Examples with SeriesOpener uk.ac.sussex.gdsc.core.ij.SeriesOpener used on opensource projects

Example 1 with SeriesOpener

use of uk.ac.sussex.gdsc.core.ij.SeriesOpener in project GDSC-SMLM by aherbert.

the class PeakFit method setup.

@Override
public int setup(String arg, ImagePlus imp) {
    SmlmUsageTracker.recordPlugin(this.getClass(), arg);
    pluginFlags = FLAGS;
    extraOptions = ImageJUtils.isExtraOptions();
    maximaIdentification = StringUtils.contains(arg, "spot");
    fitMaxima = StringUtils.contains(arg, "maxima");
    simpleFit = StringUtils.contains(arg, "simple");
    final boolean runSeries = StringUtils.contains(arg, "series");
    ImageSource imageSource = null;
    if (fitMaxima) {
        // The image source will be found from the peak results.
        if (!showMaximaDialog()) {
            return DONE;
        }
        final MemoryPeakResults localResults = ResultsManager.loadInputResults(settings.inputOption, false, DistanceUnit.PIXEL);
        if (localResults == null || localResults.size() == 0) {
            IJ.error(TITLE, "No results could be loaded");
            return DONE;
        }
        if (settings.fitAcrossAllFrames) {
            // Allow the user to select a different image. The source will be set as per the
            // main fit routine from the image (imp).
            singleFrame = 0;
        } else {
            // Check for single frame
            singleFrame = getSingleFrame(localResults);
            // Forces the maxima to be used with their original source.
            imp = null;
            imageSource = localResults.getSource();
            pluginFlags |= NO_IMAGE_REQUIRED;
        }
    } else if (runSeries) {
        imp = null;
        // Select input folder
        final String inputDirectory = IJ.getDirectory("Select image series ...");
        if (inputDirectory == null) {
            return DONE;
        }
        // Load input series ...
        SeriesOpener series;
        if (extraOptions) {
            final String helpKey = maximaIdentification ? "spot-finder-series" : "peak-fit-series";
            series = SeriesOpener.create(inputDirectory, true, HelpUrls.getUrl(helpKey));
        } else {
            series = new SeriesOpener(inputDirectory);
        }
        if (series.getNumberOfImages() == 0) {
            IJ.error(TITLE, "No images in the selected directory:\n" + inputDirectory);
            return DONE;
        }
        final SeriesImageSource seriesImageSource = new SeriesImageSource(getName(series.getImageList()), series);
        // TrackProgress logging is very verbose if the series has many images
        // Status is used only when reading TIFF info.
        // seriesImageSource.setTrackProgress(SimpleImageJTrackProgress.getInstance());
        seriesImageSource.setTrackProgress(new TrackProgressAdaptor() {

