public void WritePackedUInt(uint value, int context)
{
int bucket = NetworkCompressionUtils.CalculateBucket(value);
uint offset = NetworkCompressionConstants.k_BucketOffsets[bucket];
int bits = NetworkCompressionConstants.k_BucketSizes[bucket];
WritePackedNibble((uint)bucket, context);
if (bits > 0)
{
WriteRawBits(value - offset, bits);
}
}
public void WritePackedUInt(uint value, int context)
{
if (m_Capture != null)
{
m_Capture.AddUInt(context, value);
}
int bucket = NetworkCompressionUtils.CalculateBucket(value);
uint offset = NetworkCompressionConstants.k_BucketOffsets[bucket];
int bits = NetworkCompressionConstants.k_BucketSizes[bucket];
ushort encodeEntry = m_Model.encodeTable[context, bucket];
WriteRawBitsInternal((uint)(encodeEntry >> 8), encodeEntry & 0xFF);
WriteRawBitsInternal(value - offset, bits);
FlushBits();
}
public NetworkCompressionModel(byte[] modelData)
{
if (modelData == null)
{
modelData = m_DefaultModelData;
}
int numContexts = NetworkConfig.maxContexts;
int alphabetSize = 16;
byte[,] symbolLengths = new byte[numContexts, alphabetSize];
int readOffset = 0;
{
// default model
int defaultModelAlphabetSize = modelData[readOffset++];
Debug.Assert(defaultModelAlphabetSize == alphabetSize);
for (int i = 0; i < alphabetSize; i++)
{
byte length = modelData[readOffset++];
for (int context = 0; context < numContexts; context++)
{
symbolLengths[context, i] = length;
}
}
// additional models
int numModels = modelData[readOffset] | (modelData[readOffset + 1] << 8);
readOffset += 2;
for (int model = 0; model < numModels; model++)
{
int context = modelData[readOffset] | (modelData[readOffset + 1] << 8);
readOffset += 2;
int modelAlphabetSize = modelData[readOffset++];
Debug.Assert(modelAlphabetSize == alphabetSize);
for (int i = 0; i < alphabetSize; i++)
{
byte length = modelData[readOffset++];
symbolLengths[context, i] = length;
}
}
}
// generate tables
encodeTable = new ushort[numContexts, alphabetSize];
decodeTable = new ushort[numContexts, 1 << NetworkCompressionConstants.k_MaxHuffmanSymbolLength];
var tmpSymbolLengths = new byte[alphabetSize];
var tmpSymbolDecodeTable = new ushort[1 << NetworkCompressionConstants.k_MaxHuffmanSymbolLength];
var symbolCodes = new byte[alphabetSize];
for (int context = 0; context < numContexts; context++)
{
for (int i = 0; i < alphabetSize; i++)
{
tmpSymbolLengths[i] = symbolLengths[context, i];
}
NetworkCompressionUtils.GenerateHuffmanCodes(symbolCodes, 0, tmpSymbolLengths, 0, alphabetSize, NetworkCompressionConstants.k_MaxHuffmanSymbolLength);
NetworkCompressionUtils.GenerateHuffmanDecodeTable(tmpSymbolDecodeTable, 0, tmpSymbolLengths, symbolCodes, alphabetSize, NetworkCompressionConstants.k_MaxHuffmanSymbolLength);
for (int i = 0; i < alphabetSize; i++)
{
encodeTable[context, i] = (ushort)((symbolCodes[i] << 8) | symbolLengths[context, i]);
}
for (int i = 0; i < (1 << NetworkCompressionConstants.k_MaxHuffmanSymbolLength); i++)
{
decodeTable[context, i] = tmpSymbolDecodeTable[i];
}
}
this.modelData = modelData;
}
public byte[] AnalyzeAndGenerateModel()
{
int alphabetSize = 16;
var model = m_Model;
int numContexts = uintData.Length;
const int numBuckets = NetworkCompressionConstants.k_NumBuckets;
var stringWriter = new StringWriter();
int[] histogram = new int[alphabetSize];
int[] safeHistogram = new int[alphabetSize];
int[,] histogram2 = new int[alphabetSize, alphabetSize];
int[,] safeHistogram2 = new int[alphabetSize, alphabetSize];
Directory.CreateDirectory("capture");
stringWriter.WriteLine("NetworkProfile:");
var combinedSOAFile = System.IO.File.OpenWrite("capture/combined_soa.dat");
List <byte> modelData = new List <byte>();
modelData.Add(16);
modelData.AddRange(new byte[] { 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 6, 6, 6 });
int numContextsOffset = modelData.Count;
modelData.Add(0); //num contexts
modelData.Add(0);
int totalNumValues = 0;
int gammaTotalCost = 0;
int currentTotalCost = 0;
int optimizedTotalCost = 0;
double entropyTotalCost = 0.0;
double entropy2TotalCost = 0.0;
int numUsedContexts = 0;
List <string> optimizedTrees = new List <string>();
for (int context = 0; context < numContexts; context++)
{
if (uintData[context].Count == 0 && nibbleData[context].Count == 0)
{
continue;
}
bool isUInt = uintData[context].Count > 0;
int numValues = 0;
if (isUInt)
{
Debug.Assert(nibbleData[context].Count == 0);
alphabetSize = numBuckets;
numValues = uintData[context].Count;
}
else
{
Debug.Assert(uintData[context].Count == 0);
Debug.Assert(nibbleData[context].Count > 0);
