public void testStrategy()
{
FastIDSet itemIDsFromUser123 = new FastIDSet();
itemIDsFromUser123.Add(1L);
FastIDSet itemIDsFromUser456 = new FastIDSet();
itemIDsFromUser456.Add(1L);
itemIDsFromUser456.Add(2L);
List<IPreference> prefs = new List<IPreference>();
prefs.Add(new GenericPreference(123L, 1L, 1.0f));
prefs.Add(new GenericPreference(456L, 1L, 1.0f));
IPreferenceArray preferencesForItem1 = new GenericItemPreferenceArray(prefs);
var dataModelMock = new DynamicMock(typeof(IDataModel));
dataModelMock.ExpectAndReturn("GetPreferencesForItem", preferencesForItem1, (1L));
dataModelMock.ExpectAndReturn("GetItemIDsFromUser", itemIDsFromUser123, (123L));
dataModelMock.ExpectAndReturn("GetItemIDsFromUser", itemIDsFromUser456, (456L));
IPreferenceArray prefArrayOfUser123 =
new GenericUserPreferenceArray( new List<IPreference>() {new GenericPreference(123L, 1L, 1.0f)} );
ICandidateItemsStrategy strategy = new PreferredItemsNeighborhoodCandidateItemsStrategy();
//EasyMock.replay(dataModel);
FastIDSet candidateItems = strategy.GetCandidateItems(123L, prefArrayOfUser123, (IDataModel)dataModelMock.MockInstance);
Assert.AreEqual(1, candidateItems.Count());
Assert.True(candidateItems.Contains(2L));
dataModelMock.Verify(); // EasyMock.verify(dataModel);
}
public void testGrow()
{
FastIDSet set = new FastIDSet(1);
set.Add(1);
set.Add(2);
Assert.True(set.Contains(1));
Assert.True(set.Contains(2));
}
public void testStrategy()
{
FastIDSet allItemIDs = new FastIDSet();
allItemIDs.AddAll(new long[] { 1L, 2L, 3L });
FastIDSet preferredItemIDs = new FastIDSet(1);
preferredItemIDs.Add(2L);
var dataModelMock = new DynamicMock(typeof(IDataModel));
dataModelMock.ExpectAndReturn("GetNumItems", 3);
dataModelMock.ExpectAndReturn("GetItemIDs", allItemIDs.GetEnumerator());
IPreferenceArray prefArrayOfUser123 = new GenericUserPreferenceArray(new List <IPreference>()
{
new GenericPreference(123L, 2L, 1.0f)
});
ICandidateItemsStrategy strategy = new AllUnknownItemsCandidateItemsStrategy();
//EasyMock.replay(dataModel);
FastIDSet candidateItems = strategy.GetCandidateItems(123L, prefArrayOfUser123, (IDataModel)dataModelMock.MockInstance);
Assert.AreEqual(2, candidateItems.Count());
Assert.True(candidateItems.Contains(1L));
Assert.True(candidateItems.Contains(3L));
dataModelMock.Verify();
//EasyMock.verify(dataModel);
}
public void testStrategy()
{
FastIDSet allItemIDs = new FastIDSet();
allItemIDs.AddAll(new long[] { 1L, 2L, 3L });
FastIDSet preferredItemIDs = new FastIDSet(1);
preferredItemIDs.Add(2L);
var dataModelMock = new DynamicMock( typeof( IDataModel ));
dataModelMock.ExpectAndReturn("GetNumItems", 3);
dataModelMock.ExpectAndReturn("GetItemIDs", allItemIDs.GetEnumerator());
IPreferenceArray prefArrayOfUser123 = new GenericUserPreferenceArray( new List<IPreference>() {
new GenericPreference(123L, 2L, 1.0f) } );
ICandidateItemsStrategy strategy = new AllUnknownItemsCandidateItemsStrategy();
//EasyMock.replay(dataModel);
FastIDSet candidateItems = strategy.GetCandidateItems(123L, prefArrayOfUser123, (IDataModel)dataModelMock.MockInstance);
Assert.AreEqual(2, candidateItems.Count() );
Assert.True(candidateItems.Contains(1L));
Assert.True(candidateItems.Contains(3L));
dataModelMock.Verify();
//EasyMock.verify(dataModel);
}
public void testContainsAndAdd()
{
FastIDSet set = new FastIDSet();
Assert.False(set.Contains(1));
set.Add(1);
Assert.True(set.Contains(1));
}
public void testClear()
{
FastIDSet set = new FastIDSet();
set.Add(1);
set.Clear();
Assert.AreEqual(0, set.Count());
Assert.True(set.IsEmpty());
Assert.False(set.Contains(1));
}
/// <summary>
/// Creates a new <see cref="GenericDataModel"/> from the given users (and their preferences). This
/// <see cref="IDataModel"/> retains all this information in memory and is effectively immutable.
