Examples with Ticker uk.ac.sussex.gdsc.core.logging.Ticker used on opensource projects

Example 26 with Ticker

use of uk.ac.sussex.gdsc.core.logging.Ticker in project GDSC-SMLM by aherbert.

the class CreateData method drawImage.

// StoredDataStatistics rawPhotons = new StoredDataStatistics();
// StoredDataStatistics drawPhotons = new StoredDataStatistics();
// private synchronized void addRaw(double d)
// {
// //rawPhotons.add(d);
// }
// 
// private synchronized void addDraw(double d)
// {
// //drawPhotons.add(d);
// }
/**
 * Create an image from the localisations using the configured PSF width. Draws a new stack image.
 *
 * <p>Note that the localisations are filtered using the signal. The input list of localisations
 * will be updated.
 *
 * @param localisationSets the localisation sets
 * @return The localisations
 */
private List<LocalisationModel> drawImage(final List<LocalisationModelSet> localisationSets) {
    if (localisationSets.isEmpty()) {
        return null;
    }
    // Create a new list for all localisation that are drawn (i.e. pass the signal filters)
    List<LocalisationModelSet> newLocalisations = Collections.synchronizedList(new ArrayList<LocalisationModelSet>(localisationSets.size()));
    photonsRemoved = new AtomicInteger();
    removedT1 = new AtomicInteger();
    removedTn = new AtomicInteger();
    photonStats = new SummaryStatistics();
    // Add drawn spots to memory
    results = new MemoryPeakResults();
    final CalibrationWriter c = new CalibrationWriter();
    c.setDistanceUnit(DistanceUnit.PIXEL);
    c.setIntensityUnit(IntensityUnit.PHOTON);
    c.setNmPerPixel(settings.getPixelPitch());
    c.setExposureTime(settings.getExposureTime());
    c.setCameraType(settings.getCameraType());
    if (settings.getCameraType() == CameraType.SCMOS) {
        c.setCameraModelName(settings.getCameraModelName());
    } else {
        final CreateDataSettingsHelper helper = new CreateDataSettingsHelper(settings);
        c.setCountPerPhoton(helper.getTotalGainSafe());
        c.setBias(settings.getBias());
        c.setReadNoise(helper.getReadNoiseInCounts());
        c.setQuantumEfficiency(helper.getQuantumEfficiency());
    }
    results.setCalibration(c.getCalibration());
    results.setSortAfterEnd(true);
    results.begin();
    maxT = localisationSets.get(localisationSets.size() - 1).getTime();
    // Display image
    final ImageStack stack = new ImageStack(settings.getSize(), settings.getSize(), maxT);
    final double psfSd = getPsfSd();
    if (psfSd <= 0) {
        return null;
    }
    final PsfModel psfModel = createPsfModel(localisationSets);
    if (psfModel == null) {
        return null;
    }
    // Create the camera noise model
    createPerPixelCameraModelData(cameraModel);
    createBackgroundPixels();
    final int threadCount = Prefs.getThreads();
    IJ.showStatus("Drawing image ...");
    // Multi-thread for speed
    final PeakResults syncResults = SynchronizedPeakResults.create(results, threadCount);
    final ExecutorService threadPool = Executors.newFixedThreadPool(threadCount);
    final List<Future<?>> futures = new LinkedList<>();
    // Count all the frames to process
    final Ticker ticker = ImageJUtils.createTicker(maxT, threadCount);
    // Collect statistics on the number of photons actually simulated
    // Process all frames
    int index = 0;
    int lastT = -1;
    for (final LocalisationModelSet l : localisationSets) {
        if (ImageJUtils.isInterrupted()) {
            break;
        }
        if (l.getTime() != lastT) {
            lastT = l.getTime();
            futures.add(threadPool.submit(new ImageGenerator(localisationSets, newLocalisations, index, lastT, psfModel.copy(), syncResults, stack, poissonNoise, createRandomGenerator(), ticker)));
        }
        index++;
    }
    // Finish processing data
    ConcurrencyUtils.waitForCompletionUnchecked(futures);
    futures.clear();
    if (ImageJUtils.isInterrupted()) {
        IJ.showProgress(1);
        return null;
    }
    // Do all the frames that had no localisations
    float[] limits = null;
    for (int t = 1; t <= maxT; t++) {
        if (ImageJUtils.isInterrupted()) {
            break;
        }
        final Object pixels = stack.getPixels(t);
        if (pixels == null) {
            futures.add(threadPool.submit(new ImageGenerator(localisationSets, newLocalisations, maxT, t, null, syncResults, stack, poissonNoise, createRandomGenerator(), ticker)));
        } else if (limits == null) {
            limits = MathUtils.limits((float[]) pixels);
        }
    }
    // Finish
    ConcurrencyUtils.waitForCompletionUnchecked(futures);
    futures.clear();
    threadPool.shutdown();
    IJ.showProgress(1);
    if (ImageJUtils.isInterrupted() || limits == null) {
        return null;
    }
