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

Example 11 with Ticker

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

the class ResultsMatchCalculator method showPairs.

/**
 * Show the match pairs in a results table.
 *
 * <p>Adds an ROI painter for the original image source of results set 1 (if it is visible) to the
 * table.
 *
 * @param results1 the first set of results
 * @param pairs the pairs
 * @param resultsWindow the results window
 */
private void showPairs(MemoryPeakResults results1, final List<PointPair> pairs, final TextWindow resultsWindow) {
    if (!settings.showPairs) {
        return;
    }
    final TextWindow pairsWindow = createPairsWindow(resultsWindow, results1.getSource());
    pairsWindow.getTextPanel().clear();
    final Ticker ticker = ImageJUtils.createTicker(pairs.size(), 0, "Writing pairs table");
    try (final BufferedTextWindow bw = new BufferedTextWindow(pairsWindow)) {
        final StringBuilder sb = new StringBuilder();
        for (final PointPair pair : pairs) {
            bw.append(addPairResult(sb, pair));
            ticker.tick();
        }
    }
    ImageJUtils.finished();
}

Example 12 with Ticker

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

the class CmosAnalysis method runAnalysis.

private void runAnalysis() {
    final long start = System.currentTimeMillis();
    // Create thread pool and workers. The system is likely to be IO limited
    // so reduce the computation threads to allow the reading thread in the
    // SeriesImageSource to run.
    // If the images are small enough to fit into memory then 3 threads are used,
    // otherwise it is 1.
    final int nThreads = Math.max(1, getThreads() - 3);
    final ExecutorService executor = Executors.newFixedThreadPool(nThreads);
    final LocalList<Future<?>> futures = new LocalList<>(nThreads);
    final LocalList<ImageWorker> workers = new LocalList<>(nThreads);
    final double[][] data = new double[subDirs.size() * 2][];
    double[] pixelOffset = null;
    double[] pixelVariance = null;
    Statistics statsOffset = null;
    Statistics statsVariance = null;
    // For each sub-directory compute the mean and variance
    final int nSubDirs = subDirs.size();
    boolean error = false;
    int width = 0;
    int height = 0;
    for (int n = 0; n < nSubDirs; n++) {
        ImageJUtils.showSlowProgress(n, nSubDirs);
        final SubDir sd = subDirs.unsafeGet(n);
        ImageJUtils.showStatus(() -> "Analysing " + sd.name);
        final StopWatch sw = StopWatch.createStarted();
        // Option to reuse data
        final File file = new File(settings.directory, "perPixel" + sd.name + ".tif");
        boolean found = false;
        if (settings.reuseProcessedData && file.exists()) {
            final Opener opener = new Opener();
            opener.setSilentMode(true);
            final ImagePlus imp = opener.openImage(file.getPath());
            if (imp != null && imp.getStackSize() == 2 && imp.getBitDepth() == 32) {
                if (n == 0) {
                    width = imp.getWidth();
                    height = imp.getHeight();
                } else if (width != imp.getWidth() || height != imp.getHeight()) {
                    error = true;
                    IJ.error(TITLE, "Image width/height mismatch in image series: " + file.getPath() + String.format("\n \nExpected %dx%d, Found %dx%d", width, height, imp.getWidth(), imp.getHeight()));
                    break;
                }
                final ImageStack stack = imp.getImageStack();
                data[2 * n] = SimpleArrayUtils.toDouble((float[]) stack.getPixels(1));
                data[2 * n + 1] = SimpleArrayUtils.toDouble((float[]) stack.getPixels(2));
                found = true;
            }
        }
        if (!found) {
            // Open the series
            final SeriesImageSource source = new SeriesImageSource(sd.name, sd.path.getPath());
            if (!source.open()) {
                error = true;
                IJ.error(TITLE, "Failed to open image series: " + sd.path.getPath());
                break;
            }
            if (n == 0) {
                width = source.getWidth();
