Java Code Examples for net.imglib2.util.Pair#getB()

private static TLongHashSet generateContainedLabelsSet(
		final RandomAccessibleInterval<Pair<UnsignedLongType, LabelMultisetType>> relevantData)
{
	final TLongHashSet currentDataAsSet = new TLongHashSet();
	for (final Pair<UnsignedLongType, LabelMultisetType> p : Views.iterable(relevantData))
	{
		final UnsignedLongType  pa  = p.getA();
		final LabelMultisetType pb  = p.getB();
		final long              pav = pa.getIntegerLong();
		if (pav == Label.INVALID)
		{
			pb
					.entrySet()
					.stream()
					.map(Entry::getElement)
					.mapToLong(Label::id)
					.forEach(currentDataAsSet::add);
		}
		else
		{
			currentDataAsSet.add(pav);
		}
	}
	return currentDataAsSet;
}
 

@Override
public Iterator<LabelMultisetType> iterator() {
	return new Iterator<LabelMultisetType>() {

		final Iterator<? extends Pair<LabelMultisetType, UnsignedLongType>> iterator = backgroundAndCanvas.iterator();

		final Converter<UnsignedLongType, LabelMultisetType> conv = new FromIntegerTypeConverter<>();

		final LabelMultisetType type = FromIntegerTypeConverter.getAppropriateType();

		@Override
		public boolean hasNext() {
			return iterator.hasNext();
		}

		@Override
		public LabelMultisetType next() {
			final Pair<LabelMultisetType, UnsignedLongType> p = iterator.next();
			final UnsignedLongType b = p.getB();
			if (Label.regular(b.getIntegerLong())) {
				conv.convert(b, type);
				return type;
			} else
				return p.getA();
		}
	};
}
 

@Override
public boolean queryParameters( SpimData2 spimData, final boolean is16bit )
{
	System.out.println( "queryParameters()" );

	if ( newTimepoints == null || newViewSetups == null )
	{
		IOFunctions.println( "new timepoints and new viewsetup list not set yet ... cannot continue" );
		return false;
	}

	perSetupExportMipmapInfo = Resave_HDF5.proposeMipmaps( newViewSetups );

	String fn = LoadParseQueryXML.defaultXMLfilename;
	if ( fn.endsWith( ".xml" ) )
		fn = fn.substring( 0, fn.length() - ".xml".length() );
	for ( int i = 0;; ++i )
	{
		Generic_Resave_HDF5.lastExportPath = String.format( "%s-f%d.xml", fn, i );
		if ( !new File( Generic_Resave_HDF5.lastExportPath ).exists() )
			break;
	}

	final int firstviewSetupId = newViewSetups.get( 0 ).getId();
	params = Generic_Resave_HDF5.getParameters( perSetupExportMipmapInfo.get( firstviewSetupId ), true, getDescription(), is16bit );

	if ( params == null )
	{
		System.out.println( "abort " );
		return false;
	}

	Pair< SpimData2, HashMap< ViewId, Partition > > init = initSpimData( newTimepoints, newViewSetups, params, perSetupExportMipmapInfo );
	this.spimData = init.getA();
	viewIdToPartition = init.getB();

	return true;
}
 

protected static File getFileNameForViewId( final ViewDescription vd, final ArrayList< Pair< Pair< Angle, Illumination >, String > > filenames )
{
	for ( final Pair< Pair< Angle, Illumination >, String > pair : filenames )
		if ( pair.getA().getA().getId() == vd.getViewSetup().getAngle().getId() && pair.getA().getB().getId() == vd.getViewSetup().getIllumination().getId() )
			return new File( pair.getB() );

	return null;
}
 

@Override
public String calculate(final IterableInterval<T> input) {
	if (min == null || max == null) {
		final Pair<T, T> minMax = minMaxFunc.calculate(input);
		if (min == null) min = minMax.getA();
		if (max == null) max = minMax.getB();
	}
	return ascii(input, min, max);
}
 

