Updated observers and Kalman Filter, added running average

spatz/observer/observer.py

@@ -1,4 +1,4 @@
-from typing import Any, List, Dict, AnyStr
+from typing import Any, List, Dict, AnyStr, Tuple
 from numpy.typing import ArrayLike
 
 from spatz.dataset import Dataset
@@ -7,7 +7,7 @@ from spatz.transforms import Transform
 
 
 class Observer:
-    def __init__(self, dataset: Dataset, logger: Logger, attributes: List[str]):
+    def __init__(self, dataset: Dataset, logger: Logger, attributes: List[str] = None):
         self._dataset = dataset
         self._logger = logger
         self.__attrs = attributes
@@ -30,11 +30,22 @@ class Observer:
             ArrayLike: Returns the values of the observed attributes at the start of the simulation.
         """
         return self(t=self._dataset.get_start_time())
+    
+    def _fetch(self, t: float) -> Tuple[ArrayLike, List[str]]:
+        """Method for collecting and preprocessing the desired data. Can be overwritten by a subclass.
+
+        Args:
+            t (float): The current time of the simulation.
+
+        Returns:
+            ArrayLike: The collected values.
+        """
+        return self._dataset.fetch_values(self.__attrs, t), self.__attrs
 
     def __call__(self, t: float | None = None) -> ArrayLike:
-        data = self._dataset.fetch_values(self.__attrs, t)
+        data, attrs = self._fetch(t)
 
-        for attrib, value in zip(self.__attrs, data):
+        for attrib, value in zip(attrs, data):
             self._log(attrib, value)
 
         return data