OA-Task: AnomalyDetector #520

fhswf · Jun 29, 2023 · 1dbef55 · 1dbef55
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diff --git a/...x2/sub/core/mlpro_oa/streams/tasks/images/MLPro-OA_Anomaly_Detectors_class_diagram.drawio b/...x2/sub/core/mlpro_oa/streams/tasks/images/MLPro-OA_Anomaly_Detectors_class_diagram.drawio
@@ -1 +1 @@
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diff --git a/src/mlpro/oa/streams/tasks/anomalydetectors.py b/src/mlpro/oa/streams/tasks/anomalydetectors.py
@@ -31,7 +31,7 @@ class AnomalyDetector(OATask):
     C_TYPE          = 'Anomaly Detector'
     C_EVENT_ANOMALY = 'ANOMALY'
 
-## -------------------------------------------------------------------------------------------------
+    ## -------------------------------------------------------------------------------------------------
     def __init__(self,
                  p_name:str = None,
                  p_range_max = StreamTask.C_RANGE_THREAD,
@@ -50,7 +50,6 @@ def __init__(self,
                          **p_kwargs)
 
         self.data_points = []
-        self.anomaly_scores = None
         self.counter = 0
         self.anomaly_scores = []
 
@@ -59,65 +58,111 @@ def __init__(self,
     def _run(self, p_inst_new: list, p_inst_del: list):
         pass
 
+    ## ---------------------------------------------------------------------------------
+    def myhandler(self, p_event_id, p_event_object:Event):
+        self.log(Log.C_LOG_TYPE_I, 'Received event id', p_event_id)
+        self.log(Log.C_LOG_TYPE_I, 'Event data:', p_event_object.get_data())
+
 
 
 ## -------------------------------------------------------------------------
 ## -------------------------------------------------------------------------
-# Custom class that inherits event management functionalities from MLPro's class EventManager
-class AnomalyEvent (EventManager):
+class AnomalyDetectorCB(AnomalyDetector):
 
-    C_NAME          = 'Event class'
+    C_TYPE = 'Cluster based Anomaly Detector'
 
-    C_EVENT_OWN     = 'ANOMALY'
 
-    def __init__(self, p_logging=Log.C_LOG_ALL):
-        super().__init__(p_logging)
-
+    ## ------------------------------------------------------------------------
+    def __init__(self,
+                 p_name:str = None,
+                 p_range_max = StreamTask.C_RANGE_THREAD,
+                 p_ada : bool = True,
+                 p_duplicate_data : bool = False,
+                 p_visualize : bool = False,
+                 p_logging=Log.C_LOG_ALL,
+                 **p_kwargs):
 
-    def raise_anomaly(self, data_points, anomaly_scores, counter):
-        eventobj = Event(p_raising_object=self, p_par1='Anomaly detected')
-        self._raise_event(self.C_EVENT_OWN, eventobj)
-        self.anomaly_characteristics(data_points, anomaly_scores, counter)
+        super().__init__(p_name = p_name,
+                         p_range_max = p_range_max,
+                         p_ada = p_ada,
+                         p_duplicate_data = p_duplicate_data,
+                         p_visualize = p_visualize,
+                         p_logging = p_logging,
+                         **p_kwargs)
+
+        self.data_points = []
+        self.counter = 0
+        self.anomaly_scores = []
 
 
-    def anomaly_characteristics(self, data_points, anomaly_scores, counter):
-
-            count = 0
-            for x in anomaly_scores:
-                if x < 0:
-                    count += 1
-
-            frequency = len(data_points)/count
+    ## -------------------------------------------------------------------------
+    def _run(self, p_inst_new: list, p_inst_del: list):
+        pass
 
 
+    ## --------------------------------------------------------------------------
+    def hdl_cluster_updates(p_event_id: str, p_event_object: Event):
+        pass
 
-## ---------------------------------------------------------
-## ---------------------------------------------------------
-# Custom event handler class
-class AnomalyEventHandler (Log):
 
-    C_TYPE          = 'Event handler'
-    C_NAME          = 'Anomaly-Event handler'
+## -------------------------------------------------------------------------
+## -------------------------------------------------------------------------
+class AnomalyEvent (Event):
 
-    def myhandler(self, p_event_id, p_event_object:Event):
-        self.log(Log.C_LOG_TYPE_I, 'Received event id', p_event_id)
-        self.log(Log.C_LOG_TYPE_I, 'Event data:', p_event_object.get_data())
+    C_TYPE     = 'Event'
+
+    C_NAME     = 'Anomaly'
+
+    def __init__(self, p_raising_object, **p_kwargs):
+        pass
+
+
+## -------------------------------------------------------------------------
+## -------------------------------------------------------------------------
+class PointAnomaly (AnomalyEvent):
+
+    C_NAME      = 'Point Anomaly'
+
+    def __init__(self, p_raising_object, p_deviation, **p_kwargs):
+        pass
+
+
+## -------------------------------------------------------------------------
+## -------------------------------------------------------------------------
+class GroupAnomaly (AnomalyEvent):
 
