public void ReleaseRef()
{
if (null != _assets)
{
foreach (var asset in _assets)
{
Logger.LogVerbose("BundlerMessenger::ReleaseRef: {0}, loader: {1}", this, asset.Loader);
asset.Release();
Logger.LogVerbose("BundlerMessenger::ReleaseRef: {0}, loader: {1}, finished!", this, asset.Loader);
}
HashSetPool <AssetBase> .Return(_assets);
}
if (null != _typedAssets)
{
foreach (var kv in _typedAssets)
{
Logger.LogVerbose("BundlerMessenger::ReleaseRef: {0}, loader: {1}", this, kv.Value.Loader);
kv.Value.Release();
Logger.LogVerbose("BundlerMessenger::ReleaseRef: {0}, loader: {1}, finished!", this, kv.Value.Loader);
}
DictionaryPool <Type, AssetBase> .Return(_typedAssets);
}
Messengers.Remove(this);
}
void OnMeshDataReceived(MeshTaskInfo info)
{
MeshData meshData = info.meshData;
//主线程回调
isWaitForData = false;
mesh = meshData.CreateMesh();// TODO pool mesh
DictionaryPool <MeshData> .Return(meshData);
hasMesh = true;
updateCallback();
}
/// <summary>
/// The last step for loading data.
/// In this step, prototype references are being resolved for this serialized data and their sub data objects.
/// </summary>
/// <param name="prototypes">Prototypes to use for remapping</param>
/// <param name="errors"></param>
public void ResolveReferenceFields(List <IPrototype> prototypes, List <ParsingError> errors, PrototypeParserState state)
{
Dictionary <string, object> updates = DictionaryPool <string, object> .Get();
try
{
foreach (var field in fields)
{
var @ref = field.Value as SerializedPrototypeReference;
if (!ReferenceEquals(@ref, null))
{
updates.Add(field.Key, @ref.Resolve(prototypes));
}
var sub = field.Value as SerializedData;
if (!ReferenceEquals(sub, null))
{
sub.ResolveReferenceFields(prototypes, errors, state);
}
var col = field.Value as SerializedCollectionData;
if (!ReferenceEquals(col, null))
{
col.ResolveReferenceFieldsAndSubData(prototypes, errors, state);
}
}
// Write updates
foreach (var update in updates)
{
this.fields[update.Key] = update.Value;
}
}
finally
{
DictionaryPool <string, object> .Return(updates);
}
}
/// <summary>
/// The last step for loading data.
/// In this step, root references are being resolved for this serialized data and their sub data objects.
/// </summary>
/// <param name="referenceables">Root objects to use for remapping</param>
/// <param name="filename">Only used for error reporting</param>
public void ResolveReferenceFields(string filename, List <ISerializableRoot> referenceables, List <SerializerError> errors, XMLSerializerParams parameters)
{
Dictionary <string, object> updates = DictionaryPool <string, object> .Get();
try
{
foreach (var field in fields)
{
var @ref = field.Value as SerializedRootObjectReference;
if (!ReferenceEquals(@ref, null))
{
updates.Add(field.Key, @ref.Resolve(referenceables));
}
var sub = field.Value as SerializedData;
if (!ReferenceEquals(sub, null))
{
sub.ResolveReferenceFields(filename, referenceables, errors, parameters);
}
var col = field.Value as SerializedCollectionData;
if (!ReferenceEquals(col, null))
{
col.ResolveReferenceFieldsAndSubData(filename, referenceables, errors, parameters);
}
}
// Write updates
foreach (var update in updates)
{
this.fields[update.Key] = update.Value;
}
}
finally
{
DictionaryPool <string, object> .Return(updates);
}
}
/// <summary>
/// Runs distribution algorithm on input.
