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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2022-11-30 18:47:00 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2022-11-30 18:47:00 +0000 |
commit | 03bf87dcb06f7021bfb2df2fa8691593c6148aff (patch) | |
tree | e16b06711a2ed77cafb4b7754be0220c3d14a9d7 /ml/kmeans/SamplesBuffer.cc | |
parent | Adding upstream version 1.36.1. (diff) | |
download | netdata-03bf87dcb06f7021bfb2df2fa8691593c6148aff.tar.xz netdata-03bf87dcb06f7021bfb2df2fa8691593c6148aff.zip |
Adding upstream version 1.37.0.upstream/1.37.0
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'ml/kmeans/SamplesBuffer.cc')
-rw-r--r-- | ml/kmeans/SamplesBuffer.cc | 150 |
1 files changed, 0 insertions, 150 deletions
diff --git a/ml/kmeans/SamplesBuffer.cc b/ml/kmeans/SamplesBuffer.cc deleted file mode 100644 index d276c6e0..00000000 --- a/ml/kmeans/SamplesBuffer.cc +++ /dev/null @@ -1,150 +0,0 @@ -// 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; -} |