Refact: StreamTask, OATask - order of processing/adaption on new/obso…

…lete instances #988

src/mlpro/oa/streams/tasks/anomalydetectors/anomalies/basics.py

@@ -63,7 +63,7 @@ class Anomaly (Id, Event, Plottable):
 
 ## -------------------------------------------------------------------------------------------------
     def __init__(self,
-                 p_instances: InstDict = None,
+                 p_instances: list[InstDict] = None,
                  p_ano_scores : list = None,
                  p_visualize : bool = False,
                  p_raising_object : object = None,
@@ -75,12 +75,12 @@ def __init__(self,
                         p_tstamp=p_det_time, **p_kwargs)
         Plottable.__init__( self, p_visualize = p_visualize )
 
-        self.instances : InstDict = p_instances
+        self.instances : list[InstDict] = p_instances
         self.ano_scores = p_ano_scores
 
 
 ## -------------------------------------------------------------------------------------------------
-    def get_instances(self) -> list[Instance]:
+    def get_instances(self) -> list[InstDict]:
         return self.instances
 
 

src/mlpro/oa/streams/tasks/anomalydetectors/anomalies/group.py

@@ -41,7 +41,7 @@ class GroupAnomaly (Anomaly):
 
 ## -------------------------------------------------------------------------------------------------
     def __init__(self,
-                 p_instances : InstDict = None,
+                 p_instances : list[InstDict] = None,
                  p_ano_scores : list = None,
                  p_visualize : bool = False,
                  p_raising_object : object = None,
@@ -53,7 +53,7 @@ def __init__(self,
                          p_visualize=p_visualize, p_raising_object=p_raising_object,
                          p_det_time=p_det_time, **p_kwargs)
 
-        self.instances = p_instances
+        self.instances : list[InstDict] = p_instances
         p_ano_scores = p_ano_scores
         self.plot_update = True
 
@@ -86,12 +86,21 @@ def _update_plot_nd(self, p_settings: PlotSettings, **p_kwargs):
         if not self.plot_update: return
 
         label = self.C_NAME[0]
-        x1 = self.get_instances()[0].get_id()
-        x2 = self.get_instances()[-1].get_id()
+
+
+        x1 : Instance = None
+        x2 : Instance = None
+        (inst_type, x1) = self.get_instances()[0].values()[-1]
+        (inst_type, x2) = self.get_instances()[-1].values()[-1]
+
+        x1 = x1.get_id()
+        x2 = x2.get_id()
         a=[]
         b=[]
         for instance in self.get_instances():
-            a.append(instance.get_feature_data().get_values())
+            inst : Instance = None
+            (inst_type, inst) = instance.values()[-1]
+            a.append(inst.get_feature_data().get_values())
         for x in a:
             b.extend(x)
         y1 = min(b)

src/mlpro/oa/streams/tasks/anomalydetectors/anomalies/point.py

@@ -44,7 +44,7 @@ class PointAnomaly (Anomaly):
 
 ## -------------------------------------------------------------------------------------------------
     def __init__(self,
-                 p_instances : InstDict = None,
+                 p_instances : list[InstDict] = None,
                  p_ano_scores : list = None,
                  p_visualize : bool = False,
                  p_raising_object : object = None,
@@ -59,7 +59,7 @@ def __init__(self,
                           p_det_time=p_det_time, 
                           **p_kwargs )
 
-        self.instances = p_instances
+        self.instances : list[InstDict] = p_instances
         self.ano_scores = p_ano_scores
 
 
@@ -90,8 +90,9 @@ def _update_plot_2d(self, p_settings: PlotSettings, p_axlimits_changed: bool, p_
 
         if ( self._plot_line_x1 is not None ) and not p_axlimits_changed: return
 
-        inst           = self.get_instances()[-1]
-        feature_values = inst.get_feature_data().get_values()  
+        inst : Instance = None
+        (inst_type, inst) = self.get_instances()[-1].values()[-1]
+        feature_values = inst.get_feature_data().get_values()
 
         len_x          = ( p_xlim[1] - p_xlim[0] ) * self.C_PLOT_CH_SIZE / 2
         len_y          = ( p_ylim[1] - p_ylim[0] ) * self.C_PLOT_CH_SIZE / 2
@@ -132,8 +133,9 @@ def _update_plot_3d(self, p_settings: PlotSettings, p_axlimits_changed: bool, p_
 
         if ( self._plot_line_x1 is not None ) and not p_axlimits_changed: return
 
-        inst           = self.get_instances()[-1]
-        feature_values = inst.get_feature_data().get_values()  
+        inst : Instance = None
+        (inst_type, inst) = self.get_instances()[-1].values()[-1]
+        feature_values = inst.get_feature_data().get_values()
 
         len_x          = ( p_xlim[1] - p_xlim[0] ) * self.C_PLOT_CH_SIZE / 2
         len_y          = ( p_ylim[1] - p_ylim[0] ) * self.C_PLOT_CH_SIZE / 2
@@ -192,7 +194,11 @@ def _update_plot_nd(self, p_settings: PlotSettings, p_axlimits_changed: bool, p_
 
         if ( self._plot_line is not None ) and not p_axlimits_changed: return
 
-        inst_id = self.get_instances()[-1].get_id()
+
+        inst : Instance = None
+        (inst_type, inst) = self.get_instances()[-1].values()[-1]
+
+        inst_id = inst.get_id()
         xpos    = [inst_id, inst_id]
 
         if self._plot_line is None:

src/mlpro/oa/streams/tasks/anomalydetectors/basics.py

@@ -208,6 +208,13 @@ def _renormalize(self, p_normalizer: Normalizer):
         p_normalizer : Normalizer
             Normalizer object to be applied on task-specific 
         """
+        anomaly : Anomaly = None
 
         for anomaly in self._anomalies.values():
-            anomaly.get_instance().renormalize( p_normalizer=p_normalizer)
+            instances : list[InstDict] = None
+            instances = anomaly.get_instances()
+
+            for item in instances:
+                (inst_id, inst) = item.values()[-1]
+                inst.remormalize( p_normalizer=p_normalizer)
+

src/mlpro/oa/streams/tasks/anomalydetectors/paga_detectors.py

@@ -88,7 +88,14 @@ def _buffer_anomaly(self, p_anomaly):
 
             if len(self.group_anomalies_instances) > 1:
 
-                if int(p_anomaly.get_instances()[-1].get_id()) - 1 == int(self.group_anomalies_instances[-2].get_id()):
+                inst_1 : Instance = None
+                inst_2 : Instance = None
+                (inst_type, inst_2) = self.group_anomalies_instances[-1].values()[-1]
+                second = inst_2.get_id()
+                (inst_type, inst_1) = self.group_anomalies_instances[-2].values()[-1]
+                first = inst_1.get_id()
+
+                if int(second) - 1 == int(first):
 
                     if len(self.group_anomalies_instances) == 3:
 
@@ -98,7 +105,7 @@ def _buffer_anomaly(self, p_anomaly):
                         anomaly = GroupAnomaly(p_instances=self.group_anomalies_instances,
                                                p_ano_scores=self.group_ano_scores, p_visualize=self._visualize,
                                                p_raising_object=self,
-                                               p_det_time=str(p_anomaly.get_instances()[-1].get_tstamp()))
+                                               p_det_time=str(inst_2.get_tstamp()))
                         anomaly.set_id( p_id = self._get_next_anomaly_id() )
                         self._anomalies[anomaly.get_id()] = anomaly
                         self.group_anomalies = []