use of gdsc.core.utils.Random in project GDSC-SMLM by aherbert.
the class PSFEstimator method calculateStatistics.
private boolean calculateStatistics(PeakFit fitter, double[] params, double[] params_dev) {
debug(" Fitting PSF");
swapStatistics();
// Create the fit engine using the PeakFit plugin
FitConfiguration fitConfig = config.getFitConfiguration();
fitConfig.setInitialAngle((float) params[0]);
fitConfig.setInitialPeakStdDev0((float) params[1]);
fitConfig.setInitialPeakStdDev1((float) params[2]);
ImageStack stack = imp.getImageStack();
Rectangle roi = stack.getProcessor(1).getRoi();
ImageSource source = new IJImageSource(imp);
// Allow interlaced data by wrapping the image source
if (interlacedData) {
source = new InterlacedImageSource(source, dataStart, dataBlock, dataSkip);
}
// Allow frame aggregation by wrapping the image source
if (integrateFrames > 1) {
source = new AggregatedImageSource(source, integrateFrames);
}
fitter.initialiseImage(source, roi, true);
fitter.addPeakResults(this);
fitter.initialiseFitting();
FitEngine engine = fitter.createFitEngine();
// Use random slices
int[] slices = new int[stack.getSize()];
for (int i = 0; i < slices.length; i++) slices[i] = i + 1;
Random rand = new Random();
rand.shuffle(slices);
IJ.showStatus("Fitting ...");
// Use multi-threaded code for speed
int i;
for (i = 0; i < slices.length; i++) {
int slice = slices[i];
//debug(" Processing slice = %d\n", slice);
IJ.showProgress(size(), settings.numberOfPeaks);
ImageProcessor ip = stack.getProcessor(slice);
// stack processor does not set the bounds required by ImageConverter
ip.setRoi(roi);
FitJob job = new FitJob(slice, ImageConverter.getData(ip), roi);
engine.run(job);
if (sampleSizeReached() || Utils.isInterrupted()) {
break;
}
}
if (Utils.isInterrupted()) {
IJ.showProgress(1);
engine.end(true);
return false;
}
// Wait until we have enough results
while (!sampleSizeReached() && !engine.isQueueEmpty()) {
IJ.showProgress(size(), settings.numberOfPeaks);
try {
Thread.sleep(50);
} catch (InterruptedException e) {
break;
}
}
// End now if we have enough samples
engine.end(sampleSizeReached());
IJ.showStatus("");
IJ.showProgress(1);
// This count will be an over-estimate given that the provider is ahead of the consumer
// in this multi-threaded system
debug(" Processed %d/%d slices (%d peaks)", i, slices.length, size());
setParams(ANGLE, params, params_dev, sampleNew[ANGLE]);
setParams(X, params, params_dev, sampleNew[X]);
setParams(Y, params, params_dev, sampleNew[Y]);
if (settings.showHistograms) {
int[] idList = new int[NAMES.length];
int count = 0;
boolean requireRetile = false;
for (int ii = 0; ii < 3; ii++) {
if (sampleNew[ii].getN() == 0)
continue;
StoredDataStatistics stats = new StoredDataStatistics(sampleNew[ii].getValues());
idList[count++] = Utils.showHistogram(TITLE, stats, NAMES[ii], 0, 0, settings.histogramBins, "Mean = " + Utils.rounded(stats.getMean()) + ". Median = " + Utils.rounded(sampleNew[ii].getPercentile(50)));
requireRetile = requireRetile || Utils.isNewWindow();
}
if (requireRetile && count > 0) {
new WindowOrganiser().tileWindows(Arrays.copyOf(idList, count));
}
}
if (size() < 2) {
log("ERROR: Insufficient number of fitted peaks, terminating ...");
return false;
}
return true;
}
use of gdsc.core.utils.Random in project GDSC-SMLM by aherbert.
the class CreateData method run.