/// </summary>
/// <param name="input"></param>
/// <param name="output"></param>
/// <param name="available">The amount you want to distribute</param>
/// <returns>The overflow</returns>
public static float ReqDistribute(List <DistributionInput> input, List <DistributionResult> output, float available)
{
List <TObject> tmp = ListPool <TObject> .Get();
List <TObject> objs = ListPool <TObject> .Get();
Dictionary <TObject, float> distributed = DictionaryPool <TObject, float> .Get();
Dictionary <TObject, float> requested = DictionaryPool <TObject, float> .Get();
float availablePrev = -available;
// Parse
foreach (var inp in input)
{
if (Mathf.Approximately(inp.requestedAmount, 0))
{
continue;
}
distributed.Add(inp.obj, 0);
requested.Add(inp.obj, inp.requestedAmount);
objs.Add(inp.obj);
}
int panic = 0;
while (available > 0 && !Mathf.Approximately(available, availablePrev) && requested.Count > 0)
{
availablePrev = available;
float perInput = available / (float)requested.Count;
foreach (var obj in objs)
{
float alreadyDistributed = distributed[obj];
float stillRequested = requested[obj];
float distributing = Mathf.Min(stillRequested, perInput);
distributed[obj] += distributing;
requested[obj] -= distributing;
available -= distributing;
if (Mathf.Approximately(requested[obj], 0))
{
tmp.Add(obj);
}
}
foreach (var obj in tmp)
{
objs.Remove(obj);
requested.Remove(obj);
}
tmp.Clear();
panic++;
if (panic > 1000)
{
Debug.LogError("Distribution alrogithm triggered panic exit!");
return(available);
}
}
// Write back
foreach (var kvp in distributed)
{
output.Add(new DistributionResult()
{
amount = kvp.Value,
obj = kvp.Key
});
}
DictionaryPool <TObject, float> .Return(distributed);
DictionaryPool <TObject, float> .Return(requested);
ListPool <TObject> .Return(tmp);
ListPool <TObject> .Return(objs);
return(available);
}
public SuggestResponseDto[] SuggestForV2(int id, int limit, string key, string value)
{
var accounts = _repo.Accounts;
var uniqueLikesOfTarget = accounts[id].GetLikesFrom().ToHashSet();
ISuggestFilter filter = null;
if (key != null)
{
filter = _factory.CreateFilter(key, value);
if (filter == null)
{
return(new SuggestResponseDto[0]);
}
}
var likersData = SimilarityDictionaryPool.Rent();
foreach (var likeeId in uniqueLikesOfTarget)
{
long targetTsSum = 0;
long targetTsCount = 0;
var likersOfTargetLike = accounts[likeeId].GetLikesToWithTs();
var l = likersOfTargetLike.GetLength(0);
for (int i = 0; i < l; i++)
{
var likerId = likersOfTargetLike[i, 0];
var ts = likersOfTargetLike[i, 1];
if (likerId == id)
{
targetTsCount++;
targetTsSum += ts;
}
else if (filter == null || filter.IsOk(likerId))
{
if (!likersData.ContainsKey(likerId))
{
likersData[likerId] = CounterPool.Rent();
}
likersData[likerId].AddTs(ts);
}
}
var targetTs = (double)(targetTsSum / targetTsCount);
foreach (var counter in likersData.Values)
{
counter.Calculate(targetTs);
}
}
if (likersData.Count == 0)
{
return(new SuggestResponseDto[0]);
}
var count = likersData.Count;
var sortedIdsBySimilarity = Pool.Rent(count);
var index = 0;
foreach (var pair in likersData)
{
sortedIdsBySimilarity[index] = pair;
index++;
}
Array.Sort(sortedIdsBySimilarity, 0, count, DescSimilarityComparer);
var allExceptLikes = new List <int>();
for (int i = 0; i < count; i++)
{
var likesFromCurrent = accounts[sortedIdsBySimilarity[i].Key].GetLikesFrom();
Array.Sort(likesFromCurrent, _descComparer);
foreach (var like in likesFromCurrent)
{
if (!uniqueLikesOfTarget.Contains(like))
{
allExceptLikes.Add(like);
uniqueLikesOfTarget.Add(like);
}
}
if (allExceptLikes.Count >= limit)
{
break;
}
}
Pool.Return(sortedIdsBySimilarity);
CounterPool.Return(sortedIdsBySimilarity.Take(count).Select(x => x.Value));
SimilarityDictionaryPool.Return(likersData);
return(allExceptLikes.Take(limit).Select(x => _converter.Convert(x)).ToArray());
}
