1 files changed, 128 insertions, 0 deletions
diff --git a/ml/Chart.h b/ml/Chart.h
new file mode 100644
index 000000000..dbd6a910f
--- /dev/null
+++ b/ml/Chart.h
@@ -0,0 +1,128 @@
+// SPDX-License-Identifier: GPL-3.0-or-later
+
+#ifndef ML_CHART_H
+#define ML_CHART_H
+
+#include "Config.h"
+#include "Dimension.h"
+
+#include "ml-private.h"
+#include "json/single_include/nlohmann/json.hpp"
+
+namespace ml
+{
+
+class Chart {
+public:
+    Chart(RRDSET *RS) :
+        RS(RS),
+        MLS()
+     { }
+
+    RRDSET *getRS() const {
+        return RS;
+    }
+
+    bool isAvailableForML() {
+        return rrdset_is_available_for_exporting_and_alarms(RS);
+    }
+
+    void addDimension(Dimension *D) {
+        std::lock_guard<Mutex> L(M);
+        Dimensions[D->getRD()] = D;
+    }
+
+    void removeDimension(Dimension *D) {
+        std::lock_guard<Mutex> L(M);
+        Dimensions.erase(D->getRD());
+    }
+
+    void getModelsAsJson(nlohmann::json &Json) {
+        std::lock_guard<Mutex> L(M);
+
+        for (auto &DP : Dimensions) {
+            Dimension *D = DP.second;
+            nlohmann::json JsonArray = nlohmann::json::array();
+            for (const KMeans &KM : D->getModels()) {
+                nlohmann::json J;
+                KM.toJson(J);
+                JsonArray.push_back(J);
+            }
+
+            Json[getMLDimensionID(D->getRD())] = JsonArray;
+        }
+    }
+
+    void updateBegin() {
+        M.lock();
+        MLS = {};
+    }
+
+    void updateDimension(Dimension *D, bool IsAnomalous) {
+        switch (D->getMLS()) {
+            case MachineLearningStatus::DisabledDueToUniqueUpdateEvery:
+                MLS.NumMachineLearningStatusDisabledUE++;
+                return;
+            case MachineLearningStatus::DisabledDueToExcludedChart:
+                MLS.NumMachineLearningStatusDisabledSP++;
+                return;
+            case MachineLearningStatus::Enabled: {
+                MLS.NumMachineLearningStatusEnabled++;
+
+                switch (D->getMT()) {
+                    case MetricType::Constant:
+                        MLS.NumMetricTypeConstant++;
+                        MLS.NumTrainingStatusTrained++;
+                        MLS.NumNormalDimensions++;
+                        return;
+                    case MetricType::Variable:
+                        MLS.NumMetricTypeVariable++;
+                        break;
+                }
+
+                switch (D->getTS()) {
+                    case TrainingStatus::Untrained:
+                        MLS.NumTrainingStatusUntrained++;
+                        return;
+                    case TrainingStatus::PendingWithoutModel:
+                        MLS.NumTrainingStatusPendingWithoutModel++;
+                        return;
+                    case TrainingStatus::Trained:
+                        MLS.NumTrainingStatusTrained++;
+
+                        MLS.NumAnomalousDimensions += IsAnomalous;
+                        MLS.NumNormalDimensions += !IsAnomalous;
+                        return;
+                    case TrainingStatus::PendingWithModel:
+                        MLS.NumTrainingStatusPendingWithModel++;
+
+                        MLS.NumAnomalousDimensions += IsAnomalous;
+                        MLS.NumNormalDimensions += !IsAnomalous;
+                        return;
+                }
+
+                return;
+            }
+        }
+    }
+
+    void updateEnd() {
+        M.unlock();
+    }
+
+    MachineLearningStats getMLS() {
+        std::lock_guard<Mutex> L(M);
+        return MLS;
+    }
+
+private:
+    RRDSET *RS;
+    MachineLearningStats MLS;
+
+    Mutex M;
+    std::unordered_map<RRDDIM *, Dimension *> Dimensions;
+};
+
+} // namespace ml
+
+#endif /* ML_CHART_H */