Examples with TIntIntHashMap gnu.trove.map.hash.TIntIntHashMap used on opensource projects

Example 1 with TIntIntHashMap

use of gnu.trove.map.hash.TIntIntHashMap in project mixcr by milaboratory.

the class FullSeqAssembler method calculateRawData.

public RawVariantsData calculateRawData(Supplier<OutputPort<VDJCAlignments>> alignments) {
    if (!sequenceToVariantId.isEmpty())
        throw new IllegalStateException();
    for (byte letter = 0; letter < NucleotideSequence.ALPHABET.basicSize(); letter++) {
        NucleotideSequence seq = new NucleotideSequence(new byte[] { letter });
        sequenceToVariantId.put(seq, letter);
        variantIdToSequence.put(letter, seq);
    }
    sequenceToVariantId.put(NucleotideSequence.EMPTY, NucleotideSequence.ALPHABET.basicSize());
    variantIdToSequence.put(NucleotideSequence.ALPHABET.basicSize(), NucleotideSequence.EMPTY);
    TIntIntHashMap coverage = new TIntIntHashMap();
    TIntObjectHashMap<TIntObjectHashMap<VariantAggregator>> variants = new TIntObjectHashMap<>();
    int nAlignments = 0;
    for (VDJCAlignments al : CUtils.it(alignments.get())) {
        ++nAlignments;
        for (PointSequence point : toPointSequences(al)) {
            int seqIndex = getVariantIndex(point.sequence.getSequence());
            coverage.adjustOrPutValue(point.point, 1, 1);
            TIntObjectHashMap<VariantAggregator> map = variants.get(point.point);
            if (map == null)
                variants.put(point.point, map = new TIntObjectHashMap<>());
            VariantAggregator var = map.get(seqIndex);
            if (var == null)
                map.put(point.point, var = new VariantAggregator());
            var.count += 1;
            var.sumQuality += 0x7F & point.quality;
        }
    }
    assert nAlignments > 0;
    long[] forSort = new long[coverage.size()];
    TIntIntIterator iterator = coverage.iterator();
    int i = 0;
    while (iterator.hasNext()) {
        iterator.advance();
        forSort[i++] = -((((long) iterator.value()) << 32) | iterator.key());
    }
    Arrays.sort(forSort);
    int[] pointsArray = Arrays.stream(forSort).mapToInt(l -> (int) (-l)).toArray();
    TIntIntHashMap revIndex = new TIntIntHashMap();
    for (int j = 0; j < pointsArray.length; j++) revIndex.put(pointsArray[j], j);
    int[] coverageArray = Arrays.stream(forSort).mapToInt(l -> (int) ((-l) >> 32)).toArray();
    int[][] packedData = new int[pointsArray.length][nAlignments];
    for (int[] aPackedData : packedData) Arrays.fill(aPackedData, -1);
    i = 0;
    for (VDJCAlignments al : CUtils.it(alignments.get())) {
        for (PointSequence point : toPointSequences(al)) {
            int pointIndex = revIndex.get(point.point);
            packedData[pointIndex][i] = (sequenceToVariantId.get(point.sequence.getSequence()) << 8) | (0xFF & point.quality);
        }
        i++;
    }
    return new RawVariantsData(nAlignments, pointsArray, coverageArray) {

        @Override
        OutputPort<int[]> createPort() {
            return CUtils.asOutputPort(Arrays.asList(packedData));
        }
    };
}

Example 2 with TIntIntHashMap

use of gnu.trove.map.hash.TIntIntHashMap in project mixcr by milaboratory.

the class CloneAssembler method runClustering.

public void runClustering() {
    if (clusteredClonesAccumulators != null)
        throw new IllegalStateException("Already clustered.");
    if (!preClusteringDone)
        throw new IllegalStateException("No preclustering done.");
    @SuppressWarnings("unchecked") Clustering clustering = new Clustering(cloneList, new SequenceExtractor<CloneAccumulator, NucleotideSequence>() {

        @Override
        public NucleotideSequence getSequence(CloneAccumulator object) {
            return object.getSequence().getConcatenated().getSequence();
        }
    }, new CloneClusteringStrategy(parameters.getCloneClusteringParameters(), this));
    this.progressReporter = clustering;
    List<Cluster<CloneAccumulator>> clusters = clustering.performClustering();
    clusteredClonesAccumulators = new ArrayList<>(clusters.size());
    idMapping = new TIntIntHashMap(cloneList.size());
    for (int i = 0; i < clusters.size(); ++i) {
        final Cluster<CloneAccumulator> cluster = clusters.get(i);
        final CloneAccumulator head = cluster.getHead();
        idMapping.put(head.getCloneIndex(), i);
        head.setCloneIndex(i);
        final int k = ~i;
        cluster.processAllChildren(new TObjectProcedure<Cluster<CloneAccumulator>>() {