    results.end();
    if (photonsRemoved.get() > 0) {
        ImageJUtils.log("Removed %d localisations with less than %.1f rendered photons", photonsRemoved.get(), settings.getMinPhotons());
    }
    if (removedT1.get() > 0) {
        ImageJUtils.log("Removed %d localisations with no neighbours @ SNR %.2f", removedT1.get(), settings.getMinSnrT1());
    }
    if (removedTn.get() > 0) {
        ImageJUtils.log("Removed %d localisations with valid neighbours @ SNR %.2f", removedTn.get(), settings.getMinSnrTN());
    }
    if (photonStats.getN() > 0) {
        ImageJUtils.log("Average photons rendered = %s +/- %s", MathUtils.rounded(photonStats.getMean()), MathUtils.rounded(photonStats.getStandardDeviation()));
    }
    // System.out.printf("rawPhotons = %f\n", rawPhotons.getMean());
    // System.out.printf("drawPhotons = %f\n", drawPhotons.getMean());
    // new HistogramPlotBuilder("draw photons", drawPhotons, "photons", true, 0, 1000);
    // Update with all those localisation that have been drawn
    localisationSets.clear();
    localisationSets.addAll(newLocalisations);
    newLocalisations = null;
    IJ.showStatus("Displaying image ...");
    ImageStack newStack = stack;
    if (!settings.getRawImage()) {
        // Get the global limits and ensure all values can be represented
        final Object[] imageArray = stack.getImageArray();
        limits = MathUtils.limits((float[]) imageArray[0]);
        for (int j = 1; j < imageArray.length; j++) {
            limits = MathUtils.limits(limits, (float[]) imageArray[j]);
        }
        // float limits0 = limits[0];
        // Leave bias in place
        final float limits0 = 0;
        // Check if the image will fit in a 16-bit range
        if ((limits[1] - limits0) < 65535) {
            // Convert to 16-bit
            newStack = new ImageStack(stack.getWidth(), stack.getHeight(), stack.getSize());
            // Account for rounding
            final float min = (float) (limits0 - 0.5);
            for (int j = 0; j < imageArray.length; j++) {
                final float[] image = (float[]) imageArray[j];
                final short[] pixels = new short[image.length];
                for (int k = 0; k < pixels.length; k++) {
                    pixels[k] = (short) (image[k] - min);
                }
                newStack.setPixels(pixels, j + 1);
                // Free memory
                imageArray[j] = null;
                // Attempt to stay within memory (check vs 32MB)
                if (MemoryUtils.getFreeMemory() < 33554432L) {
                    MemoryUtils.runGarbageCollectorOnce();
                }
            }
            for (int k = 2; k-- > 0; ) {
                limits[k] = (float) Math.floor(limits[k] - min);
            }
        } else {
            // Keep as 32-bit but round to whole numbers
            for (int j = 0; j < imageArray.length; j++) {
                final float[] pixels = (float[]) imageArray[j];
                for (int k = 0; k < pixels.length; k++) {
                    pixels[k] = Math.round(pixels[k]);
                }
            }
            for (int k = 2; k-- > 0; ) {
                limits[k] = Math.round(limits[k]);
            }
        }
    }
    // Show image
    final ImagePlus imp = ImageJUtils.display(CREATE_DATA_IMAGE_TITLE, newStack);
    final ij.measure.Calibration cal = new ij.measure.Calibration();
    String unit = "nm";
    double unitPerPixel = settings.getPixelPitch();
    if (unitPerPixel > 100) {
        unit = "um";
        unitPerPixel /= 1000.0;
    }
    cal.setUnit(unit);
    cal.pixelHeight = cal.pixelWidth = unitPerPixel;
    final Rectangle bounds = cameraModel.getBounds();
    if (bounds != null) {
        cal.xOrigin = -bounds.x;
        cal.yOrigin = -bounds.y;
    }
    imp.setCalibration(cal);
    imp.setDimensions(1, 1, newStack.getSize());
    imp.setDisplayRange(limits[0], limits[1]);
    imp.updateAndDraw();
    saveImage(imp);
    final IJImageSource imageSource = new IJImageSource(imp);
    // Shift simulation image source to correct location
    results.setSource(imageSource);
    results.setName(CREATE_DATA_IMAGE_TITLE + " (" + TITLE + ")");
    // Bounds are relative to the image source
    results.setBounds(new Rectangle(settings.getSize(), settings.getSize()));
    results.setPsf(createPsf(psfSd));
    MemoryPeakResults.addResults(results);
    setBenchmarkResults(imp, results);
    if (benchmarkMode && benchmarkParameters != null) {
        benchmarkParameters.setPhotons(results);
    }
    final List<LocalisationModel> localisations = toLocalisations(localisationSets);
    savePulses(localisations, results);
    // Saved the fixed and moving localisations into different datasets
    saveFixedAndMoving(results);
    saveCompoundMolecules(results);
    return localisations;
}

