net.imglib2.FinalInterval Java Examples

@SuppressWarnings("unchecked")
@Test
public void testComputer() {
	// create 4D image
	final RandomAccessibleInterval<BitType> in = ops.create().img(new FinalInterval(20, 20, 5, 3), new BitType());
	generate4DImg(in);
	
	// create output
	final RandomAccessibleInterval<FloatType> out = ops.create().img(in, new FloatType());

	/*
	 * test normal DT
	 */
	ops.run(DefaultDistanceTransform.class, out, in);
	compareResults(out, in, new double[] { 1, 1, 1, 1 });

	/*
	 * test calibrated DT
	 */
	final double[] calibration = new double[] { 3.74, 5.19, 1.21, 2.21 };
	ops.run(DefaultDistanceTransformCalibration.class, out, in,
			calibration);
	compareResults(out, in, calibration);
	
}
 

public ArrayImg<UnsignedVariableBitLengthType, LongArray>
	generateUnsignedVariableBitLengthTypeArrayTestImg(final boolean fill,
		final int nbits, final long... dims)
{
	final long[] array = new long[(int) Intervals.numElements(new FinalInterval(
		dims))];

	if (fill) {
		seed = 17;
		for (int i = 0; i < array.length; i++) {
			array[i] = (long) (((pseudoRandom() / Integer.MAX_VALUE)) % (Math.pow(2, nbits))) ;
		}
	}

	final LongArray l = new LongArray(array);

	return ArrayImgs.unsignedVariableBitLengths(l, nbits, dims);
}
 

@Test
public void UnshearIntervalTest() {
	Img<DoubleType> img = new ArrayImgFactory<DoubleType>().create(new int[] { 2, 2 }, new DoubleType());
	Cursor<DoubleType> imgC = img.cursor();
	while (imgC.hasNext()) {
		imgC.next().set(1);
	}

	Cursor<DoubleType> il2 = Views
			.unshear(Views.shear(Views.extendZero(img), 0, 1), new FinalInterval(new long[] { 0, 0 }, new long[] { 3, 3 }), 0, 1)
			.cursor();
	RandomAccess<DoubleType> opr = ops.transform()
			.unshearView(Views.shear(Views.extendZero(img), 0, 1), new FinalInterval(new long[] { 0, 0 }, new long[] { 3, 3 }), 0, 1)
			.randomAccess();

	while (il2.hasNext()) {
		il2.next();
		opr.setPosition(il2);
		assertEquals(il2.get().get(), opr.get().get(), 1e-10);
	}
}
 

/**
 * create an integer interval from real interval, being conservatie on the size
 * (min is ceiled, max is floored)
 * @param overlap real input
 * @return interger interval, with mins ceiled and maxs floored
 */
public static FinalInterval getLocalRasterOverlap(RealInterval overlap)
{
	final int n = overlap.numDimensions();
	final long [] min = new long [n];
	final long [] max = new long [n];
	
	for (int i = 0; i< n; i++)
	{
		// round down errors when it is exactly 0.5, if we do not do this we end up with two intervals
		// of different size, e.g.:
		// if the first interval starts at 139.5 going to 199, the second one at 0.0 going to 59.5
		// then the rastered 1st would go from round(139.5)=140 + 1 = 141 -to- round(199)=199 - 1 = 198, dim=58
		// and  the rastered 2nd would go from round(0.0)=0 + 1     =   1 -to- round(59.5)=60 - 1 = 59,  dim=59
		min[i] = Math.round((overlap.realMin(i) - 0.0001 )) + 1;
		max[i] = Math.round((overlap.realMax(i) + 0.0001 )) - 1;
	}
	
	return new FinalInterval(min, max);
}
 

@Test
public void testNonZeroMinimumInterval() {

	Img<ByteType> img3D = ArrayImgs.bytes(50, 50, 3);
	IntervalView<ByteType> interval2D = Views.interval(img3D,
			new FinalInterval(new long[] { 25, 25, 2 }, new long[] { 35, 35, 2 }));
	final int[] xyAxis = new int[] { 0, 1 };