            @Override
            public boolean execute(Cluster<CloneAccumulator> object) {
                onClustered(head, object.getHead());
                if (parameters.isAddReadsCountOnClustering())
                    head.mergeCounts(object.getHead());
                idMapping.put(object.getHead().getCloneIndex(), k);
                return true;
            }
        });
        clusteredClonesAccumulators.add(head);
    }
    this.progressReporter = null;
}

Example 3 with TIntIntHashMap

use of gnu.trove.map.hash.TIntIntHashMap in project mixcr by milaboratory.

the class ActionSlice method sliceClnA.

void sliceClnA(ActionHelper helper) throws Exception {
    try (ClnAReader reader = new ClnAReader(params.getInputFileName(), VDJCLibraryRegistry.getDefault());
        ClnAWriter writer = new ClnAWriter(params.getOutputFileName())) {
        // Getting full clone set
        CloneSet cloneSet = reader.readCloneSet();
        // old clone id -> new clone id
        TIntIntHashMap idMapping = new TIntIntHashMap();
        long newNumberOfAlignments = 0;
        // Creating new cloneset
        List<Clone> clones = new ArrayList<>();
        int i = 0;
        List<OutputPort<VDJCAlignments>> allAlignmentsList = new ArrayList<>();
        for (Long cloneId_ : params.ids) {
            int cloneId = (int) ((long) cloneId_);
            newNumberOfAlignments += reader.numberOfAlignmentsInClone(cloneId);
            Clone clone = cloneSet.get(cloneId);
            idMapping.put(clone.getId(), i);
            clones.add(clone.setId(i).resetParentCloneSet());
            OutputPort<VDJCAlignments> als = reader.readAlignmentsOfClone(cloneId);
            final int ii = i;
            allAlignmentsList.add(() -> {
                VDJCAlignments al = als.take();
                if (al == null)
                    return null;
                return al.updateCloneIndex(ii);
            });
            i++;
        }
        CloneSet newCloneSet = new CloneSet(clones, cloneSet.getUsedGenes(), cloneSet.getAlignedFeatures(), cloneSet.getAlignmentParameters(), cloneSet.getAssemblerParameters());
        OutputPort<VDJCAlignments> allAlignmentsPortRaw = new FlatteningOutputPort<>(CUtils.asOutputPort(allAlignmentsList));
        AtomicLong idGen = new AtomicLong();
        OutputPort<VDJCAlignments> allAlignmentsPort = () -> {
            VDJCAlignments al = allAlignmentsPortRaw.take();
            if (al == null)
                return null;
            return al.setAlignmentsIndex(idGen.getAndIncrement());
        };
        writer.writeClones(newCloneSet);
        writer.sortAlignments(allAlignmentsPort, newNumberOfAlignments);
        writer.writeAlignmentsAndIndex();
    }
}

Example 4 with TIntIntHashMap

use of gnu.trove.map.hash.TIntIntHashMap in project BuildCraft by BuildCraft.

the class NbtSquishMapWriter method writeListPacked.

private void writeListPacked(WrittenType type, DataOutput to, NBTTagList list) throws IOException {
    profiler.startSection("list_packed");
    to.writeByte(NbtSquishConstants.COMPLEX_LIST_PACKED);
    profiler.startSection("header");
    profiler.startSection("init");
    int[] data = new int[list.tagCount()];
    TIntIntHashMap indexes = new TIntIntHashMap();
    for (int i = 0; i < list.tagCount(); i++) {
        profiler.startSection("entry");
        profiler.startSection("index");
        int index = map.indexOfTag(list.get(i));
        profiler.endSection();
        data[i] = index;
        if (!indexes.increment(index)) {
            indexes.put(index, 1);
        }
        profiler.endSection();
    }
    // First try to make a simple table
    // First sort the indexes into highest count first
    profiler.endStartSection("sort");
    List<IndexEntry> entries = new ArrayList<>();
    for (int index : indexes.keys()) {
        int count = indexes.get(index);
        IndexEntry entry = new IndexEntry(index, count);
        entries.add(entry);
    }
    entries.sort(Comparator.reverseOrder());
    if (debug)
        log("\n " + entries.size() + " List entries");
    writeVarInt(to, entries.size());
    profiler.endStartSection("write");
    TIntArrayList sortedIndexes = new TIntArrayList();
    int i = 0;
    for (IndexEntry entry : entries) {
        final int j = i;
        NBTBase base = map.getTagForWriting(entry.index);
        String n = safeToString(base);
        if (debug)
            log("\n List entry #" + j + " = " + entry.count + "x" + entry.index + " (" + n + ")");
        sortedIndexes.add(entry.index);
        type.writeIndex(to, entry.index);
        i++;
    }
    TIntArrayList nextData = new TIntArrayList();
    nextData.add(data);
    writeVarInt(to, data.length);
    profiler.endSection();
    profiler.endStartSection("contents");
    for (int b = 1; !nextData.isEmpty(); b++) {
        profiler.startSection("entry");
        CompactingBitSet bitset = new CompactingBitSet(b);
        bitset.ensureCapacityValues(nextData.size());
        TIntArrayList nextNextData = new TIntArrayList();
        int maxVal = (1 << b) - 1;
        profiler.startSection("iter");
        for (int d : nextData.toArray()) {
            // profiler.startSection("entry");
            // profiler.startSection("index");
            int index = sortedIndexes.indexOf(d);
            // profiler.endSection();
            if (index < maxVal) {
                // profiler.startSection("bitset_append");
                bitset.append(index);
            // profiler.endSection();
            } else {
                // profiler.startSection("bitset_append");
                bitset.append(maxVal);
                // profiler.endStartSection("next_add");
                nextNextData.add(d);
            // profiler.endSection();
            }
        // profiler.endSection();
        }
        profiler.endSection();
        sortedIndexes.remove(0, Math.min(sortedIndexes.size(), maxVal));
        byte[] bitsetBytes = bitset.getBytes();
        if (debug)
            log("\n List bitset #" + (bitset.bits - 1));
        writeVarInt(to, bitsetBytes.length);
        to.write(bitsetBytes);
        nextData = nextNextData;
        profiler.endSection();
    }
    profiler.endSection();
    profiler.endSection();
}

