Album.java

// Album.java
// From Classic Computer Science Problems in Java Chapter 6
// Copyright 2020 David Kopec
//
// 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.

package chapter6;

import java.util.ArrayList;
import java.util.List;

public class Album extends DataPoint {

	private String name;
	private int year;

	public Album(String name, int year, double length, double tracks) {
		super(List.of(length, tracks));
		this.name = name;
		this.year = year;
	}

	@Override
	public String toString() {
		return "(" + name + ", " + year + ")";
	}

	public static void main(String[] args) {
		List<Album> albums = new ArrayList<>();
		albums.add(new Album("Got to Be There", 1972, 35.45, 10));
		albums.add(new Album("Ben", 1972, 31.31, 10));
		albums.add(new Album("Music & Me", 1973, 32.09, 10));
		albums.add(new Album("Forever, Michael", 1975, 33.36, 10));
		albums.add(new Album("Off the Wall", 1979, 42.28, 10));
		albums.add(new Album("Thriller", 1982, 42.19, 9));
		albums.add(new Album("Bad", 1987, 48.16, 10));
		albums.add(new Album("Dangerous", 1991, 77.03, 14));
		albums.add(new Album("HIStory: Past, Present and Future, Book I", 1995, 148.58, 30));
		albums.add(new Album("Invincible", 2001, 77.05, 16));
		KMeans<Album> kmeans = new KMeans<>(2, albums);
		List<KMeans<Album>.Cluster> clusters = kmeans.run(100);
		for (int clusterIndex = 0; clusterIndex < clusters.size(); clusterIndex++) {
			System.out.printf("Cluster %d Avg Length %f Avg Tracks %f: %s%n",
					clusterIndex, clusters.get(clusterIndex).centroid.dimensions.get(0),
					clusters.get(clusterIndex).centroid.dimensions.get(1),
					clusters.get(clusterIndex).points);
		}
	}

}