@Override
public RandomAccessibleInterval<V> compute(
RandomAccessibleInterval<T> input, RandomAccessibleInterval<V> output) {
setUpNeighbours(input.numDimensions());
// OutOfBounds for marker
V zeroV = output.randomAccess().get().createVariable();
zeroV.set(getVMinValue(zeroV));
OutOfBounds<V> marker =
new OutOfBoundsConstantValueFactory<V, RandomAccessibleInterval<V>>(zeroV).create(output);
Cursor<V> cur = new Cursor<V>(output);
// OutOfBounds for mask
T zeroT = input.randomAccess().get().createVariable();
zeroT.set(getTMinValue(zeroT));
OutOfBounds<T> mask =
new OutOfBoundsConstantValueFactory<T, RandomAccessibleInterval<T>>(zeroT).create(input);
scanInRasterOrder(cur, marker, mask);
scanInAntiRasterOrder(cur, marker, mask);
propagate(marker, mask, m_neighbours);
return output;
}
protected void generateHistogramData(DataContainer<T> container) {
double ch1BinWidth = getXBinWidth(container);
double ch2BinWidth = getYBinWidth(container);
// get the 2 images for the calculation of Pearson's
final RandomAccessibleInterval<T> img1 = getImageCh1(container);
final RandomAccessibleInterval<T> img2 = getImageCh2(container);
final RandomAccessibleInterval<BitType> mask = container.getMask();
// get the cursors for iterating through pixels in images
TwinCursor<T> cursor =
new TwinCursor<T>(
img1.randomAccess(), img2.randomAccess(), Views.iterable(mask).localizingCursor());
// create new image to put the scatter-plot in
final ImgFactory<LongType> scatterFactory = new ArrayImgFactory<LongType>();
plotImage = scatterFactory.create(new int[] {xBins, yBins}, new LongType());
// create access cursors
final RandomAccess<LongType> histogram2DCursor = plotImage.randomAccess();
// iterate over images
long[] pos = new long[plotImage.numDimensions()];
while (cursor.hasNext()) {
cursor.fwd();
double ch1 = cursor.getFirst().getRealDouble();
double ch2 = cursor.getSecond().getRealDouble();
/* Scale values for both channels to fit in the range.
* Moreover mirror the y value on the x axis.
*/
pos[0] = getXValue(ch1, ch1BinWidth, ch2, ch2BinWidth);
pos[1] = getYValue(ch1, ch1BinWidth, ch2, ch2BinWidth);
// set position of input/output cursor
histogram2DCursor.setPosition(pos);
// get current value at position and increment it
long count = histogram2DCursor.get().getIntegerLong();
count++;
histogram2DCursor.get().set(count);
}
xBinWidth = ch1BinWidth;
yBinWidth = ch2BinWidth;
xLabel = getLabelCh1();
yLabel = getLabelCh2();
xMin = getXMin(container);
xMax = getXMax(container);
yMin = getYMin(container);
yMax = getYMax(container);
}
@Override
public void map() {
for (int d = 2; d < position.length; ++d) min[d] = max[d] = position[d];
min[0] = target.min(0);
min[1] = target.min(1);
max[0] = target.max(0);
max[1] = target.max(1);
final FinalInterval sourceInterval = new FinalInterval(min, max);
final long cr = -target.dimension(0);
final RandomAccess<B> targetRandomAccess = target.randomAccess(target);
final RandomAccess<A> sourceRandomAccess = source.randomAccess(sourceInterval);
for (sourceRandomAccess.setPosition(min),
targetRandomAccess.setPosition(min[0], 0),
targetRandomAccess.setPosition(min[1], 1);
targetRandomAccess.getLongPosition(1) <= max[1];
sourceRandomAccess.move(cr, 0), targetRandomAccess.move(cr, 0), sourceRandomAccess.fwd(1),
targetRandomAccess.fwd(1)) {
for (;
targetRandomAccess.getLongPosition(0) <= max[0];
sourceRandomAccess.fwd(0), targetRandomAccess.fwd(0))
converter.convert(sourceRandomAccess.get(), targetRandomAccess.get());
}
}
/**
* A table of x-values, y-values and the counts is generated and returned as a string. The single
* fields in one row (X Y Count) are separated by tabs.
*
* @return A String representation of the histogram data.