@Override
public void compute(final Pair<RealLocalizable, RealLocalizable> input, final DoubleType output) {

	final RealLocalizable p1 = input.getA();
	final RealLocalizable p2 = input.getB();

	output.set(Math.hypot(p1.getDoublePosition(0) - p2.getDoublePosition(0),
			p1.getDoublePosition(1) - p2.getDoublePosition(1)));
}
 

@Override
public void compute(final Pair<RealLocalizable, RealLocalizable> input, final DoubleType output) {

	final RealLocalizable p1 = input.getA();
	final RealLocalizable p2 = input.getB();

	final double degree = Math.atan2(p2.getDoublePosition(1) - p1.getDoublePosition(1),
			p2.getDoublePosition(0) - p1.getDoublePosition(0)) * (180.0 / Math.PI);

	output.set(degree % 180);
}
 

public void setSelectedLink(Pair<Group<ViewId>, Group<ViewId>> link)
{
	if (link == null)
		selectedLink = null;
	else
		selectedLink = new ValuePair<>( link.getA(), link.getB() );
}
 

private void setMeshVisibility(final Pair<MeshView, Node> meshAndBlock, final boolean isVisible)
{
	if (meshAndBlock.getA() != null)
		meshAndBlock.getA().setVisible(isVisible);

	if (meshAndBlock.getB() != null)
		meshAndBlock.getB().setVisible(isVisible);
}
 

public static < T extends RealType< T > > Pair<Pair< AffineGet, Double >, RealInterval> computeStitchingLucasKanade(
		final Group<? extends ViewId> viewIdsA,
		final Group<? extends ViewId> viewIdsB,
		final ViewRegistrations vrs,
		final LucasKanadeParameters params,
		final AbstractSequenceDescription< ?,? extends BasicViewDescription<?>, ? > sd,
		final GroupedViewAggregator gva,
		final long[] downsampleFactors,
		final ExecutorService service )
{
	
	// the transformation that maps the downsampled image coordinates back to the original input(!) image space
	final AffineTransform3D dsCorrectionT1 = new AffineTransform3D();
	final AffineTransform3D dsCorrectionT2 = new AffineTransform3D();

	// get Overlap Bounding Box
	final List<List<ViewId>> views = new ArrayList<>();
	views.add( new ArrayList<>(viewIdsA.getViews()) );
	views.add( new ArrayList<>(viewIdsB.getViews()) );
	BoundingBoxMaximalGroupOverlap< ViewId > bbDet = new BoundingBoxMaximalGroupOverlap<ViewId>( views, sd, vrs );
	BoundingBox bbOverlap = bbDet.estimate( "Max Overlap" );

	// this should be caught outside of this method already, but check nonetheless
	if (bbOverlap == null)
		return null;

	// get one image per group
	final RandomAccessibleInterval<T> img1 = gva.aggregate( viewIdsA, sd, downsampleFactors, dsCorrectionT1 );	
	final RandomAccessibleInterval<T> img2 = gva.aggregate( viewIdsB, sd, downsampleFactors, dsCorrectionT2 );

	if (img1 == null || img2 == null)
	{
		IOFunctions.println( "WARNING: Tried to open missing View when computing Stitching for " + viewIdsA + " and " + 
					viewIdsB + ". No link between those could be determined");
		return null;
	}

	// get translations
	// TODO: is the 2d check here meaningful?
	boolean is2d = img1.numDimensions() == 2;
	Pair< AffineGet, TranslationGet > t1 = TransformTools.getInitialTransforms( vrs.getViewRegistration(viewIdsA.iterator().next()), is2d, dsCorrectionT1 );
	Pair< AffineGet, TranslationGet > t2 = TransformTools.getInitialTransforms( vrs.getViewRegistration(viewIdsB.iterator().next()), is2d, dsCorrectionT2 );

	final Pair< AffineTransform, Double > result  = PairwiseStitching.getShiftLucasKanade(  img1, img2, t1.getB(), t2.getB(), params, service );

	if (result == null)
		return null;

	// TODO: is scaling just the translational part okay here?
	for (int i = 0; i< result.getA().numDimensions(); ++i)			
		result.getA().set( result.getA().get(i, result.getA().numDimensions()) * downsampleFactors[i], i, result.getA().numDimensions() ); 

	// TODO (?): Different translational part of downsample Transformations should be considered via TransformTools.getInitialTransforms
	// we probalbly do not have to correct for them ?