            @Override
            public void status(String format, Object... args) {
                ImageJUtils.showStatus(() -> String.format(format, args));
            }
        });
        imageSource = seriesImageSource;
        pluginFlags |= NO_IMAGE_REQUIRED;
    }
    // If the image source has not been set then use the input image
    if (imageSource == null) {
        if (imp == null) {
            IJ.noImage();
            return DONE;
        }
        // Check it is not a previous result
        if (imp.getTitle().endsWith(ImageJImagePeakResults.IMAGE_SUFFIX)) {
            IJImageSource ijImageSource = null;
            // Check the image to see if it has an image source XML structure in the info property
            final Object o = imp.getProperty("Info");
            final Pattern pattern = Pattern.compile("Source: (<.*IJImageSource>.*<.*IJImageSource>)", Pattern.DOTALL);
            final Matcher match = pattern.matcher((o == null) ? "" : o.toString());
            if (match.find()) {
                final ImageSource tmpSource = ImageSource.fromXml(match.group(1));
                if (tmpSource instanceof IJImageSource) {
                    ijImageSource = (IJImageSource) tmpSource;
                    if (!ijImageSource.open()) {
                        ijImageSource = null;
                    } else {
                        imp = WindowManager.getImage(ijImageSource.getName());
                    }
                }
            }
            if (ijImageSource == null) {
                // Look for a parent using the title
                final String parentTitle = imp.getTitle().substring(0, imp.getTitle().length() - ImageJImagePeakResults.IMAGE_SUFFIX.length() - 1);
                final ImagePlus parentImp = WindowManager.getImage(parentTitle);
                if (parentImp != null) {
                    ijImageSource = new IJImageSource(parentImp);
                    imp = parentImp;
                }
            }
            String message = "The selected image may be a previous fit result";
            if (ijImageSource != null) {
                if (!TextUtils.isNullOrEmpty(ijImageSource.getName())) {
                    message += " of: \n \n" + ijImageSource.getName();
                }
                message += " \n \nFit the parent?";
            } else {
                message += " \n \nDo you want to continue?";
            }
            final YesNoCancelDialog d = new YesNoCancelDialog(null, TITLE, message);
            if (ijImageSource == null) {
                if (!d.yesPressed()) {
                    return DONE;
                }
            } else {
                if (d.yesPressed()) {
                    imageSource = ijImageSource;
                }
                if (d.cancelPressed()) {
                    return DONE;
                }
            }
        }
        if (imageSource == null) {
            try {
                imageSource = new IJImageSource(imp);
            } catch (final IllegalArgumentException ex) {
                // This can happen if the image has an origin not in integer pixels
                // e.g. the plugin is run on a plot
                IJ.error(TITLE, "Error using image: " + imp.getTitle() + "\n \n" + ex.getMessage());
                return DONE;
            }
        }
    }
    time = -1;
    if (!initialiseImage(imageSource, getBounds(imp), false)) {
        IJ.error(TITLE, "Failed to initialise the source image: " + imageSource.getName());
        return DONE;
    }
    final int flags = showDialog(imp);
    if ((flags & DONE) == 0) {
        initialiseFitting();
    }
    return flags;
}

Example 2 with SeriesOpener

use of uk.ac.sussex.gdsc.core.ij.SeriesOpener in project GDSC-SMLM by aherbert.

the class TiffSeriesViewer method run.

@Override
public void run(String arg) {
    SmlmUsageTracker.recordPlugin(this.getClass(), arg);
    settings = Settings.load();
    final ExtendedGenericDialog gd = new ExtendedGenericDialog(TITLE);
    gd.addChoice("Mode", Settings.MODE, settings.inputMode, new OptionListener<Integer>() {

        @Override
        public boolean collectOptions(Integer value) {
            settings.inputMode = value;
            return collectOptions(false);
        }

        @Override
        public boolean collectOptions() {
            return collectOptions(true);
        }

        private boolean collectOptions(boolean silent) {
            // This has limited silent support to fake running in a macro
            if (settings.inputMode == 0) {
                String dir = null;
                final String title = "Select image series ...";
                if (silent) {
                    final String macroOptions = Macro.getOptions();
                    if (macroOptions != null) {
                        dir = Macro.getValue(macroOptions, title, null);
                    }
                } else {
                    dir = ImageJUtils.getDirectory(title, settings.inputDirectory);
                }
                if (TextUtils.isNullOrEmpty(dir)) {
                    return false;
                }
                settings.inputDirectory = dir;
            } else {
                String file = null;
                final String title = "Select image ...";
                if (silent) {
                    final String macroOptions = Macro.getOptions();
                    if (macroOptions != null) {
                        file = Macro.getValue(macroOptions, title, null);
                    }
                } else {
                    file = ImageJUtils.getFilename(title, settings.inputFile);
                }
                if (TextUtils.isNullOrEmpty(file)) {
                    return false;
                }
                settings.inputFile = file;
            }
            updateLabel();
            return true;
        }
    });
    gd.addMessage("");
    label = gd.getLastLabel();
    if (ImageJUtils.isShowGenericDialog()) {
        final Choice choice = gd.getLastChoice();
        choice.addItemListener(event -> {
            settings.inputMode = choice.getSelectedIndex();
            updateLabel();
        });
        updateLabel();
    }
    gd.addCheckbox("Log_progress", settings.logProgress);
    gd.addChoice("Output_mode", Settings.OUTPUT_MODE, settings.outputMode, new OptionListener<Integer>() {

        @Override
        public boolean collectOptions(Integer value) {
            settings.outputMode = value;
            return collectOptions(false);
        }

