Examples with MemoryPeakResults gdsc.smlm.results.MemoryPeakResults used on opensource projects

Example 71 with MemoryPeakResults

use of gdsc.smlm.results.MemoryPeakResults in project GDSC-SMLM by aherbert.

the class FilterAnalysis method readResults.

private List<MemoryPeakResults> readResults() {
    if (resultsList != null && inputDirectory.equals(lastInputDirectory)) {
        GenericDialog gd = new GenericDialog(TITLE);
        gd.addMessage("Re-use results from the same directory (no to refresh)?");
        gd.enableYesNoCancel();
        gd.hideCancelButton();
        gd.showDialog();
        if (gd.wasOKed())
            return resultsList;
    }
    List<MemoryPeakResults> resultsList = new LinkedList<MemoryPeakResults>();
    File[] fileList = (new File(inputDirectory)).listFiles(new FilenameFilter() {

        public boolean accept(File dir, String name) {
            return (name.endsWith(".xls") || name.endsWith(".csv") || name.endsWith(".bin"));
        }
    });
    if (fileList != null) {
        // Exclude directories
        for (int i = 0; i < fileList.length; i++) {
            if (fileList[i].isFile()) {
                IJ.showStatus(String.format("Reading results ... %d/%d", i + 1, fileList.length));
                IJ.showProgress(i, fileList.length);
                PeakResultsReader reader = new PeakResultsReader(fileList[i].getPath());
                MemoryPeakResults results = reader.getResults();
                if (results != null && results.size() > 0) {
                    resultsList.add(results);
                }
            }
        }
    }
    IJ.showStatus("");
    IJ.showProgress(1);
    lastInputDirectory = inputDirectory;
    return resultsList;
}

Example 72 with MemoryPeakResults

use of gdsc.smlm.results.MemoryPeakResults in project GDSC-SMLM by aherbert.

the class DriftCalculator method run.

/*
	 * (non-Javadoc)
	 * 
	 * @see ij.plugin.PlugIn#run(java.lang.String)
	 */
public void run(String arg) {
    SMLMUsageTracker.recordPlugin(this.getClass(), arg);
    // Require some fit results and selected regions
    if (MemoryPeakResults.isMemoryEmpty()) {
        IJ.error(TITLE, "There are no fitting results in memory");
        return;
    }
    Roi[] rois = getRois();
    String[] stackTitles = createStackImageList();
    if (!showDialog(rois, stackTitles))
        return;
    MemoryPeakResults results = ResultsManager.loadInputResults(inputOption, false);
    if (results == null || results.size() < 2) {
        IJ.error(TITLE, "There are not enough fitting results for drift correction");
        return;
    }
    double[][] drift = null;
    int[] limits = findTimeLimits(results);
    if (method.equals(MARKED_ROIS)) {
        drift = calculateUsingMarkers(results, limits, rois);
    } else if (method.equals(STACK_ALIGNMENT)) {
        ImageStack stack = showStackDialog(stackTitles);
        if (stack == null)
            return;
        drift = calculateUsingImageStack(stack, limits);
    } else if (method.equals(DRIFT_FILE)) {
        drift = calculateUsingDriftFile(limits);
    } else {
        if (!showSubImageDialog())
            return;
        drift = calculateUsingFrames(results, limits, Integer.parseInt(reconstructionSize));
    }
    if (drift == null)
        return;
    Utils.log("Drift correction interpolated for frames [%d - %d] of [%d - %d] (%s%%)", interpolationStart, interpolationEnd, limits[0], limits[1], Utils.rounded((100.0 * (interpolationEnd - interpolationStart + 1)) / (limits[1] - limits[0] + 1)));
    applyDriftCorrection(results, drift);
}

Example 73 with MemoryPeakResults

use of gdsc.smlm.results.MemoryPeakResults in project GDSC-SMLM by aherbert.

the class CropResults method cropResults.

/**
	 * Apply the filters to the data
	 */
private void cropResults() {
    MemoryPeakResults newResults = new MemoryPeakResults();
    // These bounds are integer. But this is because the results are meant to come from an image.
    Rectangle bounds = results.getBounds(true);
    // The crop bounds can be floating point...
    // Border
    double xx = bounds.x + border;
    double yy = bounds.y + border;
    double w = Math.max(0, bounds.width - 2 * border);
    double h = Math.max(0, bounds.height - 2 * border);
    Rectangle2D borderBounds = new Rectangle2D.Double(xx, yy, w, h);
    // Bounding box
    if (selectRegion) {
        Rectangle2D boxBounds = new Rectangle2D.Double(x, y, width, height);
        borderBounds = borderBounds.createIntersection(boxBounds);
    }
    // and create another intersection
    if (myUseRoi) {
        ImagePlus imp = WindowManager.getImage(roiImage);
        if (imp != null && imp.getRoi() != null) {
            Rectangle roi = imp.getRoi().getBounds();
            int roiImageWidth = imp.getWidth();
            int roiImageHeight = imp.getHeight();
            double xscale = (double) roiImageWidth / bounds.width;
            double yscale = (double) roiImageHeight / bounds.height;
            Rectangle2D roiBounds = new Rectangle2D.Double(roi.x / xscale, roi.y / yscale, roi.width / xscale, roi.height / yscale);
            borderBounds = borderBounds.createIntersection(roiBounds);
        }
    }
    if (borderBounds.getWidth() > 0 && borderBounds.getHeight() > 0) {
        for (PeakResult result : results.getResults()) {
            if (borderBounds.contains(result.getXPosition(), result.getYPosition()))
                newResults.add(result);
        }
    }
    newResults.copySettings(results);
    newResults.setBounds(new Rectangle((int) Math.floor(borderBounds.getX()), (int) Math.floor(borderBounds.getY()), (int) Math.ceil(borderBounds.getWidth()), (int) Math.ceil(borderBounds.getHeight())));
    if (!overwrite) {
        newResults.setName(results.getName() + " Cropped");
    }
    MemoryPeakResults.addResults(newResults);
    IJ.showStatus(newResults.size() + " Cropped localisations");
}

Example 74 with MemoryPeakResults

use of gdsc.smlm.results.MemoryPeakResults in project GDSC-SMLM by aherbert.

the class DarkTimeAnalysis method run.