Example 27 with Ticker

use of uk.ac.sussex.gdsc.core.logging.Ticker in project GDSC-SMLM by aherbert.

the class BenchmarkFilterAnalysis method scoreFilters.

@Nullable
private FilterScoreResult[] scoreFilters(FilterSet filterSet, boolean createTextResult) {
    if (filterSet.size() == 0) {
        return null;
    }
    initialiseScoring(filterSet);
    FilterScoreResult[] scoreResults = new FilterScoreResult[filterSet.size()];
    if (scoreResults.length == 1) {
        // No need to multi-thread this
        scoreResults[0] = scoreFilter((DirectFilter) filterSet.getFilters().get(0), defaultMinimalFilter, createTextResult, coordinateStore);
    } else {
        // Multi-thread score all the result
        final int nThreads = getThreads(scoreResults.length);
        final BlockingQueue<ScoreJob> jobs = new ArrayBlockingQueue<>(nThreads * 2);
        final List<Thread> threads = new LinkedList<>();
        final Ticker ticker = ImageJUtils.createTicker(scoreResults.length, nThreads, "Scoring Filters");
        for (int i = 0; i < nThreads; i++) {
            final ScoreWorker worker = new ScoreWorker(jobs, scoreResults, createTextResult, (coordinateStore == null) ? null : coordinateStore.newInstance(), ticker);
            final Thread t = new Thread(worker);
            threads.add(t);
            t.start();
        }
        int index = 0;
        for (final Filter filter : filterSet.getFilters()) {
            if (IJ.escapePressed()) {
                break;
            }
            put(jobs, new ScoreJob((DirectFilter) filter, index++));
        }
        // Finish all the worker threads by passing in a null job
        for (int i = 0; i < threads.size(); i++) {
            put(jobs, new ScoreJob(null, -1));
        }
        // Wait for all to finish
        for (int i = 0; i < threads.size(); i++) {
            try {
                threads.get(i).join();
            } catch (final InterruptedException ex) {
                Logger.getLogger(BenchmarkFilterAnalysis.class.getName()).log(Level.WARNING, "Interrupted!", ex);
                Thread.currentThread().interrupt();
                throw new ConcurrentRuntimeException("Unexpected interruption", ex);
            }
        }
        threads.clear();
        ImageJUtils.finished();
        // In case the threads were interrupted
        if (ImageJUtils.isInterrupted()) {
            scoreResults = null;
        }
    }
    finishScoring();
    return scoreResults;
}

Example 28 with Ticker

use of uk.ac.sussex.gdsc.core.logging.Ticker in project GDSC-SMLM by aherbert.

the class BenchmarkFit method runFit.