	// iterate through every slice, should return a single
	// RandomAccessibleInterval<?> from 25, 25, 2 to 35, 35, 2

	final SlicesII<ByteType> hyperSlices = new SlicesII<>(interval2D, xyAxis, true);
	final Cursor<RandomAccessibleInterval<ByteType>> c = hyperSlices.cursor();
	int i = 0;
	while (c.hasNext()) {
		c.next();
		i++;
	}

	assertEquals(1, i);
}
 

@SuppressWarnings("unchecked")
@Test
public void test() {
	// create 4D image
	final RandomAccessibleInterval<BitType> in = ops.create().img(new FinalInterval(20, 20, 5, 3), new BitType());
	generate4DImg(in);

	/*
	 * test normal DT
	 */
	RandomAccessibleInterval<FloatType> out = (RandomAccessibleInterval<FloatType>) ops
			.run(DefaultDistanceTransform.class, null, in);
	compareResults(out, in, new double[] { 1, 1, 1, 1 });

	/*
	 * test calibrated DT
	 */
	final double[] calibration = new double[] { 3.74, 5.19, 1.21, 2.21 };
	out = (RandomAccessibleInterval<FloatType>) ops.run(DefaultDistanceTransformCalibration.class, null, in,
			calibration);
	compareResults(out, in, calibration);
}
 

public static <T extends RealType<T>, S extends RealType<S>, R extends RealType<R>, C extends ComplexType<C>> RandomAccessibleInterval<R> calculatePCM(
		RandomAccessibleInterval<T> img1, RandomAccessibleInterval<S> img2, int[] extension,
		ImgFactory<R> factory, R type, ImgFactory<C> fftFactory, C fftType, ExecutorService service){

	
	// TODO: Extension absolute per dimension in pixels, i.e. int[] extension
	// TODO: not bigger than the image dimension because the second mirroring is identical to the image
	
	Dimensions extSize = PhaseCorrelation2Util.getExtendedSize(img1, img2, extension);
	long[] paddedDimensions = new long[extSize.numDimensions()];
	long[] fftSize = new long[extSize.numDimensions()];
	FFTMethods.dimensionsRealToComplexFast(extSize, paddedDimensions, fftSize);
	
	RandomAccessibleInterval<C> fft1 = fftFactory.create(fftSize, fftType);
	RandomAccessibleInterval<C> fft2 = fftFactory.create(fftSize, fftType);
	
	FFT.realToComplex(Views.interval(PhaseCorrelation2Util.extendImageByFactor(img1, extension), 
			FFTMethods.paddingIntervalCentered(img1, new FinalInterval(paddedDimensions))), fft1, service);
	FFT.realToComplex(Views.interval(PhaseCorrelation2Util.extendImageByFactor(img2, extension), 
			FFTMethods.paddingIntervalCentered(img2, new FinalInterval(paddedDimensions))), fft2, service);
	
	RandomAccessibleInterval<R> pcm = calculatePCMInPlace(fft1, fft2, factory, type, service);
	return pcm;
	
}
 

@Test
public void testImageMinimum() {

	final MersenneTwisterFast randomGenerator = new MersenneTwisterFast(SEED);

	for (int i = 0; i < TEST_SIZE; i++) {

		// between 2 and 5 dimensions
		final long[] max = new long[randomGenerator.nextInt(4) + 2];
		final long[] min = new long[max.length];

		// between 2 and 10 pixels per dimensions
		for (int j = 0; j < max.length; j++) {
			max[j] = randomGenerator.nextInt(9) + 2;
			min[j] = Math.max(0, max[j] - randomGenerator.nextInt(4));
		}

		// create img
		final Img<?> img = (Img<?>) ops.run(CreateImgFromInterval.class,
			new FinalInterval(min, max));

		assertArrayEquals("Image Minimum:", min, Intervals.minAsLongArray(img));
		assertArrayEquals("Image Maximum:", max, Intervals.maxAsLongArray(img));
	}
}
 

/** Tests {@link ShearViewInterval}. */
@Test
public void ShearIntervalTest() {
	Img<DoubleType> img = new ArrayImgFactory<DoubleType>().create(new int[] { 2, 2 }, new DoubleType());
	Cursor<DoubleType> imgC = img.cursor();
	while (imgC.hasNext()) {
		imgC.next().set(1);
	}

