001/*
002 * Licensed to the Apache Software Foundation (ASF) under one or more
003 * contributor license agreements.  See the NOTICE file distributed with
004 * this work for additional information regarding copyright ownership.
005 * The ASF licenses this file to You under the Apache License, Version 2.0
006 * (the "License"); you may not use this file except in compliance with
007 * the License.  You may obtain a copy of the License at
008 *
009 *      http://www.apache.org/licenses/LICENSE-2.0
010 *
011 * Unless required by applicable law or agreed to in writing, software
012 * distributed under the License is distributed on an "AS IS" BASIS,
013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014 * See the License for the specific language governing permissions and
015 * limitations under the License.
016 */
017
018package org.apache.commons.math4.ml.neuralnet.sofm.util;
019
020import org.apache.commons.math4.analysis.function.Logistic;
021import org.apache.commons.math4.exception.NotStrictlyPositiveException;
022import org.apache.commons.math4.exception.NumberIsTooLargeException;
023
024/**
025 * Decay function whose shape is similar to a sigmoid.
026 * <br>
027 * Class is immutable.
028 *
029 * @since 3.3
030 */
031public class QuasiSigmoidDecayFunction {
032    /** Sigmoid. */
033    private final Logistic sigmoid;
034    /** See {@link #value(long)}. */
035    private final double scale;
036
037    /**
038     * Creates an instance.
039     * The function {@code f} will have the following properties:
040     * <ul>
041     *  <li>{@code f(0) = initValue}</li>
042     *  <li>{@code numCall} is the inflexion point</li>
043     *  <li>{@code slope = f'(numCall)}</li>
044     * </ul>
045     *
046     * @param initValue Initial value, i.e. {@link #value(long) value(0)}.
047     * @param slope Value of the function derivative at {@code numCall}.
048     * @param numCall Inflexion point.
049     * @throws NotStrictlyPositiveException if {@code initValue <= 0}.
050     * @throws NumberIsTooLargeException if {@code slope >= 0}.
051     * @throws NotStrictlyPositiveException if {@code numCall <= 0}.
052     */
053    public QuasiSigmoidDecayFunction(double initValue,
054                                     double slope,
055                                     long numCall) {
056        if (initValue <= 0) {
057            throw new NotStrictlyPositiveException(initValue);
058        }
059        if (slope >= 0) {
060            throw new NumberIsTooLargeException(slope, 0, false);
061        }
062        if (numCall <= 1) {
063            throw new NotStrictlyPositiveException(numCall);
064        }
065
066        final double k = initValue;
067        final double m = numCall;
068        final double b = 4 * slope / initValue;
069        final double q = 1;
070        final double a = 0;
071        final double n = 1;
072        sigmoid = new Logistic(k, m, b, q, a, n);
073
074        final double y0 = sigmoid.value(0);
075        scale = k / y0;
076    }
077
078    /**
079     * Computes the value of the learning factor.
080     *
081     * @param numCall Current step of the training task.
082     * @return the value of the function at {@code numCall}.
083     */
084    public double value(long numCall) {
085        return scale * sigmoid.value(numCall);
086    }
087}