samoa-api/src/main/java/org/apache/samoa/moa/cluster/Cluster.java - incubator-samoa - Git at Google

 /*
  * 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.samoa.moa.cluster;

 import java.util.ArrayList;
 import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
 import java.util.Random;

 import org.apache.samoa.instances.Instance;
 import org.apache.samoa.moa.AbstractMOAObject;

 public abstract class Cluster extends AbstractMOAObject {

   private static final long serialVersionUID = 1L;

   private double id = -1;
   private double gtLabel = -1;

   private Map<String, String> measure_values;

   public Cluster() {
     this.measure_values = new HashMap<>();
   }

   /**
    * @return the center of the cluster
    */
   public abstract double[] getCenter();

   /**
    * Returns the weight of this cluster, not neccessarily normalized. It could, for instance, simply return the number
    * of points contined in this cluster.
    *
    * @return the weight
    */
   public abstract double getWeight();

   /**
    * Returns the probability of the given point belonging to this cluster.
    *
    * @param instance
    * @return a value between 0 and 1
    */
   public abstract double getInclusionProbability(Instance instance);

   // TODO: for non sphere cluster sample points, find out MIN MAX neighbours
   // within cluster
   // and return the relative distance
   // public abstract double getRelativeHullDistance(Instance instance);

   @Override
   public void getDescription(StringBuilder sb, int i) {
     sb.append("Cluster Object");
   }

   public void setId(double id) {
     this.id = id;
   }

   public double getId() {
     return id;
   }

   public boolean isGroundTruth() {
     return gtLabel != -1;
   }

   public void setGroundTruth(double truth) {
     gtLabel = truth;
   }

   public double getGroundTruth() {
     return gtLabel;
   }

   /**
    * Samples this cluster by returning a point from inside it.
    *
    * @param random
    *          a random number source
    * @return an Instance that lies inside this cluster
    */
   public abstract Instance sample(Random random);

   public void setMeasureValue(String measureKey, String value) {
     measure_values.put(measureKey, value);
   }

   public void setMeasureValue(String measureKey, double value) {
     measure_values.put(measureKey, Double.toString(value));
   }

   public String getMeasureValue(String measureKey) {
     if (measure_values.containsKey(measureKey))
       return measure_values.get(measureKey);
     else
       return "";
   }

   protected void getClusterSpecificInfo(List<String> infoTitle, List<String> infoValue) {
     infoTitle.add("ClusterID");
     infoValue.add(Integer.toString((int) getId()));

     infoTitle.add("Type");
     infoValue.add(getClass().getSimpleName());

     double c[] = getCenter();
     if (c != null)
       for (int i = 0; i < c.length; i++) {
         infoTitle.add("Dim" + i);
         infoValue.add(Double.toString(c[i]));
       }

     infoTitle.add("Weight");
     infoValue.add(Double.toString(getWeight()));

   }

   public String getInfo() {
     List<String> infoTitle = new ArrayList<>();
     List<String> infoValue = new ArrayList<>();
     getClusterSpecificInfo(infoTitle, infoValue);

     StringBuilder sb = new StringBuilder();

     // Cluster properties
     sb.append("<html>");
     sb.append("<table>");
     int i = 0;
     while (i < infoTitle.size() && i < infoValue.size()) {
       sb.append("<tr><td>" + infoTitle.get(i) + "</td><td>" + infoValue.get(i) + "</td></tr>");
       i++;
     }
     sb.append("</table>");

     // Evaluation info
     sb.append("<br>");
     sb.append("<b>Evaluation</b><br>");
     sb.append("<table>");
     for (Object o : measure_values.entrySet()) {
       Map.Entry e = (Map.Entry) o;
       sb.append("<tr><td>" + e.getKey() + "</td><td>" + e.getValue() + "</td></tr>");
     }
     sb.append("</table>");
     sb.append("</html>");
     return sb.toString();
   }

 }
	/*
	* 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.samoa.moa.cluster;

	import java.util.ArrayList;
	import java.util.HashMap;
	import java.util.List;
	import java.util.Map;
	import java.util.Random;

	import org.apache.samoa.instances.Instance;
	import org.apache.samoa.moa.AbstractMOAObject;

	public abstract class Cluster extends AbstractMOAObject {

	private static final long serialVersionUID = 1L;

	private double id = -1;
	private double gtLabel = -1;

	private Map<String, String> measure_values;

	public Cluster() {
	this.measure_values = new HashMap<>();
	}

	/**
	* @return the center of the cluster
	*/
	public abstract double[] getCenter();

	/**
	* Returns the weight of this cluster, not neccessarily normalized. It could, for instance, simply return the number
	* of points contined in this cluster.
	*
	* @return the weight
	*/
	public abstract double getWeight();

	/**
	* Returns the probability of the given point belonging to this cluster.
	*
	* @param instance
	* @return a value between 0 and 1
	*/
	public abstract double getInclusionProbability(Instance instance);

	// TODO: for non sphere cluster sample points, find out MIN MAX neighbours
	// within cluster
	// and return the relative distance
	// public abstract double getRelativeHullDistance(Instance instance);

	@Override
	public void getDescription(StringBuilder sb, int i) {
	sb.append("Cluster Object");
	}

	public void setId(double id) {
	this.id = id;
	}

	public double getId() {
	return id;
	}

	public boolean isGroundTruth() {
	return gtLabel != -1;
	}

	public void setGroundTruth(double truth) {
	gtLabel = truth;
	}

	public double getGroundTruth() {
	return gtLabel;
	}

	/**
	* Samples this cluster by returning a point from inside it.
	*
	* @param random
	* a random number source
	* @return an Instance that lies inside this cluster
	*/
	public abstract Instance sample(Random random);

	public void setMeasureValue(String measureKey, String value) {
	measure_values.put(measureKey, value);
	}

	public void setMeasureValue(String measureKey, double value) {
	measure_values.put(measureKey, Double.toString(value));
	}

	public String getMeasureValue(String measureKey) {
	if (measure_values.containsKey(measureKey))
	return measure_values.get(measureKey);
	else
	return "";
	}

	protected void getClusterSpecificInfo(List<String> infoTitle, List<String> infoValue) {
	infoTitle.add("ClusterID");
	infoValue.add(Integer.toString((int) getId()));

	infoTitle.add("Type");
	infoValue.add(getClass().getSimpleName());

	double c[] = getCenter();
	if (c != null)
	for (int i = 0; i < c.length; i++) {
	infoTitle.add("Dim" + i);
	infoValue.add(Double.toString(c[i]));
	}

	infoTitle.add("Weight");
	infoValue.add(Double.toString(getWeight()));

	}

	public String getInfo() {
	List<String> infoTitle = new ArrayList<>();
	List<String> infoValue = new ArrayList<>();
	getClusterSpecificInfo(infoTitle, infoValue);

	StringBuilder sb = new StringBuilder();

	// Cluster properties
	sb.append("<html>");
	sb.append("<table>");
	int i = 0;
	while (i < infoTitle.size() && i < infoValue.size()) {
	sb.append("<tr><td>" + infoTitle.get(i) + "</td><td>" + infoValue.get(i) + "</td></tr>");
	i++;
	}
	sb.append("</table>");

	// Evaluation info
	sb.append("<br>");
	sb.append("<b>Evaluation</b><br>");
	sb.append("<table>");
	for (Object o : measure_values.entrySet()) {
	Map.Entry e = (Map.Entry) o;
	sb.append("<tr><td>" + e.getKey() + "</td><td>" + e.getValue() + "</td></tr>");
	}
	sb.append("</table>");
	sb.append("</html>");
	return sb.toString();
	}

	}