/// </summary>
/// <param name="userData">users to include; (see also <see cref="GenericDataModel.ToDataMap(FastByIDMap, bool)"/>)</param>
/// <param name="timestamps">timestamps optionally, provided timestamps of preferences as milliseconds since the epoch. User IDs are mapped to maps of item IDs to long timestamps.</param>
public GenericDataModel(FastByIDMap<IPreferenceArray> userData, FastByIDMap<FastByIDMap<DateTime?>> timestamps) {
//Preconditions.checkArgument(userData != null, "userData is null");
this.preferenceFromUsers = userData;
FastByIDMap<IList<IPreference>> prefsForItems = new FastByIDMap<IList<IPreference>>();
FastIDSet itemIDSet = new FastIDSet();
int currentCount = 0;
float maxPrefValue = float.NegativeInfinity;
float minPrefValue = float.PositiveInfinity;
foreach (var entry in preferenceFromUsers.EntrySet()) {
IPreferenceArray prefs = entry.Value;
prefs.SortByItem();
foreach (IPreference preference in prefs) {
long itemID = preference.GetItemID();
itemIDSet.Add(itemID);
var prefsForItem = prefsForItems.Get(itemID);
if (prefsForItem == null) {
prefsForItem = new List<IPreference>(2);
prefsForItems.Put(itemID, prefsForItem);
}
prefsForItem.Add(preference);
float value = preference.GetValue();
if (value > maxPrefValue) {
maxPrefValue = value;
}
if (value < minPrefValue) {
minPrefValue = value;
}
}
if (++currentCount % 10000 == 0) {
log.Info("Processed {0} users", currentCount);
}
}
log.Info("Processed {0} users", currentCount);
setMinPreference(minPrefValue);
setMaxPreference(maxPrefValue);
this.itemIDs = itemIDSet.ToArray();
itemIDSet = null; // Might help GC -- this is big
Array.Sort(itemIDs);
this.preferenceForItems = ToDataMap(prefsForItems, false);
foreach (var entry in preferenceForItems.EntrySet()) {
entry.Value.SortByUser();
}
this.userIDs = new long[userData.Count()];
int i = 0;
foreach (var v in userData.Keys) {
userIDs[i++] = v;
}
Array.Sort(userIDs);
this.timestamps = timestamps;
}
protected override FastIDSet doGetCandidateItems(long[] preferredItemIDs, IDataModel dataModel) {
FastIDSet possibleItemIDs = new FastIDSet(dataModel.GetNumItems());
var allItemIDs = dataModel.GetItemIDs();
while (allItemIDs.MoveNext()) {
possibleItemIDs.Add(allItemIDs.Current);
}
possibleItemIDs.RemoveAll(preferredItemIDs);
return possibleItemIDs;
}
public void recommend()
{
var dataModelMock = new DynamicMock(typeof(IDataModel));
var preferencesFromUserMock = new DynamicMock(typeof(IPreferenceArray));
var candidateItemsStrategyMock = new DynamicMock(typeof(ICandidateItemsStrategy));
var factorizerMock = new DynamicMock(typeof(IFactorizer));
var factorization = new Factorization_recommend_TestMock();
FastIDSet candidateItems = new FastIDSet();
candidateItems.Add(5L);
candidateItems.Add(3L);
factorizerMock.ExpectAndReturn("Factorize", factorization);
dataModelMock.ExpectAndReturn("GetPreferencesFromUser", preferencesFromUserMock.MockInstance, (1L));
candidateItemsStrategyMock.ExpectAndReturn("GetCandidateItems", candidateItems,
1L, preferencesFromUserMock.MockInstance, dataModelMock.MockInstance);
