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WIP: Port threshold
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‎src/main/java/net/imagej/ops/filter/AbstractCenterAwareNeighborhoodBasedFilter.java‎

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/*
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* #%L
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* ImageJ software for multidimensional image processing and analysis.
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* %%
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* Copyright (C) 2014 - 2018 ImageJ developers.
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* %%
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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* 1. Redistributions of source code must retain the above copyright notice,
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* this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
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* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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* #L%
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*/
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package net.imagej.ops.filter;
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import net.imglib2.Cursor;
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import net.imglib2.IterableInterval;
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import net.imglib2.RandomAccess;
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import net.imglib2.RandomAccessibleInterval;
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import net.imglib2.algorithm.neighborhood.Shape;
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import net.imglib2.outofbounds.OutOfBoundsBorderFactory;
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import net.imglib2.outofbounds.OutOfBoundsFactory;
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import net.imglib2.view.Views;
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import org.scijava.ops.core.computer.BiComputer;
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import org.scijava.param.Mutable;
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public abstract class AbstractCenterAwareNeighborhoodBasedFilter<I, O> {
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private static final OutOfBoundsFactory<?, ?> DEFAULT_OUT_OF_BOUNDS_FACTORY =
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new OutOfBoundsBorderFactory<>();
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@SuppressWarnings("unchecked")
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public static <I> OutOfBoundsFactory<I, RandomAccessibleInterval<I>>
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defaultOutOfBoundsFactory()
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{
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return (OutOfBoundsFactory<I, RandomAccessibleInterval<I>>) DEFAULT_OUT_OF_BOUNDS_FACTORY;
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}
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protected void computeInternal(final RandomAccessibleInterval<I> input,
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final Shape inputNeighborhoodShape,
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OutOfBoundsFactory<I, RandomAccessibleInterval<I>> outOfBoundsFactory,
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final BiComputer<Iterable<I>, I, O> filterOp,
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@Mutable final IterableInterval<O> output)
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{
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if (outOfBoundsFactory == null) outOfBoundsFactory =
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defaultOutOfBoundsFactory();
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final RandomAccessibleInterval<I> inputCenterPixels = Views.interval(Views
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.extend(input, outOfBoundsFactory), input);
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final IterableInterval<? extends Iterable<I>> inputNeighborhoods =
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inputNeighborhoodShape.neighborhoodsSafe(inputCenterPixels);
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map(inputNeighborhoods, inputCenterPixels, filterOp, output);
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}
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private static <I1, I2, O> void map(
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final IterableInterval<? extends I1> inputNeighborhoods,
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final RandomAccessibleInterval<I2> inputCenterPixels,
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final BiComputer<I1, I2, O> filterOp, final IterableInterval<O> output)
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{
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// TODO: This used to be done via a net.imagej.ops.Ops.Map meta op. We may
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// want to revert to that approach if this proves to be too inflexible.
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// (Parallelization would be useful, for instance.)
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final Cursor<? extends I1> neighborhoodCursor = inputNeighborhoods
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.localizingCursor();
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final RandomAccess<I2> centerPixelsAccess = inputCenterPixels
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.randomAccess();
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final Cursor<O> outputCursor = output.cursor();
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while (neighborhoodCursor.hasNext()) {
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neighborhoodCursor.fwd();
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centerPixelsAccess.setPosition(neighborhoodCursor);
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filterOp.compute(neighborhoodCursor.get(), centerPixelsAccess.get(),
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outputCursor.next());
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}
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}
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}

‎src/main/java/net/imagej/ops/threshold/AbstractApplyThresholdImg.java‎

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/*
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* #%L
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* ImageJ software for multidimensional image processing and analysis.
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* %%
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* Copyright (C) 2014 - 2016 Board of Regents of the University of
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* Wisconsin-Madison and University of Konstanz.
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* %%
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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* 1. Redistributions of source code must retain the above copyright notice,
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* this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
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* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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* #L%
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*/
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package net.imagej.ops.threshold;
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import java.util.function.Function;
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import net.imglib2.histogram.Histogram1d;
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import net.imglib2.type.numeric.RealType;
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import org.scijava.ops.OpDependency;
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import org.scijava.ops.core.computer.Computer;
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/**
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* @author Curtis Rueden
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* @author Christian Dietz (University of Konstanz)
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*/
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public abstract class AbstractApplyThresholdImg<T extends RealType<T>> extends
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AbstractApplyThresholdIterable<T>
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{
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@OpDependency(name = "image.histogram")
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private Function<Iterable<T>, Histogram1d<T>> createHistogramOp;
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@Override
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protected T computeThreshold(final Iterable<T> input) {
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final Histogram1d<T> inputHistogram = createHistogramOp.apply(input);
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final T threshold = input.iterator().next().createVariable();
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final Computer<Histogram1d<T>, T> computeThresholdOp =
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getComputeThresholdOp();
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computeThresholdOp.compute(inputHistogram, threshold);
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return threshold;
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}
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protected abstract Computer<Histogram1d<T>, T> getComputeThresholdOp();
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}

‎src/main/java/net/imagej/ops/threshold/AbstractApplyThresholdIterable.java‎

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/*
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* #%L
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* ImageJ software for multidimensional image processing and analysis.
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* %%
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* Copyright (C) 2014 - 2018 ImageJ developers.
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* %%
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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* 1. Redistributions of source code must retain the above copyright notice,
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* this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
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* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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* #L%
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*/
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package net.imagej.ops.threshold;
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import net.imglib2.type.logic.BitType;
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import org.scijava.ops.OpDependency;
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import org.scijava.ops.core.computer.BiComputer;
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import org.scijava.ops.core.computer.Computer;
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import org.scijava.param.Mutable;
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import org.scijava.param.Parameter;
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import org.scijava.struct.ItemIO;
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/**
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* @author Curtis Rueden
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* @author Christian Dietz (University of Konstanz)
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*/
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@Parameter(key = "input")
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@Parameter(key = "output", type = ItemIO.BOTH)
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public abstract class AbstractApplyThresholdIterable<T> implements
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Computer<Iterable<T>, Iterable<BitType>>
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{
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@OpDependency(name = "threshold.apply")
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private BiComputer<Iterable<T>, T, Iterable<BitType>> applyThresholdOp;
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@Override
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public void compute(final Iterable<T> input,
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@Mutable final Iterable<BitType> output)
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{
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applyThresholdOp.compute(input, computeThreshold(input), output);
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}
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protected abstract T computeThreshold(Iterable<T> input);
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}

‎src/main/java/net/imagej/ops/threshold/AbstractComputeThresholdHistogram.java‎

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* %%
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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*
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* 1. Redistributions of source code must retain the above copyright notice,
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* this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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public abstract class AbstractComputeThresholdHistogram<T extends RealType<T>>
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implements Computer<Histogram1d<T>, T>
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{
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@Override
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public void compute(final Histogram1d<T> input, final T output) {
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final long binPos = computeBin(input);
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// convert bin number to corresponding gray level
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input.getCenterValue(binPos, output);
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}
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abstract protected long computeBin(final Histogram1d<T> input);
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protected abstract long computeBin(final Histogram1d<T> input);
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}

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