use of gdsc.smlm.model.ImageModel 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.smlm.model.ImageModel in project GDSC-SMLM by aherbert.
the class BlinkEstimatorTest method estimateBlinking.
private TIntHashSet estimateBlinking(double nBlinks, double tOn, double tOff, int particles, double fixedFraction, boolean timeAtLowerBound, boolean doAssert) {
SpatialIllumination activationIllumination = new UniformIllumination(100);
int totalSteps = 100;
double eAct = totalSteps * 0.3 * activationIllumination.getAveragePhotons();
ImageModel imageModel = new ActivationEnergyImageModel(eAct, activationIllumination, tOn, 0, tOff, 0, nBlinks);
imageModel.setRandomGenerator(rand);
double[] max = new double[] { 256, 256, 32 };
double[] min = new double[3];
SpatialDistribution distribution = new UniformDistribution(min, max, rand.nextInt());
List<CompoundMoleculeModel> compounds = new ArrayList<CompoundMoleculeModel>(1);
CompoundMoleculeModel c = new CompoundMoleculeModel(1, 0, 0, 0, Arrays.asList(new MoleculeModel(0, 0, 0, 0)));
c.setDiffusionRate(diffusionRate);
c.setDiffusionType(DiffusionType.RANDOM_WALK);
compounds.add(c);
List<CompoundMoleculeModel> molecules = imageModel.createMolecules(compounds, particles, distribution, false);
// Activate fluorophores
List<? extends FluorophoreSequenceModel> fluorophores = imageModel.createFluorophores(molecules, totalSteps);
totalSteps = checkTotalSteps(totalSteps, fluorophores);
List<LocalisationModel> localisations = imageModel.createImage(molecules, fixedFraction, totalSteps, photons, 0.5, false);
// // Remove localisations to simulate missed counts.
// List<LocalisationModel> newLocalisations = new ArrayList<LocalisationModel>(localisations.size());
// boolean[] id = new boolean[fluorophores.size() + 1];
// Statistics photonStats = new Statistics();
// for (LocalisationModel l : localisations)
// {
// photonStats.add(l.getIntensity());
// // Remove by intensity threshold and optionally at random.
// if (l.getIntensity() < minPhotons || rand.nextDouble() < pDelete)
// continue;
// newLocalisations.add(l);
// id[l.getId()] = true;
// }
// localisations = newLocalisations;
// System.out.printf("Photons = %f\n", photonStats.getMean());
//
// List<FluorophoreSequenceModel> newFluorophores = new ArrayList<FluorophoreSequenceModel>(fluorophores.size());
// for (FluorophoreSequenceModel f : fluorophores)
// {
// if (id[f.getId()])
// newFluorophores.add(f);
// }
// fluorophores = newFluorophores;
MemoryPeakResults results = new MemoryPeakResults();
results.setCalibration(new Calibration(pixelPitch, 1, msPerFrame));
for (LocalisationModel l : localisations) {
// Remove by intensity threshold and optionally at random.
if (l.getIntensity() < minPhotons || rand.nextDouble() < pDelete)
continue;
float[] params = new float[7];
params[Gaussian2DFunction.X_POSITION] = (float) l.getX();
params[Gaussian2DFunction.Y_POSITION] = (float) l.getY();
params[Gaussian2DFunction.X_SD] = params[Gaussian2DFunction.Y_SD] = psfWidth;
params[Gaussian2DFunction.SIGNAL] = (float) (l.getIntensity());
results.addf(l.getTime(), 0, 0, 0, 0, 0, params, null);
}
// Add random localisations
for (int i = (int) (localisations.size() * pAdd); i-- > 0; ) {
float[] params = new float[7];
params[Gaussian2DFunction.X_POSITION] = (float) (rand.nextDouble() * max[0]);
params[Gaussian2DFunction.Y_POSITION] = (float) (rand.nextDouble() * max[1]);
params[Gaussian2DFunction.X_SD] = params[Gaussian2DFunction.Y_SD] = psfWidth;
// Intensity doesn't matter at the moment for tracing
params[Gaussian2DFunction.SIGNAL] = (float) (photons);
results.addf(1 + rand.nextInt(totalSteps), 0, 0, 0, 0, 0, params, null);
}
// Get actual simulated stats ...
