blob: 1ae5fcb62aeed259623e2961a2174223e09f0089 [file] [log] [blame]
/*
* 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.services.ILearning_StochasticLinearRanker;
import android.bordeaux.services.StringFloat;
import android.content.Context;
import android.os.RemoteException;
import android.util.Log;
import java.util.ArrayList;
import java.util.List;
import java.util.HashMap;
import java.util.Map;
/** Ranker for the Learning framework.
* For training: call updateClassifier with a pair of samples.
* For ranking: call scoreSample to the score of the rank
* Data is represented as sparse key, value pair. And key is a String, value
* is a float.
* Note: since the actual ranker is running in a remote the service.
* Sometimes the connection may be lost or not established.
*
*/
public class BordeauxRanker {
static final String TAG = "BordeauxRanker";
static final String RANKER_NOTAVAILABLE = "Ranker not Available";
private Context mContext;
private String mName;
private ILearning_StochasticLinearRanker mRanker;
private ArrayList<StringFloat> getArrayList(final HashMap<String, Float> sample) {
ArrayList<StringFloat> stringfloat_sample = new ArrayList<StringFloat>();
for (Map.Entry<String, Float> x : sample.entrySet()) {
StringFloat v = new StringFloat();
v.key = x.getKey();
v.value = x.getValue();
stringfloat_sample.add(v);
}
return stringfloat_sample;
}
public boolean retrieveRanker() {
if (mRanker == null)
mRanker = BordeauxManagerService.getRanker(mContext, mName);
// if classifier is not available, return false
if (mRanker == null) {
Log.e(TAG,"Ranker not available.");
return false;
}
return true;
}
public BordeauxRanker(Context context) {
mContext = context;
mName = "defaultRanker";
mRanker = BordeauxManagerService.getRanker(context, mName);
}
public BordeauxRanker(Context context, String name) {
mContext = context;
mName = name;
mRanker = BordeauxManagerService.getRanker(context, mName);
}
// Update the ranker with two samples, sample1 has higher rank than
// sample2.
public boolean update(final HashMap<String, Float> sample1,
final HashMap<String, Float> sample2) {
if (!retrieveRanker())
return false;
try {
mRanker.UpdateClassifier(getArrayList(sample1), getArrayList(sample2));
} catch (RemoteException e) {
Log.e(TAG,"Exception: updateClassifier.");
return false;
}
return true;
}
public boolean reset() {
if (!retrieveRanker()){
Log.e(TAG,"Exception: Ranker is not availible");
return false;
}
try {
mRanker.ResetRanker();
return true;
} catch (RemoteException e) {
}
return false;
}
public float scoreSample(final HashMap<String, Float> sample) {
if (!retrieveRanker())
throw new RuntimeException(RANKER_NOTAVAILABLE);
try {
return mRanker.ScoreSample(getArrayList(sample));
} catch (RemoteException e) {
Log.e(TAG,"Exception: scoring the sample.");
throw new RuntimeException(RANKER_NOTAVAILABLE);
}
}
public boolean setPriorWeight(final HashMap<String, Float> sample) {
if (!retrieveRanker())
throw new RuntimeException(RANKER_NOTAVAILABLE);
try {
return mRanker.SetModelPriorWeight(getArrayList(sample));
} catch (RemoteException e) {
Log.e(TAG,"Exception: set prior Weights");
throw new RuntimeException(RANKER_NOTAVAILABLE);
}
}
public boolean setParameter(String key, String value) {
if (!retrieveRanker())
throw new RuntimeException(RANKER_NOTAVAILABLE);
try {
return mRanker.SetModelParameter(key, value);
} catch (RemoteException e) {
Log.e(TAG,"Exception: Setting Parameter");
throw new RuntimeException(RANKER_NOTAVAILABLE);
}
}
}