	// NB: as we will deal in global coordinates, not pixel coordinates in global optimization,
	// calculate global R' = VT^-1 * R * VT from pixel transformation R 
	ViewRegistration vrOld = vrs.getViewRegistration(viewIdsB.iterator().next());
	AffineTransform3D resTransform = new AffineTransform3D();
	resTransform.set( result.getA().getRowPackedCopy() );
	resTransform.concatenate( vrOld.getModel().inverse() );
	resTransform.preConcatenate( vrOld.getModel() );

	IOFunctions.println("resulting transformation (pixel coordinates): " + Util.printCoordinates(result.getA().getRowPackedCopy()));
	IOFunctions.println("resulting transformation (global coordinates): " + Util.printCoordinates(resTransform.getRowPackedCopy()));

	return new ValuePair<>( new ValuePair<>( resTransform, result.getB() ), bbOverlap );
}
 

public static < T extends RealType< T > > Pair<Pair< AffineGet, Double >, RealInterval> computeStitching(
		final Group<? extends ViewId> viewIdsA,
		final Group<? extends ViewId> viewIdsB,
		final ViewRegistrations vrs,
		final PairwiseStitchingParameters params,
		final AbstractSequenceDescription< ?,? extends BasicViewDescription<?>, ? > sd,
		final GroupedViewAggregator gva,
		final long[] downsampleFactors,
		final ExecutorService service )
{

	// the transformation that maps the downsampled image coordinates back to the original input(!) image space
	final AffineTransform3D dsCorrectionT1 = new AffineTransform3D();
	final AffineTransform3D dsCorrectionT2 = new AffineTransform3D();

	// get Overlap Bounding Box
	final List<List<ViewId>> views = new ArrayList<>();
	views.add( new ArrayList<>(viewIdsA.getViews()) );
	views.add( new ArrayList<>(viewIdsB.getViews()) );
	BoundingBoxMaximalGroupOverlap< ViewId > bbDet = new BoundingBoxMaximalGroupOverlap<ViewId>( views, sd, vrs );
	BoundingBox bbOverlap = bbDet.estimate( "Max Overlap" );

	// this should be caught outside of this method already, but check nonetheless
	if (bbOverlap == null)
		return null;

	// get one image per group
	final RandomAccessibleInterval<T> img1 = gva.aggregate( viewIdsA, sd, downsampleFactors, dsCorrectionT1 );	
	final RandomAccessibleInterval<T> img2 = gva.aggregate( viewIdsB, sd, downsampleFactors, dsCorrectionT2 );

	if (img1 == null || img2 == null)
	{
		IOFunctions.println( "WARNING: Tried to open missing View when computing Stitching for " + viewIdsA + " and " + 
					viewIdsB + ". No link between those could be determined");
		return null;
	}

	// get translations
	// TODO: is the 2d check here meaningful?
	// everything will probably be 3d at this point, since ImgLoaders return 3d images
	boolean is2d = img1.numDimensions() == 2;
	Pair< AffineGet, TranslationGet > t1 = TransformTools.getInitialTransforms( vrs.getViewRegistration(viewIdsA.iterator().next()), is2d, dsCorrectionT1 );
	Pair< AffineGet, TranslationGet > t2 = TransformTools.getInitialTransforms( vrs.getViewRegistration(viewIdsB.iterator().next()), is2d, dsCorrectionT2 );

	final Pair< Translation, Double > result  = PairwiseStitching.getShift( img1, img2, t1.getB(), t2.getB(), params, service );

	if (result == null)
		return null;
	
	for (int i = 0; i< result.getA().numDimensions(); ++i)			
		result.getA().set( result.getA().get(i, result.getA().numDimensions()) * downsampleFactors[i], i ); 

	// TODO (?): Different translational part of downsample Transformations should be considered via TransformTools.getInitialTransforms
	// we probalbly do not have to correct for them ?