Example 5 with TIntIntHashMap

use of gnu.trove.map.hash.TIntIntHashMap in project GDSC-SMLM by aherbert.

the class CreateData method run.

@Override
public void run(String arg) {
    SmlmUsageTracker.recordPlugin(this.getClass(), arg);
    extraOptions = ImageJUtils.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 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.setExposureTime(1000);
        areaInUm = settings.getSize() * settings.getPixelPitch() * settings.getSize() * settings.getPixelPitch() / 1e6;
        // Number of spots per frame
        int count = 0;
        int[] nextN = null;
        SpatialDistribution dist;
        if (benchmarkMode) {
            // --------------------
            // BENCHMARK SIMULATION
            // --------------------
            // Draw the same point on the image repeatedly
            count = 1;
            dist = createFixedDistribution();
            try {
                reportAndSaveFittingLimits(dist);
            } catch (final Exception ex) {
                // This will be from the computation of the CRLB
                IJ.error(TITLE, ex.getMessage());
                return;
            }
        } 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.getParticles() * 2];
            Arrays.fill(nextN, 0, settings.getParticles(), 1);
            RandomUtils.shuffle(nextN, UniformRandomProviders.create());
            // Only put spots in the central part of the image
            final double border = settings.getSize() / 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.getSamplePerFrame()) {
                final double mean = areaInUm * settings.getDensity();
                ImageJUtils.log("Mean samples = %f", mean);
                if (mean < 0.5) {
                    final GenericDialog gd = new GenericDialog(TITLE);
                    gd.addMessage("The mean samples per frame is low: " + MathUtils.rounded(mean) + "\n \nContinue?");
                    gd.enableYesNoCancel();
                    gd.hideCancelButton();
                    gd.showDialog();
                    if (!gd.wasOKed()) {
                        return;
                    }
                }
                final PoissonSampler poisson = new PoissonSampler(createRandomGenerator(), mean);
                final StoredDataStatistics samples = new StoredDataStatistics(settings.getParticles());
                while (samples.getSum() < settings.getParticles()) {
                    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
                count = (int) Math.max(1, Math.round(areaInUm * settings.getDensity()));
            }
        }
        UniformRandomProvider rng = null;
        localisationSets = new ArrayList<>(settings.getParticles());
        final int minPhotons = (int) settings.getPhotonsPerSecond();
        final int range = (int) settings.getPhotonsPerSecondMaximum() - minPhotons + 1;
        if (range > 1) {
            rng = createRandomGenerator();
        }
        // Add frames at the specified density until the number of particles has been reached
        int id = 0;
        int time = 0;
        while (id < settings.getParticles()) {
            // Allow the number per frame to be specified
            if (nextN != null) {
                if (time >= nextN.length) {
                    break;
                }
                count = nextN[time];
            }
            // Simulate random positions in the frame for the specified density
            time++;
            for (int j = 0; j < count; 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 + ((rng != null) ? rng.nextInt(range) : 0);
                final LocalisationModel m = new LocalisationModel(id, time, xyz, intensity, LocalisationModel.CONTINUOUS);
                // Each localisation can be a separate localisation set
                final LocalisationModelSet set = new LocalisationModelSet(id, time);
                set.add(m);
                localisationSets.add(set);
                id++;
            }
        }
    } else {
        if (!showDialog()) {
            return;
        }
        resetMemory();
        areaInUm = settings.getSize() * settings.getPixelPitch() * settings.getSize() * settings.getPixelPitch() / 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.setSeconds((int) Math.ceil(settings.getParticles() * (settings.getExposureTime() + settings.getTOn()) / 1000));
            totalSteps = 0;
            final double simulationStepsPerFrame = (settings.getStepsPerSecond() * settings.getExposureTime()) / 1000.0;
