/*
 * #%L
 * Image processing operations for SciJava Ops.
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package org.scijava.ops.image.transform.slice.slice;

import net.imglib2.Cursor;
import net.imglib2.RandomAccessibleInterval;

import org.scijava.function.Computers;
import org.scijava.ops.spi.Nullable;

/**
 * {@code transform.slice} implementation for {@link RandomAccessibleInterval}
 * input and {@link RandomAccessibleInterval} output.
 * <p>
 * The input {@link RandomAccessibleInterval} will be wrapped into a
 * {@link SlicesII}, so that the given Op can compute on a per-slice base.
 * </p>
 *
 * @author Christian Dietz (University of Konstanz)
 * @author Martin Horn (University of Konstanz)
 * @implNote op names='transform.slice', priority='10000.'
 */
public class SliceRAI2RAI<I, O> implements
	Computers.Arity4<RandomAccessibleInterval<I>, Computers.Arity1<RandomAccessibleInterval<I>, RandomAccessibleInterval<O>>, int[], Boolean, RandomAccessibleInterval<O>>
{

	/**
	 * TODO
	 *
	 * @param input
	 * @param op
	 * @param axisIndices
	 * @param dropSingleDimensions
	 * @param output
	 */
	@Override
	public void compute( //
		final RandomAccessibleInterval<I> input, //
		final Computers.Arity1<RandomAccessibleInterval<I>, RandomAccessibleInterval<O>> op, //
		final int[] axisIndices, //
		@Nullable Boolean dropSingleDimensions, //
		final RandomAccessibleInterval<O> output //
	) {
		if (dropSingleDimensions == null) {
			dropSingleDimensions = true;
		}

        var slicedInput = new SlicesII<I>(input, axisIndices,
			dropSingleDimensions);
        var slicedOutput = new SlicesII<O>(output, axisIndices,
			dropSingleDimensions);

		// TODO: can we make this more efficient?
        var slicedInputCursor = slicedInput
			.cursor();
        var slicedOutputCursor = slicedOutput
			.cursor();
		while (slicedInputCursor.hasNext()) {
			op.compute(slicedInputCursor.next(), slicedOutputCursor.next());
		}
	}

}
