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Diffstat (limited to 'ml/SamplesBuffer.cc')
-rw-r--r-- | ml/SamplesBuffer.cc | 150 |
1 files changed, 150 insertions, 0 deletions
diff --git a/ml/SamplesBuffer.cc b/ml/SamplesBuffer.cc new file mode 100644 index 0000000000..d276c6e094 --- /dev/null +++ b/ml/SamplesBuffer.cc @@ -0,0 +1,150 @@ +// SPDX-License-Identifier: GPL-3.0-or-later +// +#include "SamplesBuffer.h" + +#include <fstream> +#include <sstream> +#include <string> + +void Sample::print(std::ostream &OS) const { + for (size_t Idx = 0; Idx != NumDims - 1; Idx++) + OS << CNs[Idx] << ", "; + + OS << CNs[NumDims - 1]; +} + +void SamplesBuffer::print(std::ostream &OS) const { + for (size_t Idx = Preprocessed ? (DiffN + (SmoothN - 1) + (LagN)) : 0; + Idx != NumSamples; Idx++) { + Sample S = Preprocessed ? getPreprocessedSample(Idx) : getSample(Idx); + OS << S << std::endl; + } +} + +std::vector<Sample> SamplesBuffer::getPreprocessedSamples() const { + std::vector<Sample> V; + + for (size_t Idx = Preprocessed ? (DiffN + (SmoothN - 1) + (LagN)) : 0; + Idx != NumSamples; Idx++) { + Sample S = Preprocessed ? getPreprocessedSample(Idx) : getSample(Idx); + V.push_back(S); + } + + return V; +} + +void SamplesBuffer::diffSamples() { + // Panda's DataFrame default behaviour is to subtract each element from + // itself. For us `DiffN = 0` means "disable diff-ing" when preprocessing + // the samples buffer. This deviation will make it easier for us to test + // the KMeans implementation. + if (DiffN == 0) + return; + + for (size_t Idx = 0; Idx != (NumSamples - DiffN); Idx++) { + size_t High = (NumSamples - 1) - Idx; + size_t Low = High - DiffN; + + Sample LHS = getSample(High); + Sample RHS = getSample(Low); + + LHS.diff(RHS); + } +} + +void SamplesBuffer::smoothSamples() { + // Holds the mean value of each window + CalculatedNumber *AccCNs = new CalculatedNumber[NumDimsPerSample](); + Sample Acc(AccCNs, NumDimsPerSample); + + // Used to avoid clobbering the accumulator when moving the window + CalculatedNumber *TmpCNs = new CalculatedNumber[NumDimsPerSample](); + Sample Tmp(TmpCNs, NumDimsPerSample); + + CalculatedNumber Factor = (CalculatedNumber) 1 / SmoothN; + + // Calculate the value of the 1st window + for (size_t Idx = 0; Idx != std::min(SmoothN, NumSamples); Idx++) { + Tmp.add(getSample(NumSamples - (Idx + 1))); + } + + Acc.add(Tmp); + Acc.scale(Factor); + + // Move the window and update the samples + for (size_t Idx = NumSamples; Idx != (DiffN + SmoothN - 1); Idx--) { + Sample S = getSample(Idx - 1); + + // Tmp <- Next window (if any) + if (Idx >= (SmoothN + 1)) { + Tmp.diff(S); + Tmp.add(getSample(Idx - (SmoothN + 1))); + } + + // S <- Acc + S.copy(Acc); + + // Acc <- Tmp + Acc.copy(Tmp); + Acc.scale(Factor); + } + + delete[] AccCNs; + delete[] TmpCNs; +} + +void SamplesBuffer::lagSamples() { + if (LagN == 0) + return; + + for (size_t Idx = NumSamples; Idx != LagN; Idx--) { + Sample PS = getPreprocessedSample(Idx - 1); + PS.lag(getSample(Idx - 1), LagN); + } +} + +std::vector<DSample> SamplesBuffer::preprocess() { + assert(Preprocessed == false); + + std::vector<DSample> DSamples; + size_t OutN = NumSamples; + + // Diff + if (DiffN >= OutN) + return DSamples; + OutN -= DiffN; + diffSamples(); + + // Smooth + if (SmoothN == 0 || SmoothN > OutN) + return DSamples; + OutN -= (SmoothN - 1); + smoothSamples(); + + // Lag + if (LagN >= OutN) + return DSamples; + OutN -= LagN; + lagSamples(); + + DSamples.reserve(OutN); + Preprocessed = true; + + uint32_t MaxMT = std::numeric_limits<uint32_t>::max(); + uint32_t CutOff = static_cast<double>(MaxMT) * SamplingRatio; + + for (size_t Idx = NumSamples - OutN; Idx != NumSamples; Idx++) { + if (RandNums[Idx] > CutOff) + continue; + + DSample DS; + DS.set_size(NumDimsPerSample * (LagN + 1)); + + const Sample PS = getPreprocessedSample(Idx); + PS.initDSample(DS); + + DSamples.push_back(DS); + } + + return DSamples; +} |