/*
* 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.normalize;
import com.heatonresearch.aifh.AIFH;
import com.heatonresearch.aifh.AIFHError;
import com.heatonresearch.aifh.distance.CalculateDistance;
import com.heatonresearch.aifh.distance.EuclideanDistance;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.junit.runners.JUnit4;
import static org.junit.Assert.assertEquals;
/**
* Test equilateral.
*/
@RunWith(JUnit4.class)
public class TestEquilateral {
@Test(expected = AIFHError.class)
public void testTooFew() {
new Equilateral(2, -1, 1);
}
@Test
public void testEncode() {
final Equilateral eq = new Equilateral(3, -1, 1);
final double[] d = eq.encode(1);
assertEquals(0.8660254037844386, d[0], AIFH.DEFAULT_PRECISION);
assertEquals(-0.5, d[1], AIFH.DEFAULT_PRECISION);
}
@Test
public void testDecode() {
final Equilateral eq = new Equilateral(3, -1, 1);
final double[] d0 = {0.866, 0.5};
final double[] d1 = {-0.866, 0.5};
final double[] d2 = {0, -1};
assertEquals(2, eq.decode(d0));
assertEquals(2, eq.decode(d1));
assertEquals(0, eq.decode(d2));
}
@Test(expected = AIFHError.class)
public void testError() {
final Equilateral eq = new Equilateral(3, -1, 1);
eq.encode(10);
}
/**
* The idea of equalateral encoding is that every class is equal distant from the others.
* This makes sure that is true.
*/
@Test
public void testAllEqual() {
final Equilateral eq = new Equilateral(10, -1, 1);
final CalculateDistance dc = new EuclideanDistance();
double compareDist = 0;
for (int x = 0; x < 10; x++) {
double[] baseClass = eq.encode(x);
for (int y = 0; y < 10; y++) {
if (x != y) {
double[] otherClass = eq.encode(y);
double dist = dc.calculate(baseClass, otherClass);
if (compareDist < AIFH.DEFAULT_PRECISION) {
compareDist = dist;
} else {
assertEquals(compareDist, dist, AIFH.DEFAULT_PRECISION);
}
}
}
}
}
}