/*
* (non-Javadoc)
*
* @see ij.plugin.PlugIn#run(java.lang.String)
*/
public void run(String arg) {
SMLMUsageTracker.recordPlugin(this.getClass(), arg);
extraOptions = Utils.isExtraOptions();
simpleMode = (arg != null && arg.contains("simple"));
benchmarkMode = (arg != null && arg.contains("benchmark"));
spotMode = (arg != null && arg.contains("spot"));
trackMode = (arg != null && arg.contains("track"));
if ("load".equals(arg)) {
loadBenchmarkData();
return;
}
// Each localisation is a simulated emission of light from a point in space and time
List<LocalisationModel> localisations = null;
// Each localisation set is a collection of localisations that represent all localisations
// with the same ID that are on in the same image time frame (Note: the simulation
// can create many localisations per fluorophore per time frame which is useful when
// modelling moving particles)
List<LocalisationModelSet> localisationSets = null;
// Each fluorophore contains the on and off times when light was emitted
List<? extends FluorophoreSequenceModel> fluorophores = null;
if (simpleMode || benchmarkMode || spotMode) {
if (!showSimpleDialog())
return;
resetMemory();
// 1 second frames
settings.exposureTime = 1000;
areaInUm = settings.size * settings.pixelPitch * settings.size * settings.pixelPitch / 1e6;
// Number of spots per frame
int n = 0;
int[] nextN = null;
SpatialDistribution dist;
if (benchmarkMode) {
// --------------------
// BENCHMARK SIMULATION
// --------------------
// Draw the same point on the image repeatedly
n = 1;
dist = createFixedDistribution();
reportAndSaveFittingLimits(dist);
} else if (spotMode) {
// ---------------
// SPOT SIMULATION
// ---------------
// The spot simulation draws 0 or 1 random point per frame.
// Ensure we have 50% of the frames with a spot.
nextN = new int[settings.particles * 2];
Arrays.fill(nextN, 0, settings.particles, 1);
Random rand = new Random();
rand.shuffle(nextN);
// Only put spots in the central part of the image
double border = settings.size / 4.0;
dist = createUniformDistribution(border);
} else {
// -----------------
// SIMPLE SIMULATION
// -----------------
// The simple simulation draws n random points per frame to achieve a specified density.
// No points will appear in multiple frames.
// Each point has a random number of photons sampled from a range.
// We can optionally use a mask. Create his first as it updates the areaInUm
dist = createDistribution();
// Randomly sample (i.e. not uniform density in all frames)
if (settings.samplePerFrame) {
final double mean = areaInUm * settings.density;
System.out.printf("Mean samples = %f\n", mean);
if (mean < 0.5) {
GenericDialog gd = new GenericDialog(TITLE);
gd.addMessage("The mean samples per frame is low: " + Utils.rounded(mean) + "\n \nContinue?");
gd.enableYesNoCancel();
gd.hideCancelButton();
gd.showDialog();
if (!gd.wasOKed())
return;
}
PoissonDistribution poisson = new PoissonDistribution(createRandomGenerator(), mean, PoissonDistribution.DEFAULT_EPSILON, PoissonDistribution.DEFAULT_MAX_ITERATIONS);
StoredDataStatistics samples = new StoredDataStatistics(settings.particles);
while (samples.getSum() < settings.particles) {
samples.add(poisson.sample());
}
nextN = new int[samples.getN()];
for (int i = 0; i < nextN.length; i++) nextN[i] = (int) samples.getValue(i);
} else {
// Use the density to get the number per frame
n = (int) FastMath.max(1, Math.round(areaInUm * settings.density));
}
}
RandomGenerator random = null;
localisations = new ArrayList<LocalisationModel>(settings.particles);
localisationSets = new ArrayList<LocalisationModelSet>(settings.particles);
final int minPhotons = (int) settings.photonsPerSecond;
final int range = (int) settings.photonsPerSecondMaximum - minPhotons + 1;
if (range > 1)
random = createRandomGenerator();
// Add frames at the specified density until the number of particles has been reached
int id = 0;
int t = 0;
while (id < settings.particles) {
// Allow the number per frame to be specified
if (nextN != null) {
if (t >= nextN.length)
break;
n = nextN[t];
}
// Simulate random positions in the frame for the specified density
t++;
for (int j = 0; j < n; j++) {
final double[] xyz = dist.next();
// Ignore within border. We do not want to draw things we cannot fit.
//if (!distBorder.isWithinXY(xyz))
// continue;
// Simulate random photons
final int intensity = minPhotons + ((random != null) ? random.nextInt(range) : 0);
LocalisationModel m = new LocalisationModel(id, t, xyz, intensity, LocalisationModel.CONTINUOUS);
localisations.add(m);
// Each localisation can be a separate localisation set
LocalisationModelSet set = new LocalisationModelSet(id, t);
set.add(m);
localisationSets.add(set);
id++;
}
}
} else {
if (!showDialog())
return;
resetMemory();
areaInUm = settings.size * settings.pixelPitch * settings.size * settings.pixelPitch / 1e6;
int totalSteps;
double correlation = 0;
ImageModel imageModel;
if (trackMode) {
// ----------------
// TRACK SIMULATION
// ----------------
// In track mode we create fixed lifetime fluorophores that do not overlap in time.
