void C4Network2ResChunkData::AddChunkRange(int32_t iStart, int32_t iLength)
{
// security
if (iStart < 0 || iStart + iLength > iChunkCnt || iLength <= 0) return;
// find position
ChunkRange *pRange, *pPrev;
for (pRange = pChunkRanges, pPrev = NULL; pRange; pPrev = pRange, pRange = pRange->Next)
if (pRange->Start >= iStart)
break;
// create new
ChunkRange *pNew = new ChunkRange;
pNew->Start = iStart; pNew->Length = iLength;
// add to list
pNew->Next = pRange;
(pPrev ? pPrev->Next : pChunkRanges) = pNew;
// counts
iPresentChunkCnt += iLength; iChunkRangeCnt++;
// check merges
if (pPrev && MergeRanges(pPrev))
while (MergeRanges(pPrev)) {}
else
while (MergeRanges(pNew)) {}
}
void udtPatternSearchPlugIn::FinishDemoAnalysis()
{
if(_analyzers.GetSize() == 0)
{
return;
}
for(u32 i = 0, analyzerCount = _analyzers.GetSize(); i < analyzerCount; ++i)
{
_analyzers[i]->FinishAnalysis();
}
// If we only have 1 analyzer, we don't need to do any sorting.
if(_analyzers.GetSize() == 1)
{
MergeRanges(CutSections, _analyzers[0]->CutSections);
return;
}
//
// Create a list with all the cut sections.
//
udtVMArray<CutSection> tempCutSections(1 << 16, "CutByPatternPlugIn::FinishDemoAnalysis::TempCutSectionsArray");
for(u32 i = 0, analyzerCount = _analyzers.GetSize(); i < analyzerCount; ++i)
{
udtPatternSearchAnalyzerBase* const analyzer = _analyzers[i];
for(u32 j = 0, cutCount = analyzer->CutSections.GetSize(); j < cutCount; ++j)
{
const udtCutSection cut = _analyzers[i]->CutSections[j];
CutSection newCut;
newCut.udtCutSection::operator=(cut);
tempCutSections.Add(newCut);
}
}
//
// Apply sorting pass #1.
//
const u32 cutCount = tempCutSections.GetSize();
qsort(tempCutSections.GetStartAddress(), (size_t)cutCount, sizeof(CutSection), &SortByStartTimeAscending);
//
// Apply sorting pass #2, which must be stable with respect to
// the sorting of pass #1.
//
for(u32 i = 0; i < cutCount; ++i)
{
tempCutSections[i].Order = (int)i;
}
qsort(tempCutSections.GetStartAddress(), (size_t)cutCount, sizeof(CutSection), &StableSortByGameStateIndexAscending);
//
// Create a new list with the sorted data using the final data format
// and merge the sections if asked for it.
//
if((GetInfo().Flags & (u32)udtPatternSearchArgFlags::MergeCutSections) != 0)
{
udtVMArray<udtCutSection> cutSections(1 << 16, "CutByPatternPlugIn::FinishDemoAnalysis::MergedCutSectionsArray");
AppendCutSections(cutSections, tempCutSections);
MergeRanges(CutSections, cutSections);
}
else
{
CutSections.Clear();
AppendCutSections(CutSections, tempCutSections);
}
}
void DecisionStump<MatType>::TrainOnAtt(const arma::rowvec& attribute,
const arma::Row<size_t>& labels)
{
size_t i, count, begin, end;
arma::rowvec sortedSplitAtt = arma::sort(attribute);
arma::uvec sortedSplitIndexAtt = arma::stable_sort_index(attribute.t());
arma::Row<size_t> sortedLabels(attribute.n_elem);
sortedLabels.fill(0);
arma::vec tempSplit;
arma::Row<size_t> tempLabel;
for (i = 0; i < attribute.n_elem; i++)
sortedLabels(i) = labels(sortedSplitIndexAtt(i));
arma::rowvec subCols;
rType mostFreq;
i = 0;
count = 0;
while (i < sortedLabels.n_elem)
{
count++;
if (i == sortedLabels.n_elem - 1)
{
begin = i - count + 1;
end = i;
arma::rowvec zSubCols((sortedLabels.cols(begin, end)).n_elem);
zSubCols.fill(0.0);
subCols = sortedLabels.cols(begin, end) + zSubCols;
mostFreq = CountMostFreq<double>(subCols);
split.resize(split.n_elem + 1);
split(split.n_elem - 1) = sortedSplitAtt(begin);
binLabels.resize(binLabels.n_elem + 1);
binLabels(binLabels.n_elem - 1) = mostFreq;
i++;
}
else if (sortedLabels(i) != sortedLabels(i + 1))
{
if (count < bucketSize)
{
// Test for different values of bucketSize, especially extreme cases.
begin = i - count + 1;
end = begin + bucketSize - 1;
if (end > sortedLabels.n_elem - 1)
end = sortedLabels.n_elem - 1;
}
else
{
begin = i - count + 1;
end = i;
}
arma::rowvec zSubCols((sortedLabels.cols(begin, end)).n_elem);
zSubCols.fill(0.0);
subCols = sortedLabels.cols(begin, end) + zSubCols;
// Find the most frequent element in subCols so as to assign a label to
// the bucket of subCols.
mostFreq = CountMostFreq<double>(subCols);
split.resize(split.n_elem + 1);
split(split.n_elem - 1) = sortedSplitAtt(begin);
binLabels.resize(binLabels.n_elem + 1);
binLabels(binLabels.n_elem - 1) = mostFreq;
i = end + 1;
count = 0;
}
else
i++;
}
// Now trim the split matrix so that buckets one after the after which point
// to the same classLabel are merged as one big bucket.
MergeRanges();
}