                height = source.getHeight();
            } else if (width != source.getWidth() || height != source.getHeight()) {
                error = true;
                IJ.error(TITLE, "Image width/height mismatch in image series: " + sd.path.getPath() + String.format("\n \nExpected %dx%d, Found %dx%d", width, height, source.getWidth(), source.getHeight()));
                break;
            }
            // So the bar remains at 99% when workers have finished use frames + 1
            final Ticker ticker = ImageJUtils.createTicker(source.getFrames() + 1L, nThreads);
            // Open the first frame to get the bit depth.
            // Assume the first pixels are not empty as the source is open.
            Object pixels = source.nextRaw();
            final int bitDepth = ImageJUtils.getBitDepth(pixels);
            ArrayMoment moment;
            if (settings.rollingAlgorithm) {
                moment = new RollingArrayMoment();
            // We assume 16-bit camera at the maximum
            } else if (bitDepth <= 16 && IntegerArrayMoment.isValid(IntegerType.UNSIGNED_16, source.getFrames())) {
                moment = new IntegerArrayMoment();
            } else {
                moment = new SimpleArrayMoment();
            }
            final BlockingQueue<Object> jobs = new ArrayBlockingQueue<>(nThreads * 2);
            for (int i = 0; i < nThreads; i++) {
                final ImageWorker worker = new ImageWorker(ticker, jobs, moment);
                workers.add(worker);
                futures.add(executor.submit(worker));
            }
            // Process the raw pixel data
            long lastTime = 0;
            while (pixels != null) {
                final long time = System.currentTimeMillis();
                if (time - lastTime > 150) {
                    if (ImageJUtils.isInterrupted()) {
                        error = true;
                        break;
                    }
                    lastTime = time;
                    IJ.showStatus("Analysing " + sd.name + " Frame " + source.getStartFrameNumber());
                }
                put(jobs, pixels);
                pixels = source.nextRaw();
            }
            source.close();
            if (error) {
                // Kill the workers
                workers.stream().forEach(worker -> worker.finished = true);
                // Clear the queue
                jobs.clear();
                // Signal any waiting workers
                workers.stream().forEach(worker -> jobs.add(ImageWorker.STOP_SIGNAL));
                // Cancel by interruption. We set the finished flag so the ImageWorker should
                // ignore the interrupt.
                futures.stream().forEach(future -> future.cancel(true));
                break;
            }
            // Finish all the worker threads cleanly
            workers.stream().forEach(worker -> jobs.add(ImageWorker.STOP_SIGNAL));
            // Wait for all to finish
            ConcurrencyUtils.waitForCompletionUnchecked(futures);
            // Create the final aggregate statistics
            for (final ImageWorker w : workers) {
                moment.add(w.moment);
            }
            data[2 * n] = moment.getMean();
            data[2 * n + 1] = moment.getVariance();
            // Get the processing speed.
            sw.stop();
            // ticker holds the number of number of frames processed
            final double bits = (double) bitDepth * source.getFrames() * source.getWidth() * source.getHeight();
            final double bps = bits / sw.getTime(TimeUnit.SECONDS);
            final SiPrefix prefix = SiPrefix.getSiPrefix(bps);
            ImageJUtils.log("Processed %d frames. Time = %s. Rate = %s %sbits/s", moment.getN(), sw.toString(), MathUtils.rounded(prefix.convert(bps)), prefix.getPrefix());
            // Reset
            futures.clear();
            workers.clear();
            final ImageStack stack = new ImageStack(width, height);
            stack.addSlice("Mean", SimpleArrayUtils.toFloat(data[2 * n]));
            stack.addSlice("Variance", SimpleArrayUtils.toFloat(data[2 * n + 1]));