//EasyMock.replay(dataModel, candidateItemsStrategy, factorizer, factorization);
SVDRecommender svdRecommender = new SVDRecommender(
(IDataModel)dataModelMock.MockInstance,
(IFactorizer)factorizerMock.MockInstance,
(ICandidateItemsStrategy)candidateItemsStrategyMock.MockInstance);
IList <IRecommendedItem> recommendedItems = svdRecommender.Recommend(1L, 5);
Assert.AreEqual(2, recommendedItems.Count);
Assert.AreEqual(3L, recommendedItems[0].GetItemID());
Assert.AreEqual(2.0f, recommendedItems[0].GetValue(), EPSILON);
Assert.AreEqual(5L, recommendedItems[1].GetItemID());
Assert.AreEqual(1.0f, recommendedItems[1].GetValue(), EPSILON);
dataModelMock.Verify();
candidateItemsStrategyMock.Verify();
factorizerMock.Verify();
Assert.AreEqual(2, factorization.getItemFeaturesCallCount);
Assert.AreEqual(2, factorization.getUserFeaturesCallCount);
//EasyMock.verify(dataModel, candidateItemsStrategy, factorizer, factorization);
}
public virtual long[] AllSimilarItemIDs(long itemID) {
FastIDSet allSimilarItemIDs = new FastIDSet();
var allItemIDs = dataModel.GetItemIDs();
while (allItemIDs.MoveNext()) {
long possiblySimilarItemID = allItemIDs.Current;
if (!Double.IsNaN(ItemSimilarity(itemID, possiblySimilarItemID))) {
allSimilarItemIDs.Add(possiblySimilarItemID);
}
}
return allSimilarItemIDs.ToArray();
}
public void recommend()
{
var dataModelMock = new DynamicMock( typeof(IDataModel) );
var preferencesFromUserMock = new DynamicMock( typeof(IPreferenceArray) );
var candidateItemsStrategyMock = new DynamicMock( typeof(ICandidateItemsStrategy) );
var factorizerMock = new DynamicMock( typeof(IFactorizer) );
var factorization = new Factorization_recommend_TestMock();
FastIDSet candidateItems = new FastIDSet();
candidateItems.Add(5L);
candidateItems.Add(3L);
factorizerMock.ExpectAndReturn("Factorize", factorization);
dataModelMock.ExpectAndReturn("GetPreferencesFromUser", preferencesFromUserMock.MockInstance, (1L));
candidateItemsStrategyMock.ExpectAndReturn("GetCandidateItems", candidateItems,
1L, preferencesFromUserMock.MockInstance, dataModelMock.MockInstance);
//EasyMock.replay(dataModel, candidateItemsStrategy, factorizer, factorization);
SVDRecommender svdRecommender = new SVDRecommender(
(IDataModel)dataModelMock.MockInstance,
(IFactorizer)factorizerMock.MockInstance,
(ICandidateItemsStrategy)candidateItemsStrategyMock.MockInstance);
IList<IRecommendedItem> recommendedItems = svdRecommender.Recommend(1L, 5);
Assert.AreEqual(2, recommendedItems.Count);
Assert.AreEqual(3L, recommendedItems[0].GetItemID());
Assert.AreEqual(2.0f, recommendedItems[0].GetValue(), EPSILON);
Assert.AreEqual(5L, recommendedItems[1].GetItemID());
Assert.AreEqual(1.0f, recommendedItems[1].GetValue(), EPSILON);
dataModelMock.Verify();
candidateItemsStrategyMock.Verify();
factorizerMock.Verify();
Assert.AreEqual(2, factorization.getItemFeaturesCallCount);
Assert.AreEqual(2, factorization.getUserFeaturesCallCount);
//EasyMock.verify(dataModel, candidateItemsStrategy, factorizer, factorization);
}
protected override FastIDSet doGetCandidateItems(long[] preferredItemIDs, IDataModel dataModel)
{
FastIDSet possibleItemIDs = new FastIDSet(dataModel.GetNumItems());