	Cursor<DoubleType> il2 = Views
			.shear(Views.extendZero(img), new FinalInterval(new long[] { 0, 0 }, new long[] { 3, 3 }), 0, 1)
			.cursor();
	RandomAccess<DoubleType> opr = ops.transform()
			.shearView(Views.extendZero(img), new FinalInterval(new long[] { 0, 0 }, new long[] { 3, 3 }), 0, 1)
			.randomAccess();

	while (il2.hasNext()) {
		il2.next();
		opr.setPosition(il2);
		assertEquals(il2.get().get(), opr.get().get(), 1e-10);
	}
}
 

/**
 * Apply mean filter with given size of reactangle shape
 * 
 * @param input
 *            Input image
 * @param i
 *            Size of rectangle shape
 * @return Filered mean image
 */
@SuppressWarnings("unchecked")
private Img<I> mean(final RandomAccessibleInterval<I> input, final int i) {

	long[] dims = new long[input.numDimensions()];
	input.dimensions(dims);

	final byte[] array = new byte[(int) Intervals.numElements(new FinalInterval(dims))];
	Img<I> meanImg = (Img<I>) ArrayImgs.unsignedBytes(array, dims);

	OutOfBoundsMirrorFactory<ByteType, Img<ByteType>> oobFactory = new OutOfBoundsMirrorFactory<>(
			Boundary.SINGLE);

	ops().run(MeanFilterOp.class, meanImg, input, new RectangleShape(i, true), oobFactory);

	return meanImg;
}
 

/**
 * Removes leading 0s from integral image after composite creation.
 *
 * @param input Input RAI (can be a RAI of Composite)
 * @return An extended and cropped version of input
 */
private <T> RandomAccessibleInterval<T> removeLeadingZeros(
	final RandomAccessibleInterval<T> input)
{
	// Remove 0s from integralImg by shifting its interval by +1
	final long[] min = Intervals.minAsLongArray(input);
	final long[] max = Intervals.maxAsLongArray(input);

	for (int d = 0; d < input.numDimensions(); ++d) {
		int correctedSpan = getShape().getSpan() - 1;
		min[d] += (1 + correctedSpan);
		max[d] -= correctedSpan;
	}

	// Define the Interval on the infinite random accessibles
	final FinalInterval interval = new FinalInterval(min, max);

	final RandomAccessibleInterval<T> extendedImg = Views.offsetInterval(Views
		.extendBorder(input), interval);
	return extendedImg;
}
 

@Override
@SuppressWarnings("unchecked")
public O calculate(final I input, final Interval centeredInterval) {

	int numDimensions = input.numDimensions();

	// compute where to place the final Interval for the input so that the
	// coordinate in the center
	// of the input is at position (0,0).
	final long[] min = new long[numDimensions];
	final long[] max = new long[numDimensions];

	for (int d = 0; d < numDimensions; ++d) {
		min[d] = input.min(d) + input.dimension(d) / 2;
		max[d] = min[d] + centeredInterval.dimension(d) - 1;
	}

	return (O) new FinalInterval(min, max);
}
 

@Test
public void testCreateFromRaiDifferentType() {
	final IntervalView<ByteType> input =
		Views.interval(PlanarImgs.bytes(10, 10, 10), new FinalInterval(
			new long[] { 10, 10, 1 }));

	final Img<?> res = (Img<?>) ops.run(CreateImgFromDimsAndType.class, input,
		new ShortType());

	assertEquals("Image Type: ", ShortType.class, res.firstElement().getClass());

	assertArrayEquals("Image Dimensions: ", Intervals
		.dimensionsAsLongArray(input), Intervals.dimensionsAsLongArray(res));

	assertEquals("Image Factory: ", ArrayImgFactory.class, res.factory()
		.getClass());
}
 

@Override
public RandomAccessibleInterval<T> calculate() {
	long[] dim = new long[4];

	dim[0] = 3;
	dim[1] = 1;

	for (int k = 2; k < dim.length; k++) {
		dim[k] = 1;
	}

	dim[dim.length - 1] = 2;

