public override void RemovePreference(long userID, long itemID)
{
IDataModel dataModel = GetDataModel();
float? oldPref = dataModel.GetPreferenceValue(userID, itemID);
base.RemovePreference(userID, itemID);
if (oldPref.HasValue)
{
lock (this) {
//buildAveragesLock.writeLock().lock();
IRunningAverage itemAverage = itemAverages.Get(itemID);
if (itemAverage == null)
{
throw new InvalidOperationException("No preferences exist for item ID: " + itemID);
}
itemAverage.RemoveDatum(oldPref.Value);
IRunningAverage userAverage = userAverages.Get(userID);
if (userAverage == null)
{
throw new InvalidOperationException("No preferences exist for user ID: " + userID);
}
userAverage.RemoveDatum(oldPref.Value);
overallAveragePrefValue.RemoveDatum(oldPref.Value);
}/* finally {
* buildAveragesLock.writeLock().unlock();
* }*/
}
}
public static void Evaluate(IRecommender recommender,
IDataModel model,
int samples,
IRunningAverage tracker,
String tag)
{
printHeader();
var users = recommender.GetDataModel().GetUserIDs();
while (users.MoveNext())
{
long userID = users.Current;
var recs1 = recommender.Recommend(userID, model.GetNumItems());
IPreferenceArray prefs2 = model.GetPreferencesFromUser(userID);
prefs2.SortByValueReversed();
FastIDSet commonSet = new FastIDSet();
long maxItemID = setBits(commonSet, recs1, samples);
FastIDSet otherSet = new FastIDSet();
maxItemID = Math.Max(maxItemID, setBits(otherSet, prefs2, samples));
int max = mask(commonSet, otherSet, maxItemID);
max = Math.Min(max, samples);
if (max < 2)
{
continue;
}
long[] items1 = getCommonItems(commonSet, recs1, max);
long[] items2 = getCommonItems(commonSet, prefs2, max);
double variance = scoreCommonSubset(tag, userID, samples, max, items1, items2);
tracker.AddDatum(variance);
}
}
private void buildAverageDiffs()
{
lock (this) {
//buildAveragesLock.writeLock().lock();
IDataModel dataModel = GetDataModel();
var it = dataModel.GetUserIDs();
while (it.MoveNext())
{
IPreferenceArray prefs = dataModel.GetPreferencesFromUser(it.Current);
int size = prefs.Length();
for (int i = 0; i < size; i++)
{
long itemID = prefs.GetItemID(i);
IRunningAverage average = itemAverages.Get(itemID);
if (average == null)
{
average = new FullRunningAverage();
itemAverages.Put(itemID, average);
}
average.AddDatum(prefs.GetValue(i));
}
}
}
//finally {
//buildAveragesLock.writeLock().unlock();
//}
}
public static void Evaluate(IRecommender recommender,
IDataModel model,
int samples,
IRunningAverage tracker,
String tag) {
printHeader();
var users = recommender.GetDataModel().GetUserIDs();
while (users.MoveNext()) {
long userID = users.Current;
var recs1 = recommender.Recommend(userID, model.GetNumItems());
IPreferenceArray prefs2 = model.GetPreferencesFromUser(userID);
prefs2.SortByValueReversed();
FastIDSet commonSet = new FastIDSet();
long maxItemID = setBits(commonSet, recs1, samples);
FastIDSet otherSet = new FastIDSet();
maxItemID = Math.Max(maxItemID, setBits(otherSet, prefs2, samples));
int max = mask(commonSet, otherSet, maxItemID);
max = Math.Min(max, samples);
if (max < 2) {
continue;
}
long[] items1 = getCommonItems(commonSet, recs1, max);
long[] items2 = getCommonItems(commonSet, prefs2, max);
double variance = scoreCommonSubset(tag, userID, samples, max, items1, items2);
tracker.AddDatum(variance);
}
}
public override void SetPreference(long userID, long itemID, float value)
{
IDataModel dataModel = GetDataModel();
double prefDelta;
try {
float?oldPref = dataModel.GetPreferenceValue(userID, itemID);
prefDelta = !oldPref.HasValue ? value : value - oldPref.Value;
} catch (NoSuchUserException nsee) {
prefDelta = value;
}
base.SetPreference(userID, itemID, value);
lock (this) {
//buildAveragesLock.writeLock().lock();
IRunningAverage average = itemAverages.Get(itemID);
if (average == null)
{
IRunningAverage newAverage = new FullRunningAverage();
newAverage.AddDatum(prefDelta);
itemAverages.Put(itemID, newAverage);
}
else
{
average.ChangeDatum(prefDelta);
}
}
//finally {
//buildAveragesLock.writeLock().unlock();
//}
}
private static void addDatumAndCreateIfNeeded(long itemID, float value, FastByIDMap <IRunningAverage> averages)
{
IRunningAverage itemAverage = averages.Get(itemID);
if (itemAverage == null)
{
itemAverage = new FullRunningAverage();
averages.Put(itemID, itemAverage);
}
itemAverage.AddDatum(value);
}
private float doEstimatePreference(long itemID)
{
lock (this) { // buildAveragesLock.readLock().lock();
//try {
IRunningAverage average = itemAverages.Get(itemID);
return(average == null ? float.NaN : (float)average.GetAverage());
//} finally {
//buildAveragesLock.readLock().unlock();
//}
}
}
public ItemUserAverageRecommender(IDataModel dataModel) : base(dataModel)
{
this.itemAverages = new FastByIDMap <IRunningAverage>();
this.userAverages = new FastByIDMap <IRunningAverage>();
this.overallAveragePrefValue = new FullRunningAverage();
//this.buildAveragesLock = new ReentrantReadWriteLock();
this.refreshHelper = new RefreshHelper(() => {
buildAverageDiffs();
});
refreshHelper.AddDependency(dataModel);
buildAverageDiffs();
}
private float doEstimatePreference(long userID, long itemID)
{
//buildAveragesLock.readLock().lock();
lock (this) {
IRunningAverage itemAverage = itemAverages.Get(itemID);
if (itemAverage == null)
{
return(float.NaN);
}
IRunningAverage userAverage = userAverages.Get(userID);
if (userAverage == null)
{
return(float.NaN);
}
double userDiff = userAverage.GetAverage() - overallAveragePrefValue.GetAverage();
return((float)(itemAverage.GetAverage() + userDiff));
} /*finally {
* buildAveragesLock.readLock().unlock();
* }*/
}
public LoadStatistics(IRunningAverage timing) {
this.timing = timing;
}
public LoadStatistics(IRunningAverage timing)
{
this.timing = timing;
}
protected override void reset()
{
average = new FullRunningAverage();
}
protected override void reset() {
average = new FullRunningAverage();
}
public InvertedRunningAverage(IRunningAverage deleg) {
this._Delegate = deleg;
}
public InvertedRunningAverage(IRunningAverage deleg)
{
this._Delegate = deleg;
}