Statistics statsNBlinks = new Statistics();
Statistics statsTOn = new Statistics();
Statistics statsTOff = new Statistics();
Statistics statsSampledNBlinks = new Statistics();
Statistics statsSampledTOn = new Statistics();
StoredDataStatistics statsSampledTOff = new StoredDataStatistics();
for (FluorophoreSequenceModel f : fluorophores) {
statsNBlinks.add(f.getNumberOfBlinks());
statsTOn.add(f.getOnTimes());
statsTOff.add(f.getOffTimes());
int[] on = f.getSampledOnTimes();
statsSampledNBlinks.add(on.length);
statsSampledTOn.add(on);
statsSampledTOff.add(f.getSampledOffTimes());
}
System.out.printf("N = %d (%d), N-blinks = %f, tOn = %f, tOff = %f, Fixed = %f\n", fluorophores.size(), localisations.size(), nBlinks, tOn, tOff, fixedFraction);
System.out.printf("Actual N-blinks = %f (%f), tOn = %f (%f), tOff = %f (%f), 95%% = %f, max = %f\n", statsNBlinks.getMean(), statsSampledNBlinks.getMean(), statsTOn.getMean(), statsSampledTOn.getMean(), statsTOff.getMean(), statsSampledTOff.getMean(), statsSampledTOff.getStatistics().getPercentile(95), statsSampledTOff.getStatistics().getMax());
System.out.printf("-=-=--=-\n");
BlinkEstimator be = new BlinkEstimator();
be.maxDarkTime = (int) (tOff * 10);
be.msPerFrame = msPerFrame;
be.relativeDistance = false;
double d = ImageModel.getRandomMoveDistance(diffusionRate);
be.searchDistance = (fixedFraction < 1) ? Math.sqrt(2 * d * d) * 3 : 0;
be.timeAtLowerBound = timeAtLowerBound;
be.showPlots = false;
//Assert.assertTrue("Max dark time must exceed the dark time of the data (otherwise no plateau)",
// be.maxDarkTime > statsSampledTOff.getStatistics().getMax());
int nMolecules = fluorophores.size();
if (usePopulationStatistics) {
nBlinks = statsNBlinks.getMean();
tOff = statsTOff.getMean();
} else {
nBlinks = statsSampledNBlinks.getMean();
tOff = statsSampledTOff.getMean();
}
// See if any fitting regime gets a correct answer
TIntHashSet ok = new TIntHashSet();
for (int nFittedPoints = MIN_FITTED_POINTS; nFittedPoints <= MAX_FITTED_POINTS; nFittedPoints++) {
be.nFittedPoints = nFittedPoints;
be.computeBlinkingRate(results, true);
double moleculesError = DoubleEquality.relativeError(nMolecules, be.getNMolecules());
double blinksError = DoubleEquality.relativeError(nBlinks, be.getNBlinks());
double offError = DoubleEquality.relativeError(tOff * msPerFrame, be.getTOff());
System.out.printf("Error %d: N = %f, blinks = %f, tOff = %f : %f\n", nFittedPoints, moleculesError, blinksError, offError, (moleculesError + blinksError + offError) / 3);
if (moleculesError < relativeError && blinksError < relativeError && offError < relativeError) {
ok.add(nFittedPoints);
System.out.printf("-=-=--=-\n");
System.out.printf("*** Correct at %d fitted points ***\n", nFittedPoints);
if (doAssert)
break;
}
//if (!be.isIncreaseNFittedPoints())
// break;
}
System.out.printf("-=-=--=-\n");
if (doAssert)
Assert.assertFalse(ok.isEmpty());
//Assert.assertEquals("Invalid t-off", tOff * msPerFrame, be.getTOff(), tOff * msPerFrame * relativeError);
return ok;
}
Aggregations