alphabetSize = 16;
numValues = nibbleData[context].Count;
}
// build histograms
for (int i = 0; i < numBuckets; i++)
{
histogram[i] = 0;
}
for (int i = 0; i < alphabetSize; i++)
{
for (int j = 0; j < alphabetSize; j++)
{
histogram2[i, j] = 0;
}
}
combinedSOAFile.WriteByte((byte)(numValues & 0xFF));
combinedSOAFile.WriteByte((byte)((numValues >> 8) & 0xFF));
combinedSOAFile.WriteByte((byte)((numValues >> 16) & 0xFF));
combinedSOAFile.WriteByte((byte)((numValues >> 24) & 0xFF));
var contextFile = System.IO.File.OpenWrite("capture/context" + context);
int gammaCost = 0;
int prevSymbol = 0;
for (int i = 0; i < numValues; i++)
{
uint value;
if (isUInt)
{
value = uintData[context][i];
int bucket = NetworkCompressionUtils.CalculateBucket(value);
histogram[bucket]++;
histogram2[prevSymbol, bucket]++;
prevSymbol = bucket;
}
else
{
value = nibbleData[context][i];
histogram[value]++;
histogram2[prevSymbol, value]++;
prevSymbol = (int)value;
}
gammaCost += NetworkCompressionUtils.CalculateNumGammaBits(value);
combinedSOAFile.WriteByte((byte)(value & 0xFF));
combinedSOAFile.WriteByte((byte)((value >> 8) & 0xFF));
combinedSOAFile.WriteByte((byte)((value >> 16) & 0xFF));
combinedSOAFile.WriteByte((byte)((value >> 24) & 0xFF));
contextFile.WriteByte((byte)(value & 0xFF));
contextFile.WriteByte((byte)((value >> 8) & 0xFF));
contextFile.WriteByte((byte)((value >> 16) & 0xFF));
contextFile.WriteByte((byte)((value >> 24) & 0xFF));
}
contextFile.Close();
// safe histogram where all values have at least one occurrence
int safeNumValues = numValues;
for (int i = 0; i < alphabetSize; i++)
{
int n = histogram[i];
if (n == 0)
{
n = 1;
safeNumValues++;
}
safeHistogram[i] = n;
}
byte[] optimizedSymbolLengths = new byte[alphabetSize];
NetworkCompressionUtils.GenerateLengthLimitedHuffmanCodeLengths(optimizedSymbolLengths, 0, safeHistogram, alphabetSize, NetworkCompressionConstants.k_MaxHuffmanSymbolLength);
modelData.Add((byte)(context & 0xFF));
modelData.Add((byte)(context >> 8));
modelData.Add((byte)alphabetSize);
for (int i = 0; i < alphabetSize; i++)
{
modelData.Add((byte)optimizedSymbolLengths[i]);
}
int currentCost = 0;
int optimizedCost = 0;
double entropyCost = 0.0;
for (int i = 0; i < alphabetSize; i++)
{
int n = histogram[i];
if (n > 0)
{
int currentBitLength = model.encodeTable[context, i] & 0xFF;
int optimizedBitLength = optimizedSymbolLengths[i] & 0xFF;
currentCost += n * currentBitLength;
optimizedCost += n * optimizedBitLength;
double p = n / (double)safeNumValues;
entropyCost += n * -Math.Log(p, 2.0);
if (isUInt)
{
currentCost += n * NetworkCompressionConstants.k_BucketSizes[i];
optimizedCost += n * NetworkCompressionConstants.k_BucketSizes[i];
entropyCost += n * NetworkCompressionConstants.k_BucketSizes[i];
}
}
}
double entropy2Cost = 0.0;
for (int i = 0; i < alphabetSize; i++)
{
int total = 0;
for (int j = 0; j < alphabetSize; j++)
{
int n = histogram2[i, j];
if (n == 0)
{
n = 1;
}
safeHistogram2[i, j] = n;
total += n;
}
for (int j = 0; j < alphabetSize; j++)
{
int n = histogram2[i, j];
if (n > 0)
{
double p = n / (double)total;
entropy2Cost += n * -Math.Log(p, 2.0);
if (isUInt)
{
entropy2Cost += n * NetworkCompressionConstants.k_BucketSizes[j];
}
}
}
}
totalNumValues += numValues;
gammaTotalCost += gammaCost;
currentTotalCost += currentCost;
optimizedTotalCost += optimizedCost;
entropyTotalCost += entropyCost;
entropy2TotalCost += entropy2Cost;
var l = new List <byte>(optimizedSymbolLengths);
string symLengths = string.Join(":", l);
stringWriter.WriteLine("{0,4}: {1,8} {2,8:0.00} {3,8:0.00} {4,8:0.00} {5,8:0.00} {6,8:0.00} {7}", context, numValues, gammaCost / 8.0f, currentCost / 8.0f, optimizedCost / 8.0f, entropyCost / 8.0, entropy2Cost / 8.0, symLengths);
optimizedTrees.Add("" + string.Format("{0,10:000000}", currentCost - optimizedCost) + " " + symLengths);
numUsedContexts++;
}
optimizedTrees.Sort();
foreach (var l in optimizedTrees)
{
GameDebug.Log(" " + l);
}
stringWriter.WriteLine("Total: {0,8} {1,8:0.00} {2,8:0.00} {3,8:0.00} {4,8:0.00} {5,8:0.00}", totalNumValues, gammaTotalCost / 8.0f, currentTotalCost / 8.0f, optimizedTotalCost / 8.0f, entropyTotalCost / 8.0, entropy2TotalCost / 8.0);
stringWriter.WriteLine("Num used contexts: {0}", numUsedContexts);
GameDebug.Log(stringWriter.ToString());
combinedSOAFile.Close();
System.IO.File.WriteAllBytes("capture/combined_aos.dat", rawData.ToArray());
modelData[numContextsOffset + 0] = (byte)(numUsedContexts & 0xFF);
modelData[numContextsOffset + 1] = (byte)(numUsedContexts >> 8);
return(modelData.ToArray());
}