	// NB: as we will deal in global coordinates, not pixel coordinates in global optimization,
	// calculate global R' = VT^-1 * R * VT from pixel transformation R 
	ViewRegistration vrOld = vrs.getViewRegistration(viewIdsB.iterator().next());
	AffineTransform3D resTransform = new AffineTransform3D();
	resTransform.set( result.getA().getRowPackedCopy() );
	resTransform.concatenate( vrOld.getModel().inverse() );
	resTransform.preConcatenate( vrOld.getModel() );

	System.out.println("shift (pixel coordinates): " + Util.printCoordinates(result.getA().getTranslationCopy()));
	System.out.println("shift (global coordinates): " + Util.printCoordinates(resTransform.getRowPackedCopy()));
	System.out.print("cross-corr: " + result.getB());

	return new ValuePair<>( new ValuePair<>( resTransform, result.getB() ), bbOverlap );
}
 

public static <T extends RealType<T>> List<PhaseCorrelationPeak2> getPCMMaxima(RandomAccessibleInterval<T> pcm, ExecutorService service, int maxN, boolean subpixelAccuracy){
	
	List<PhaseCorrelationPeak2> res = new ArrayList<PhaseCorrelationPeak2>();
	
	ArrayList<Pair<Localizable, Double>> maxima = FourNeighborhoodExtrema.findMaxMT(Views.extendPeriodic(pcm), pcm, maxN, service);
	//ArrayList<Pair<Localizable, Double>> maxima = FourNeighborhoodExtrema.findMax(Views.extendPeriodic(pcm), pcm, maxN);
	
	
			
	for (Pair<Localizable, Double> p: maxima){
		PhaseCorrelationPeak2 pcp = new PhaseCorrelationPeak2(p.getA(), p.getB());
		if (subpixelAccuracy)
			pcp.calculateSubpixelLocalization(pcm);

		res.add(pcp);
	}
	return res;		
}
 

public static < T extends RealType< T > > Pair<Pair< AffineGet, Double >, RealInterval> computeStitchingNonEqualTransformationsLucasKanade(
		final Group<? extends ViewId> viewIdsA,
		final Group<? extends ViewId> viewIdsB,
		final ViewRegistrations vrs,
		final LucasKanadeParameters params,
		final AbstractSequenceDescription< ?,? extends BasicViewDescription<?>, ? > sd,
		final GroupedViewAggregator gva,
		final long[] downsampleFactors,
		final ExecutorService service )
{
	final double[] downsampleDbl = new double[downsampleFactors.length];
	for (int d = 0; d < downsampleFactors.length; d++)
		downsampleDbl[d] = downsampleFactors[d];

	// get Overlap Bounding Box
	final List<List<ViewId>> views = new ArrayList<>();
	views.add( new ArrayList<>(viewIdsA.getViews()) );
	views.add( new ArrayList<>(viewIdsB.getViews()) );
	BoundingBoxMaximalGroupOverlap< ViewId > bbDet = new BoundingBoxMaximalGroupOverlap<ViewId>( views, sd, vrs );
	BoundingBox bbOverlap = bbDet.estimate( "Max Overlap" );

	// we could not find overlap -> ignore this pair
	if (bbOverlap == null)
		return null;

	List<RandomAccessibleInterval< FloatType >> raiOverlaps = new ArrayList<>();		
	for (List< ViewId > tileViews : views)
	{
		// wrap every view id (corresponding e.g. to different channels, illums,.. ) in list
		List<List< ViewId >> wrapped = tileViews.stream().map( v -> {
			ArrayList< ViewId > wrp = new ArrayList<ViewId>();
			wrp.add( v );
			return wrp;} ).collect( Collectors.toList() );