        @Override
        public boolean collectOptions() {
            return collectOptions(true);
        }

        private boolean collectOptions(boolean silent) {
            if (settings.outputMode == 0) {
                // Nothing to do
                return false;
            }
            final ExtendedGenericDialog egd = new ExtendedGenericDialog("Output Options");
            egd.addNumericField("Slices_per_image", settings.imageCount, 0);
            egd.addDirectoryField("Output_directory", settings.outputDirectory);
            egd.setSilent(silent);
            egd.showDialog(true, gd);
            if (egd.wasCanceled()) {
                return false;
            }
            settings.imageCount = (int) egd.getNextNumber();
            settings.outputDirectory = egd.getNextString();
            updateLabel2();
            return true;
        }
    });
    gd.addMessage("");
    label2 = gd.getLastLabel();
    if (ImageJUtils.isShowGenericDialog()) {
        final Choice choice = gd.getLastChoice();
        choice.addItemListener(event -> {
            settings.outputMode = choice.getSelectedIndex();
            updateLabel2();
        });
        updateLabel2();
    }
    gd.addHelp(HelpUrls.getUrl("tiff-series-viewer"));
    gd.showDialog();
    if (gd.wasCanceled()) {
        return;
    }
    settings.inputMode = gd.getNextChoiceIndex();
    settings.logProgress = gd.getNextBoolean();
    settings.outputMode = gd.getNextChoiceIndex();
    settings.save();
    SeriesImageSource source;
    if (settings.inputMode == 0) {
        final SeriesOpener series = new SeriesOpener(settings.inputDirectory);
        if (series.getNumberOfImages() == 0) {
            IJ.error(TITLE, "No images in the selected directory:\n" + settings.inputDirectory);
            return;
        }
        source = new SeriesImageSource(PeakFit.getName(series.getImageList()), series);
    } else {
        source = new SeriesImageSource(FileUtils.getName(settings.inputFile), new String[] { settings.inputFile });
    }
    // No memory buffer
    source.setBufferLimit(0);
    source.setReadHint(ReadHint.NONSEQUENTIAL);
    if (!source.isTiffSeries) {
        IJ.error(TITLE, "Not a TIFF image");
        return;
    }
    ImageJUtils.showStatus("Opening TIFF ...");
    final TrackProgressAdaptor progress = new TrackProgressAdaptor() {

        @Override
        public void progress(double fraction) {
            IJ.showProgress(fraction);
        }

        @Override
        public void progress(long position, long total) {
            IJ.showProgress((double) position / total);
        }

        @Override
        public void log(String format, Object... args) {
            if (settings.logProgress) {
                ImageJUtils.log(format, args);
            }
        }

        @Override
        public void status(String format, Object... args) {
            ImageJUtils.showStatus(() -> String.format(format, args));
        }

        @Override
        public boolean isLog() {
            return settings.logProgress;
        }
    };
    source.setTrackProgress(progress);
    if (!source.open()) {
        IJ.error(TITLE, "Cannot open the image");
        return;
    }
    ImageJUtils.showStatus("");
    // Create a virtual stack
    final TiffSeriesVirtualStack stack = new TiffSeriesVirtualStack(source);
    if (settings.outputMode == 0) {
        stack.show();
    } else {
        final int nImages = Math.max(1, settings.imageCount);
        final ImagePlus imp = stack.createImp();
        // The calibration only has the offset so ignore for speed.
        // Calibration cal = imp.getCalibration();
        final int size = stack.getSize();
        // Create the format string
        final int digits = String.format("%d", size).length();
        final String format = new File(settings.outputDirectory, imp.getShortTitle() + "%0" + digits + "d.tif").getPath();
        IJ.showStatus("Saving image ...");
        try {
            for (int i = 1; i <= size; i += nImages) {
                if (ImageJUtils.isInterrupted()) {
                    break;
                }
                ImageJUtils.showSlowProgress(i, size);
                final String path = String.format(format, i);
                final ImageStack out = new ImageStack(source.getWidth(), source.getHeight());
                for (int j = 0, k = i; j < nImages && k <= size; j++, k++) {
                    out.addSlice(null, stack.getPixels(k));
                }
                final ImagePlus outImp = new ImagePlus(path, out);
                // outImp.setCalibration(cal);
                saveAsTiff(outImp, path);
            }
            IJ.showStatus("Saved image");
        } catch (final IOException ex) {
            IJ.log(ExceptionUtils.getStackTrace(ex));
            IJ.error(TITLE, "Failed to save image: " + ex.getMessage());
            IJ.showStatus("Failed to save image");
        } finally {
            ImageJUtils.clearSlowProgress();
        }
    }
}

Example 3 with SeriesOpener

use of uk.ac.sussex.gdsc.core.ij.SeriesOpener in project GDSC-SMLM by aherbert.

the class MeanVarianceTest method run.

