content: /*
   * Copyright (C) 2008-2009 The Android Open Source Project
   *
   * 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 android.gesture;
  
  import java.util.ArrayList;
  import java.util.Collections;
  import java.util.Comparator;
  import java.util.TreeMap;
  
  /**
   * An implementation of an instance-based learner
   */
  
  class InstanceLearner extends Learner {
      private static final Comparator<Prediction> sComparator = new Comparator<Prediction>() {
          public int compare(Prediction object1, Prediction object2) {
              double score1 = object1.score;
              double score2 = object2.score;
              if (score1 > score2) {
                  return -1;
              } else if (score1 < score2) {
                  return 1;
              } else {
                  return 0;
              }
          }
      };
  
      @Override
      ArrayList<Prediction> classify(int sequenceType, int orientationType, float[] vector) {
          ArrayList<Prediction> predictions = new ArrayList<Prediction>();
          ArrayList<Instance> instances = getInstances();
          int count = instances.size();
          TreeMap<String, Double> label2score = new TreeMap<String, Double>();
          for (int i = 0; i < count; i++) {
              Instance sample = instances.get(i);
              if (sample.vector.length != vector.length) {
                  continue;
              }
              double distance;
              if (sequenceType == GestureStore.SEQUENCE_SENSITIVE) {
                  distance = GestureUtils.minimumCosineDistance(sample.vector, vector, orientationType);
              } else {
                  distance = GestureUtils.squaredEuclideanDistance(sample.vector, vector);
              }
              double weight;
              if (distance == 0) {
                  weight = Double.MAX_VALUE;
              } else {
                  weight = 1 / distance;
              }
              Double score = label2score.get(sample.label);
              if (score == null || weight > score) {
                  label2score.put(sample.label, weight);
              }
          }
  
  //        double sum = 0;
          for (String name : label2score.keySet()) {
              double score = label2score.get(name);
  //            sum += score;
              predictions.add(new Prediction(name, score));
          }
  
          // normalize
  //        for (Prediction prediction : predictions) {
  //            prediction.score /= sum;
  //        }
  
          Collections.sort(predictions, sComparator);
  
          return predictions;
      }
  }
  