*/
public String getData() {
StringBuffer sb = new StringBuffer();
double xBinWidth = 1.0 / getXBinWidth();
double yBinWidth = 1.0 / getYBinWidth();
double xMin = getXMin();
double yMin = getYMin();
// check if we have bins of size one or other ones
boolean xBinWidthIsOne = Math.abs(xBinWidth - 1.0) < 0.00001;
boolean yBinWidthIsOne = Math.abs(yBinWidth - 1.0) < 0.00001;
// configure decimal places accordingly
int xDecimalPlaces = xBinWidthIsOne ? 0 : 3;
int yDecimalPlaces = yBinWidthIsOne ? 0 : 3;
// create a cursor to access the histogram data
RandomAccess<LongType> cursor = plotImage.randomAccess();
// loop over 2D histogram
for (int i = 0; i < plotImage.dimension(0); ++i) {
for (int j = 0; j < plotImage.dimension(1); ++j) {
cursor.setPosition(i, 0);
cursor.setPosition(j, 1);
sb.append(
ResultsTable.d2s(xMin + (i * xBinWidth), xDecimalPlaces)
+ "\t"
+ ResultsTable.d2s(yMin + (j * yBinWidth), yDecimalPlaces)
+ "\t"
+ ResultsTable.d2s(cursor.get().getRealDouble(), 0)
+ "\n");
}
}
return sb.toString();
}
@SuppressWarnings({"rawtypes", "unchecked"})
public static <T extends Type<T>> ImageRenderer<T>[] createSuitableRenderer(
final RandomAccessibleInterval<T> img) {
final List<ImageRenderer> res = new ArrayList<ImageRenderer>();
if (Util.getTypeFromInterval(img) instanceof LabelingType) {
res.add(new ColorLabelingRenderer());
res.add(new BoundingBoxLabelRenderer());
res.add(new BoundingBoxRandomColorLabelRenderer());
} else {
final T type = img.randomAccess().get();
if (type instanceof RealType) {
res.add(new Real2GreyRenderer(((RealType) Util.getTypeFromInterval(img)).getMinValue()));
for (int d = 0; d < img.numDimensions(); d++) {
if ((img.dimension(d) > 1) && (img.dimension(d) < 4)) {
res.add(new Real2ColorRenderer(d));
}
}
}
}
return res.toArray(new ImageRenderer[res.size()]);
}
@Override
public RealSum call() throws Exception {
final Cursor<FloatType> psiCursor = psiIterable.localizingCursor();
psiCursor.jumpFwd(portion.getStartPosition());
final int m = iterableImgs.size();
if (compatibleIteration) {
final ArrayList<Cursor<FloatType>> cursorWeights = new ArrayList<Cursor<FloatType>>();
final ArrayList<Cursor<FloatType>> cursorImgs = new ArrayList<Cursor<FloatType>>();
for (final IterableInterval<FloatType> img : iterableImgs) {
final Cursor<FloatType> imgCursor = img.cursor();
imgCursor.jumpFwd(portion.getStartPosition());
cursorImgs.add(imgCursor);
}
for (final IterableInterval<FloatType> weight : iterableWeights) {
final Cursor<FloatType> weightCursor = weight.cursor();
weightCursor.jumpFwd(portion.getStartPosition());
cursorWeights.add(weightCursor);
}
for (int j = 0; j < portion.getLoopSize(); ++j)
compatibleLoop(psiCursor, cursorWeights, cursorImgs, realSum, m);
} else {
final ArrayList<RandomAccess<FloatType>> randomAccessWeights =
new ArrayList<RandomAccess<FloatType>>();
final ArrayList<RandomAccess<FloatType>> randomAccessImgs =
new ArrayList<RandomAccess<FloatType>>();
for (final RandomAccessibleInterval<FloatType> img : imgs)
randomAccessImgs.add(img.randomAccess());
for (final RandomAccessibleInterval<FloatType> weight : weights)
randomAccessWeights.add(weight.randomAccess());
for (int j = 0; j < portion.getLoopSize(); ++j)
incompatibleLoop(psiCursor, randomAccessWeights, randomAccessImgs, realSum, m);
}
return realSum;
}
@Override
public void compute(final RandomAccessibleInterval<T> input, final IterableInterval<V> output) {
final Cursor<V> cursor = output.localizingCursor();
final RandomAccess<T> access = input.randomAccess();
while (cursor.hasNext()) {
cursor.fwd();
for (int d = 0; d < input.numDimensions(); d++) {
if (d != dim) {
access.setPosition(cursor.getIntPosition(d - d > dim ? -1 : 0), d);
}
}
method.compute(new DimensionIterable(input.dimension(dim), access), cursor.get());
}
}
@SuppressWarnings({"rawtypes", "unchecked"})
public static <T extends Type<T>> ImageRenderer<T>[] createSuitableRenderer(
final RandomAccessibleInterval<T> img, final ImageMetadata imageMetaData) {
final List<ImageRenderer> res = new ArrayList<ImageRenderer>();
res.addAll(Arrays.asList(createSuitableRenderer(img)));
// color rendering
final T type = img.randomAccess().get();
if (type instanceof RealType) {
if ((imageMetaData != null) && (imageMetaData.getColorTableCount() > 0)) {