		// open all of them "virtually fused"
		List< RandomAccessibleInterval< FloatType > > openFused = 
				DisplayOverlapTestPopup.openVirtuallyFused( sd, vrs, wrapped, bbOverlap, downsampleDbl );

		// aggregate the group into one image
		RandomAccessibleInterval< FloatType > raiI = gva.aggregate( 
				openFused, 
				tileViews,
				sd );

		raiOverlaps.add(raiI);
	}

	// the overlap in both images
	final RandomAccessibleInterval< FloatType > img1 = raiOverlaps.get(0);
	final RandomAccessibleInterval< FloatType > img2 = raiOverlaps.get(1);
	
	// compute phase correlation shift (passing (0,0,..) translations prevents any overlap correction inside)
	final Pair< AffineTransform, Double > result = PairwiseStitching.getShiftLucasKanade(
			img1,
			img2,
			new Translation( img1.numDimensions() ),
			new Translation( img1.numDimensions() ),
			params,
			service );

	if (result == null)
		return null;

	// scale just the translational part
	for (int i = 0; i< result.getA().numDimensions(); ++i)			
		result.getA().set( result.getA().get(i, result.getA().numDimensions()) * downsampleFactors[i], i ); 

	// TODO (?): Different translational part of downsample Transformations should be considered via TransformTools.getInitialTransforms
	// we probalbly do not have to correct for them ?

	final AffineTransform3D vr = vrs.getViewRegistration(viewIdsB.iterator().next()).getModel();		
	final AffineTransform resCorrected = new AffineTransform( result.getA().numDimensions() );
	resCorrected.set( result.getA() );

	IOFunctions.println("resulting transformation: " + Util.printCoordinates(result.getA().getRowPackedCopy()));

	return new ValuePair<>( new ValuePair<>( resCorrected, result.getB() ), bbOverlap );
}
 

public static < T extends RealType< T > > Pair<Pair< AffineGet, Double >, RealInterval> computeStitchingNonEqualTransformations(
		final Group<? extends ViewId> viewIdsA,
		final Group<? extends ViewId> viewIdsB,
		final ViewRegistrations vrs,
		final PairwiseStitchingParameters params,
		final AbstractSequenceDescription< ?,? extends BasicViewDescription<?>, ? > sd,
		final GroupedViewAggregator gva,
		final long[] downsampleFactors,
		final ExecutorService service )
{

	final double[] downsampleDbl = new double[downsampleFactors.length];
	for (int d = 0; d < downsampleFactors.length; d++)
		downsampleDbl[d] = downsampleFactors[d];

	// get Overlap Bounding Box
	final List<List<ViewId>> views = new ArrayList<>();
	views.add( new ArrayList<>(viewIdsA.getViews()) );
	views.add( new ArrayList<>(viewIdsB.getViews()) );
	BoundingBoxMaximalGroupOverlap< ViewId > bbDet = new BoundingBoxMaximalGroupOverlap<ViewId>( views, sd, vrs );
	BoundingBox bbOverlap = bbDet.estimate( "Max Overlap" );

	// we could not find overlap -> ignore this pair
	if (bbOverlap == null)
		return null;

	List<RandomAccessibleInterval< FloatType >> raiOverlaps = new ArrayList<>();		
	for (List< ViewId > tileViews : views)
	{
		// wrap every view id (corresponding e.g. to different channels, illums,.. ) in list
		List<List< ViewId >> wrapped = tileViews.stream().map( v -> {
			ArrayList< ViewId > wrp = new ArrayList<ViewId>();
			wrp.add( v );
			return wrp;} ).collect( Collectors.toList() );

		// open all of them "virtually fused"
		List< RandomAccessibleInterval< FloatType > > openFused = 
				DisplayOverlapTestPopup.openVirtuallyFused( sd, vrs, wrapped, bbOverlap, downsampleDbl );

