use of uk.ac.sussex.gdsc.smlm.results.count.FrameCounter in project GDSC-SMLM by aherbert.
the class CreateData method showSummary.
private double showSummary(List<? extends FluorophoreSequenceModel> fluorophores, List<LocalisationModel> localisations) {
IJ.showStatus("Calculating statistics ...");
final Statistics[] stats = new Statistics[NAMES.length];
for (int i = 0; i < stats.length; i++) {
stats[i] = (settings.getShowHistograms() || alwaysRemoveOutliers[i]) ? new StoredDataStatistics() : new Statistics();
}
// Find the largest timepoint
final ImagePlus outputImp = WindowManager.getImage(benchmarkImageId);
int frameCount;
if (outputImp == null) {
sortLocalisationsByTime(localisations);
frameCount = localisations.get(localisations.size() - 1).getTime();
} else {
frameCount = outputImp.getStackSize();
}
final int[] countHistogram = new int[frameCount + 1];
// Use the localisations that were drawn to create the sampled on/off times
rebuildNeighbours(localisations);
// Assume that there is at least one localisation
final LocalisationModel first = localisations.get(0);
// The current localisation
int currentId = first.getId();
// The last time this localisation was on
int lastT = first.getTime();
// Number of blinks
int blinks = 0;
// On-time of current pulse
int currentT = 0;
double signal = 0;
final double centreOffset = settings.getSize() * 0.5;
// Used to convert the sampled times in frames into seconds
final double framesPerSecond = 1000.0 / settings.getExposureTime();
// final double gain = new CreateDataSettingsHelper(settings).getTotalGainSafe();
for (final LocalisationModel l : localisations) {
final double[] data = l.getData();
if (data == null) {
throw new IllegalStateException("No localisation data. This should not happen!");
}
final double noise = data[1];
final double sx = data[2];
final double sy = data[3];
final double intensityInPhotons = data[4];
// Q. What if the noise is zero, i.e. no background photon / read noise?
// Just ignore it at current. This is only an approximation to the SNR estimate
// if this is not a Gaussian spot.
final double snr = Gaussian2DPeakResultHelper.getMeanSignalUsingP05(intensityInPhotons, sx, sy) / noise;
stats[SIGNAL].add(intensityInPhotons);
stats[NOISE].add(noise);
if (noise != 0) {
stats[SNR].add(snr);
}
// if (l.isContinuous())
if (l.getNext() != null && l.getPrevious() != null) {
stats[SIGNAL_CONTINUOUS].add(intensityInPhotons);
if (noise != 0) {
stats[SNR_CONTINUOUS].add(snr);
}
}
final int id = l.getId();
// Check if this a new fluorophore
if (currentId != id) {
// Add previous fluorophore
stats[SAMPLED_BLINKS].add(blinks);
stats[SAMPLED_T_ON].add(currentT / framesPerSecond);
stats[TOTAL_SIGNAL].add(signal);
// Reset
blinks = 0;
currentT = 1;
currentId = id;
signal = intensityInPhotons;
} else {
signal += intensityInPhotons;
// Check if the current fluorophore pulse is broken (i.e. a blink)
if (l.getTime() - 1 > lastT) {
blinks++;
stats[SAMPLED_T_ON].add(currentT / framesPerSecond);
currentT = 1;
stats[SAMPLED_T_OFF].add(((l.getTime() - 1) - lastT) / framesPerSecond);
} else {
// Continuous on-time
currentT++;
}
}
lastT = l.getTime();
countHistogram[lastT]++;
stats[X].add((l.getX() - centreOffset) * settings.getPixelPitch());
stats[Y].add((l.getY() - centreOffset) * settings.getPixelPitch());
stats[Z].add(l.getZ() * settings.getPixelPitch());
}
// Final fluorophore
stats[SAMPLED_BLINKS].add(blinks);
stats[SAMPLED_T_ON].add(currentT / framesPerSecond);
stats[TOTAL_SIGNAL].add(signal);
// Samples per frame
for (int t = 1; t < countHistogram.length; t++) {
stats[SAMPLES].add(countHistogram[t]);
}
if (fluorophores != null) {
for (final FluorophoreSequenceModel f : fluorophores) {
stats[BLINKS].add(f.getNumberOfBlinks());
// On-time
for (final double t : f.getOnTimes()) {
stats[T_ON].add(t);
}
