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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.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);
}
}
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