Segment info #693 (#700)

analytics/analytics/analytic_types/segment.py

@@ -5,14 +5,16 @@ class Segment:
     Used for segment manipulation instead of { 'from': ..., 'to': ... } dict
     '''
 
-    def __init__(self, from_timestamp: int, to_timestamp: int):
+    def __init__(self, from_timestamp: int, to_timestamp: int, message: str = None):
         if to_timestamp < from_timestamp:
             raise ValueError(f'Can`t create segment with to < from: {to_timestamp} < {from_timestamp}')
         self.from_timestamp = from_timestamp
         self.to_timestamp = to_timestamp
+        self.message = message
 
     def to_json(self):
         return {
             'from': self.from_timestamp,
-            'to': self.to_timestamp
+            'to': self.to_timestamp,
+            'message': self.message
         }

analytics/analytics/detectors/anomaly_detector.py

@@ -116,6 +116,7 @@ class AnomalyDetector(ProcessingDetector):
         segments = [Segment(
             utils.convert_pd_timestamp_to_ms(dataframe['timestamp'][segment[0]]),
             utils.convert_pd_timestamp_to_ms(dataframe['timestamp'][segment[1]]),
+            f'{data[segment[0]]} out of bound'
         ) for segment in segments]
 
         last_dataframe_time = dataframe.iloc[-1]['timestamp']

analytics/analytics/detectors/threshold_detector.py

@@ -1,5 +1,6 @@
 import logging as log
 
+import operator
 import pandas as pd
 import numpy as np
 from typing import Optional, List
@@ -49,24 +50,23 @@ class ThresholdDetector(Detector):
             # TODO: merge segments
             if pd.isnull(current_value):
                 if condition == 'NO_DATA':
+                    segment.message = 'NO_DATA detected'
                     segments.append(segment)
                 continue
 
-            if condition == '>':
-                if current_value > value:
-                    segments.append(segment)
-            elif condition == '>=':
-                if current_value >= value:
-                    segments.append(segment)
-            elif condition == '=':
-                if current_value == value:
-                    segments.append(segment)
-            elif condition == '<=':
-                if current_value <= value:
-                    segments.append(segment)
-            elif condition == '<':
-                if current_value < value:
-                    segments.append(segment)
+            comparators = {
+                '>': operator.gt,
+                '<': operator.lt,
+                '=': operator.eq,
+                '>=': operator.ge,
+                '<=': operator.le
+            }
+
+            assert condition in comparators.keys(), f'condition {condition} not allowed'
+
+            if comparators[condition](current_value, value):
+                segment.message = f"{current_value} {condition} threshold's value {value}"
+                segments.append(segment)
 
         last_entry = dataframe.iloc[-1]
         last_detection_time = utils.convert_pd_timestamp_to_ms(last_entry['timestamp'])

analytics/analytics/utils/common.py

@@ -137,6 +137,7 @@ def merge_intersecting_segments(segments: List[Segment], time_step: int) -> List
     previous_segment = segments[0]
     for i in range(1, len(segments)):
         if segments[i].from_timestamp <= previous_segment.to_timestamp + time_step:
+            segments[i].message = segments[-1].message
             segments[i].from_timestamp = min(previous_segment.from_timestamp, segments[i].from_timestamp)
             segments[i].to_timestamp = max(previous_segment.to_timestamp, segments[i].to_timestamp)
             segments[i - 1] = None

analytics/tests/test_detectors.py

@@ -2,6 +2,7 @@ import unittest
 import pandas as pd
 
 from detectors import pattern_detector, threshold_detector, anomaly_detector
+from analytic_types.detector_typing import DetectionResult
 
 class TestPatternDetector(unittest.TestCase):
 
@@ -44,6 +45,8 @@ class TestAnomalyDetector(unittest.TestCase):
             'timeStep': 1
         }
         detector = anomaly_detector.AnomalyDetector('test_id')
-        detect_result = detector.detect(dataframe, cache)
+        detect_result: DetectionResult = detector.detect(dataframe, cache)
+
+        detected_segments = list(map(lambda s: {'from': s.from_timestamp, 'to': s.to_timestamp}, detect_result.segments))
         result = [{ 'from': 1523889000005.0, 'to': 1523889000005.0 }]
-        self.assertEqual(result, detect_result.to_json()['segments'])
+        self.assertEqual(result, detected_segments)

server/src/controllers/analytics_controller.ts

@@ -451,9 +451,9 @@ async function processDetectionResult(analyticUnitId: AnalyticUnit.AnalyticUnitI
   }
   console.log(`got detection result for ${analyticUnitId} with ${detectionResult.segments.length} segments`);
 
-  const sortedSegments: {from, to}[] = _.sortBy(detectionResult.segments, 'from');
+  const sortedSegments: {from, to, message?}[] = _.sortBy(detectionResult.segments, 'from');
   const segments = sortedSegments.map(
-    segment => new Segment.Segment(analyticUnitId, segment.from, segment.to, false, false)
+    segment => new Segment.Segment(analyticUnitId, segment.from, segment.to, false, false, undefined, segment.message)
   );
 
   return {

server/src/models/segment_model.ts

@@ -17,7 +17,7 @@ export class Segment {
     public labeled: boolean = false,
     public deleted: boolean = false,
     public id?: SegmentId,
-    public params?: any
+    public message?: string
   ) {
     if(analyticUnitId === undefined) {
       throw new Error('AnalyticUnitId is undefined');
@@ -43,7 +43,8 @@ export class Segment {
       from: this.from,
       to: this.to,
       labeled: this.labeled,
-      deleted: this.deleted
+      deleted: this.deleted,
+      message: this.message
     };
   }
 
@@ -54,7 +55,8 @@ export class Segment {
     return new Segment(
       obj.analyticUnitId,
       +obj.from, +obj.to,
-      obj.labeled, obj.deleted, obj._id
+      obj.labeled, obj.deleted,
+      obj._id, obj.message
     );
   }
 

server/src/services/alert_service.ts

@@ -33,7 +33,8 @@ export class Alert {
       analyticUnitId: this.analyticUnit.id,
       grafanaUrl,
       from: segment.from,
-      to: segment.to 
+      to: segment.to,
+      message: segment.message
     };
 
     return alert;
@@ -46,7 +47,8 @@ export class Alert {
     ``,
     `From: ${new Date(meta.from)}`,
     `To: ${new Date(meta.to)}`,
-    `ID: ${meta.analyticUnitId}`
+    `ID: ${meta.analyticUnitId}`,
+    `Message: ${meta.message}`
     ].join('\n');
   }
 }
@@ -111,12 +113,8 @@ class ThresholdAlert extends Alert {
       `ID: ${meta.analyticUnitId}`
     ].join('\n');
 
-    if(meta.params !== undefined) {
-      const metrics = `
-        Metrics:
-        ${this.analyticUnit.metric.targets[0].expr}: ${meta.params.value}
-      `;
-      message += metrics;
+    if(meta.message !== undefined) {
+      message += meta.message;
     }
     return message;
   }

server/src/services/notification_service.ts

@@ -25,7 +25,7 @@ export declare type AnalyticMeta = {
   grafanaUrl: string,
   from: number,
   to: number
-  params?: any,
+  message?: any,
   regionImage?: any
 }