private void runFit() {
    // Initialise the answer.
    answer[Gaussian2DFunction.BACKGROUND] = benchmarkParameters.getBackground();
    answer[Gaussian2DFunction.SIGNAL] = benchmarkParameters.getSignal();
    answer[Gaussian2DFunction.X_POSITION] = benchmarkParameters.x;
    answer[Gaussian2DFunction.Y_POSITION] = benchmarkParameters.y;
    answer[Gaussian2DFunction.Z_POSITION] = benchmarkParameters.z;
    answer[Gaussian2DFunction.X_SD] = benchmarkParameters.sd / benchmarkParameters.pixelPitch;
    answer[Gaussian2DFunction.Y_SD] = benchmarkParameters.sd / benchmarkParameters.pixelPitch;
    // Set up the fit region. Always round down since 0.5 is the centre of the pixel.
    final int x = (int) benchmarkParameters.x;
    final int y = (int) benchmarkParameters.y;
    region = new Rectangle(x - regionSize, y - regionSize, 2 * regionSize + 1, 2 * regionSize + 1);
    if (!new Rectangle(0, 0, imp.getWidth(), imp.getHeight()).contains(region)) {
        // Check if it is incorrect by only 1 pixel
        if (region.width <= imp.getWidth() + 1 && region.height <= imp.getHeight() + 1) {
            ImageJUtils.log("Adjusting region %s to fit within image bounds (%dx%d)", region.toString(), imp.getWidth(), imp.getHeight());
            region = new Rectangle(0, 0, imp.getWidth(), imp.getHeight());
        } else {
            IJ.error(TITLE, "Fit region does not fit within the image");
            return;
        }
    }
    // Adjust the centre & account for 0.5 pixel offset during fitting
    answer[Gaussian2DFunction.X_POSITION] -= (region.x + 0.5);
    answer[Gaussian2DFunction.Y_POSITION] -= (region.y + 0.5);
    // Configure for fitting
    fitConfig.setBackgroundFitting(backgroundFitting);
    fitConfig.setNotSignalFitting(!signalFitting);
    fitConfig.setComputeDeviations(false);
    // Create the camera model
    CameraModel cameraModel = fitConfig.getCameraModel();
    // Crop for speed. Reset origin first so the region is within the model
    cameraModel.setOrigin(0, 0);
    cameraModel = cameraModel.crop(region, false);
    final ImageStack stack = imp.getImageStack();
    final int totalFrames = benchmarkParameters.frames;
    // Create a pool of workers
    final int nThreads = Prefs.getThreads();
    final BlockingQueue<Integer> jobs = new ArrayBlockingQueue<>(nThreads * 2);
    final List<Worker> workers = new LinkedList<>();
    final List<Thread> threads = new LinkedList<>();
    final Ticker ticker = ImageJUtils.createTicker(totalFrames, nThreads, "Fitting frames ...");
    for (int i = 0; i < nThreads; i++) {
        final Worker worker = new Worker(jobs, stack, region, fitConfig, cameraModel, ticker);
        final Thread t = new Thread(worker);
        workers.add(worker);
        threads.add(t);
        t.start();
    }
    // Store all the fitting results
    results = new double[totalFrames * startPoints.length][];
    resultsTime = new long[results.length];
    // Fit the frames
    for (int i = 0; i < totalFrames; i++) {
        // Only fit if there were simulated photons
        if (benchmarkParameters.framePhotons[i] > 0) {
            put(jobs, i);
        }
    }
    // Finish all the worker threads by passing in a null job
    for (int i = 0; i < threads.size(); i++) {
        put(jobs, -1);
    }
    // Wait for all to finish
    for (int i = 0; i < threads.size(); i++) {
        try {
            threads.get(i).join();
        } catch (final InterruptedException ex) {
            Thread.currentThread().interrupt();
            throw new ConcurrentRuntimeException(ex);
        }
    }
    threads.clear();
    if (hasOffsetXy()) {
        ImageJUtils.log(TITLE + ": CoM within start offset = %d / %d (%s%%)", comValid.intValue(), totalFrames, MathUtils.rounded((100.0 * comValid.intValue()) / totalFrames));
    }
    ImageJUtils.finished("Collecting results ...");
    // Collect the results
    Statistics[] stats = null;
    for (int i = 0; i < workers.size(); i++) {
        final Statistics[] next = workers.get(i).stats;
        if (stats == null) {
            stats = next;
            continue;
        }
        for (int j = 0; j < next.length; j++) {
            stats[j].add(next[j]);
        }
    }
    workers.clear();
    Objects.requireNonNull(stats, "No statistics were computed");
    // Show a table of the results
    summariseResults(stats, cameraModel);
    // Optionally show histograms
    if (showHistograms) {
        IJ.showStatus("Calculating histograms ...");
        final WindowOrganiser windowOrganiser = new WindowOrganiser();
        final double[] convert = getConversionFactors();
        final HistogramPlotBuilder builder = new HistogramPlotBuilder(TITLE).setNumberOfBins(histogramBins);
        for (int i = 0; i < NAMES.length; i++) {
            if (displayHistograms[i] && convert[i] != 0) {
                // We will have to convert the values...
                final double[] tmp = ((StoredDataStatistics) stats[i]).getValues();
                for (int j = 0; j < tmp.length; j++) {
                    tmp[j] *= convert[i];
                }
                final StoredDataStatistics tmpStats = StoredDataStatistics.create(tmp);
                builder.setData(tmpStats).setName(NAMES[i]).setPlotLabel(String.format("%s +/- %s", MathUtils.rounded(tmpStats.getMean()), MathUtils.rounded(tmpStats.getStandardDeviation()))).show(windowOrganiser);
            }
        }
        windowOrganiser.tile();
    }
    if (saveRawData) {
        final String dir = ImageJUtils.getDirectory("Data_directory", rawDataDirectory);
        if (dir != null) {
            saveData(stats, dir);
        }
    }
    IJ.showStatus("");
}