// This is the simplest simulation to test moving molecules.
settings.seconds = (int) Math.ceil(settings.particles * (settings.exposureTime + settings.tOn) / 1000);
totalSteps = 0;
final double simulationStepsPerFrame = (settings.stepsPerSecond * settings.exposureTime) / 1000.0;
imageModel = new FixedLifetimeImageModel(settings.stepsPerSecond * settings.tOn / 1000.0, simulationStepsPerFrame);
} else {
// ---------------
// FULL SIMULATION
// ---------------
// The full simulation draws n random points in space.
// The same molecule may appear in multiple frames, move and blink.
//
// Points are modelled as fluorophores that must be activated and then will
// blink and photo-bleach. The molecules may diffuse and this can be simulated
// with many steps per image frame. All steps from a frame are collected
// into a localisation set which can be drawn on the output image.
SpatialIllumination activationIllumination = createIllumination(settings.pulseRatio, settings.pulseInterval);
// Generate additional frames so that each frame has the set number of simulation steps
totalSteps = (int) Math.ceil(settings.seconds * settings.stepsPerSecond);
// Since we have an exponential decay of activations
// ensure half of the particles have activated by 30% of the frames.
double eAct = totalSteps * 0.3 * activationIllumination.getAveragePhotons();
// Q. Does tOn/tOff change depending on the illumination strength?
imageModel = new ActivationEnergyImageModel(eAct, activationIllumination, settings.stepsPerSecond * settings.tOn / 1000.0, settings.stepsPerSecond * settings.tOffShort / 1000.0, settings.stepsPerSecond * settings.tOffLong / 1000.0, settings.nBlinksShort, settings.nBlinksLong);
imageModel.setUseGeometricDistribution(settings.nBlinksGeometricDistribution);
// Only use the correlation if selected for the distribution
if (PHOTON_DISTRIBUTION[PHOTON_CORRELATED].equals(settings.photonDistribution))
correlation = settings.correlation;
}
imageModel.setRandomGenerator(createRandomGenerator());
imageModel.setPhotonBudgetPerFrame(true);
imageModel.setDiffusion2D(settings.diffuse2D);
imageModel.setRotation2D(settings.rotate2D);
IJ.showStatus("Creating molecules ...");
SpatialDistribution distribution = createDistribution();
List<CompoundMoleculeModel> compounds = createCompoundMolecules();
if (compounds == null)
return;
List<CompoundMoleculeModel> molecules = imageModel.createMolecules(compounds, settings.particles, distribution, settings.rotateInitialOrientation);
// Activate fluorophores
IJ.showStatus("Creating fluorophores ...");
// Note: molecules list will be converted to compounds containing fluorophores
fluorophores = imageModel.createFluorophores(molecules, totalSteps);
if (fluorophores.isEmpty()) {
IJ.error(TITLE, "No fluorophores created");
return;
}
IJ.showStatus("Creating localisations ...");
// TODO - Output a molecule Id for each fluorophore if using compound molecules. This allows analysis
// of the ratio of trimers, dimers, monomers, etc that could be detected.
totalSteps = checkTotalSteps(totalSteps, fluorophores);
if (totalSteps == 0)
return;
imageModel.setPhotonDistribution(createPhotonDistribution());
imageModel.setConfinementDistribution(createConfinementDistribution());
// This should be optimised
imageModel.setConfinementAttempts(10);
localisations = imageModel.createImage(molecules, settings.fixedFraction, totalSteps, (double) settings.photonsPerSecond / settings.stepsPerSecond, correlation, settings.rotateDuringSimulation);
// Re-adjust the fluorophores to the correct time
if (settings.stepsPerSecond != 1) {
final double scale = 1.0 / settings.stepsPerSecond;
for (FluorophoreSequenceModel f : fluorophores) f.adjustTime(scale);
}
// Integrate the frames
localisationSets = combineSimulationSteps(localisations);
localisationSets = filterToImageBounds(localisationSets);
}
datasetNumber++;
localisations = drawImage(localisationSets);
if (localisations == null || localisations.isEmpty()) {
IJ.error(TITLE, "No localisations created");
return;
}
fluorophores = removeFilteredFluorophores(fluorophores, localisations);
double signalPerFrame = showSummary(fluorophores, localisations);
if (!benchmarkMode) {
boolean fullSimulation = (!(simpleMode || spotMode));
saveSimulationParameters(localisations.size(), fullSimulation, signalPerFrame);
}
IJ.showStatus("Saving data ...");
//convertRelativeToAbsolute(molecules);
saveFluorophores(fluorophores);
saveImageResults(results);
saveLocalisations(localisations);
// The settings for the filenames may have changed
SettingsManager.saveSettings(globalSettings);
IJ.showStatus("Done");
}
use of gdsc.core.utils.Random in project GDSC-SMLM by aherbert.