	RandomAccessibleInterval<T> output = createOp.calculate(new FinalInterval(dim));
	final Cursor<T> cursor = Views.iterable(output).cursor();
	int i = 0;
	while (cursor.hasNext()) {
		cursor.fwd();
		cursor.get().setReal(values[i]);
		i++;
	}

	return output;
}
 

private static Interval initIntervals(final Interval src, final int[] axesOfInterest) {

		final long[] dimensionsToIterate = new long[src.numDimensions()];
		src.dimensions(dimensionsToIterate);

		// determine axis to iterate
		for (int i = 0; i < src.numDimensions(); i++) {
			for (int j = 0; j < axesOfInterest.length; j++) {

				if (axesOfInterest[j] == i) {
					dimensionsToIterate[i] = 1;
					break;
				}
			}
		}

		return new FinalInterval(dimensionsToIterate);
	}
 

@Override
public void compute(final RandomAccessibleInterval<T> in1,
	final List<Shape> in2, final IterableInterval<T> out)
{
	final long[][] minSize = Morphologies.computeMinSize(in1, in2);
	final Interval interval = new FinalInterval(minSize[1]);
	Img<T> upstream = imgCreator.calculate(interval);
	Img<T> downstream = imgCreator.calculate(interval);
	Img<T> tmp;

	erodeComputer.compute(in1, in2.get(0), Views.translate(downstream,
		minSize[0]));
	for (int i = 1; i < in2.size(); i++) {
		// Ping-ponging intermediate results between upstream and downstream to
		// avoid repetitively creating new Imgs.
		tmp = downstream;
		downstream = upstream;
		upstream = tmp;
		erodeComputer.compute(Views.interval(Views.extendValue(upstream, maxVal),
			interval), in2.get(i), downstream);
	}
	if (isFull) copyImg.compute(downstream, out);
	else copyImg.compute(Views.interval(Views.translate(downstream,
		minSize[0]), out), out);
}
 

/**
 * @see DefaultIntegralImg
 * @see SquareIntegralImg
 */
@SuppressWarnings({ "unchecked" })
@Test
public void testIntegralImageSimilarity() {
	RandomAccessibleInterval<LongType> out1 =
		(RandomAccessibleInterval<LongType>) ops.run(DefaultIntegralImg.class,
			in);
	RandomAccessibleInterval<DoubleType> out2 =
		(RandomAccessibleInterval<DoubleType>) ops.run(WrappedIntegralImg.class,
			in);

	// Remove 0s from integralImg by shifting its interval by +1
	final long[] min = new long[out2.numDimensions()];
	final long[] max = new long[out2.numDimensions()];

	for (int d = 0; d < out2.numDimensions(); ++d) {
		min[d] = out2.min(d) + 1;
		max[d] = out2.max(d);
	}

	// Define the Interval on the infinite random accessibles
	final FinalInterval interval = new FinalInterval(min, max);

	LocalThresholdTest.testIterableIntervalSimilarity(Views.iterable(out1),
		Views.iterable(Views.offsetInterval(out2, interval)));
}
 

@Override
public Void call() throws Exception {

	final FinalInterval interval = new FinalInterval(in.dimension(0), in.dimension(1));
	for (int j = 0; j < in.dimension(1); j++) {
		// sum up the magnitudes of all bins in a neighborhood
		raNeighbor.setPosition(new long[] { i, j });
		final Cursor<FloatType> cursorNeighborHood = raNeighbor.get().cursor();
		while (cursorNeighborHood.hasNext()) {
			cursorNeighborHood.next();
			if (Intervals.contains(interval, cursorNeighborHood)) {
				raAngles.setPosition(cursorNeighborHood);
				raMagnitudes.setPosition(cursorNeighborHood);
				raOut.setPosition(new long[] { i, j,
						(int) (raAngles.get().getRealFloat() / (360 / numOrientations) - 0.5) });
				raOut.get().add(raMagnitudes.get());
			}
		}
	}
	return null;
}
 