            IJ.save(new ImagePlus("PerPixel", stack), file.getPath());
        }
        final Statistics s = Statistics.create(data[2 * n]);
        if (pixelOffset != null) {
            // Compute mean ADU
            final Statistics signal = new Statistics();
            final double[] mean = data[2 * n];
            for (int i = 0; i < pixelOffset.length; i++) {
                signal.add(mean[i] - pixelOffset[i]);
            }
            ImageJUtils.log("%s Mean = %s +/- %s. Signal = %s +/- %s ADU", sd.name, MathUtils.rounded(s.getMean()), MathUtils.rounded(s.getStandardDeviation()), MathUtils.rounded(signal.getMean()), MathUtils.rounded(signal.getStandardDeviation()));
        } else {
            // Set the offset assuming the first sub-directory is the bias image
            pixelOffset = data[0];
            pixelVariance = data[1];
            statsOffset = s;
            statsVariance = Statistics.create(pixelVariance);
            ImageJUtils.log("%s Offset = %s +/- %s. Variance = %s +/- %s", sd.name, MathUtils.rounded(s.getMean()), MathUtils.rounded(s.getStandardDeviation()), MathUtils.rounded(statsVariance.getMean()), MathUtils.rounded(statsVariance.getStandardDeviation()));
        }
        IJ.showProgress(1);
    }
    ImageJUtils.clearSlowProgress();
    if (error) {
        executor.shutdownNow();
        IJ.showStatus(TITLE + " cancelled");
        return;
    }
    executor.shutdown();
    if (pixelOffset == null || pixelVariance == null) {
        IJ.showStatus(TITLE + " error: no bias image");
        return;
    }
    // Compute the gain
    ImageJUtils.showStatus("Computing gain");
    final double[] pixelGain = new double[pixelOffset.length];
    final double[] bibiT = new double[pixelGain.length];
    final double[] biaiT = new double[pixelGain.length];
    // Ignore first as this is the 0 exposure image
    for (int n = 1; n < nSubDirs; n++) {
        // Use equation 2.5 from the Huang et al paper.
        final double[] b = data[2 * n];
        final double[] a = data[2 * n + 1];
        for (int i = 0; i < pixelGain.length; i++) {
            final double bi = b[i] - pixelOffset[i];
            final double ai = a[i] - pixelVariance[i];
            bibiT[i] += bi * bi;
            biaiT[i] += bi * ai;
        }
    }
    for (int i = 0; i < pixelGain.length; i++) {
        pixelGain[i] = biaiT[i] / bibiT[i];
    }
    final Statistics statsGain = Statistics.create(pixelGain);
    ImageJUtils.log("Gain Mean = %s +/- %s", MathUtils.rounded(statsGain.getMean()), MathUtils.rounded(statsGain.getStandardDeviation()));
    // Histogram of offset, variance and gain
    final int bins = 2 * HistogramPlot.getBinsSturgesRule(pixelGain.length);
    final WindowOrganiser wo = new WindowOrganiser();
    showHistogram("Offset (ADU)", pixelOffset, bins, statsOffset, wo);
    showHistogram("Variance (ADU^2)", pixelVariance, bins, statsVariance, wo);
    showHistogram("Gain (ADU/e)", pixelGain, bins, statsGain, wo);
    wo.tile();
    // Save
    final float[] bias = SimpleArrayUtils.toFloat(pixelOffset);
    final float[] variance = SimpleArrayUtils.toFloat(pixelVariance);
    final float[] gain = SimpleArrayUtils.toFloat(pixelGain);
    measuredStack = new ImageStack(width, height);
    measuredStack.addSlice("Offset", bias);
    measuredStack.addSlice("Variance", variance);
    measuredStack.addSlice("Gain", gain);
    final ExtendedGenericDialog egd = new ExtendedGenericDialog(TITLE);
    egd.addMessage("Save the sCMOS camera model?");
    if (settings.modelDirectory == null) {
        settings.modelDirectory = settings.directory;
        settings.modelName = "sCMOS Camera";
    }
    egd.addStringField("Model_name", settings.modelName, 30);
    egd.addDirectoryField("Model_directory", settings.modelDirectory);
    egd.showDialog();
    if (!egd.wasCanceled()) {
        settings.modelName = egd.getNextString();
        settings.modelDirectory = egd.getNextString();
        saveCameraModel(width, height, bias, gain, variance);
    }
    // Remove the status from the ij.io.ImageWriter class
    IJ.showStatus("");
    ImageJUtils.log("Analysis time = " + TextUtils.millisToString(System.currentTimeMillis() - start));
}