@Override
public void run(String arg) {
    SmlmUsageTracker.recordPlugin(this.getClass(), arg);
    settings = Settings.load();
    settings.save();
    String helpKey = "mean-variance-test";
    if (ImageJUtils.isExtraOptions()) {
        final ImagePlus imp = WindowManager.getCurrentImage();
        if (imp.getStackSize() > 1) {
            final GenericDialog gd = new GenericDialog(TITLE);
            gd.addMessage("Perform single image analysis on the current image?");
            gd.addNumericField("Bias", settings.bias, 0);
            gd.addHelp(HelpUrls.getUrl(helpKey));
            gd.showDialog();
            if (gd.wasCanceled()) {
                return;
            }
            singleImage = true;
            settings.bias = Math.abs(gd.getNextNumber());
        } else {
            IJ.error(TITLE, "Single-image mode requires a stack");
            return;
        }
    }
    List<ImageSample> images;
    String inputDirectory = "";
    if (singleImage) {
        IJ.showStatus("Loading images...");
        images = getImages();
        if (images.size() == 0) {
            IJ.error(TITLE, "Not enough images for analysis");
            return;
        }
    } else {
        inputDirectory = IJ.getDirectory("Select image series ...");
        if (inputDirectory == null) {
            return;
        }
        final SeriesOpener series = new SeriesOpener(inputDirectory);
        series.setVariableSize(true);
        if (series.getNumberOfImages() < 3) {
            IJ.error(TITLE, "Not enough images in the selected directory");
            return;
        }
        if (!IJ.showMessageWithCancel(TITLE, String.format("Analyse %d images, first image:\n%s", series.getNumberOfImages(), series.getImageList()[0]))) {
            return;
        }
        IJ.showStatus("Loading images");
        images = getImages(series);
        if (images.size() < 3) {
            IJ.error(TITLE, "Not enough images for analysis");
            return;
        }
        if (images.get(0).exposure != 0) {
            IJ.error(TITLE, "First image in series must have exposure 0 (Bias image)");
            return;
        }
    }
    final boolean emMode = (arg != null && arg.contains("em"));
    GenericDialog gd = new GenericDialog(TITLE);
    gd.addMessage("Set the output options:");
    gd.addCheckbox("Show_table", settings.showTable);
    gd.addCheckbox("Show_charts", settings.showCharts);
    if (emMode) {
        // Ask the user for the camera gain ...
        gd.addMessage("Estimating the EM-gain requires the camera gain without EM readout enabled");
        gd.addNumericField("Camera_gain (Count/e-)", settings.cameraGain, 4);
    }
    if (emMode) {
        helpKey += "-em-ccd";
    }
    gd.addHelp(HelpUrls.getUrl(helpKey));
    gd.showDialog();
    if (gd.wasCanceled()) {
        return;
    }
    settings.showTable = gd.getNextBoolean();
    settings.showCharts = gd.getNextBoolean();
    if (emMode) {
        settings.cameraGain = gd.getNextNumber();
    }
    IJ.showStatus("Computing mean & variance");
    final double nImages = images.size();
    for (int i = 0; i < images.size(); i++) {
        IJ.showStatus(String.format("Computing mean & variance %d/%d", i + 1, images.size()));
        images.get(i).compute(singleImage, i / nImages, (i + 1) / nImages);
    }
    IJ.showProgress(1);
    IJ.showStatus("Computing results");
    // Allow user to input multiple bias images
    int start = 0;
    final Statistics biasStats = new Statistics();
    final Statistics noiseStats = new Statistics();
    final double bias;
    if (singleImage) {
        bias = settings.bias;
    } else {
        while (start < images.size()) {
            final ImageSample sample = images.get(start);
            if (sample.exposure == 0) {
                biasStats.add(sample.means);
                for (final PairSample pair : sample.samples) {
                    noiseStats.add(pair.variance);
                }
                start++;
            } else {
                break;
            }
        }
        bias = biasStats.getMean();
    }
    // Get the mean-variance data
    int total = 0;
