Examples with FitJob gdsc.smlm.engine.FitJob used on opensource projects

Example 1 with FitJob

use of gdsc.smlm.engine.FitJob in project GDSC-SMLM by aherbert.

the class PeakFit method processResults.

private boolean processResults(FitEngine engine, ArrayList<PeakResult> sliceCandidates, int slice) {
    // Process results
    int[] maxIndices = new int[sliceCandidates.size()];
    int count = 0;
    ArrayList<PeakResult> processedResults = new ArrayList<PeakResult>(sliceCandidates.size());
    for (PeakResult result : sliceCandidates) {
        // Add ExtendedPeakResults to the results if they span multiple frames (they are the result of previous fitting).
        if (result instanceof ExtendedPeakResult && result.getFrame() != result.getEndFrame()) {
            processedResults.add(result);
        } else {
            // Fit single frame results.
            maxIndices[count++] = result.origX + bounds.width * result.origY;
        }
    }
    if (!processedResults.isEmpty())
        this.results.addAll(processedResults);
    if (count != 0) {
        float[] data = source.get(slice);
        if (data == null)
            return false;
        FitParameters fitParams = new FitParameters();
        fitParams.maxIndices = Arrays.copyOf(maxIndices, count);
        FitJob job = new ParameterisedFitJob(fitParams, slice, data, bounds);
        engine.run(job);
    }
    return true;
}

Example 2 with FitJob

use of gdsc.smlm.engine.FitJob in project GDSC-SMLM by aherbert.

the class PSFEstimator method calculateStatistics.

private boolean calculateStatistics(PeakFit fitter, double[] params, double[] params_dev) {
    debug("  Fitting PSF");
    swapStatistics();
    // Create the fit engine using the PeakFit plugin
    FitConfiguration fitConfig = config.getFitConfiguration();
    fitConfig.setInitialAngle((float) params[0]);
    fitConfig.setInitialPeakStdDev0((float) params[1]);
    fitConfig.setInitialPeakStdDev1((float) params[2]);
    ImageStack stack = imp.getImageStack();
    Rectangle roi = stack.getProcessor(1).getRoi();
    ImageSource source = new IJImageSource(imp);
    // Allow interlaced data by wrapping the image source
    if (interlacedData) {
        source = new InterlacedImageSource(source, dataStart, dataBlock, dataSkip);
    }
    // Allow frame aggregation by wrapping the image source
    if (integrateFrames > 1) {
        source = new AggregatedImageSource(source, integrateFrames);
    }
    fitter.initialiseImage(source, roi, true);
    fitter.addPeakResults(this);
    fitter.initialiseFitting();
    FitEngine engine = fitter.createFitEngine();
    // Use random slices
    int[] slices = new int[stack.getSize()];
    for (int i = 0; i < slices.length; i++) slices[i] = i + 1;
    Random rand = new Random();
    rand.shuffle(slices);
    IJ.showStatus("Fitting ...");
    // Use multi-threaded code for speed
    int i;
    for (i = 0; i < slices.length; i++) {
        int slice = slices[i];
        //debug("  Processing slice = %d\n", slice);
        IJ.showProgress(size(), settings.numberOfPeaks);
        ImageProcessor ip = stack.getProcessor(slice);
        // stack processor does not set the bounds required by ImageConverter
        ip.setRoi(roi);
        FitJob job = new FitJob(slice, ImageConverter.getData(ip), roi);
        engine.run(job);
        if (sampleSizeReached() || Utils.isInterrupted()) {
            break;
        }
    }
    if (Utils.isInterrupted()) {
        IJ.showProgress(1);
        engine.end(true);
        return false;
    }
    // Wait until we have enough results
    while (!sampleSizeReached() && !engine.isQueueEmpty()) {
        IJ.showProgress(size(), settings.numberOfPeaks);
        try {
            Thread.sleep(50);
        } catch (InterruptedException e) {
            break;
        }
    }
    // End now if we have enough samples
    engine.end(sampleSizeReached());
    IJ.showStatus("");
    IJ.showProgress(1);
    // This count will be an over-estimate given that the provider is ahead of the consumer
    // in this multi-threaded system
    debug("  Processed %d/%d slices (%d peaks)", i, slices.length, size());
    setParams(ANGLE, params, params_dev, sampleNew[ANGLE]);
    setParams(X, params, params_dev, sampleNew[X]);
    setParams(Y, params, params_dev, sampleNew[Y]);
    if (settings.showHistograms) {
        int[] idList = new int[NAMES.length];
        int count = 0;
        boolean requireRetile = false;
        for (int ii = 0; ii < 3; ii++) {
            if (sampleNew[ii].getN() == 0)
                continue;
            StoredDataStatistics stats = new StoredDataStatistics(sampleNew[ii].getValues());
            idList[count++] = Utils.showHistogram(TITLE, stats, NAMES[ii], 0, 0, settings.histogramBins, "Mean = " + Utils.rounded(stats.getMean()) + ". Median = " + Utils.rounded(sampleNew[ii].getPercentile(50)));
            requireRetile = requireRetile || Utils.isNewWindow();
        }
        if (requireRetile && count > 0) {
            new WindowOrganiser().tileWindows(Arrays.copyOf(idList, count));
        }
    }
    if (size() < 2) {
        log("ERROR: Insufficient number of fitted peaks, terminating ...");
        return false;
    }
    return true;
}

Example 3 with FitJob

use of gdsc.smlm.engine.FitJob in project GDSC-SMLM by aherbert.

the class PeakFit method createJob.

private FitJob createJob(int slice, int endFrame, float[] data, Rectangle bounds2, float noise) {
    FitParameters fitParams = null;
    if (slice != endFrame) {
        fitParams = new FitParameters();
        fitParams.endT = endFrame;
    }
    if (maximaIdentification) {
        if (fitParams == null)
            fitParams = new FitParameters();
        fitParams.fitTask = FitTask.MAXIMA_IDENITIFICATION;
        fitParams.noise = noise;
    } else if (!Float.isNaN(noise)) {
        if (fitParams == null)
            fitParams = new FitParameters();
        fitParams.fitTask = FitTask.PSF_FITTING;
        fitParams.noise = noise;
    }
    if (fitParams != null)
        return new ParameterisedFitJob(fitParams, slice, data, bounds);
    else
        return new FitJob(slice, data, bounds);
}