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/*
* Copyright (C) 2012 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.bordeaux.services;
import android.bordeaux.learning.StochasticLinearRanker;
import android.bordeaux.services.IBordeauxLearner.ModelChangeCallback;
import android.os.IBinder;
import android.util.Log;
import java.util.List;
import java.util.ArrayList;
import java.io.*;
import java.lang.ClassNotFoundException;
import java.util.Arrays;
import java.util.ArrayList;
import java.util.List;
import java.util.Scanner;
import java.io.ByteArrayOutputStream;
import java.util.HashMap;
import java.util.Map;
public class Learning_StochasticLinearRanker extends ILearning_StochasticLinearRanker.Stub
implements IBordeauxLearner {
private final String TAG = "ILearning_StochasticLinearRanker";
private StochasticLinearRankerWithPrior mLearningSlRanker = null;
private ModelChangeCallback modelChangeCallback = null;
public Learning_StochasticLinearRanker(){
}
public void ResetRanker(){
if (mLearningSlRanker == null)
mLearningSlRanker = new StochasticLinearRankerWithPrior();
mLearningSlRanker.resetRanker();
}
public boolean UpdateClassifier(List<StringFloat> sample_1, List<StringFloat> sample_2){
ArrayList<StringFloat> temp_1 = (ArrayList<StringFloat>)sample_1;
String[] keys_1 = new String[temp_1.size()];
float[] values_1 = new float[temp_1.size()];
for (int i = 0; i < temp_1.size(); i++){
keys_1[i] = temp_1.get(i).key;
values_1[i] = temp_1.get(i).value;
}
ArrayList<StringFloat> temp_2 = (ArrayList<StringFloat>)sample_2;
String[] keys_2 = new String[temp_2.size()];
float[] values_2 = new float[temp_2.size()];
for (int i = 0; i < temp_2.size(); i++){
keys_2[i] = temp_2.get(i).key;
values_2[i] = temp_2.get(i).value;
}
if (mLearningSlRanker == null)
mLearningSlRanker = new StochasticLinearRankerWithPrior();
boolean res = mLearningSlRanker.updateClassifier(keys_1,values_1,keys_2,values_2);
if (res && modelChangeCallback != null) {
modelChangeCallback.modelChanged(this);
}
return res;
}
public float ScoreSample(List<StringFloat> sample) {
ArrayList<StringFloat> temp = (ArrayList<StringFloat>)sample;
String[] keys = new String[temp.size()];
float[] values = new float[temp.size()];
for (int i = 0; i < temp.size(); i++){
keys[i] = temp.get(i).key;
values[i] = temp.get(i).value;
}
if (mLearningSlRanker == null)
mLearningSlRanker = new StochasticLinearRankerWithPrior();
return mLearningSlRanker.scoreSample(keys,values);
}
public boolean SetModelPriorWeight(List<StringFloat> sample) {
ArrayList<StringFloat> temp = (ArrayList<StringFloat>)sample;
HashMap<String, Float> weights = new HashMap<String, Float>();
for (int i = 0; i < temp.size(); i++)
weights.put(temp.get(i).key, temp.get(i).value);
if (mLearningSlRanker == null)
mLearningSlRanker = new StochasticLinearRankerWithPrior();
return mLearningSlRanker.setModelPriorWeights(weights);
}
public boolean SetModelParameter(String key, String value) {
if (mLearningSlRanker == null)
mLearningSlRanker = new StochasticLinearRankerWithPrior();
return mLearningSlRanker.setModelParameter(key,value);
}
// Beginning of the IBordeauxLearner Interface implementation
public byte [] getModel() {
if (mLearningSlRanker == null)
mLearningSlRanker = new StochasticLinearRankerWithPrior();
StochasticLinearRankerWithPrior.Model model = mLearningSlRanker.getModel();
try {
ByteArrayOutputStream byteStream = new ByteArrayOutputStream();
ObjectOutputStream objStream = new ObjectOutputStream(byteStream);
objStream.writeObject(model);
//return byteStream.toByteArray();
byte[] bytes = byteStream.toByteArray();
return bytes;
} catch (IOException e) {
throw new RuntimeException("Can't get model");
}
}
public boolean setModel(final byte [] modelData) {
try {
ByteArrayInputStream input = new ByteArrayInputStream(modelData);
ObjectInputStream objStream = new ObjectInputStream(input);
StochasticLinearRankerWithPrior.Model model =
(StochasticLinearRankerWithPrior.Model) objStream.readObject();
if (mLearningSlRanker == null)
mLearningSlRanker = new StochasticLinearRankerWithPrior();
boolean res = mLearningSlRanker.loadModel(model);
return res;
} catch (IOException e) {
throw new RuntimeException("Can't load model");
} catch (ClassNotFoundException e) {
throw new RuntimeException("Learning class not found");
}
}
public IBinder getBinder() {
return this;
}
public void setModelChangeCallback(ModelChangeCallback callback) {
modelChangeCallback = callback;
}
// End of IBordeauxLearner Interface implemenation
}
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