@Override
public RandomAccessibleInterval<T> calculate(double[] input) {
	final double[] sigmaPixels = new double[input.length];

	final long[] dims = new long[input.length];
	final double[][] kernelArrays = new double[input.length][];

	for (int d = 0; d < input.length; d++) {
		sigmaPixels[d] = input[d];

		dims[d] = Math.max(3, (2 * (int) (3 * sigmaPixels[d] + 0.5) + 1));
		kernelArrays[d] = Util.createGaussianKernel1DDouble(sigmaPixels[d], true);
	}

	final RandomAccessibleInterval<T> out = createOp.calculate(new FinalInterval(
		dims));

	final Cursor<T> cursor = Views.iterable(out).cursor();
	while (cursor.hasNext()) {
		cursor.fwd();
		double result = 1.0f;
		for (int d = 0; d < input.length; d++) {
			result *= kernelArrays[d][cursor.getIntPosition(d)];
		}

		cursor.get().setReal(result);
	}

	return out;
}
 

public ArrayImg<LongType, LongArray> generateLongArrayTestImg(
	final boolean fill, final long... dims)
{
	final long[] array = new long[(int) Intervals.numElements(new FinalInterval(
		dims))];

	if (fill) {
		seed = 17;
		for (int i = 0; i < array.length; i++) {
			array[i] = (long) (pseudoRandom() / Integer.MAX_VALUE);
		}
	}

	return ArrayImgs.longs(array, dims);
}
 

public VolatileHierarchyProjectorPreMultiply(
		final List<? extends RandomAccessible<A>> sources,
		final Converter<? super A, ARGBType> converter,
		final RandomAccessibleInterval<ARGBType> target,
		final RandomAccessibleInterval<ByteType> mask,
		final int numThreads,
		final ExecutorService executorService)
{
	super(Math.max(2, sources.get(0).numDimensions()), converter, target);

	this.sources.addAll(sources);
	numInvalidLevels = sources.size();

	this.mask = mask;

	iterableTarget = Views.iterable(target);

	target.min(min);
	target.max(max);
	sourceInterval = new FinalInterval(min, max);

	width = (int) target.dimension(0);
	height = (int) target.dimension(1);
	cr = -width;

	this.numThreads = numThreads;
	this.executorService = executorService;

	lastFrameRenderNanoTime = -1;
	clearMask();
}
 

public ArrayImg<UnsignedShortType, ShortArray>
	generateUnsignedShortArrayTestImg(final boolean fill, final long... dims)
{
	final short[] array = new short[(int) Intervals.numElements(
		new FinalInterval(dims))];

	if (fill) {
		seed = 17;
		for (int i = 0; i < array.length; i++) {
			array[i] = (short) (pseudoRandom() / Integer.MAX_VALUE);
		}
	}

	return ArrayImgs.unsignedShorts(array, dims);
}
 

private static Interval padInterval(final Interval interval, final int[] padding, final int[] imageSize)
{
	final long[] paddedIntervalMin = new long[2], paddedIntervalMax = new long[2];
	Arrays.setAll(paddedIntervalMin, d -> Math.max(interval.min(d) - padding[d], 0));
	Arrays.setAll(paddedIntervalMax, d -> Math.min(interval.max(d) + padding[d], imageSize[d] - 1));
	return new FinalInterval(paddedIntervalMin, paddedIntervalMax);
}
 

@Override
public IterableInterval<T> createOutput(final RandomAccessibleInterval<T> in1,
	final List<Shape> in2)
{
	if (isFull) {
		final long[][] maxSize = Morphologies.computeMinSize(in1, in2);
		return imgCreator.calculate(new FinalInterval(maxSize[1]));
	}
	return imgCreator.calculate(in1);
}
 

@Override
public IterableInterval<T> createOutput(final RandomAccessibleInterval<T> in1,
	final List<Shape> in2)
{
	if (isFull) {
		final long[][] minSize = Morphologies.computeMinSize(in1, in2);
		return imgCreator.calculate(new FinalInterval(minSize[1]));
	}
	return imgCreator.calculate(in1);
}
 