res.add(new Real2TableColorRenderer());
}
}
return res.toArray(new ImageRenderer[res.size()]);
}
public Cursor(final RandomAccessibleInterval<U> ra) {
m_ra = ra.randomAccess();
m_numPixel = numPixels(ra);
m_lastPos = new long[ra.numDimensions()];
for (int i = 0; i < m_lastPos.length; i++) {
m_lastPos[i] = ra.dimension(i) - 1;
}
m_breaks = new long[ra.numDimensions()];
ra.dimensions(m_breaks);
for (int i = 1; i < m_breaks.length; i++) {
m_breaks[i] *= m_breaks[i - 1];
}
setToOrigin();
}
private static void adjustForOSEM(
final HashMap<ViewId, RandomAccessibleInterval<FloatType>> weights,
final WeightType weightType,
final double osemspeedup) {
if (osemspeedup == 1.0) return;
if (weightType == WeightType.PRECOMPUTED_WEIGHTS
|| weightType == WeightType.WEIGHTS_ONLY
|| weightType == WeightType.LOAD_WEIGHTS) {
for (final RandomAccessibleInterval<FloatType> w : weights.values()) {
for (final FloatType f : Views.iterable(w))
f.set(
Math.min(
1, f.get() * (float) osemspeedup)); // individual contribution never higher than 1
}
} else if (weightType == WeightType.NO_WEIGHTS) {
for (final RandomAccessibleInterval<FloatType> w : weights.values()) {
final RandomAccess<FloatType> r = w.randomAccess();
final long[] min = new long[w.numDimensions()];
w.min(min);
r.setPosition(min);
r.get()
.set(
Math.min(
1,
r.get().get()
* (float) osemspeedup)); // individual contribution never higher than 1
}
} else if (weightType == WeightType.VIRTUAL_WEIGHTS) {
for (final RandomAccessibleInterval<FloatType> w : weights.values())
((NormalizingRandomAccessibleInterval<FloatType>) w).setOSEMspeedup(osemspeedup);
} else {
throw new RuntimeException(
"Weight Type: "
+ weightType.name()
+ " not supported in ProcessForDeconvolution.adjustForOSEM()");
}
}
/** Compute the inverse Hessian matrix from the the steepest descent images. */
public static <T extends RealType<T>> double[][] computeInverseHessian(
final RandomAccessibleInterval<T> descent) {
final int n = descent.numDimensions() - 1;
final int numParameters = (int) descent.dimension(n);
final long[] dim = new long[n + 1];
descent.dimensions(dim);
dim[n] = 1;
final LocalizingIntervalIterator pos = new LocalizingIntervalIterator(dim);
final RandomAccess<T> r = descent.randomAccess();
final double[] deriv = new double[numParameters];
final double[][] H = new double[numParameters][numParameters];
while (pos.hasNext()) {
pos.fwd();
r.setPosition(pos);
for (int p = 0; p < numParameters; ++p) {
deriv[p] = r.get().getRealDouble();
r.fwd(n);
}
for (int i = 0; i < numParameters; ++i)
for (int j = 0; j < numParameters; ++j) H[i][j] += deriv[i] * deriv[j];
}
return new Matrix(H).inverse().getArray();
}
/**
* TODO
*
* @param r The segmentation image.
* @param op0 Source intensity image.
* @param op1 Start position.
*/
public final void compute(
RandomAccessibleInterval<T> op0, final long[] op1, final RandomAccessibleInterval<T> r) {
final RandomAccess<T> rc = r.randomAccess();
final RandomAccess<T> op0c = op0.randomAccess();
op0c.setPosition(op1);
final T floodVal = op0c.get().copy();
final LinkedList<long[]> q = new LinkedList<long[]>();
q.addFirst(op1.clone());
long[] pos, nextPos;
long[] perm = new long[r.numDimensions()];
while (!q.isEmpty()) {
pos = q.removeLast();
rc.setPosition(pos);
if (rc.get().compareTo(floodVal) == 0) {
continue;
}
op0c.setPosition(pos);
if (op0c.get().compareTo(floodVal) == 0) {
// set new label
rc.get().set(floodVal);
switch (m_type) {
case EIGHT_CONNECTED:
Arrays.fill(perm, -1);
int i = r.numDimensions() - 1;
boolean add;
while (i > -1) {
nextPos = pos.clone();
add = true;
// Modify position
for (int j = 0; j < r.numDimensions(); j++) {
nextPos[j] += perm[j];
// Check boundaries
if (nextPos[j] < 0 || nextPos[j] >= r.dimension(j)) {
add = false;
break;
}
}
if (add) {
q.addFirst(nextPos);
}
// Calculate next permutation
for (i = perm.length - 1; i > -1; i--) {
if (perm[i] < 1) {
perm[i]++;
for (int j = i + 1; j < perm.length; j++) {
perm[j] = -1;
}
break;
}
}
}
break;
case FOUR_CONNECTED:
default:
for (int j = 0; j < r.numDimensions(); j++) {
if (pos[j] + 1 < r.dimension(j)) {
nextPos = pos.clone();
nextPos[j]++;
q.addFirst(nextPos);
}
if (pos[j] - 1 >= 0) {
nextPos = pos.clone();
nextPos[j]--;
q.addFirst(nextPos);
}
}
break;
}
}
}
}
