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/*
* 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;
import org.apache.commons.math3.ml.neuralnet.sofm.util.ExponentialDecayFunction;
import org.apache.commons.math3.ml.neuralnet.sofm.util.QuasiSigmoidDecayFunction;
import org.apache.commons.math3.exception.OutOfRangeException;
/**
* Factory for creating instances of {@link LearningFactorFunction}.
*
* @since 3.3
*/
public class LearningFactorFunctionFactory {
/** Class contains only static methods. */
private LearningFactorFunctionFactory() {}
/**
* Creates an exponential decay {@link LearningFactorFunction function}.
* It will compute <code>a e<sup>-x / b</sup></code>,
* where {@code x} is the (integer) independent variable and
* <ul>
* <li><code>a = initValue</code>
* <li><code>b = -numCall / ln(valueAtNumCall / initValue)</code>
* </ul>
*
* @param initValue Initial value, i.e.
* {@link LearningFactorFunction#value(long) value(0)}.
* @param valueAtNumCall Value of the function at {@code numCall}.
* @param numCall Argument for which the function returns
* {@code valueAtNumCall}.
* @return the learning factor function.
* @throws org.apache.commons.math3.exception.OutOfRangeException
* if {@code initValue <= 0} or {@code initValue > 1}.
* @throws org.apache.commons.math3.exception.NotStrictlyPositiveException
* if {@code valueAtNumCall <= 0}.
* @throws org.apache.commons.math3.exception.NumberIsTooLargeException
* if {@code valueAtNumCall >= initValue}.
* @throws org.apache.commons.math3.exception.NotStrictlyPositiveException
* if {@code numCall <= 0}.
*/
public static LearningFactorFunction exponentialDecay(final double initValue,
final double valueAtNumCall,
final long numCall) {
if (initValue <= 0 ||
initValue > 1) {
throw new OutOfRangeException(initValue, 0, 1);
}
return new LearningFactorFunction() {
/** DecayFunction. */
private final ExponentialDecayFunction decay
= new ExponentialDecayFunction(initValue, valueAtNumCall, numCall);
/** {@inheritDoc} */
public double value(long n) {
return decay.value(n);
}
};
}
/**
* Creates an sigmoid-like {@code LearningFactorFunction function}.
* The function {@code f} will have the following properties:
* <ul>
* <li>{@code f(0) = initValue}</li>
* <li>{@code numCall} is the inflexion point</li>
* <li>{@code slope = f'(numCall)}</li>
* </ul>
*
* @param initValue Initial value, i.e.
* {@link LearningFactorFunction#value(long) value(0)}.
* @param slope Value of the function derivative at {@code numCall}.
* @param numCall Inflexion point.
* @return the learning factor function.
* @throws org.apache.commons.math3.exception.OutOfRangeException
* if {@code initValue <= 0} or {@code initValue > 1}.
* @throws org.apache.commons.math3.exception.NumberIsTooLargeException
* if {@code slope >= 0}.
* @throws org.apache.commons.math3.exception.NotStrictlyPositiveException
* if {@code numCall <= 0}.
*/
public static LearningFactorFunction quasiSigmoidDecay(final double initValue,
final double slope,
final long numCall) {
if (initValue <= 0 ||
initValue > 1) {
throw new OutOfRangeException(initValue, 0, 1);
}
return new LearningFactorFunction() {
/** DecayFunction. */
private final QuasiSigmoidDecayFunction decay
= new QuasiSigmoidDecayFunction(initValue, slope, numCall);
/** {@inheritDoc} */
public double value(long n) {
return decay.value(n);
}
};
}
}
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