Example 29 with Ticker

use of uk.ac.sussex.gdsc.core.logging.Ticker in project GDSC-SMLM by aherbert.

the class BenchmarkSmartSpotRanking method runAnalysis.

private void runAnalysis() {
    // Extract all the results in memory into a list per frame. This can be cached
    boolean refresh = false;
    final Pair<Integer, TIntObjectHashMap<List<Coordinate>>> coords = coordinateCache.get();
    TIntObjectHashMap<List<Coordinate>> actualCoordinates;
    if (coords.getKey() != simulationParameters.id) {
        // Do not get integer coordinates
        // The Coordinate objects will be PeakResultPoint objects that store the original PeakResult
        // from the MemoryPeakResults
        actualCoordinates = ResultsMatchCalculator.getCoordinates(results, false);
        coordinateCache.set(Pair.of(simulationParameters.id, actualCoordinates));
        refresh = true;
    } else {
        actualCoordinates = coords.getValue();
    }
    // Extract all the candidates into a list per frame. This can be cached if the settings have not
    // changed.
    CandidateData candidateData = candidateDataCache.get();
    if (refresh || candidateData == null || candidateData.differentSettings(filterResult.id, settings)) {
        candidateData = subsetFilterResults(filterResult.filterResults);
        candidateDataCache.set(candidateData);
    }
    final TIntObjectHashMap<FilterCandidates> filterCandidates = candidateData.filterCandidates;
    final ImageStack stack = imp.getImageStack();
    // Create a pool of workers
    final int nThreads = Prefs.getThreads();
    final BlockingQueue<Integer> jobs = new ArrayBlockingQueue<>(nThreads * 2);
    final List<Worker> workers = new LinkedList<>();
    final List<Thread> threads = new LinkedList<>();
    final Ticker ticker = ImageJUtils.createTicker(filterCandidates.size(), nThreads);
    for (int i = 0; i < nThreads; i++) {
        final Worker worker = new Worker(jobs, stack, actualCoordinates, filterCandidates, ticker);
        final Thread t = new Thread(worker);
        workers.add(worker);
        threads.add(t);
        t.start();
    }
    // Process the frames
    filterCandidates.forEachKey(value -> {
        put(jobs, value);
        return true;
    });
    // Finish all the worker threads by passing in a null job
    for (int i = 0; i < threads.size(); i++) {
        put(jobs, -1);
    }
    // Wait for all to finish
    for (int i = 0; i < threads.size(); i++) {
        try {
            threads.get(i).join();
        } catch (final InterruptedException ex) {
            Thread.currentThread().interrupt();
            throw new ConcurrentRuntimeException("Unexpected interrupt", ex);
        }
    }
    threads.clear();
    IJ.showProgress(1);
    if (ImageJUtils.isInterrupted()) {
        IJ.showStatus("Aborted");
        return;
    }
    IJ.showStatus("Collecting results ...");
    final TIntObjectHashMap<RankResults> rankResults = new TIntObjectHashMap<>();
    for (final Worker w : workers) {
        rankResults.putAll(w.results);
    }
    summariseResults(rankResults, candidateData);
    IJ.showStatus("");
}