/*
	 * (non-Javadoc)
	 * 
	 * @see ij.plugin.PlugIn#run(java.lang.String)
	 */
public void run(String arg) {
    SMLMUsageTracker.recordPlugin(this.getClass(), arg);
    // Require some fit results and selected regions
    if (MemoryPeakResults.isMemoryEmpty()) {
        IJ.error(TITLE, "There are no fitting results in memory");
        return;
    }
    if (!showDialog())
        return;
    MemoryPeakResults results = ResultsManager.loadInputResults(inputOption, true);
    if (results == null || results.size() == 0) {
        IJ.error(TITLE, "No results could be loaded");
        IJ.showStatus("");
        return;
    }
    msPerFrame = results.getCalibration().getExposureTime();
    Utils.log("%s: %d localisations", TITLE, results.size());
    if (results.size() == 0) {
        IJ.error(TITLE, "No results were loaded");
        return;
    }
    analyse(results);
}

Example 75 with MemoryPeakResults

use of gdsc.smlm.results.MemoryPeakResults in project GDSC-SMLM by aherbert.

the class DiffusionRateTest method aggregateIntoFrames.

private void aggregateIntoFrames(ArrayList<Point> points, boolean addError, double precisionInPixels, RandomGenerator[] random) {
    if (myAggregateSteps < 1)
        return;
    MemoryPeakResults results = new MemoryPeakResults(points.size() / myAggregateSteps);
    Calibration cal = new Calibration(settings.pixelPitch, 1, myAggregateSteps * 1000.0 / settings.stepsPerSecond);
    results.setCalibration(cal);
    results.setName(TITLE + " Aggregated");
    MemoryPeakResults.addResults(results);
    lastSimulatedDataset[1] = results.getName();
    int id = 0;
    int peak = 1;
    int n = 0;
    double cx = 0, cy = 0;
    // Get the mean square distance
    double sum = 0;
    int count = 0;
    PeakResult last = null;
    for (Point result : points) {
        final boolean newId = result.id != id;
        if (n >= myAggregateSteps || newId) {
            if (n != 0) {
                final float[] params = new float[7];
                double[] xyz = new double[] { cx / n, cy / n };
                if (addError)
                    xyz = addError(xyz, precisionInPixels, random);
                params[Gaussian2DFunction.X_POSITION] = (float) xyz[0];
                params[Gaussian2DFunction.Y_POSITION] = (float) xyz[1];
                params[Gaussian2DFunction.SIGNAL] = n;
                params[Gaussian2DFunction.X_SD] = params[Gaussian2DFunction.Y_SD] = 1;
                final float noise = 0.1f;
                PeakResult r = new ExtendedPeakResult(peak, (int) params[Gaussian2DFunction.X_POSITION], (int) params[Gaussian2DFunction.Y_POSITION], n, 0, noise, params, null, peak, id);
                results.add(r);
                if (last != null) {
                    sum += last.distance2(r);
                    count++;
                }
                last = r;
                n = 0;
                cx = cy = 0;
                peak++;
            }
            if (newId) {
                // Increment the frame so that tracing analysis can distinguish traces
                peak++;
                last = null;
                id = result.id;
            }
        }
        n++;
        cx += result.x;
        cy += result.y;
    }
    // Final peak
    if (n != 0) {
        final float[] params = new float[7];
        double[] xyz = new double[] { cx / n, cy / n };
        if (addError)
            xyz = addError(xyz, precisionInPixels, random);
        params[Gaussian2DFunction.X_POSITION] = (float) xyz[0];
        params[Gaussian2DFunction.Y_POSITION] = (float) xyz[1];
        params[Gaussian2DFunction.SIGNAL] = n;
        params[Gaussian2DFunction.X_SD] = params[Gaussian2DFunction.Y_SD] = 1;
        final float noise = 0.1f;
        PeakResult r = new ExtendedPeakResult(peak, (int) params[Gaussian2DFunction.X_POSITION], (int) params[Gaussian2DFunction.Y_POSITION], n, 0, noise, params, null, peak, id);
        results.add(r);
        if (last != null) {
            sum += last.distance2(r);
            count++;
        }
    }
    // MSD in pixels^2 / frame
    double msd = sum / count;
    // Convert to um^2/second
    Utils.log("Aggregated data D=%s um^2/s, Precision=%s nm, N=%d, step=%s s, mean=%s um^2, MSD = %s um^2/s", Utils.rounded(settings.diffusionRate), Utils.rounded(myPrecision), count, Utils.rounded(results.getCalibration().getExposureTime() / 1000), Utils.rounded(msd / conversionFactor), Utils.rounded((msd / conversionFactor) / (results.getCalibration().getExposureTime() / 1000)));
    msdAnalysis(points);
}