Example 13 with Ticker

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

the class CmosAnalysis method simulate.

private void simulate() throws IOException {
    // Create the offset, variance and gain for each pixel
    final int n = settings.size * settings.size;
    final float[] pixelOffset = new float[n];
    final float[] pixelVariance = new float[n];
    final float[] pixelGain = new float[n];
    IJ.showStatus("Creating random per-pixel readout");
    final long start = System.currentTimeMillis();
    final UniformRandomProvider rg = UniformRandomProviders.create();
    final DiscreteSampler pd = PoissonSamplerUtils.createPoissonSampler(rg, settings.offset);
    final ContinuousSampler ed = SamplerUtils.createExponentialSampler(rg, settings.variance);
    final SharedStateContinuousSampler gauss = SamplerUtils.createGaussianSampler(rg, settings.gain, settings.gainStdDev);
    Ticker ticker = ImageJUtils.createTicker(n, 0);
    for (int i = 0; i < n; i++) {
        // Q. Should these be clipped to a sensible range?
        pixelOffset[i] = pd.sample();
        pixelVariance[i] = (float) ed.sample();
        pixelGain[i] = (float) gauss.sample();
        ticker.tick();
    }
    IJ.showProgress(1);
    // Save to the directory as a stack
    final ImageStack simulationStack = new ImageStack(settings.size, settings.size);
    simulationStack.addSlice("Offset", pixelOffset);
    simulationStack.addSlice("Variance", pixelVariance);
    simulationStack.addSlice("Gain", pixelGain);
    simulationImp = new ImagePlus("PerPixel", simulationStack);
    // Only the info property is saved to the TIFF file
    simulationImp.setProperty("Info", String.format("Offset=%s; Variance=%s; Gain=%s +/- %s", MathUtils.rounded(settings.offset), MathUtils.rounded(settings.variance), MathUtils.rounded(settings.gain), MathUtils.rounded(settings.gainStdDev)));
    IJ.save(simulationImp, new File(settings.directory, "perPixelSimulation.tif").getPath());
    // Create thread pool and workers
    final int threadCount = getThreads();
    final ExecutorService executor = Executors.newFixedThreadPool(threadCount);
    final LocalList<Future<?>> futures = new LocalList<>(numberOfThreads);
    // Simulate the exposure input.
    final int[] photons = settings.getPhotons();
    // For saving stacks
    final int blockSize = 10;
    int numberPerThread = (int) Math.ceil((double) settings.frames / numberOfThreads);
    // Convert to fit the block size
    numberPerThread = (int) Math.ceil((double) numberPerThread / blockSize) * blockSize;
    final Pcg32 rng = Pcg32.xshrs(start);
    // Note the bias is increased by 3-fold so add 2 to the length
    ticker = Ticker.createStarted(new ImageJTrackProgress(true), (long) (photons.length + 2) * settings.frames, threadCount > 1);
    for (final int p : photons) {
        ImageJUtils.showStatus(() -> "Simulating " + TextUtils.pleural(p, "photon"));
        // Create the directory
        final Path out = Paths.get(settings.directory, String.format("photon%03d", p));
        Files.createDirectories(out);
        // Increase frames for bias image
        final int frames = settings.frames * (p == 0 ? 3 : 1);
        for (int from = 0; from < frames; ) {
            final int to = Math.min(from + numberPerThread, frames);
            futures.add(executor.submit(new SimulationWorker(ticker, rng.split(), out.toString(), simulationStack, from, to, blockSize, p)));
            from = to;
        }
        ConcurrencyUtils.waitForCompletionUnchecked(futures);
        futures.clear();
    }
    final String msg = "Simulation time = " + TextUtils.millisToString(System.currentTimeMillis() - start);
    IJ.showStatus(msg);
    ImageJUtils.clearSlowProgress();
    executor.shutdown();
    ImageJUtils.log(msg);
}

Example 14 with Ticker

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

the class DriftCalculator method calculateDriftUsingImageStack.

/**
 * Calculate the drift of images to the reference image. If no reference is provided then produce
 * a combined z-projection. Update the current drift parameters.
 *
 * @param reference the reference
 * @param images The images to align
 * @param fhtImages The images to align (pre-transformed to a FHT)
 * @param blockT The frame number for each image
 * @param dx The X drift
 * @param dy The Y drift
 * @param originalDriftTimePoints Non-zero when the frame number refers to an aligned image frame
 * @param smoothing the smoothing
 * @param iterations the iterations
 * @return The change in the drift (NaN is an error occurred)
 */
private double calculateDriftUsingImageStack(FloatProcessor reference, ImageProcessor[] images, Fht[] fhtImages, int[] blockT, double[] dx, double[] dy, double[] originalDriftTimePoints, double smoothing, int iterations) {
    Ticker ticker = Ticker.createStarted(tracker, images.length, true);
    if (reference == null) {
        // Construct images using the current drift
        tracker.status("Constructing reference image");
        // Build an image using the current drift
        final List<Future<?>> futures = new LinkedList<>();
        ticker = Ticker.createStarted(tracker, images.length * 2L, true);
        final ImageProcessor[] blockIp = new ImageProcessor[images.length];
        final double[] threadDx = new double[images.length];
        final double[] threadDy = new double[images.length];
        for (int i = 0; i < images.length; i++) {
            threadDx[i] = dx[blockT[i]];
            threadDy[i] = dy[blockT[i]];
        }
        final int imagesPerThread = getImagesPerThread(images);
        for (int i = 0; i < images.length; i += imagesPerThread) {
            futures.add(executor.submit(new ImageTranslator(images, blockIp, threadDx, threadDy, i, i + imagesPerThread, ticker, settings.interpolationMethod)));
        }
        ConcurrencyUtils.waitForCompletionUnchecked(futures);
        // Build an image with all results.
        reference = new FloatProcessor(blockIp[0].getWidth(), blockIp[0].getHeight());
        for (final ImageProcessor ip : blockIp) {
            reference.copyBits(ip, 0, 0, Blitter.ADD);
        }
    }
    // Ensure the reference is windowed
    AlignImagesFft.applyWindowSeparable(reference, WindowMethod.TUKEY);
    return calculateDrift(blockT, 1f, dx, dy, originalDriftTimePoints, smoothing, iterations, fhtImages, reference, false, ticker);
}