Example 30 with Ticker

use of uk.ac.sussex.gdsc.core.logging.Ticker in project GDSC-SMLM by aherbert.

the class FilterResults method filterResults.

/**
 * Apply the filters to the data.
 */
private void filterResults() {
    checkLimits();
    final MemoryPeakResults newResults = new MemoryPeakResults();
    newResults.copySettings(results);
    newResults.setName(results.getName() + " Filtered");
    // Initialise the mask
    CoordFilter maskFilter;
    final ImagePlus maskImp = WindowManager.getImage(filterSettings.getMaskTitle());
    if (maskImp != null) {
        final int maxx = maskImp.getWidth();
        final int maxy = maskImp.getHeight();
        final Rectangle bounds = results.getBounds();
        final double ox = bounds.getX();
        final double oy = bounds.getY();
        final double scaleX = bounds.getWidth() / maxx;
        final double scaleY = bounds.getHeight() / maxy;
        // Improve to allow stacks
        if (maskImp.getStackSize() > 1) {
            // 3D filter. The frame is mapped to the stack index.
            final ImageStack stack = maskImp.getImageStack();
            final ImageProcessor ip = stack.getProcessor(1);
            maskFilter = (t, x, y) -> {
                // Check stack index
                if (t >= 1 && t <= stack.size()) {
                    int ix = (int) ((x - ox) / scaleX);
                    int iy = (int) ((y - oy) / scaleY);
                    if (ix >= 0 && ix < maxx && iy >= 0 && iy < maxy) {
                        ip.setPixels(stack.getPixels(t));
                        return ip.get(iy * maxx + ix) != 0;
                    }
                }
                return false;
            };
        } else {
            // 2D filter.
            final ImageProcessor ip = maskImp.getProcessor();
            maskFilter = (t, x, y) -> {
                int ix = (int) ((x - ox) / scaleX);
                int iy = (int) ((y - oy) / scaleY);
                return (ix >= 0 && ix < maxx && iy >= 0 && iy < maxy && ip.get(iy * maxx + ix) != 0);
            };
        }
    } else {
        maskFilter = (t, x, y) -> true;
    }
    // Create the ticker with size+1 as we tick at the start of the loop
    final Ticker ticker = ImageJUtils.createTicker(results.size() + 1, 0);
    for (int i = 0, size = results.size(); i < size; i++) {
        ticker.tick();
        // We stored the drift=z, intensity=signal, background=snr
        if (sp.z[i] > filterSettings.getMaxDrift()) {
            continue;
        }
        if (sp.intensity[i] < filterSettings.getMinSignal()) {
            continue;
        }
        if (sp.background[i] < filterSettings.getMinSnr()) {
            continue;
        }
        final PeakResult peakResult = sp.peakResults[i];
        // Check the coordinates are inside the mask
        if (!maskFilter.match(peakResult.getFrame(), sp.x[i], sp.y[i])) {
            continue;
        }
        if (pp != null && pp.precisions[i] > maxPrecision) {
            continue;
        }
        if (wp != null) {
            final float width = wp.wx[i];
            if (width < filterSettings.getMinWidth() || width > filterSettings.getMaxWidth()) {
                continue;
            }
        }
        // Passed all filters. Add to the results
        newResults.add(peakResult);
    }
    ImageJUtils.finished(TextUtils.pleural(newResults.size(), "Filtered localisation"));
    MemoryPeakResults.addResults(newResults);
}