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.math3.ml.neuralnet.sofm; 019 020import org.apache.commons.math3.ml.neuralnet.sofm.util.ExponentialDecayFunction; 021import org.apache.commons.math3.ml.neuralnet.sofm.util.QuasiSigmoidDecayFunction; 022import org.apache.commons.math3.exception.OutOfRangeException; 023 024/** 025 * Factory for creating instances of {@link LearningFactorFunction}. 026 * 027 * @since 3.3 028 */ 029public class LearningFactorFunctionFactory { 030 /** Class contains only static methods. */ 031 private LearningFactorFunctionFactory() {} 032 033 /** 034 * Creates an exponential decay {@link LearningFactorFunction function}. 035 * It will compute <code>a e<sup>-x / b</sup></code>, 036 * where {@code x} is the (integer) independent variable and 037 * <ul> 038 * <li><code>a = initValue</code> 039 * <li><code>b = -numCall / ln(valueAtNumCall / initValue)</code> 040 * </ul> 041 * 042 * @param initValue Initial value, i.e. 043 * {@link LearningFactorFunction#value(long) value(0)}. 044 * @param valueAtNumCall Value of the function at {@code numCall}. 045 * @param numCall Argument for which the function returns 046 * {@code valueAtNumCall}. 047 * @return the learning factor function. 048 * @throws org.apache.commons.math3.exception.OutOfRangeException 049 * if {@code initValue <= 0} or {@code initValue > 1}. 050 * @throws org.apache.commons.math3.exception.NotStrictlyPositiveException 051 * if {@code valueAtNumCall <= 0}. 052 * @throws org.apache.commons.math3.exception.NumberIsTooLargeException 053 * if {@code valueAtNumCall >= initValue}. 054 * @throws org.apache.commons.math3.exception.NotStrictlyPositiveException 055 * if {@code numCall <= 0}. 056 */ 057 public static LearningFactorFunction exponentialDecay(final double initValue, 058 final double valueAtNumCall, 059 final long numCall) { 060 if (initValue <= 0 || 061 initValue > 1) { 062 throw new OutOfRangeException(initValue, 0, 1); 063 } 064 065 return new LearningFactorFunction() { 066 /** DecayFunction. */ 067 private final ExponentialDecayFunction decay 068 = new ExponentialDecayFunction(initValue, valueAtNumCall, numCall); 069 070 /** {@inheritDoc} */ 071 public double value(long n) { 072 return decay.value(n); 073 } 074 }; 075 } 076 077 /** 078 * Creates an sigmoid-like {@code LearningFactorFunction function}. 079 * The function {@code f} will have the following properties: 080 * <ul> 081 * <li>{@code f(0) = initValue}</li> 082 * <li>{@code numCall} is the inflexion point</li> 083 * <li>{@code slope = f'(numCall)}</li> 084 * </ul> 085 * 086 * @param initValue Initial value, i.e. 087 * {@link LearningFactorFunction#value(long) value(0)}. 088 * @param slope Value of the function derivative at {@code numCall}. 089 * @param numCall Inflexion point. 090 * @return the learning factor function. 091 * @throws org.apache.commons.math3.exception.OutOfRangeException 092 * if {@code initValue <= 0} or {@code initValue > 1}. 093 * @throws org.apache.commons.math3.exception.NumberIsTooLargeException 094 * if {@code slope >= 0}. 095 * @throws org.apache.commons.math3.exception.NotStrictlyPositiveException 096 * if {@code numCall <= 0}. 097 */ 098 public static LearningFactorFunction quasiSigmoidDecay(final double initValue, 099 final double slope, 100 final long numCall) { 101 if (initValue <= 0 || 102 initValue > 1) { 103 throw new OutOfRangeException(initValue, 0, 1); 104 } 105 106 return new LearningFactorFunction() { 107 /** DecayFunction. */ 108 private final QuasiSigmoidDecayFunction decay 109 = new QuasiSigmoidDecayFunction(initValue, slope, numCall); 110 111 /** {@inheritDoc} */ 112 public double value(long n) { 113 return decay.value(n); 114 } 115 }; 116 } 117}