// Off-time
for (final double t : f.getOffTimes()) {
stats[T_OFF].add(t);
}
}
} else {
// show no blinks
stats[BLINKS].add(0);
stats[T_ON].add(1);
}
if (results != null) {
// Convert depth-of-field to pixels
final double depth = settings.getDepthOfField() / settings.getPixelPitch();
try {
// Get widths
final WidthResultProcedure wp = new WidthResultProcedure(results, DistanceUnit.PIXEL);
wp.getW();
stats[WIDTH].add(wp.wx);
} catch (final DataException ex) {
ImageJUtils.log("Unable to compute width: " + ex.getMessage());
}
try {
// Get z depth
final StandardResultProcedure sp = new StandardResultProcedure(results, DistanceUnit.PIXEL);
sp.getXyz();
// Get precision
final PrecisionResultProcedure pp = new PrecisionResultProcedure(results);
pp.getPrecision();
stats[PRECISION].add(pp.precisions);
for (int i = 0; i < pp.size(); i++) {
if (Math.abs(sp.z[i]) < depth) {
stats[PRECISION_IN_FOCUS].add(pp.precisions[i]);
}
}
} catch (final DataException ex) {
ImageJUtils.log("Unable to compute LSE precision: " + ex.getMessage());
}
// Compute density per frame. Multi-thread for speed
if (settings.getDensityRadius() > 0) {
final int threadCount = Prefs.getThreads();
final Ticker ticker = ImageJUtils.createTicker(results.getLastFrame(), threadCount, "Calculating density ...");
final ExecutorService threadPool = Executors.newFixedThreadPool(threadCount);
final List<Future<?>> futures = new LinkedList<>();
final TFloatArrayList coordsX = new TFloatArrayList();
final TFloatArrayList coordsY = new TFloatArrayList();
final Statistics densityStats = stats[DENSITY];
final float radius = (float) (settings.getDensityRadius() * getHwhm());
final Rectangle bounds = results.getBounds();
final double area = (double) bounds.width * bounds.height;
// Store the density for each result.
final int[] allDensity = new int[results.size()];
final FrameCounter counter = results.newFrameCounter();
results.forEach((PeakResultProcedure) result -> {
if (counter.advance(result.getFrame())) {
counter.increment(runDensityCalculation(threadPool, futures, coordsX, coordsY, densityStats, radius, area, allDensity, counter.getCount(), ticker));
}
coordsX.add(result.getXPosition());
coordsY.add(result.getYPosition());
});
runDensityCalculation(threadPool, futures, coordsX, coordsY, densityStats, radius, area, allDensity, counter.getCount(), ticker);
ConcurrencyUtils.waitForCompletionUnchecked(futures);
threadPool.shutdown();
ImageJUtils.finished();
// Split results into singles (density = 0) and clustered (density > 0)
final MemoryPeakResults singles = copyMemoryPeakResults("No Density");
final MemoryPeakResults clustered = copyMemoryPeakResults("Density");
counter.reset();
results.forEach((PeakResultProcedure) result -> {
final int density = allDensity[counter.getAndIncrement()];
result.setOrigValue(density);
if (density == 0) {
singles.add(result);
} else {
clustered.add(result);
}
});
}
}
final StringBuilder sb = new StringBuilder();
sb.append(datasetNumber).append('\t');
if (settings.getCameraType() == CameraType.SCMOS) {
sb.append("sCMOS (").append(settings.getCameraModelName()).append(") ");
final Rectangle bounds = cameraModel.getBounds();
sb.append(" ").append(bounds.x).append(",").append(bounds.y);
final int size = settings.getSize();
sb.append(" ").append(size).append("x").append(size);
} else if (CalibrationProtosHelper.isCcdCameraType(settings.getCameraType())) {
sb.append(CalibrationProtosHelper.getName(settings.getCameraType()));
final int size = settings.getSize();
sb.append(" ").append(size).append("x").append(size);
if (settings.getCameraType() == CameraType.EMCCD) {
sb.append(" EM=").append(settings.getEmGain());
}
sb.append(" CG=").append(settings.getCameraGain());
sb.append(" RN=").append(settings.getReadNoise());
sb.append(" B=").append(settings.getBias());
} else {
