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      1 /*
      2  * Copyright (C) 2008-2009 The Android Open Source Project
      3  *
      4  * Licensed under the Apache License, Version 2.0 (the "License");
      5  * you may not use this file except in compliance with the License.
      6  * You may obtain a copy of the License at
      7  *
      8  *      http://www.apache.org/licenses/LICENSE-2.0
      9  *
     10  * Unless required by applicable law or agreed to in writing, software
     11  * distributed under the License is distributed on an "AS IS" BASIS,
     12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     13  * See the License for the specific language governing permissions and
     14  * limitations under the License.
     15  */
     16 
     17 package android.gesture;
     18 
     19 import java.util.ArrayList;
     20 import java.util.Collections;
     21 import java.util.Comparator;
     22 import java.util.TreeMap;
     23 
     24 /**
     25  * An implementation of an instance-based learner
     26  */
     27 
     28 class InstanceLearner extends Learner {
     29     private static final Comparator<Prediction> sComparator = new Comparator<Prediction>() {
     30         public int compare(Prediction object1, Prediction object2) {
     31             double score1 = object1.score;
     32             double score2 = object2.score;
     33             if (score1 > score2) {
     34                 return -1;
     35             } else if (score1 < score2) {
     36                 return 1;
     37             } else {
     38                 return 0;
     39             }
     40         }
     41     };
     42 
     43     @Override
     44     ArrayList<Prediction> classify(int sequenceType, int orientationType, float[] vector) {
     45         ArrayList<Prediction> predictions = new ArrayList<Prediction>();
     46         ArrayList<Instance> instances = getInstances();
     47         int count = instances.size();
     48         TreeMap<String, Double> label2score = new TreeMap<String, Double>();
     49         for (int i = 0; i < count; i++) {
     50             Instance sample = instances.get(i);
     51             if (sample.vector.length != vector.length) {
     52                 continue;
     53             }
     54             double distance;
     55             if (sequenceType == GestureStore.SEQUENCE_SENSITIVE) {
     56                 distance = GestureUtils.minimumCosineDistance(sample.vector, vector, orientationType);
     57             } else {
     58                 distance = GestureUtils.squaredEuclideanDistance(sample.vector, vector);
     59             }
     60             double weight;
     61             if (distance == 0) {
     62                 weight = Double.MAX_VALUE;
     63             } else {
     64                 weight = 1 / distance;
     65             }
     66             Double score = label2score.get(sample.label);
     67             if (score == null || weight > score) {
     68                 label2score.put(sample.label, weight);
     69             }
     70         }
     71 
     72 //        double sum = 0;
     73         for (String name : label2score.keySet()) {
     74             double score = label2score.get(name);
     75 //            sum += score;
     76             predictions.add(new Prediction(name, score));
     77         }
     78 
     79         // normalize
     80 //        for (Prediction prediction : predictions) {
     81 //            prediction.score /= sum;
     82 //        }
     83 
     84         Collections.sort(predictions, sComparator);
     85 
     86         return predictions;
     87     }
     88 }
     89