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Java implementation of the SciJava Ops matching engine.
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/*-
 * #%L
 * Java implementation of the SciJava Ops matching engine.
 * %%
 * Copyright (C) 2016 - 2024 SciJava developers.
 * %%
 * 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 org.scijava.ops.engine.math;

import java.util.Arrays;

import org.scijava.function.Functions;
import org.scijava.ops.spi.Op;
import org.scijava.ops.spi.OpClass;

public class Normalize {

	public static final String NAMES = "math.minmax";

	@OpClass(names = NAMES)
	public static class MathMinMaxNormalizeFunction implements
		Functions.Arity3, Op
	{

		/**
		 * TODO
		 *
		 * @param t
		 * @param newMin
		 * @param newMax
		 */
		@Override
		public double[] apply(double[] t, Double newMin, Double newMax) {
			if (newMax == null) {
				newMax = 1.0;
			}
			if (newMin >= newMax) {
				throw new IllegalStateException("Min must be smaller than max.");
			}

			double min = Arrays.stream(t).min().getAsDouble();
			double max = Arrays.stream(t).max().getAsDouble();
			double nMin = newMin;
			double nMax = newMax;

			return Arrays.stream(t).map(d -> norm(d, min, max, nMin, nMax)).toArray();
		}

		private double norm(double d, double dataMin, double dataMax, double newMin,
			double newMax)
		{
			return newMin + (((d - dataMin) * (newMax - newMin)) / (dataMax -
				dataMin));
		}
	}

}