@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());
}
}
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()");
}
}
/**
* TODO
*
* @param cumulativeMinCutoff
* @param cumulativeMaxCutoff
* @param state
* @param setupAssignments
*/
public static void initBrightness(
final double cumulativeMinCutoff,
final double cumulativeMaxCutoff,
final ViewerState state,
final SetupAssignments setupAssignments) {
final Source<?> source = state.getSources().get(state.getCurrentSource()).getSpimSource();
final int timepoint = state.getCurrentTimepoint();
if (!source.isPresent(timepoint)) return;
if (!UnsignedShortType.class.isInstance(source.getType())) return;
@SuppressWarnings("unchecked")
final RandomAccessibleInterval<UnsignedShortType> img =
(RandomAccessibleInterval<UnsignedShortType>)
source.getSource(timepoint, source.getNumMipmapLevels() - 1);
final long z = (img.min(2) + img.max(2) + 1) / 2;
final int numBins = 6535;
final Histogram1d<UnsignedShortType> histogram =
new Histogram1d<UnsignedShortType>(
Views.iterable(Views.hyperSlice(img, 2, z)),
new Real1dBinMapper<UnsignedShortType>(0, 65535, numBins, false));
final DiscreteFrequencyDistribution dfd = histogram.dfd();
final long[] bin = new long[] {0};
double cumulative = 0;
int i = 0;
for (; i < numBins && cumulative < cumulativeMinCutoff; ++i) {
bin[0] = i;
cumulative += dfd.relativeFrequency(bin);
}
final int min = i * 65535 / numBins;
for (; i < numBins && cumulative < cumulativeMaxCutoff; ++i) {
bin[0] = i;
cumulative += dfd.relativeFrequency(bin);
}
final int max = i * 65535 / numBins;
final MinMaxGroup minmax = setupAssignments.getMinMaxGroups().get(0);
minmax.getMinBoundedValue().setCurrentValue(min);
minmax.getMaxBoundedValue().setCurrentValue(max);
}