/*
 * #%L
 * ImageJ software for multidimensional image processing and analysis.
 * %%
 * Copyright (C) 2014 - 2016 Board of Regents of the University of
 * Wisconsin-Madison, University of Konstanz and Brian Northan.
 * %%
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 * 
 * 1. Redistributions of source code must retain the above copyright notice,
 *    this list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 *    this list of conditions and the following disclaimer in the documentation
 *    and/or other materials provided with the distribution.
 * 
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
 * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
 * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
 * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
 * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
 * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
 * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
 * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 * POSSIBILITY OF SUCH DAMAGE.
 * #L%
 */

package net.imagej.ops.threshold.localMean;

import net.imagej.ops.Ops;
import net.imagej.ops.special.computer.AbstractUnaryComputerOp;
import net.imglib2.RandomAccessibleInterval;
import net.imglib2.algorithm.neighborhood.Shape;
import net.imglib2.outofbounds.OutOfBoundsFactory;
import net.imglib2.type.logic.BitType;
import net.imglib2.type.numeric.RealType;
import net.imglib2.util.ValuePair;
import org.scijava.Priority;
import org.scijava.plugin.Parameter;
import org.scijava.plugin.Plugin;

/**
 * LocalThresholdMethod that uses the mean and operates directly of RAIs.
 * 
 * @author Jonathan Hale (University of Konstanz)
 * @author Martin Horn (University of Konstanz)
 * @author Stefan Helfrich (University of Konstanz)
 */
@Plugin(type = Ops.Threshold.LocalMean.class, priority = Priority.LOW_PRIORITY)
public class LocalMeanRAI<T extends RealType<T>>
	extends AbstractUnaryComputerOp<RandomAccessibleInterval<T>, RandomAccessibleInterval<BitType>>
	implements Ops.Threshold.LocalMean
{
	
	@Parameter
	private Shape shape;

	@Parameter(required = false)
	private OutOfBoundsFactory<T, RandomAccessibleInterval<T>> outOfBounds;
	
	@Parameter
	private double c;

	private LocalMean<T> localMeanOp;
	
	@SuppressWarnings({ "unchecked" })
	@Override
	public void initialize()
	{
		localMeanOp = ops().op(LocalMean.class, BitType.class, new ValuePair<T, RandomAccessibleInterval<T>>(null, in()), c);
	}

	@Override
	public void compute1(final RandomAccessibleInterval<T> input, final RandomAccessibleInterval<BitType> output)
	{	
		ops().threshold().apply(
			output,
			input,
			localMeanOp,
			shape,
			outOfBounds);
	}

}

/*
 * #%L
 * ImageJ software for multidimensional image processing and analysis.
 * %%
 * Copyright (C) 2014 - 2016 Board of Regents of the University of
 * Wisconsin-Madison, University of Konstanz and Brian Northan.
 * %%
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 * 
 * 1. Redistributions of source code must retain the above copyright notice,
 *    this list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 *    this list of conditions and the following disclaimer in the documentation
 *    and/or other materials provided with the distribution.
 * 
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
 * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
 * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
 * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
 * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
 * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
 * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
 * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 * POSSIBILITY OF SUCH DAMAGE.
 * #L%
 */

package net.imagej.ops.threshold.localMean;

import net.imagej.ops.Ops;
import net.imagej.ops.special.computer.AbstractUnaryComputerOp;
import net.imglib2.RandomAccessibleInterval;
import net.imglib2.algorithm.neighborhood.Shape;
import net.imglib2.outofbounds.OutOfBoundsFactory;
import net.imglib2.type.logic.BitType;
import net.imglib2.type.numeric.RealType;
import net.imglib2.util.ValuePair;

import org.scijava.Priority;
import org.scijava.plugin.Parameter;
import org.scijava.plugin.Plugin;

/**
 * LocalThresholdMethod that uses the mean and operates directly of RAIs.
 *
 * @author Jonathan Hale (University of Konstanz)
 * @author Martin Horn (University of Konstanz)
 * @author Stefan Helfrich (University of Konstanz)
 */
@Plugin(type = Ops.Threshold.LocalMean.class, priority = Priority.LOW_PRIORITY)
public class LocalMeanRAI<T extends RealType<T>> extends
		AbstractUnaryComputerOp<RandomAccessibleInterval<T>, RandomAccessibleInterval<BitType>>
		implements Ops.Threshold.LocalMean {

	@Parameter
	private Shape shape;

	@Parameter(required = false)
	private OutOfBoundsFactory<T, RandomAccessibleInterval<T>> outOfBounds;

	@Parameter
	private double c;

	private LocalMean<T> localMeanOp;

	@SuppressWarnings({ "unchecked" })
	@Override
	public void initialize() {
		localMeanOp = ops().op(LocalMean.class, BitType.class,
				new ValuePair<T, RandomAccessibleInterval<T>>(null, in()), c);
	}

	@Override
	public void compute1(final RandomAccessibleInterval<T> input,
			final RandomAccessibleInterval<BitType> output) {
		// FIXME Apply in initialize()
		ops().threshold().apply(output, input, localMeanOp, shape, outOfBounds);
	}

}

Fix code style