            imageModel = new FixedLifetimeImageModel(settings.getStepsPerSecond() * settings.getTOn() / 1000.0, simulationStepsPerFrame, createRandomGenerator());
        } 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.
            final SpatialIllumination activationIllumination = createIllumination(settings.getPulseRatio(), settings.getPulseInterval());
            // Generate additional frames so that each frame has the set number of simulation steps
            totalSteps = (int) Math.ceil(settings.getSeconds() * settings.getStepsPerSecond());
            // Since we have an exponential decay of activations
            // ensure half of the particles have activated by 30% of the frames.
            final double eAct = totalSteps * 0.3 * activationIllumination.getAveragePhotons();
            // Q. Does tOn/tOff change depending on the illumination strength?
            imageModel = new ActivationEnergyImageModel(eAct, activationIllumination, settings.getStepsPerSecond() * settings.getTOn() / 1000.0, settings.getStepsPerSecond() * settings.getTOffShort() / 1000.0, settings.getStepsPerSecond() * settings.getTOffLong() / 1000.0, settings.getNBlinksShort(), settings.getNBlinksLong(), createRandomGenerator());
            imageModel.setUseGeometricDistribution(settings.getNBlinksGeometricDistribution());
            // Only use the correlation if selected for the distribution
            if (PHOTON_DISTRIBUTION[PHOTON_CORRELATED].equals(settings.getPhotonDistribution())) {
                correlation = settings.getCorrelation();
            }
        }
        imageModel.setPhotonBudgetPerFrame(true);
        imageModel.setDiffusion2D(settings.getDiffuse2D());
        imageModel.setRotation2D(settings.getRotate2D());
        IJ.showStatus("Creating molecules ...");
        final SpatialDistribution distribution = createDistribution();
        final List<CompoundMoleculeModel> compounds = createCompoundMolecules();
        if (compounds == null) {
            return;
        }
        final List<CompoundMoleculeModel> molecules = imageModel.createMolecules(compounds, settings.getParticles(), distribution, settings.getRotateInitialOrientation());
        // 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;
        }
        // Map the fluorophore ID to the compound for mixtures
        if (compounds.size() > 1) {
            idToCompound = new TIntIntHashMap(fluorophores.size());
            for (final FluorophoreSequenceModel l : fluorophores) {
                idToCompound.put(l.getId(), l.getLabel());
            }
        }
        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());
        try {
            imageModel.setConfinementDistribution(createConfinementDistribution());
        } catch (final ConfigurationException ex) {
            // We asked the user if it was OK to continue and they said no
            return;
        }
        // This should be optimised
        imageModel.setConfinementAttempts(10);
        final List<LocalisationModel> localisations = imageModel.createImage(molecules, settings.getFixedFraction(), totalSteps, settings.getPhotonsPerSecond() / settings.getStepsPerSecond(), correlation, settings.getRotateDuringSimulation());
        // Re-adjust the fluorophores to the correct time
        if (settings.getStepsPerSecond() != 1) {
            final double scale = 1.0 / settings.getStepsPerSecond();
            for (final FluorophoreSequenceModel f : fluorophores) {
                f.adjustTime(scale);
            }
        }
        // Integrate the frames
        localisationSets = combineSimulationSteps(localisations);
        localisationSets = filterToImageBounds(localisationSets);
    }
    datasetNumber.getAndIncrement();
    final List<LocalisationModel> localisations = drawImage(localisationSets);
    if (localisations == null || localisations.isEmpty()) {
        IJ.error(TITLE, "No localisations created");
        return;
    }
    fluorophores = removeFilteredFluorophores(fluorophores, localisations);
    final double signalPerFrame = showSummary(fluorophores, localisations);
    if (!benchmarkMode) {
        final boolean fullSimulation = (!(simpleMode || spotMode));
        saveSimulationParameters(localisations.size(), fullSimulation, signalPerFrame);
    }
    IJ.showStatus("Saving data ...");
    saveFluorophores(fluorophores);
    saveImageResults(results);
    saveLocalisations(localisations);
    // The settings for the filenames may have changed
    SettingsManager.writeSettings(settings.build());
    IJ.showStatus("Done");
}