+    C_NAME      = 'Group Anomaly'
+
+    def __init__(self, p_raising_object, p_mean, p_mean_deviation, **p_kwargs):
+        pass
+
+
+## -------------------------------------------------------------------------
+## -------------------------------------------------------------------------
+class ContextualAnomaly (AnomalyEvent):
+
+    C_NAME      = 'Contextual Anomaly'
+
+    def __init__(self, p_raising_object, **p_kwargs):
+        pass
 
 
 ## -------------------------------------------------------------------------
 ## -------------------------------------------------------------------------
 class DriftEvent (AnomalyEvent):
 
-    C_NAME          = 'Drift Anomaly'
+    C_NAME      = 'Drift'
 
-    C_EVENT_OWN     = 'DRIFT'
+    def __init__(self, p_raising_object, p_deviation, **p_kwargs):
+        pass
 
-    def __init__(self, p_logging=Log.C_LOG_ALL):
-        super().__init__(p_logging)
-
 
-    def do_something(self, data_points, anomaly_scores, counter):
-        eventobj = Event(p_raising_object=self, p_par1='Drift detected')
-        self._raise_event(self.C_EVENT_OWN, eventobj)
+## -------------------------------------------------------------------------
+## -------------------------------------------------------------------------
+class DriftEventCB (DriftEvent):
+
+    C_NAME      = 'Cluster based Drift'
+
+    def __init__(self, p_raising_object, p_deviation, **p_kwargs):
+        pass
 
diff --git a/src/mlpro/wrappers/sklearn/anomalydetectors.py b/src/mlpro/wrappers/sklearn/anomalydetectors.py
@@ -26,9 +26,7 @@
 
 from mlpro.wrappers.sklearn.basics import *
 from mlpro.oa.streams.basics import Instance, List
-from mlpro.oa.streams.tasks.anomalydetectors import AnomalyDetector
-from mlpro.oa.streams.tasks.anomalydetectors import AnomalyEventHandler
-from mlpro.oa.streams.tasks.anomalydetectors import AnomalyEvent
+from mlpro.oa.streams.tasks.anomalydetectors import *
 from sklearn.neighbors import LocalOutlierFactor
 from sklearn.svm import OneClassSVM
 from sklearn.ensemble import IsolationForest
@@ -82,11 +80,10 @@ def _run(self, p_inst_new: list, p_inst_del: list):
 
             # Determine if data point is an anomaly based on its outlier score
             if self.anomaly_scores[-1] == -1:
-                self.counter += 1
-                handler_obj = AnomalyEventHandler()
-                event_obj = AnomalyEvent()
-                event_obj.register_event_handler(AnomalyEvent.C_EVENT_OWN, handler_obj.myhandler)
-                event_obj.raise_anomaly(self.data_points, self.anomaly_scores, self.counter)
+                event_obj = AnomalyEvent(p_raising_object=self, p_kwargs=self.data_points[-1])                )
+                handler = self.myhandler
+                self.register_event_handler(event_obj.C_NAME, handler)
+                self._raise_event(event_obj.C_NAME, event_obj)
 
 
 
@@ -142,10 +139,10 @@ def _run(self, p_inst_new: list, p_inst_del: list):
             # Determine if the data point is an anomaly based on its outlier score
             if self.anomaly_scores[-1] < 0:
                 self.counter += 1
-                handler_obj = AnomalyEventHandler()
-                event_obj = AnomalyEvent()
-                event_obj.register_event_handler(AnomalyEvent.C_EVENT_OWN, handler_obj.myhandler)
-                event_obj.raise_anomaly()
+                event_obj = AnomalyEvent(p_raising_object=self, p_kwargs=self.data_points[-1]) 
+                handler = self.myhandler
+                self.register_event_handler(event_obj.C_NAME, handler)
+                self._raise_event(event_obj.C_NAME, event_obj)
 
 
 
@@ -202,11 +199,9 @@ def _run(self, p_inst_new: list, p_inst_del: list):
             # Determine if the latest data point is an anomaly based on its outlier score
             if self.anomaly_scores[-1] < 0:
                 self.counter += 1
-                handler_obj = AnomalyEventHandler()
-                event_obj = AnomalyEvent()
-                event_obj.register_event_handler(AnomalyEvent.C_EVENT_OWN, handler_obj.myhandler)
-                event_obj.raise_anomaly()
-
-
+                event_obj = AnomalyEvent(p_raising_object=self, p_kwargs=self.data_points[-1]) 
+                handler = self.myhandler
+                self.register_event_handler(event_obj.C_NAME, handler)
+                self._raise_event(event_obj.C_NAME, event_obj)