		// aggregate the group into one image
		RandomAccessibleInterval< FloatType > raiI = gva.aggregate( 
				openFused, 
				tileViews,
				sd );

		raiOverlaps.add(raiI);
	}

	// the overlap in both images
	final RandomAccessibleInterval< FloatType > img1 = raiOverlaps.get(0);
	final RandomAccessibleInterval< FloatType > img2 = raiOverlaps.get(1);
	
	// compute phase correlation shift (passing (0,0,..) translations prevents any overlap correction inside)
	final Pair< Translation, Double > result = PairwiseStitching.getShift(
			img1,
			img2,
			new Translation( img1.numDimensions() ),
			new Translation( img1.numDimensions() ),
			params,
			service );

	if (result == null)
		return null;

	for (int i = 0; i< result.getA().numDimensions(); ++i)			
		result.getA().set( result.getA().get(i, result.getA().numDimensions()) * downsampleFactors[i], i ); 

	// TODO (?): Different translational part of downsample Transformations should be considered via TransformTools.getInitialTransforms
	// we probalbly do not have to correct for them ?
	final AffineTransform3D vr = vrs.getViewRegistration(viewIdsB.iterator().next()).getModel();		
	final AffineTransform resCorrected = new AffineTransform( result.getA().numDimensions() );
	resCorrected.set( result.getA() );

	System.out.println("shift: " + Util.printCoordinates(result.getA().getTranslationCopy()));
	System.out.print("cross-corr: " + result.getB());

	return new ValuePair<>( new ValuePair<>( resCorrected, result.getB() ), bbOverlap );
}
 

public static < A > Pair< A, A > reversePair( final Pair< A, A > pair )
{
	return new ValuePair< A, A >( pair.getB(), pair.getA() );
}
 

@Override
public void run( String arg )
{
	if ( showNote )
	{
		showNote();
		showNote = false;
	}

	final LoadParseQueryXML result = new LoadParseQueryXML();

	result.addButton( "Define a new dataset", new ActionListener()
	{
		@Override
		public void actionPerformed(ActionEvent e)
		{
			result.setReturnFalse( true );
			result.getGenericDialog().dispose();
			setDefineNewDataset();
		}
	});

	if ( !result.queryXML( "XML Explorer", "", false, false, false, false ) && !newDataset )
		return;

	final SpimData2 data;
	final String xml;
	final XmlIoSpimData2 io;

	if ( newDataset )
	{
		final Pair< SpimData2, String > dataset = new Define_Multi_View_Dataset().defineDataset( true );

		if ( dataset == null )
			return;

		data = dataset.getA();
		xml = dataset.getB();
		io = new XmlIoSpimData2( "" );
	}
	else
	{
		data = result.getData();
		xml = result.getXMLFileName();
		io = result.getIO();
	}

	final ViewSetupExplorer< SpimData2, XmlIoSpimData2 > explorer = new ViewSetupExplorer<SpimData2, XmlIoSpimData2 >( data, xml, io );

	explorer.getFrame().toFront();

	
}
 

@Override
public void actionPerformed( final ActionEvent e )
{
	if ( panel == null )
	{
		IOFunctions.println( "Panel not set for " + this.getClass().getSimpleName() );
		return;
	}

	if ( !SpimData2.class.isInstance( panel.getSpimData() ) )
	{
		IOFunctions.println( "Only supported for SpimData2 objects: " + this.getClass().getSimpleName() );
		return;
	}


	if ( index == 0 )
	{
		final List< ViewId > viewIds = panel.selectedRowsViewId();
		final SpimData2 data = (SpimData2)panel.getSpimData();

		// ask which channels have the objects we are searching for
		final List< ChannelProcessThinOut > channels = ThinOut_Detections.getChannelsAndLabels( data, viewIds );

		if ( channels == null )
			return;

		// get the actual min/max thresholds for cutting out
		if ( !ThinOut_Detections.getThinOutThresholds( data, viewIds, channels ) )
			return;

