Revert "add support of threshold line"

This reverts commit f4a5f20313.

analytics/analytics/analytic_types/detector_typing.py

@@ -50,11 +50,3 @@ class AnomalyProcessingResult():
     ):
         self.lower_bound = lower_bound
         self.upper_bound = upper_bound
-@utils.meta.JSONClass
-class ThresholdProcessingResult():
-
-    def __init__(
-        self,
-        threshold: Optional[TimeSeries] = None,
-    ):
-        self.threshold = threshold

analytics/analytics/detectors/threshold_detector.py

@@ -6,9 +6,9 @@ import numpy as np
 from typing import Optional, List
 
 from analytic_types import ModelCache
-from analytic_types.detector_typing import DetectionResult, ThresholdProcessingResult
+from analytic_types.detector_typing import DetectionResult
 from analytic_types.segment import Segment
-from detectors import ProcessingDetector
+from detectors import Detector
 from time import time
 import utils
 
@@ -16,7 +16,7 @@ import utils
 logger = log.getLogger('THRESHOLD_DETECTOR')
 
 
-class ThresholdDetector(ProcessingDetector):
+class ThresholdDetector(Detector):
 
     WINDOW_SIZE = 3
 
@@ -89,21 +89,3 @@ class ThresholdDetector(ProcessingDetector):
             result.cache = detection.cache
         result.segments = utils.merge_intersecting_segments(result.segments, time_step)
         return result
-
-    def process_data(self, dataframe: pd.DataFrame, cache: ModelCache) -> ThresholdProcessingResult:
-        data = dataframe['value']
-        value = cache['value']
-        data.values[:]  = value
-        timestamps = utils.convert_series_to_timestamp_list(dataframe.timestamp)
-        result_series = list(zip(timestamps, data.values.tolist()))
-        return ThresholdProcessingResult(result_series)
-
-    def concat_processing_results(self, processing_results: List[ThresholdProcessingResult]) -> Optional[ThresholdProcessingResult]:
-        if len(processing_results) == 0:
-            return None
-
-        united_result = ThresholdProcessingResult([])
-        for result in processing_results:
-            united_result.threshold.extend(result.threshold)
-
-        return united_result

server/src/controllers/analytics_controller.ts

@@ -631,78 +631,47 @@ export async function getHSR(
   try {
     const grafanaUrl = getGrafanaUrl(analyticUnit.grafanaUrl);
     const data = await queryByMetric(analyticUnit.metric, grafanaUrl, from, to, HASTIC_API_KEY);
-    let resultSeries = {
-      hsr: data
-    }
 
-    if(analyticUnit.detectorType === AnalyticUnit.DetectorType.THRESHOLD) {
+    if(analyticUnit.detectorType !== AnalyticUnit.DetectorType.ANOMALY) {
-      let cache = await AnalyticUnitCache.findById(analyticUnit.id);
+      return { hsr: data };
-      if(
+    }
-        cache === null ||
+    let cache = await AnalyticUnitCache.findById(analyticUnit.id);
-        cache.data.alpha !== (analyticUnit as AnalyticUnit.ThresholdAnalyticUnit).value ||
+    if(
-        cache.data.confidence !== (analyticUnit as AnalyticUnit.ThresholdAnalyticUnit).condition
+      cache === null ||
-      ) {
+      cache.data.alpha !== (analyticUnit as AnalyticUnit.AnomalyAnalyticUnit).alpha ||
-        await runLearning(analyticUnit.id, from, to);
+      cache.data.confidence !== (analyticUnit as AnalyticUnit.AnomalyAnalyticUnit).confidence
-        cache = await AnalyticUnitCache.findById(analyticUnit.id);
+    ) {
-      }
+      await runLearning(analyticUnit.id, from, to);
-
+      cache = await AnalyticUnitCache.findById(analyticUnit.id);
-      cache = cache.data;
-
-      const analyticUnitType = analyticUnit.type;
-      const detector = analyticUnit.detectorType;
-      const payload = {
-        data: data.values,
-        analyticUnitType,
-        detector,
-        cache
-      };
-
-      const processingTask = new AnalyticsTask(analyticUnit.id, AnalyticsTaskType.PROCESS, payload);
-      const result = await runTask(processingTask);
-      if(result.status !== AnalyticUnit.AnalyticUnitStatus.SUCCESS) {
-        throw new Error(`Data processing error: ${result.error}`);
-      }
-
-      if(result.payload.threshold !== undefined) {
-        resultSeries['threshold'] = { values: result.payload.threshold, columns: data.columns };
-      }
     }
 
-    if(analyticUnit.detectorType === AnalyticUnit.DetectorType.ANOMALY) {
+    cache = cache.data;
-      let cache = await AnalyticUnitCache.findById(analyticUnit.id);
-      if(
-        cache === null ||
-        cache.data.alpha !== (analyticUnit as AnalyticUnit.AnomalyAnalyticUnit).alpha ||
-        cache.data.confidence !== (analyticUnit as AnalyticUnit.AnomalyAnalyticUnit).confidence
-      ) {
-        await runLearning(analyticUnit.id, from, to);
-        cache = await AnalyticUnitCache.findById(analyticUnit.id);
-      }
-
-      cache = cache.data;
 
-      const analyticUnitType = analyticUnit.type;
+    const analyticUnitType = analyticUnit.type;
-      const detector = analyticUnit.detectorType;
+    const detector = analyticUnit.detectorType;
-      const payload = {
+    const payload = {
-        data: data.values,
+      data: data.values,
-        analyticUnitType,
+      analyticUnitType,
-        detector,
+      detector,
-        cache
+      cache
-      };
+    };
+
+    const processingTask = new AnalyticsTask(analyticUnit.id, AnalyticsTaskType.PROCESS, payload);
+    const result = await runTask(processingTask);
+    if(result.status !== AnalyticUnit.AnalyticUnitStatus.SUCCESS) {
+      throw new Error(`Data processing error: ${result.error}`);
+    }
 
-      const processingTask = new AnalyticsTask(analyticUnit.id, AnalyticsTaskType.PROCESS, payload);
+    let resultSeries = {
-      const result = await runTask(processingTask);
+      hsr: data
-      if(result.status !== AnalyticUnit.AnalyticUnitStatus.SUCCESS) {
+    }
-        throw new Error(`Data processing error: ${result.error}`);
-      }
 
-      if(result.payload.lowerBound !== undefined) {
+    if(result.payload.lowerBound !== undefined) {
-        resultSeries['lowerBound'] = { values: result.payload.lowerBound, columns: data.columns };
+      resultSeries['lowerBound'] = { values: result.payload.lowerBound, columns: data.columns };
-      }
+    }
 
-      if(result.payload.upperBound !== undefined) {
+    if(result.payload.upperBound !== undefined) {
-        resultSeries['upperBound'] = { values: result.payload.upperBound, columns: data.columns };
+      resultSeries['upperBound'] = { values: result.payload.upperBound, columns: data.columns };
-      }
     }
 
     return resultSeries;