/**
 * RealRandomAccess that computes a blending function for a certain {@link Interval}
 * 
 * @param interval - the interval it is defined on (return zero outside of it)
 * @param border - how many pixels to skip before starting blending (on each side of each dimension)
 * @param blending - how many pixels to compute the blending function on (on each side of each dimension)
 */
public Blending( final Interval interval, final float[] border, final float[] blending )
{
	// in case the interval is actually image data re-instantiate just a simple FinalInterval
	this.interval = new FinalInterval( interval );
	this.border = border;
	this.blending = blending;
}
 

private static final void copy( final long start, final long loopSize, final RandomAccessible< FloatType > source, final RandomAccessibleInterval< FloatType > block, final long[] offset )
{
	final int numDimensions = source.numDimensions();
	final Cursor< FloatType > cursor = Views.iterable( block ).localizingCursor();

	// define where we will query the RandomAccess on the source
	// (we say it is the entire block, although it is just a part of it,
	// but which part depends on the underlying container)
	final long[] min = new long[ numDimensions ];
	final long[] max = new long[ numDimensions ];
	
	for ( int d = 0; d < numDimensions; ++d )
	{
		min[ d ] = offset[ d ];
		max[ d ] = offset[ d ] + block.dimension( d ) - 1;
	}

	final RandomAccess< FloatType > randomAccess = source.randomAccess( new FinalInterval( min, max ) );

	cursor.jumpFwd( start );

	final long[] tmp = new long[ numDimensions ];

	for ( long l = 0; l < loopSize; ++l )
	{
		cursor.fwd();
		cursor.localize( tmp );
		
		for ( int d = 0; d < numDimensions; ++d )
			tmp[ d ] += offset[ d ];
		
		randomAccess.setPosition( tmp );
		cursor.get().set( randomAccess.get() );
	}
}
 

public ArrayImg<ByteType, ByteArray> generateByteArrayTestImg(
	final boolean fill, final long... dims)
{
	final byte[] array = new byte[(int) Intervals.numElements(new FinalInterval(
		dims))];

	if (fill) {
		seed = 17;
		for (int i = 0; i < array.length; i++) {
			array[i] = (byte) pseudoRandom();
		}
	}

	return ArrayImgs.bytes(array, dims);
}
 

public ArrayImg<UnsignedByteType, ByteArray> generateUnsignedByteArrayTestImg(
	final boolean fill, final long... dims)
{
	final byte[] array = new byte[(int) Intervals.numElements(new FinalInterval(
		dims))];

	if (fill) {
		seed = 17;
		for (int i = 0; i < array.length; i++) {
			array[i] = (byte) pseudoRandom();
		}
	}

	return ArrayImgs.unsignedBytes(array, dims);
}
 

private static final void copy3dArray( final int threadIdx, final int numThreads, final RandomAccessible< FloatType > source, final ArrayImg< FloatType, ? > block, final long[] offset )
{
	final int w = (int)block.dimension( 0 );
	final int h = (int)block.dimension( 1 );
	final int d = (int)block.dimension( 2 );

	final long offsetX = offset[ 0 ];
	final long offsetY = offset[ 1 ];
	final long offsetZ = offset[ 2 ];
	final float[] blockArray = ((FloatArray)block.update( null ) ).getCurrentStorageArray();

	// define where we will query the RandomAccess on the source
	final FinalInterval interval = new FinalInterval( new long[] { offsetX, offsetY, offsetZ }, new long[] { offsetX + w - 1, offsetY + h - 1, offsetZ + d - 1 } );
	final RandomAccess< FloatType > randomAccess = source.randomAccess( interval );

	final long[] tmp = new long[]{ offsetX, offsetY, 0 };

	for ( int z = threadIdx; z < d; z += numThreads )
	{
		tmp[ 2 ] = z + offsetZ;
		randomAccess.setPosition( tmp );

		int i = z * h * w;

		for ( int y = 0; y < h; ++y )
		{
			randomAccess.setPosition( offsetX, 0 );

			for ( int x = 0; x < w; ++x )
			{
				blockArray[ i++ ] = randomAccess.get().get();
				randomAccess.fwd( 0 );
			}

			randomAccess.move( -w, 0 );
			randomAccess.fwd( 1 );
		}
	}
}