowDataSource) workflowObject;
            data = taskContext.getRepository().getData(dataHolder);
        } else if (workflowObject instanceof DataInput) {
            DataInput dataInput = (DataInput) workflowObject;
            data = taskContext.getData(dataInput);
        }
        if (data instanceof RowColumnResultSet) {
            RowColumnResultSet rc = (RowColumnResultSet) data;
            try {
                new DisplayPlotOp().displayPlot(rc, title, listener);
            } catch (ExpressionException e) {
                e.printStackTrace();
            }
        } else if (data instanceof ROI) {
            ROI roi = (ROI) data;
            Image image = roi.getRoiImages()[0];
            new DisplayImageOp().displayImage(image, title, listener);
        } else if (data instanceof ProfileData[]) {
            ProfileData[] profileData = (ProfileData[]) data;
            new DisplayProfileLikelihoodPlotsOp().displayProfileLikelihoodPlots(profileData, title, listener);
        } else if (data instanceof Image) {
            Image image = (Image) data;
            new DisplayImageOp().displayImage(image, title, listener);
        } else if (data instanceof ImageTimeSeries) {
            ImageTimeSeries imageTimeSeries = (ImageTimeSeries) data;
            try {
                DisplayTimeSeries.displayImageTimeSeries(imageTimeSeries, title, listener);
            } catch (ImageException | IOException e) {
                e.printStackTrace();
            }
        }
    }
}

Example 3 with DisplayProfileLikelihoodPlotsOp

use of org.vcell.vmicro.op.display.DisplayProfileLikelihoodPlotsOp 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 4 with DisplayProfileLikelihoodPlotsOp

use of org.vcell.vmicro.op.display.DisplayProfileLikelihoodPlotsOp in project vcell by virtualcell.

the class DisplayProfileLikelihoodPlots method compute0.

@Override
protected void compute0(TaskContext context, final ClientTaskStatusSupport clientTaskStatusSupport) throws Exception {
    // get input
    ProfileData[] profiledata = context.getData(profileData);
    String titleString = context.getDataWithDefault(title, "no title");
    WindowListener listener = null;
    // do op
    DisplayProfileLikelihoodPlotsOp op = new DisplayProfileLikelihoodPlotsOp();
    op.displayProfileLikelihoodPlots(profiledata, titleString, listener);
    // set output
    context.setData(displayed, true);
}