throw new IllegalStateException();
}
sb.append(" QE=").append(settings.getQuantumEfficiency()).append('\t');
sb.append(settings.getPsfModel());
if (psfModelType == PSF_MODEL_IMAGE) {
sb.append(" Image").append(settings.getPsfImageName());
} else if (psfModelType == PSF_MODEL_ASTIGMATISM) {
sb.append(" model=").append(settings.getAstigmatismModel());
} else {
sb.append(" DoF=").append(MathUtils.rounded(settings.getDepthOfFocus()));
if (settings.getEnterWidth()) {
sb.append(" SD=").append(MathUtils.rounded(settings.getPsfSd()));
} else {
sb.append(" λ=").append(MathUtils.rounded(settings.getWavelength()));
sb.append(" NA=").append(MathUtils.rounded(settings.getNumericalAperture()));
}
}
sb.append('\t');
sb.append((fluorophores == null) ? localisations.size() : fluorophores.size()).append('\t');
sb.append(stats[SAMPLED_BLINKS].getN() + (int) stats[SAMPLED_BLINKS].getSum()).append('\t');
sb.append(localisations.size()).append('\t');
sb.append(frameCount).append('\t');
sb.append(MathUtils.rounded(areaInUm)).append('\t');
sb.append(MathUtils.rounded(localisations.size() / (areaInUm * frameCount), 4)).append('\t');
sb.append(MathUtils.rounded(getHwhm(), 4)).append('\t');
double sd = getPsfSd();
sb.append(MathUtils.rounded(sd, 4)).append('\t');
sd *= settings.getPixelPitch();
final double sa = PsfCalculator.squarePixelAdjustment(sd, settings.getPixelPitch()) / settings.getPixelPitch();
sb.append(MathUtils.rounded(sa, 4)).append('\t');
// Width not valid for the Image PSF.
// Q. Is this true? We can approximate the FHWM for a spot-like image PSF.
final int nStats = (psfModelType == PSF_MODEL_IMAGE) ? stats.length - 1 : stats.length;
for (int i = 0; i < nStats; i++) {
final double centre = (alwaysRemoveOutliers[i]) ? ((StoredDataStatistics) stats[i]).getStatistics().getPercentile(50) : stats[i].getMean();
sb.append(MathUtils.rounded(centre, 4)).append('\t');
}
createSummaryTable().accept(sb.toString());
// Show histograms
if (settings.getShowHistograms() && !java.awt.GraphicsEnvironment.isHeadless()) {
IJ.showStatus("Calculating histograms ...");
final boolean[] chosenHistograms = getChoosenHistograms();
final WindowOrganiser wo = new WindowOrganiser();
final HistogramPlotBuilder builder = new HistogramPlotBuilder(TITLE);
for (int i = 0; i < NAMES.length; i++) {
if (chosenHistograms[i]) {
builder.setData((StoredDataStatistics) stats[i]).setName(NAMES[i]).setIntegerBins(integerDisplay[i]).setRemoveOutliersOption((settings.getRemoveOutliers() || alwaysRemoveOutliers[i]) ? 2 : 0).setNumberOfBins(settings.getHistogramBins()).show(wo);
}
}
wo.tile();
}
IJ.showStatus("");
return stats[SIGNAL].getMean();
}
use of uk.ac.sussex.gdsc.smlm.results.count.FrameCounter in project GDSC-SMLM by aherbert.
the class CreateData method saveFixedAndMoving.
private void saveFixedAndMoving(MemoryPeakResults results) {
if (simpleMode || benchmarkMode || spotMode) {
return;
}
if (settings.getDiffusionRate() <= 0 || settings.getFixedFraction() >= 1) {
return;
}
final MemoryPeakResults fixedResults = copyMemoryPeakResults("Fixed");
final MemoryPeakResults movingResults = copyMemoryPeakResults("Moving");
final PeakResult[] peakResults = results.toArray();
// Sort using the ID
Arrays.sort(peakResults, new Comparator<PeakResult>() {
@Override
public int compare(PeakResult o1, PeakResult o2) {
return o1.getId() - o2.getId();
}
});
MemoryPeakResults currentResults = movingResults;
final FrameCounter counter = new FrameCounter(-1);
for (final PeakResult p : peakResults) {
if (counter.advance(p.getId())) {
currentResults = (movingMolecules.contains(p.getId())) ? movingResults : fixedResults;
}
currentResults.add(p);
}
movingResults.end();
fixedResults.end();
}
use of uk.ac.sussex.gdsc.smlm.results.count.FrameCounter in project GDSC-SMLM by aherbert.
the class TraceExporter method exportVbSpt.
