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
17package android.gesture;
18
19import java.util.ArrayList;
20import java.util.Collections;
21import java.util.Comparator;
22import java.util.TreeMap;
23
24/**
25 * An implementation of an instance-based learner
26 */
27
28class 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