Example 15 with Ticker

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

the class DriftCalculator method calculateUsingImageStack.

/**
 * Calculates drift using images from a reference stack aligned to the overall z-projection.
 *
 * @param stack the stack
 * @param limits the limits
 * @return the drift { dx[], dy[] }
 */
@Nullable
private double[][] calculateUsingImageStack(ImageStack stack, int[] limits) {
    // Update the limits using the stack size
    final int upperT = settings.startFrame + settings.frameSpacing * (stack.getSize() - 1);
    limits[1] = Math.max(limits[1], upperT);
    // TODO - Truncate the stack if there are far too many frames for the localisation limits
    tracker.status("Constructing images");
    executor = Executors.newFixedThreadPool(Prefs.getThreads());
    // Built an image and FHT image for each slice
    final ImageProcessor[] images = new ImageProcessor[stack.getSize()];
    final Fht[] fhtImages = new Fht[stack.getSize()];
    final List<Future<?>> futures = new LinkedList<>();
    final Ticker ticker = Ticker.createStarted(tracker, images.length, true);
    final int imagesPerThread = getImagesPerThread(images);
    final AlignImagesFft aligner = new AlignImagesFft();
    final FloatProcessor referenceIp = stack.getProcessor(1).toFloat(0, null);
    // We do not care about the window method because this processor will not
    // actually be used for alignment, it is a reference for the FHT size
    aligner.initialiseReference(referenceIp, WindowMethod.NONE, false);
    for (int i = 0; i < images.length; i += imagesPerThread) {
        futures.add(executor.submit(new ImageFhtInitialiser(stack, images, aligner, fhtImages, i, i + imagesPerThread, ticker)));
    }
    ConcurrencyUtils.waitForCompletionUnchecked(futures);
    tracker.progress(1);
    if (tracker.isEnded()) {
        return null;
    }
    final double[] dx = new double[limits[1] + 1];
    final double[] dy = new double[dx.length];
    final double[] originalDriftTimePoints = new double[dx.length];
    final int[] blockT = new int[stack.getSize()];
    for (int i = 0, t = settings.startFrame; i < stack.getSize(); i++, t += settings.frameSpacing) {
        originalDriftTimePoints[t] = 1;
        blockT[i] = t;
    }
    final double smoothing = updateSmoothingParameter(originalDriftTimePoints);
    lastdx = null;
    // For the first iteration calculate drift to the first image in the stack
    // (since the average projection may have a large drift blurring the image)
    double change = calculateDriftUsingImageStack(referenceIp, images, fhtImages, blockT, dx, dy, originalDriftTimePoints, smoothing, settings.iterations);
    if (Double.isNaN(change) || tracker.isEnded()) {
        return null;
    }
    plotDrift(limits, dx, dy);
    ImageJUtils.log("Drift Calculator : Initial drift " + MathUtils.rounded(change));
    for (int i = 1; i <= settings.maxIterations; i++) {
        change = calculateDriftUsingImageStack(null, images, fhtImages, blockT, dx, dy, originalDriftTimePoints, smoothing, settings.iterations);
        if (Double.isNaN(change)) {
            return null;
        }
        plotDrift(limits, dx, dy);
        if (converged(i, change, getTotalDrift(dx, dy, originalDriftTimePoints))) {
            break;
        }
    }
    if (tracker.isEnded()) {
        return null;
    }
    plotDrift(limits, dx, dy);
    return new double[][] { dx, dy };
}