		// thin out detections and save the new interestpoint files
		if ( !ThinOut_Detections.thinOut( data, viewIds, channels, false ) )
			return;

		panel.updateContent(); // update interestpoint panel if available

		return;
	}
	else
	{
		final List< BasicViewDescription< ? extends BasicViewSetup > > vds = panel.selectedRows();

		if ( vds.size() != 1 )
		{
			JOptionPane.showMessageDialog( null, "Interactive Removal of Detections only supports a single view at a time." );
			return;
		}

		final Pair< String, String > labels = Interactive_Remove_Detections.queryLabelAndNewLabel( (SpimData2)panel.getSpimData(), (ViewDescription)vds.get( 0 ) );

		if ( labels == null )
			return;

		final SpimData2 spimData = (SpimData2)panel.getSpimData();
		final ViewDescription vd = (ViewDescription)vds.get( 0 );
		final ViewInterestPoints interestPoints = spimData.getViewInterestPoints();
		final ViewInterestPointLists lists = interestPoints.getViewInterestPointLists( vd );
		final String label = labels.getA();
		final String newLabel = labels.getB();

		final InteractiveProjections ip = new InteractiveProjections( spimData, vd, label, newLabel, 2 - (index - 1) );

		ip.runWhenDone( new Thread( new Runnable()
		{
			@Override
			public void run()
			{
				if ( ip.wasCanceled() )
					return;

				final List< InterestPoint > ipList = ip.getInterestPointList();

				if ( ipList.size() == 0 )
				{
					IOFunctions.println( "No detections remaining. Quitting." );
					return;
				}

				// add new label
				final InterestPointList newIpl = new InterestPointList(
						lists.getInterestPointList( label ).getBaseDir(),
						new File(
								lists.getInterestPointList( label ).getFile().getParentFile(),
								"tpId_" + vd.getTimePointId() + "_viewSetupId_" + vd.getViewSetupId() + "." + newLabel ) );

				newIpl.setInterestPoints( ipList );
				newIpl.setParameters( "manually removed detections from '" +label + "'" );

				lists.addInterestPointList( newLabel, newIpl );

				panel.updateContent(); // update interestpoint panel if available
			}
		}) );

		return;
	}
}
 

private static <T, U> void restrictTo(
		final RandomAccessible<Pair<T, U>> source,
		final RandomAccessible<UnsignedLongType> mask,
		final Localizable seed,
		final Shape shape,
		final Predicate<T> backgroundFilter,
		final Predicate<U> canvasFilter)
{
	final int n = source.numDimensions();

	final RandomAccessible<Pair<Pair<T, U>, UnsignedLongType>> paired = Views.pair(source, mask);

	final TLongList[] coordinates = new TLongList[n];
	for (int d = 0; d < n; ++d)
	{
		coordinates[d] = new TLongArrayList();
		coordinates[d].add(seed.getLongPosition(d));
	}

	final RandomAccessible<Neighborhood<Pair<Pair<T, U>, UnsignedLongType>>> neighborhood       = shape
			.neighborhoodsRandomAccessible(
			paired);
	final RandomAccess<Neighborhood<Pair<Pair<T, U>, UnsignedLongType>>>     neighborhoodAccess = neighborhood
			.randomAccess();

	final RandomAccess<UnsignedLongType> targetAccess = mask.randomAccess();
	targetAccess.setPosition(seed);
	targetAccess.get().set(1);

	final UnsignedLongType zero = new UnsignedLongType(0);
	final UnsignedLongType one  = new UnsignedLongType(1);
	final UnsignedLongType two  = new UnsignedLongType(2);

	for (int i = 0; i < coordinates[0].size(); ++i)
	{
		for (int d = 0; d < n; ++d)
		{
			neighborhoodAccess.setPosition(coordinates[d].get(i), d);
		}

		final Cursor<Pair<Pair<T, U>, UnsignedLongType>> neighborhoodCursor = neighborhoodAccess.get().cursor();