var allItemIDs = dataModel.GetItemIDs();
while (allItemIDs.MoveNext())
{
possibleItemIDs.Add(allItemIDs.Current);
}
possibleItemIDs.RemoveAll(preferredItemIDs);
return(possibleItemIDs);
}
public override FastIDSet GetItemIDsFromUser(long userID)
{
IPreferenceArray prefs = GetPreferencesFromUser(userID);
int size = prefs.Length();
FastIDSet result = new FastIDSet(size);
for (int i = 0; i < size; i++)
{
result.Add(prefs.GetItemID(i));
}
return(result);
}
public void testStrategy()
{
FastIDSet itemIDsFromUser123 = new FastIDSet();
itemIDsFromUser123.Add(1L);
FastIDSet itemIDsFromUser456 = new FastIDSet();
itemIDsFromUser456.Add(1L);
itemIDsFromUser456.Add(2L);
List <IPreference> prefs = new List <IPreference>();
prefs.Add(new GenericPreference(123L, 1L, 1.0f));
prefs.Add(new GenericPreference(456L, 1L, 1.0f));
IPreferenceArray preferencesForItem1 = new GenericItemPreferenceArray(prefs);
var dataModelMock = new DynamicMock(typeof(IDataModel));
dataModelMock.ExpectAndReturn("GetPreferencesForItem", preferencesForItem1, (1L));
dataModelMock.ExpectAndReturn("GetItemIDsFromUser", itemIDsFromUser123, (123L));
dataModelMock.ExpectAndReturn("GetItemIDsFromUser", itemIDsFromUser456, (456L));
IPreferenceArray prefArrayOfUser123 =
new GenericUserPreferenceArray(new List <IPreference>()
{
new GenericPreference(123L, 1L, 1.0f)
});
ICandidateItemsStrategy strategy = new PreferredItemsNeighborhoodCandidateItemsStrategy();
//EasyMock.replay(dataModel);
FastIDSet candidateItems = strategy.GetCandidateItems(123L, prefArrayOfUser123, (IDataModel)dataModelMock.MockInstance);
Assert.AreEqual(1, candidateItems.Count());
Assert.True(candidateItems.Contains(2L));
dataModelMock.Verify(); // EasyMock.verify(dataModel);
}
/// Sets temporary preferences for a given anonymous user.
public void SetTempPrefs(IPreferenceArray prefs, long anonymousUserID)
{
//Preconditions.checkArgument(prefs != null && prefs.Length() > 0, "prefs is null or empty");
this.tempPrefs[anonymousUserID] = prefs;
FastIDSet userPrefItemIDs = new FastIDSet();
for (int i = 0; i < prefs.Length(); i++)
{
userPrefItemIDs.Add(prefs.GetItemID(i));
}
this.prefItemIDs[anonymousUserID] = userPrefItemIDs;
}
public FastIDSet GetRelevantItemsIDs(long userID,
int at,
double relevanceThreshold,
IDataModel dataModel) {
IPreferenceArray prefs = dataModel.GetPreferencesFromUser(userID);
FastIDSet relevantItemIDs = new FastIDSet(at);
prefs.SortByValueReversed();
for (int i = 0; i < prefs.Length() && relevantItemIDs.Count() < at; i++) {
if (prefs.GetValue(i) >= relevanceThreshold) {
relevantItemIDs.Add(prefs.GetItemID(i));
}
}
return relevantItemIDs;
}
private static long setBits(FastIDSet modelSet, IList <IRecommendedItem> items, int max)
{
long maxItem = -1;
for (int i = 0; i < items.Count && i < max; i++)
{
long itemID = items[i].GetItemID();
modelSet.Add(itemID);
if (itemID > maxItem)
{
maxItem = itemID;
}
}
return(maxItem);
}
private static long setBits(FastIDSet modelSet, IPreferenceArray prefs, int max)
{
long maxItem = -1;
for (int i = 0; i < prefs.Length() && i < max; i++)
{