@SuppressWarnings("resource")
private void exportVbSpt(MemoryPeakResults results) {
// vbSPT file format:
// https://sourceforge.net/projects/vbspt/
// Matlab matrix file (.mat) containing at least one variable that is a cell
// array where each element, representing a trajectory, is a matrix
// where the rows define the coordinates in one, two or three dimensions
// in subsequent timesteps. The number of dimensions to be used for the
// analysis will be set by the runinputfile.
// The units are arbitrary but vbSPT starting estimates must be in the same
// units. Either nm or μm are recommended.
// 3 columns for n rows of localisations
// 1. x coordinate (μm)
// 2. y coordinate (μm)
// 3. z coordinate (μm)
//
// Note: An extra column is added containing the frame. This allows results to
// be uniquely identified using frame,x,y,z
// Count the IDs. Each new result ID will increment the count.
final FrameCounter idCounter = new FrameCounter(results.getFirst().getId() - 1);
results.forEach((PeakResultProcedure) result -> {
if (idCounter.advance(result.getId())) {
idCounter.increment();
}
});
// Create the cell array as 1xN
final Cell out = Mat5.newCell(1, idCounter.getCount());
// This will reset the counter to zero and ensure the current frame does not match
// in the event of a single track
idCounter.advanceAndReset(idCounter.currentFrame() + 1);
final boolean is3d = results.is3D();
// Write the tracks
final LocalList<double[]> list = new LocalList<>();
results.forEach(DistanceUnit.UM, (XyzrResultProcedure) (x, y, z, result) -> {
if (idCounter.advance(result.getId())) {
addTrack(out, idCounter.getCount() - 1, list, is3d);
idCounter.increment();
list.clear();
}
list.add(new double[] { x, y, z, result.getFrame() });
});
addTrack(out, idCounter.getCount() - 1, list, is3d);
try (MatFile matFile = Mat5.newMatFile()) {
matFile.addArray("tracks", out);
Mat5.writeToFile(matFile, Paths.get(settings.directory, results.getName() + ".mat").toFile());
} catch (final IOException ex) {
handleException(ex);
}
}
use of uk.ac.sussex.gdsc.smlm.results.count.FrameCounter in project GDSC-SMLM by aherbert.
the class TcPalmAnalysis method createClusterData.
@SuppressWarnings("null")
private static LocalList<ClusterData> createClusterData(MemoryPeakResults results) {
results.sort(IdFramePeakResultComparator.INSTANCE);
final LocalList<ClusterData> clusterData = new LocalList<>();
final FrameCounter counter = new FrameCounter(results.getFirst().getId() - 1);
ClusterData data = null;
final int size = results.size();
for (int i = 0; i < size; i++) {
final PeakResult result = results.get(i);
if (counter.advance(result.getId())) {
clusterData.add(data);
data = new ClusterData(result);
} else {
data.add(result);
}
}
// Final cluster
clusterData.add(data);
// Remove the first null object and compact the frame arrays
clusterData.remove(0);
clusterData.forEach(ClusterData::finish);
// Sort by time then cluster ID
clusterData.sort((c1, c2) -> {
final int result = Integer.compare(c1.start, c2.start);
if (result != 0) {
return result;
}
// }
return Integer.compare(c1.id, c2.id);
});
return clusterData;
}
use of uk.ac.sussex.gdsc.smlm.results.count.FrameCounter in project GDSC-SMLM by aherbert.
the class PeakFit method getSingleFrame.
/**
* Gets the single frame containing all the results (if they are all in a single frame), else 0.
*
* @param results the results (must not be empty)
* @return the single frame (or zero)
*/
private static int getSingleFrame(MemoryPeakResults results) {
final FrameCounter counter = new FrameCounter(results.getFirstFrame());
// The counter will return true (stop execution) if a new frame
results.forEach((PeakResultProcedureX) peakResult -> counter.advance(peakResult.getFrame()));
if (counter.currentFrame() != counter.previousFrame()) {
return 0;
}
return counter.currentFrame();
}
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