    for (int i = start; i < images.size(); i++) {
        total += images.get(i).samples.size();
    }
    if (settings.showTable && total > 2000) {
        gd = new GenericDialog(TITLE);
        gd.addMessage("Table output requires " + total + " entries.\n \nYou may want to disable the table.");
        gd.addCheckbox("Show_table", settings.showTable);
        gd.showDialog();
        if (gd.wasCanceled()) {
            return;
        }
        settings.showTable = gd.getNextBoolean();
    }
    final TextWindow results = (settings.showTable) ? createResultsWindow() : null;
    double[] mean = new double[total];
    double[] variance = new double[mean.length];
    final Statistics gainStats = (singleImage) ? new StoredDataStatistics(total) : new Statistics();
    final WeightedObservedPoints obs = new WeightedObservedPoints();
    for (int i = (singleImage) ? 0 : start, j = 0; i < images.size(); i++) {
        final StringBuilder sb = (settings.showTable) ? new StringBuilder() : null;
        final ImageSample sample = images.get(i);
        for (final PairSample pair : sample.samples) {
            if (j % 16 == 0) {
                IJ.showProgress(j, total);
            }
            mean[j] = pair.getMean();
            variance[j] = pair.variance;
            // Gain is in Count / e
            double gain = variance[j] / (mean[j] - bias);
            gainStats.add(gain);
            obs.add(mean[j], variance[j]);
            if (emMode) {
                gain /= (2 * settings.cameraGain);
            }
            if (sb != null) {
                sb.append(sample.title).append('\t');
                sb.append(sample.exposure).append('\t');
                sb.append(pair.slice1).append('\t');
                sb.append(pair.slice2).append('\t');
                sb.append(IJ.d2s(pair.mean1, 2)).append('\t');
                sb.append(IJ.d2s(pair.mean2, 2)).append('\t');
                sb.append(IJ.d2s(mean[j], 2)).append('\t');
                sb.append(IJ.d2s(variance[j], 2)).append('\t');
                sb.append(MathUtils.rounded(gain, 4)).append("\n");
            }
            j++;
        }
        if (results != null && sb != null) {
            results.append(sb.toString());
        }
    }
    IJ.showProgress(1);
    if (singleImage) {
        StoredDataStatistics stats = (StoredDataStatistics) gainStats;
        ImageJUtils.log(TITLE);
        if (emMode) {
            final double[] values = stats.getValues();
            MathArrays.scaleInPlace(0.5, values);
            stats = StoredDataStatistics.create(values);
        }
        if (settings.showCharts) {
            // Plot the gain over time
            final String title = TITLE + " Gain vs Frame";
            final Plot plot = new Plot(title, "Slice", "Gain");
            plot.addPoints(SimpleArrayUtils.newArray(gainStats.getN(), 1, 1.0), stats.getValues(), Plot.LINE);
            final PlotWindow pw = ImageJUtils.display(title, plot);
            // Show a histogram
            final String label = String.format("Mean = %s, Median = %s", MathUtils.rounded(stats.getMean()), MathUtils.rounded(stats.getMedian()));
            final WindowOrganiser wo = new WindowOrganiser();
            final PlotWindow pw2 = new HistogramPlotBuilder(TITLE, stats, "Gain").setRemoveOutliersOption(1).setPlotLabel(label).show(wo);
            if (wo.isNotEmpty()) {
                final Point point = pw.getLocation();
                point.y += pw.getHeight();
                pw2.setLocation(point);
            }
        }
        ImageJUtils.log("Single-image mode: %s camera", (emMode) ? "EM-CCD" : "Standard");
        final double gain = stats.getMedian();
        if (emMode) {
            final double totalGain = gain;
            final double emGain = totalGain / settings.cameraGain;
            ImageJUtils.log("  Gain = 1 / %s (Count/e-)", MathUtils.rounded(settings.cameraGain, 4));
            ImageJUtils.log("  EM-Gain = %s", MathUtils.rounded(emGain, 4));
            ImageJUtils.log("  Total Gain = %s (Count/e-)", MathUtils.rounded(totalGain, 4));
        } else {
            settings.cameraGain = gain;