long itemID = prefs.GetItemID(i);
modelSet.Add(itemID);
if (itemID > maxItem)
{
maxItem = itemID;
}
}
return(maxItem);
}
public virtual long[] AllSimilarItemIDs(long itemID)
{
FastIDSet allSimilarItemIDs = new FastIDSet();
var allItemIDs = dataModel.GetItemIDs();
while (allItemIDs.MoveNext())
{
long possiblySimilarItemID = allItemIDs.Current;
if (!Double.IsNaN(ItemSimilarity(itemID, possiblySimilarItemID)))
{
allSimilarItemIDs.Add(possiblySimilarItemID);
}
}
return(allSimilarItemIDs.ToArray());
}
private void addSomeOf(FastIDSet possibleItemIDs, FastIDSet itemIDs)
{
if (itemIDs.Count() > maxItemsPerUser)
{
var it =
new SamplinglongPrimitiveIterator(itemIDs.GetEnumerator(), (double)maxItemsPerUser / itemIDs.Count());
while (it.MoveNext())
{
possibleItemIDs.Add(it.Current);
}
}
else
{
possibleItemIDs.AddAll(itemIDs);
}
}
public static IDataModel getBooleanDataModel(long[] userIDs, bool[][] prefs)
{
FastByIDMap<FastIDSet> result = new FastByIDMap<FastIDSet>();
for (int i = 0; i < userIDs.Length; i++) {
FastIDSet prefsSet = new FastIDSet();
for (int j = 0; j < prefs[i].Length; j++) {
if (prefs[i][j]) {
prefsSet.Add(j);
}
}
if (!prefsSet.IsEmpty()) {
result.Put(userIDs[i], prefsSet);
}
}
return new GenericBooleanPrefDataModel(result);
}
public static FastByIDMap <FastIDSet> toDataMap(FastByIDMap <IPreferenceArray> data)
{
var res = new FastByIDMap <FastIDSet>(data.Count());
foreach (var entry in data.EntrySet())
{
IPreferenceArray prefArray = entry.Value;
int size = prefArray.Length();
FastIDSet itemIDs = new FastIDSet(size);
for (int i = 0; i < size; i++)
{
itemIDs.Add(prefArray.GetItemID(i));
}
res.Put(entry.Key, itemIDs);
}
return(res);
}
public FastIDSet GetRelevantItemsIDs(long userID,
int at,
double relevanceThreshold,
IDataModel dataModel)
{
IPreferenceArray prefs = dataModel.GetPreferencesFromUser(userID);
FastIDSet relevantItemIDs = new FastIDSet(at);
prefs.SortByValueReversed();
for (int i = 0; i < prefs.Length() && relevantItemIDs.Count() < at; i++)
{
if (prefs.GetValue(i) >= relevanceThreshold)
{
relevantItemIDs.Add(prefs.GetItemID(i));
}
}
return(relevantItemIDs);
}
public List <IRecommendedItem> RecommendedBecause(long userID, long itemID, int howMany)
{
//Preconditions.checkArgument(howMany >= 1, "howMany must be at least 1");
IDataModel model = GetDataModel();
TopItems.IEstimator <long> estimator = new RecommendedBecauseEstimator(this, userID, itemID);
IPreferenceArray prefs = model.GetPreferencesFromUser(userID);
int size = prefs.Length();
FastIDSet allUserItems = new FastIDSet(size);
for (int i = 0; i < size; i++)
{
allUserItems.Add(prefs.GetItemID(i));
}
allUserItems.Remove(itemID);
return(TopItems.GetTopItems(howMany, allUserItems.GetEnumerator(), null, estimator));
}
public static IDataModel getBooleanDataModel(long[] userIDs, bool[][] prefs)
{
FastByIDMap <FastIDSet> result = new FastByIDMap <FastIDSet>();
for (int i = 0; i < userIDs.Length; i++)
{
FastIDSet prefsSet = new FastIDSet();
for (int j = 0; j < prefs[i].Length; j++)
{
if (prefs[i][j])
{
prefsSet.Add(j);
}
}
if (!prefsSet.IsEmpty())
{
result.Put(userIDs[i], prefsSet);
}
