/*
* Artificial Intelligence for Humans
* Volume 1: Fundamental Algorithms
* Java Version
* http://www.aifh.org
* http://www.jeffheaton.com
*
* Code repository:
* https://github.com/jeffheaton/aifh
* Copyright 2013 by Jeff Heaton
*
* Licensed 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.
*
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package com.heatonresearch.aifh.discrete;
import com.heatonresearch.aifh.AIFH;
import com.heatonresearch.aifh.distance.CalculateDistance;
import com.heatonresearch.aifh.distance.EuclideanDistance;
import org.junit.Test;
import static org.junit.Assert.assertEquals;
/**
* Test the discrete anneal subclass.
*/
public class TestDiscreteAnneal {
@Test
public void testStatus() {
final DiscreteAnnealSubclass anneal = new DiscreteAnnealSubclass(1000, 4000, 1);
assertEquals("k=0,kMax=1000,t=0.0,prob=0.0", anneal.getStatus());
}
@Test
public void testGeneral() {
final DiscreteAnnealSubclass anneal = new DiscreteAnnealSubclass(1000, 4000, 1);
anneal.setCycles(100);
assertEquals(100, anneal.getCycles());
assertEquals(0, anneal.getK());
assertEquals(false, anneal.done());
}
@Test
public void testCoolingSchedule() {
final DiscreteAnnealSubclass anneal = new DiscreteAnnealSubclass(1000, 400, 1);
assertEquals(400, anneal.coolingSchedule(), AIFH.DEFAULT_PRECISION);
anneal.iteration();
assertEquals(397.61057939346017, anneal.coolingSchedule(), AIFH.DEFAULT_PRECISION);
}
@Test
public void testProbability() {
final DiscreteAnnealSubclass anneal = new DiscreteAnnealSubclass(1000, 400, 1);
assertEquals(0.9753099120283326, anneal.calcProbability(10, 20, anneal.coolingSchedule()), AIFH.DEFAULT_PRECISION);
anneal.iteration();
assertEquals(0.9751633961486054, anneal.calcProbability(10, 20, anneal.coolingSchedule()), AIFH.DEFAULT_PRECISION);
}
@Test
public void testRun() {
final DiscreteAnnealSubclass anneal = new DiscreteAnnealSubclass(1000, 400, 1);
while (!anneal.done()) {
anneal.iteration();
}
final CalculateDistance dist = new EuclideanDistance();
assertEquals(1000, anneal.getK());
assertEquals(0, dist.calculate(anneal.getBest(), DiscreteAnnealSubclass.IDEAL), AIFH.DEFAULT_PRECISION);
assertEquals(0, anneal.getBestScore(), AIFH.DEFAULT_PRECISION);
}
}