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ClearTK wrapper for the WEKA machine learning library
There is a newer version: 3.0.0
/** 
 * Copyright (c) 2012, Regents of the University of Colorado 
 * All rights reserved.
 * 
 * This program is free software; you can redistribute it and/or
 * modify it under the terms of the GNU General Public License
 * as published by the Free Software Foundation; either version 2
 * of the License, or (at your option) any later version.
 * 
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 * 
 * For a complete copy of the license please see the file LICENSE distributed 
 * with the cleartk-syntax-berkeley project or visit 
 * http://www.gnu.org/licenses/old-licenses/gpl-2.0.html.
 */
package org.cleartk.ml.weka;

import java.io.File;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.Map;

import org.cleartk.ml.Feature;
import org.cleartk.ml.encoder.features.FeaturesEncoder;

import com.google.common.annotations.Beta;

import weka.core.Attribute;
import weka.core.Utils;

/**
 * Copyright (c) 2012, Regents of the University of Colorado 

 * All rights reserved.
 * 
 * @author Philip Ogren
 * 
 */
@Beta
public class WekaFeaturesEncoder implements FeaturesEncoder> {

  private static final long serialVersionUID = 1L;

  private ArrayList attributes;

  private Map attributeMap;

  public WekaFeaturesEncoder() {
    attributes = new ArrayList();
    attributeMap = new HashMap();
  }

  public Iterable encodeAll(Iterable features) {
    for (Feature feature : features) {
      featureToAttribute(feature);
    }
    return features;
  }

  /**
   * @param feature
   * @return
   */
  private Attribute featureToAttribute(Feature feature) {
    String name = feature.getName();
    Attribute attribute = attributeMap.get(name);
    if (attribute == null) {
      attribute = featureToAttribute(feature, attributes.size());
      attributes.add(attribute);
      attributeMap.put(name, attribute);
    }
    return attribute;
  }

  public static Attribute featureToAttribute(Feature feature, int attributeIndex) {
    String name = Utils.quote(feature.getName());
    Object value = feature.getValue();
    Attribute attribute;
    // if value is a number then create a numeric attribute
    if (value instanceof Number) {
      attribute = new Attribute(name);
    }// if value is a boolean then create a numeric attribute
    else if (value instanceof Boolean) {
      attribute = new Attribute(name);
    }
    // if value is an Enum thene create a nominal attribute
    else if (value instanceof Enum) {
      Object[] enumConstants = value.getClass().getEnumConstants();
      ArrayList attributeValues = new ArrayList(enumConstants.length);
      for (Object enumConstant : enumConstants) {
        attributeValues.add(enumConstant.toString());
      }
      attribute = new Attribute(name, attributeValues);
    }
    // if value is not a number, boolean, or enum, then we will create a
    // string attribute
    else {
      attribute = new Attribute(name, (ArrayList) null);
    }
    return attribute;
  }

  public void finalizeFeatureSet(File outputDirectory) {
  }

  public ArrayList getWekaAttributes() {
    return attributes;
  }

  public Map getWekaAttributeMap() {
    return attributeMap;
  }

}