}
return(new GenericBooleanPrefDataModel(result));
}
public override long[] GetUserNeighborhood(long userID)
{
IDataModel dataModel = getDataModel();
FastIDSet neighborhood = new FastIDSet();
var usersIterable = SamplinglongPrimitiveIterator.MaybeWrapIterator(dataModel
.GetUserIDs(), getSamplingRate());
IUserSimilarity userSimilarityImpl = getUserSimilarity();
while (usersIterable.MoveNext())
{
long otherUserID = usersIterable.Current;
if (userID != otherUserID)
{
double theSimilarity = userSimilarityImpl.UserSimilarity(userID, otherUserID);
if (!Double.IsNaN(theSimilarity) && theSimilarity >= threshold)
{
neighborhood.Add(otherUserID);
}
}
}
return(neighborhood.ToArray());
}
public override long[] GetUserNeighborhood(long userID) {
IDataModel dataModel = getDataModel();
FastIDSet neighborhood = new FastIDSet();
var usersIterable = SamplinglongPrimitiveIterator.MaybeWrapIterator(dataModel
.GetUserIDs(), getSamplingRate());
IUserSimilarity userSimilarityImpl = getUserSimilarity();
while (usersIterable.MoveNext()) {
long otherUserID = usersIterable.Current;
if (userID != otherUserID) {
double theSimilarity = userSimilarityImpl.UserSimilarity(userID, otherUserID);
if (!Double.IsNaN(theSimilarity) && theSimilarity >= threshold) {
neighborhood.Add(otherUserID);
}
}
}
return neighborhood.ToArray();
}
private static long setBits(FastIDSet modelSet, IList<IRecommendedItem> items, int max) {
long maxItem = -1;
for (int i = 0; i < items.Count && i < max; i++) {
long itemID = items[i].GetItemID();
modelSet.Add(itemID);
if (itemID > maxItem) {
maxItem = itemID;
}
}
return maxItem;
}
private void addSomeOf(FastIDSet possibleItemIDs, FastIDSet itemIDs) {
if (itemIDs.Count() > maxItemsPerUser) {
var it =
new SamplinglongPrimitiveIterator(itemIDs.GetEnumerator(), (double) maxItemsPerUser / itemIDs.Count() );
while (it.MoveNext()) {
possibleItemIDs.Add(it.Current);
}
} else {
possibleItemIDs.AddAll(itemIDs);
}
}
public static FastByIDMap<FastIDSet> toDataMap(FastByIDMap<IPreferenceArray> data) {
var res = new FastByIDMap<FastIDSet>( data.Count() );
foreach (var entry in data.EntrySet()) {
IPreferenceArray prefArray = entry.Value;
int size = prefArray.Length();
FastIDSet itemIDs = new FastIDSet(size);
for (int i = 0; i < size; i++) {
itemIDs.Add(prefArray.GetItemID(i));
}
res.Put( entry.Key, itemIDs );
}
return res;
}
private static long setBits(FastIDSet modelSet, IPreferenceArray prefs, int max) {
long maxItem = -1;
for (int i = 0; i < prefs.Length() && i < max; i++) {
long itemID = prefs.GetItemID(i);
modelSet.Add(itemID);
if (itemID > maxItem) {
maxItem = itemID;
}
}
return maxItem;
}
public override FastIDSet GetItemIDsFromUser(long userID) {
IPreferenceArray prefs = GetPreferencesFromUser(userID);
int size = prefs.Length();
FastIDSet result = new FastIDSet(size);
for (int i = 0; i < size; i++) {
result.Add(prefs.GetItemID(i));
}
return result;
}
/// <summary>
/// Creates a new <see cref="GenericDataModel"/> from the given users (and their preferences). This
/// <see cref="IDataModel"/> retains all this information in memory and is effectively immutable.
