SPATZ migration + proper directory structure

spatz/logger.py

@@ -0,0 +1,75 @@
+import numpy as np
+import pandas as pd
+
+from typing import Any, Tuple
+from numpy.typing import ArrayLike
+
+from abc import abstractmethod
+
+
+class Advanceable:
+    def __init__(self) -> None:
+        self.reset()
+
+    def step(self, dt: float):
+        """Advances the simulation data in time.
+
+        Args:
+            dt (float): The step in time to make.
+        """
+        self.__t += dt
+        self._on_step(dt)
+
+    def reset(self):
+        """
+        Reset the Avanceable object to its initial state.
+        """
+        self.__t = 0
+        self._on_reset()
+
+    @abstractmethod
+    def _on_step(self, dt: float):
+        pass
+
+    @abstractmethod
+    def _on_reset(self):
+        pass
+
+    def get_time(self) -> float:
+        """
+        Returns:
+            float: Returns the current time of the Advanceable.
+        """
+        return self.__t
+
+
+class Logger(Advanceable):
+    def __init__(self) -> None:
+        super().__init__()
+        self.__idx = -1
+
+    def _on_step(self, _: float):
+        self.__df = pd.concat([self.__df, pd.Series().copy()], ignore_index=True)
+        self.__idx += 1
+        self.__df.loc[self.__idx, 'time'] = self.get_time()
+
+    def _on_reset(self):
+        self.__df = pd.DataFrame.from_dict({'time': [self.get_time()]})
+
+    def write(self, attrib: str, value: Any, domain: str = 'all'):
+        """Writes a value to the logger.
+
+        Args:
+            attrib (str): The name of the value to log.
+            value (Any): The value to log.
+            domain (str, optional): The domain the value belongs to. Defaults to 'any'.
+        """
+        name = domain + '/' + attrib
+
+        if name not in self.__df.columns:
+            self.__df[name] = pd.Series([pd.NA] * len(self.__df))
+
+        self.__df.loc[self.__idx, name] = value
+
+    def get_dataframe(self) -> pd.DataFrame:
+        return self.__df