            ImageJUtils.log("  Gain = 1 / %s (Count/e-)", MathUtils.rounded(settings.cameraGain, 4));
        }
    } else {
        IJ.showStatus("Computing fit");
        // Sort
        final int[] indices = rank(mean);
        mean = reorder(mean, indices);
        variance = reorder(variance, indices);
        // Compute optimal coefficients.
        // a - b x
        final double[] init = { 0, 1 / gainStats.getMean() };
        final PolynomialCurveFitter fitter = PolynomialCurveFitter.create(2).withStartPoint(init);
        final double[] best = fitter.fit(obs.toList());
        // Construct the polynomial that best fits the data.
        final PolynomialFunction fitted = new PolynomialFunction(best);
        if (settings.showCharts) {
            // Plot mean verses variance. Gradient is gain in Count/e.
            final String title = TITLE + " results";
            final Plot plot = new Plot(title, "Mean", "Variance");
            final double[] xlimits = MathUtils.limits(mean);
            final double[] ylimits = MathUtils.limits(variance);
            double xrange = (xlimits[1] - xlimits[0]) * 0.05;
            if (xrange == 0) {
                xrange = 0.05;
            }
            double yrange = (ylimits[1] - ylimits[0]) * 0.05;
            if (yrange == 0) {
                yrange = 0.05;
            }
            plot.setLimits(xlimits[0] - xrange, xlimits[1] + xrange, ylimits[0] - yrange, ylimits[1] + yrange);
            plot.setColor(Color.blue);
            plot.addPoints(mean, variance, Plot.CROSS);
            plot.setColor(Color.red);
            plot.addPoints(new double[] { mean[0], mean[mean.length - 1] }, new double[] { fitted.value(mean[0]), fitted.value(mean[mean.length - 1]) }, Plot.LINE);
            ImageJUtils.display(title, plot);
        }
        final double avBiasNoise = Math.sqrt(noiseStats.getMean());
        ImageJUtils.log(TITLE);
        ImageJUtils.log("  Directory = %s", inputDirectory);
        ImageJUtils.log("  Bias = %s +/- %s (Count)", MathUtils.rounded(bias, 4), MathUtils.rounded(avBiasNoise, 4));
        ImageJUtils.log("  Variance = %s + %s * mean", MathUtils.rounded(best[0], 4), MathUtils.rounded(best[1], 4));
        if (emMode) {
            // The gradient is the observed gain of the noise.
            // In an EM-CCD there is a noise factor of 2.
            // Q. Is this true for a correct noise factor calibration:
            // double noiseFactor = (Read Noise EM-CCD) / (Read Noise CCD)
            // Em-gain is the observed gain divided by the noise factor multiplied by camera gain
            final double emGain = best[1] / (2 * settings.cameraGain);
            // Compute total gain
            final double totalGain = emGain * settings.cameraGain;
            final double readNoise = avBiasNoise / settings.cameraGain;
            // Effective noise is standard deviation of the bias image divided by the total gain (in
            // Count/e-)
            final double readNoiseE = avBiasNoise / totalGain;
            ImageJUtils.log("  Read Noise = %s (e-) [%s (Count)]", MathUtils.rounded(readNoise, 4), MathUtils.rounded(avBiasNoise, 4));
            ImageJUtils.log("  Gain = 1 / %s (Count/e-)", MathUtils.rounded(1 / settings.cameraGain, 4));
            ImageJUtils.log("  EM-Gain = %s", MathUtils.rounded(emGain, 4));
            ImageJUtils.log("  Total Gain = %s (Count/e-)", MathUtils.rounded(totalGain, 4));
            ImageJUtils.log("  Effective Read Noise = %s (e-) (Read Noise/Total Gain)", MathUtils.rounded(readNoiseE, 4));
        } else {
            // The gradient is the observed gain of the noise.
            settings.cameraGain = best[1];
            // Noise is standard deviation of the bias image divided by the gain (in Count/e-)
            final double readNoise = avBiasNoise / settings.cameraGain;
            ImageJUtils.log("  Read Noise = %s (e-) [%s (Count)]", MathUtils.rounded(readNoise, 4), MathUtils.rounded(avBiasNoise, 4));
            ImageJUtils.log("  Gain = 1 / %s (Count/e-)", MathUtils.rounded(1 / settings.cameraGain, 4));
        }
    }
    IJ.showStatus("");
}