/// </summary>
/// <param name="userData">users to include; (see also <see cref="GenericDataModel.ToDataMap(FastByIDMap, bool)"/>)</param>
/// <param name="timestamps">timestamps optionally, provided timestamps of preferences as milliseconds since the epoch. User IDs are mapped to maps of item IDs to long timestamps.</param>
public GenericDataModel(FastByIDMap <IPreferenceArray> userData, FastByIDMap <FastByIDMap <DateTime?> > timestamps)
{
//Preconditions.checkArgument(userData != null, "userData is null");
this.preferenceFromUsers = userData;
FastByIDMap <IList <IPreference> > prefsForItems = new FastByIDMap <IList <IPreference> >();
FastIDSet itemIDSet = new FastIDSet();
int currentCount = 0;
float maxPrefValue = float.NegativeInfinity;
float minPrefValue = float.PositiveInfinity;
foreach (var entry in preferenceFromUsers.EntrySet())
{
IPreferenceArray prefs = entry.Value;
prefs.SortByItem();
foreach (IPreference preference in prefs)
{
long itemID = preference.GetItemID();
itemIDSet.Add(itemID);
var prefsForItem = prefsForItems.Get(itemID);
if (prefsForItem == null)
{
prefsForItem = new List <IPreference>(2);
prefsForItems.Put(itemID, prefsForItem);
}
prefsForItem.Add(preference);
float value = preference.GetValue();
if (value > maxPrefValue)
{
maxPrefValue = value;
}
if (value < minPrefValue)
{
minPrefValue = value;
}
}
if (++currentCount % 10000 == 0)
{
log.Info("Processed {0} users", currentCount);
}
}
log.Info("Processed {0} users", currentCount);
setMinPreference(minPrefValue);
setMaxPreference(maxPrefValue);
this.itemIDs = itemIDSet.ToArray();
itemIDSet = null; // Might help GC -- this is big
Array.Sort(itemIDs);
this.preferenceForItems = ToDataMap(prefsForItems, false);
foreach (var entry in preferenceForItems.EntrySet())
{
entry.Value.SortByUser();
}
this.userIDs = new long[userData.Count()];
int i = 0;
foreach (var v in userData.Keys)
{
userIDs[i++] = v;
}
Array.Sort(userIDs);
this.timestamps = timestamps;
}
/// Sets temporary preferences for a given anonymous user.
public void SetTempPrefs(IPreferenceArray prefs, long anonymousUserID) {
//Preconditions.checkArgument(prefs != null && prefs.Length() > 0, "prefs is null or empty");
this.tempPrefs[anonymousUserID] = prefs;
FastIDSet userPrefItemIDs = new FastIDSet();
for (int i = 0; i < prefs.Length(); i++) {
userPrefItemIDs.Add(prefs.GetItemID(i));
}
this.prefItemIDs[anonymousUserID] = userPrefItemIDs;
}
public void testReservedValues()
{
FastIDSet set = new FastIDSet();
try {
set.Add(Int64.MinValue);
Assert.Fail("Should have thrown IllegalArgumentException");
} catch (ArgumentException iae) { //IllegalArgumentException
// good
}
Assert.False(set.Contains(Int64.MinValue));
try {
set.Add(long.MaxValue);
Assert.Fail("Should have thrown IllegalArgumentException");
} catch (ArgumentException iae) {
// good
}
Assert.False(set.Contains(long.MaxValue));
}
public void testSizeEmpty()
{
FastIDSet set = new FastIDSet();
Assert.AreEqual(0, set.Count());
Assert.True(set.IsEmpty());
set.Add(1);
Assert.AreEqual(1, set.Count());
Assert.False(set.IsEmpty());
set.Remove(1);
Assert.AreEqual(0, set.Count());
Assert.True(set.IsEmpty());
}
private static FastIDSet buildTestFastSet()
{
FastIDSet set = new FastIDSet();
set.Add(1);
set.Add(2);
set.Add(3);
return set;
}
public void testVersusHashSet()
{
FastIDSet actual = new FastIDSet(1);
var expected = new HashSet<int>(); //1000000
var r = RandomUtils.getRandom();
for (int i = 0; i < 1000000; i++) {
double d = r.nextDouble();
var key = r.nextInt(100);
if (d < 0.4) {
Assert.AreEqual(expected.Contains(key), actual.Contains(key));
} else {
if (d < 0.7) {
Assert.AreEqual(expected.Add(key), actual.Add(key));
} else {
Assert.AreEqual(expected.Remove(key), actual.Remove(key));
}
Assert.AreEqual(expected.Count, actual.Count() );
Assert.AreEqual(expected.Count==0, actual.IsEmpty());
}
}
}