		while (neighborhoodCursor.hasNext())
		{
			final Pair<Pair<T, U>, UnsignedLongType> p                   = neighborhoodCursor.next();
			final UnsignedLongType                   m                   = p.getB();
			final Pair<T, U>                         backgroundAndCanvas = p.getA();
			if (m.valueEquals(zero) && canvasFilter.test(backgroundAndCanvas.getB()))
			{
				// If background is same as at seed, mark mask with two
				// (==not active), else with one (==active).
				m.set(backgroundFilter.test(backgroundAndCanvas.getA()) ? two : one);
				for (int d = 0; d < n; ++d)
				{
					coordinates[d].add(neighborhoodCursor.getLongPosition(d));
				}
			}

		}

		if (i > CLEANUP_THRESHOLD)
		{
			for (int d = 0; d < coordinates.length; ++d)
			{
				final TLongList c = coordinates[d];
				coordinates[d] = c.subList(i, c.size());
			}
			i = 0;
		}

	}
}
 

@Override
public boolean queryParameters( final SpimData2 spimData, final boolean is16bit )
{
	System.out.println( "queryParameters()" );

	if ( newTimepoints == null || newViewSetups == null )
	{
		IOFunctions.println( "new timepoints and new viewsetup list not set yet ... cannot continue" );
		return false;
	}

	Hdf5ImageLoader il = ( Hdf5ImageLoader ) spimData.getSequenceDescription().getImgLoader();

	perSetupExportMipmapInfo = Resave_HDF5.proposeMipmaps( newViewSetups );

	String fn = il.getHdf5File().getAbsolutePath();
	if ( fn.endsWith( ".h5" ) )
		fn = fn.substring( 0, fn.length() - ".h5".length() );
	String fusionHdfFilename = "";
	String fusionXmlFilename = "";
	for ( int i = 0;; ++i )
	{
		fusionHdfFilename = String.format( "%s-f%d.h5", fn, i );
		fusionXmlFilename = String.format( "%s-f%d.xml", fn, i );
		if ( !new File( fusionHdfFilename ).exists() && !new File( fusionXmlFilename ).exists() )
			break;
	}

	final int firstviewSetupId = newViewSetups.get( 0 ).getId();
	params = Generic_Resave_HDF5.getParameters( perSetupExportMipmapInfo.get( firstviewSetupId ), false, getDescription(), is16bit );
	if ( params == null )
	{
		System.out.println( "abort " );
		return false;
	}
	params.setHDF5File( new File( fusionHdfFilename ) );
	params.setSeqFile( new File( fusionXmlFilename ) );

	Pair< SpimData2, HashMap< ViewId, Partition > > init = ExportSpimData2HDF5.initSpimData(
			newTimepoints, newViewSetups, params, perSetupExportMipmapInfo );
	fusionOnlySpimData = init.getA();
	viewIdToPartition = init.getB();

	perSetupExportMipmapInfo.putAll(
			MergePartitionList.getHdf5PerSetupExportMipmapInfos( spimData.getSequenceDescription() ) );

	this.spimData = spimData;
	AppendSpimData2.appendSpimData2( spimData, newTimepoints, newViewSetups );

	ArrayList< Partition > mergedPartitions = MergePartitionList.getMergedHdf5PartitionList(
			spimData.getSequenceDescription(), fusionOnlySpimData.getSequenceDescription() );

	String mergedHdfFilename = "";
	for ( int i = 0;; ++i )
	{
		mergedHdfFilename = String.format( "%s-m%d.h5", fn, i );
		if ( !new File( mergedHdfFilename ).exists() )
			break;
	}

	SequenceDescription seq = spimData.getSequenceDescription();
	Hdf5ImageLoader newLoader = new Hdf5ImageLoader(
			new File( mergedHdfFilename ), mergedPartitions, seq, false );
	seq.setImgLoader( newLoader );
	WriteSequenceToHdf5.writeHdf5PartitionLinkFile( spimData.getSequenceDescription(), perSetupExportMipmapInfo );

	return true;
}