1/*
2 * Copyright (C) 2012 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.bordeaux.services;
18
19import android.bordeaux.learning.MulticlassPA;
20import android.os.IBinder;
21
22import java.util.List;
23import java.util.ArrayList;
24
25public class Learning_MulticlassPA extends ILearning_MulticlassPA.Stub
26        implements IBordeauxLearner {
27    private MulticlassPA mMulticlassPA_learner;
28    private ModelChangeCallback modelChangeCallback = null;
29
30    class IntFloatArray {
31        int[] indexArray;
32        float[] floatArray;
33    };
34
35    private IntFloatArray splitIntFloatArray(List<IntFloat> sample) {
36        IntFloatArray splited = new IntFloatArray();
37        ArrayList<IntFloat> s = (ArrayList<IntFloat>)sample;
38        splited.indexArray = new int[s.size()];
39        splited.floatArray = new float[s.size()];
40        for (int i = 0; i < s.size(); i++) {
41            splited.indexArray[i] = s.get(i).index;
42            splited.floatArray[i] = s.get(i).value;
43        }
44        return splited;
45    }
46
47    public Learning_MulticlassPA() {
48        mMulticlassPA_learner = new MulticlassPA(2, 2, 0.001f);
49    }
50
51    // Beginning of the IBordeauxLearner Interface implementation
52    public byte [] getModel() {
53        return null;
54    }
55
56    public boolean setModel(final byte [] modelData) {
57        return false;
58    }
59
60    public IBinder getBinder() {
61        return this;
62    }
63
64    public void setModelChangeCallback(ModelChangeCallback callback) {
65        modelChangeCallback = callback;
66    }
67    // End of IBordeauxLearner Interface implemenation
68
69    // This implementation, combines training and prediction in one step.
70    // The return value is the prediction value for the supplied sample. It
71    // also update the model with the current sample.
72    public void TrainOneSample(List<IntFloat> sample, int target) {
73        IntFloatArray splited = splitIntFloatArray(sample);
74        mMulticlassPA_learner.sparseTrainOneExample(splited.indexArray,
75                                                    splited.floatArray,
76                                                    target);
77        if (modelChangeCallback != null) {
78            modelChangeCallback.modelChanged(this);
79        }
80    }
81
82    public int Classify(List<IntFloat> sample) {
83        IntFloatArray splited = splitIntFloatArray(sample);
84        int prediction = mMulticlassPA_learner.sparseGetClass(splited.indexArray,
85                                                              splited.floatArray);
86        return prediction;
87    }
88
89}
90