/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.commons.math3.ml.neuralnet.sofm.util; import org.apache.commons.math3.exception.NotStrictlyPositiveException; import org.apache.commons.math3.exception.NumberIsTooLargeException; import org.apache.commons.math3.util.FastMath; /** * Exponential decay function: <code>a e<sup>-x / b</sup></code>, * where {@code x} is the (integer) independent variable. * <br/> * Class is immutable. * * @since 3.3 */ public class ExponentialDecayFunction { /** Factor {@code a}. */ private final double a; /** Factor {@code 1 / b}. */ private final double oneOverB; /** * Creates an instance. It will be such that * <ul> * <li>{@code a = initValue}</li> * <li>{@code b = -numCall / ln(valueAtNumCall / initValue)}</li> * </ul> * * @param initValue Initial value, i.e. {@link #value(long) value(0)}. * @param valueAtNumCall Value of the function at {@code numCall}. * @param numCall Argument for which the function returns * {@code valueAtNumCall}. * @throws NotStrictlyPositiveException if {@code initValue <= 0}. * @throws NotStrictlyPositiveException if {@code valueAtNumCall <= 0}. * @throws NumberIsTooLargeException if {@code valueAtNumCall >= initValue}. * @throws NotStrictlyPositiveException if {@code numCall <= 0}. */ public ExponentialDecayFunction(double initValue, double valueAtNumCall, long numCall) { if (initValue <= 0) { throw new NotStrictlyPositiveException(initValue); } if (valueAtNumCall <= 0) { throw new NotStrictlyPositiveException(valueAtNumCall); } if (valueAtNumCall >= initValue) { throw new NumberIsTooLargeException(valueAtNumCall, initValue, false); } if (numCall <= 0) { throw new NotStrictlyPositiveException(numCall); } a = initValue; oneOverB = -FastMath.log(valueAtNumCall / initValue) / numCall; } /** * Computes <code>a e<sup>-numCall / b</sup></code>. * * @param numCall Current step of the training task. * @return the value of the function at {@code numCall}. */ public double value(long numCall) { return a * FastMath.exp(-numCall * oneOverB); } }