Examples with PointSet net.imglib2.ops.pointset.PointSet used on opensource projects

Example 16 with PointSet

use of net.imglib2.ops.pointset.PointSet in project imagej-plugins-commands by imagej.

the class PointSetDemo method run.

@Override
public void run() {
    TextSpecifiedPointSet pointSet = new TextSpecifiedPointSet(specification);
    if (pointSet.getErrorString() != null) {
        cancel(pointSet.getErrorString());
        return;
    }
    long[] minBound = new long[pointSet.numDimensions()];
    long[] maxBound = new long[pointSet.numDimensions()];
    pointSet.min(minBound);
    pointSet.max(maxBound);
    for (int i = 0; i < minBound.length; i++) {
        if ((minBound[i] < 0) || (maxBound[i] < 0)) {
            cancel("For now won't handle negative space with this test plugin");
            return;
        }
        // make a border around the maximum bound
        maxBound[i] += 10;
    }
    output = ds.create(maxBound, "PointSet", null, 8, false, false);
    ImgPlus<? extends RealType<?>> imgplus = output.getImgPlus();
    RandomAccess<? extends RealType<?>> accessor = imgplus.randomAccess();
    PointSetIterator iter = pointSet.iterator();
    while (iter.hasNext()) {
        long[] pos = iter.next();
        accessor.setPosition(pos);
        accessor.get().setReal(255);
    }
}

Example 17 with PointSet

use of net.imglib2.ops.pointset.PointSet in project imagej-plugins-commands by imagej.

the class Reducer method reduceNoise.

// NOTE - because the neighborhood could be a spherical neighborhood that
// relies on a WithinRadiusOfPointCondition we cannot parallelize this
// algorithm. If we did we'd get one point per Thread with only one being
// updated correctly. One can see by trial that using a regular
// ImageAssignment here results in only a portion of the image getting noise
// reduced.
public Dataset reduceNoise(String neighDescrip) {
    notifyUserAtStart(neighDescrip);
    ImgPlus<U> newImg = input.copy();
    long[] dims = new long[newImg.numDimensions()];
    newImg.dimensions(dims);
    PointSet space = new HyperVolumePointSet(dims);
    PointSetInputIterator inputIterator = new PointSetInputIterator(space, neighborhood);
    long[] outputOrigin = new long[input.numDimensions()];
    long[] outputSpan = outputOrigin.clone();
    input.dimensions(outputSpan);
    // NB - regular ImageAssignement won't work here for radial neighborhood due
    // to the duplication of neighborhoods for parallelization and its
    // interference with the WithinRadiusOfPointSetOriginCondition.
    SerialImageAssignment<U, V, PointSet> assigner = new SerialImageAssignment<U, V, PointSet>(newImg, inputFunction, inputIterator, null);
    assigner.assign();
    notifyUserAtEnd(neighDescrip);
    return new DefaultDataset(context, newImg);
}

Example 18 with PointSet

use of net.imglib2.ops.pointset.PointSet in project imagej-plugins-commands by imagej.

the class MathCommand method initialize.

// -- private helpers --
private void initialize() {
    dataset = displayService.getActiveDataset(display);
    overlay = overlayService.getActiveOverlay(display);
    DatasetView view = displayService.getActiveDatasetView(display);
    planePos = view.getPlanePosition();
    InplaceUnaryTransform<?, ?> xform = getPreviewTransform(dataset, overlay);
    PointSet region = determineRegion(dataset, xform.getRegionOrigin(), xform.getRegionSpan());
    iter = region.iterator();
    ArrayImgFactory<DoubleType> factory = new ArrayImgFactory<DoubleType>();
    dataBackup = factory.create(new long[] { region.size() }, new DoubleType());
    backupAccess = dataBackup.randomAccess();
    dataAccess = dataset.getImgPlus().randomAccess();
    // check dimensions of Dataset
    final long w = xform.getRegionSpan()[0];
    final long h = xform.getRegionSpan()[1];
    if (w * h > Integer.MAX_VALUE)
        throw new IllegalArgumentException("preview region too large to copy into memory");
}

Example 19 with PointSet

use of net.imglib2.ops.pointset.PointSet in project imagej-plugins-commands by imagej.

the class NoiseReductionAdaptiveMedian method getNeighborhoods.

private List<PointSet> getNeighborhoods(final int numDims) {
    final ArrayList<PointSet> pointSets = new ArrayList<PointSet>();
    for (int i = 0; i < windowExpansions; i++) {
        final PointSet rect = new HyperVolumePointSet(new long[numDims], offsets(windowNegWidthSpan + i, windowNegHeightSpan + i, numDims), offsets(windowPosWidthSpan + i, windowPosHeightSpan + i, numDims));
        pointSets.add(rect);
    }
    return pointSets;
}

Example 20 with PointSet

use of net.imglib2.ops.pointset.PointSet in project imagej-plugins-commands by imagej.

the class TypeChanger method channelAveragingCase.

// -- helpers --
@SuppressWarnings("unchecked")
private Dataset channelAveragingCase(DataType<U> inType, DataType<V> outType, int chAxis, int count) {
    BigComplex[] temps = new BigComplex[count];
    for (int i = 0; i < count; i++) {
        temps[i] = new BigComplex();
    }
    BigComplex combined = new BigComplex();
    BigComplex divisor = new BigComplex(count, 0);
    long[] dims = calcDims(Intervals.dimensionsAsLongArray(data), chAxis);
    AxisType[] axes = calcAxes(SpaceUtils.getAxisTypes(data), chAxis);
    Dataset newData = datasetService.create(outType.createVariable(), dims, "Converted Image", axes);
    long[] span = Intervals.dimensionsAsLongArray(data).clone();
    span[chAxis] = 1;
    PointSet combinedSpace = new HyperVolumePointSet(span);
    PointSetIterator iter = combinedSpace.iterator();
    RandomAccess<U> inAccessor = (RandomAccess<U>) data.getImgPlus().randomAccess();
    RandomAccess<V> outAccessor = (RandomAccess<V>) newData.getImgPlus().randomAccess();
    while (iter.hasNext()) {
        long[] pos = iter.next();
        inAccessor.setPosition(pos);
        for (int i = 0; i < count; i++) {
            inAccessor.setPosition(i, chAxis);
            inType.cast(inAccessor.get(), temps[i]);
        }
        combined.setZero();
        for (int i = 0; i < count; i++) {
            combined.add(temps[i]);
        }
        int d = 0;
        for (int i = 0; i < count; i++) {
            if (i == chAxis)
                continue;
            outAccessor.setPosition(pos[i], d++);
        }
        combined.div(divisor);
        outType.cast(combined, outAccessor.get());
    }
    copyMetaDataChannelsCase(data.getImgPlus(), newData.getImgPlus());
    return newData;
}