Adding upstream version 1.37.1.upstream/1.37.1upstream

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

1 files changed, 94 insertions, 0 deletions

diff --git a/ml/Dimension.h b/ml/Dimension.h
new file mode 100644
index 0000000..3ec56e0
--- /dev/null
+++ b/ml/Dimension.h
@@ -0,0 +1,94 @@
+// SPDX-License-Identifier: GPL-3.0-or-later
+
+#ifndef ML_DIMENSION_H
+#define ML_DIMENSION_H
+
+#include "Query.h"
+#include "Config.h"
+
+#include "ml-private.h"
+
+namespace ml {
+
+enum class MLResult {
+    Success = 0,
+    MissingData,
+    NaN,
+};
+
+static inline std::string getMLDimensionID(RRDDIM *RD) {
+    RRDSET *RS = RD->rrdset;
+
+    std::stringstream SS;
+    SS << rrdset_context(RS) << "|" << rrdset_id(RS) << "|" << rrddim_name(RD);
+    return SS.str();
+}
+
+class Dimension {
+public:
+    Dimension(RRDDIM *RD) :
+        RD(RD),
+        LastTrainedAt(Seconds(0)),
+        Trained(false),
+        ConstantModel(false),
+        AnomalyScore(0.0),
+        AnomalyBit(0)
+    { }
+
+    RRDDIM *getRD() const {
+        return RD;
+    }
+
+    unsigned updateEvery() const {
+        return RD->update_every;
+    }
+
+    time_t latestTime() const {
+        return Query(RD).latestTime();
+    }
+
+    time_t oldestTime() const {
+        return Query(RD).oldestTime();
+    }
+
+    bool isTrained() const {
+        return Trained;
+    }
+
+    bool isAnomalous() const {
+        return AnomalyBit;
+    }
+
+    bool shouldTrain(const TimePoint &TP) const;
+
+    bool isActive() const;
+
+    MLResult trainModel();
+
+    bool predict(CalculatedNumber Value, bool Exists);
+
+    std::pair<bool, double> detect(size_t WindowLength, bool Reset);
+
+    std::array<KMeans, 1> getModels();
+
+private:
+    std::pair<CalculatedNumber *, size_t> getCalculatedNumbers();
+
+public:
+    RRDDIM *RD;
+
+    TimePoint LastTrainedAt;
+    std::atomic<bool> Trained;
+    std::atomic<bool> ConstantModel;
+
+    CalculatedNumber AnomalyScore;
+    std::atomic<bool> AnomalyBit;
+
+    std::vector<CalculatedNumber> CNs;
+    std::array<KMeans, 1> Models;
+    std::mutex Mutex;
+};
+
+} // namespace ml
+
+#endif /* ML_DIMENSION_H */