the class ImageSourceTest method memoryImageSourceCanReturnDataWithGet.
@Test
public void memoryImageSourceCanReturnDataWithGet() {
int w = 5;
int h = 3;
float[][] data = createData(w, h, 15);
MemoryImageSource source = new MemoryImageSource(w, h, data);
int[] frames = new int[data.length];
for (int i = 0; i < data.length; i++) frames[i] = i + 1;
Random rand = new Random();
rand.shuffle(frames);
Assert.assertTrue(source.open());
for (int i = 0; i < data.length; i++) {
int frame = frames[i];
Assert.assertTrue(source.isValid(frame));
Assert.assertArrayEquals(data[frame - 1], source.get(frame), 0);
}
Assert.assertFalse(source.isValid(0));
Assert.assertFalse(source.isValid(data.length + 1));
}
use of gdsc.core.utils.Random in project GDSC-SMLM by aherbert.
the class ImageSourceTest method aggregatedImageSourceCanReturnDataWithGet.
@Test
public void aggregatedImageSourceCanReturnDataWithGet() {
int w = 5;
int h = 3;
int aggregate = 3;
float[][] data = createData(w, h, 15);
ImageSource source = new AggregatedImageSource(new MemoryImageSource(w, h, data), aggregate);
int[] frames = new int[data.length / 3];
for (int i = 0, frame = 1; i < frames.length; i++, frame += 3) frames[i] = frame;
Random rand = new Random();
rand.shuffle(frames);
Assert.assertTrue(source.open());
for (int i = 0; i < frames.length; i++) {
int frame = frames[i];
Assert.assertTrue("Invalid frame " + frame, source.isValid(frame));
float[] d = source.get(frame);
Assert.assertEquals(frame, source.getStartFrameNumber());
Assert.assertEquals(frame + 2, source.getEndFrameNumber());
float[] all = combine(data[frame - 1], data[frame], data[frame + 1]);
Assert.assertArrayEquals("Invalid frame data " + frame, all, d, 0);
}
Assert.assertFalse(source.isValid(0));
Assert.assertFalse(source.isValid(data.length + 1));
}
use of gdsc.core.utils.Random in project GDSC-SMLM by aherbert.
the class ImageSourceTest method aggregatedImageSourceCanReturnCroppedDataWithGet.
@Test
public void aggregatedImageSourceCanReturnCroppedDataWithGet() {
int w = 5;
int h = 3;
int aggregate = 3;
float[][] data = createData(w, h, 15);
Rectangle bounds = new Rectangle(2, 1, 3, 1);
ImageSource source = new AggregatedImageSource(new MemoryImageSource(w, h, data), aggregate);
int[] frames = new int[data.length / 3];
for (int i = 0, frame = 1; i < frames.length; i++, frame += 3) frames[i] = frame;
Random rand = new Random();
rand.shuffle(frames);
Assert.assertTrue(source.open());
for (int i = 0; i < frames.length; i++) {
int frame = frames[i];
Assert.assertTrue(source.isValid(frame));
float[] d = source.get(frame, bounds);
Assert.assertEquals(frame, source.getStartFrameNumber());
Assert.assertEquals(frame + 2, source.getEndFrameNumber());
float[] all = combine(crop(data[frame - 1], w, bounds), crop(data[frame], w, bounds), crop(data[frame + 1], w, bounds));
Assert.assertArrayEquals("Invalid frame data " + frame, all, d, 0);
}
Assert.assertFalse(source.isValid(0));
Assert.assertFalse(source.isValid(data.length + 1));
}
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