Moved history to wfAlgorithm.

python/lsst/ts/wep/estimation/tie.py

@@ -22,7 +22,6 @@
 __all__ = ["TieAlgorithm"]
 
 import inspect
-import warnings
 from typing import Iterable, Optional, Union
 
 import numpy as np
@@ -80,7 +79,6 @@ class TieAlgorithm(WfAlgorithm):
         Dictionary of mask keyword arguments to pass to mask creation.
         To see possibilities, see the docstring for
         lsst.ts.wep.imageMapper.ImageMapper.createPupilMask().
-        (the default is an empty dictionary)
     saveHistory : bool, optional
         Whether to save the algorithm history in the self.history attribute.
         If True, then self.history contains information about the most recent
@@ -115,12 +113,9 @@ def __init__(
             saveHistory=saveHistory,
         )
 
-        # Instantiate an empty history
-        self._history = {}  # type: ignore
-
     @property
     def opticalModel(self) -> str:
-        """The optical model to use for"""
+        """The optical model to use for mapping the image to the pupil."""
         return self._opticalModel
 
     @opticalModel.setter
@@ -374,35 +369,6 @@ def maskKwargs(self, value: Union[dict, None]) -> None:
 
         self._maskKwargs = value
 
-    @property
-    def saveHistory(self) -> bool:
-        """Whether the algorithm history is saved."""
-        return self._saveHistory
-
-    @saveHistory.setter
-    def saveHistory(self, value: bool) -> None:
-        """Set boolean that determines whether algorithm history is saved.
-
-        Parameters
-        ----------
-        value : bool
-            Boolean that determines whether the algorithm history is saved.
-
-        Raises
-        ------
-        TypeError
-            If the value is not a boolean
-        """
-        if not isinstance(value, bool):
-            raise TypeError("saveHistory must be a boolean.")
-
-        self._saveHistory = value
-
-        # If we are turning history-saving off, delete any old history
-        # This is to avoid confusion
-        if value is False:
-            self._history = {}
-
     @property
     def history(self) -> dict:
         """The algorithm history.
@@ -426,13 +392,7 @@ def history(self) -> dict:
         Note the units for all Zernikes are in meters, and the z-derivative
         in dIdz is also in meters.
         """
-        if not self._saveHistory:
-            warnings.warn(
-                "saveHistory is False. If you want the history to be saved, "
-                "run self.config(saveHistory=True)."
-            )
-
-        return self._history
+        return super().history
 
     def _expSolve(
         self,

python/lsst/ts/wep/estimation/wfAlgorithm.py

@@ -21,6 +21,7 @@
 
 __all__ = ["WfAlgorithm"]
 
+import warnings
 from abc import ABC, abstractmethod
 from typing import Any, Optional
 
@@ -38,6 +39,10 @@ class WfAlgorithm(ABC):
         Path to file specifying values for the other parameters. If the
         path starts with "policy/", it will look in the policy directory.
         Any explicitly passed parameters override values found in this file
+    saveHistory : bool, optional
+        Whether to save the algorithm history in the self.history attribute.
+        If True, then self.history contains information about the most recent
+        time the algorithm was run.
 
     ...
 
@@ -46,18 +51,77 @@ class WfAlgorithm(ABC):
     def __init__(
         self,
         configFile: Optional[str] = None,
+        saveHistory: Optional[bool] = None,
         **kwargs: Any,
     ) -> None:
         # Merge keyword arguments with defaults from configFile
         params = mergeConfigWithFile(
             configFile,
+            saveHistory=saveHistory,
             **kwargs,
         )
 
         # Configure parameters
         for key, value in params.items():
             setattr(self, key, value)
 
+        # Instantiate an empty history
+        self._history = {}  # type: ignore
+
+    def __init_subclass__(self) -> None:
+        """This is called when you subclass.
+
+        I am using this to force you to write a docstring
+        for the history property.
+        """
+        if self.history.__doc__ is None:
+            raise AttributeError(
+                "You must write a docstring for the history property. "
+                "Please use this to describe the contents of the history dict."
+            )
+
+    @property
+    def saveHistory(self) -> bool:
+        """Whether the algorithm history is saved."""
+        return self._saveHistory
+
+    @saveHistory.setter
+    def saveHistory(self, value: bool) -> None:
+        """Set boolean that determines whether algorithm history is saved.
+
+        Parameters
+        ----------
+        value : bool
+            Boolean that determines whether the algorithm history is saved.
+
+        Raises
+        ------
+        TypeError
+            If the value is not a boolean
+        """
+        if not isinstance(value, bool):
+            raise TypeError("saveHistory must be a boolean.")
+
+        self._saveHistory = value
+
+        # If we are turning history-saving off, delete any old history
+        # This is to avoid confusion
+        if value is False:
+            self._history = {}
+
+    @property
+    def history(self) -> dict:
+        # Return the algorithm history
+        # Note I have not written a real docstring here, so that I can force
+        # subclasses to write a new docstring for this method
+        if not self._saveHistory:
+            warnings.warn(
+                "saveHistory is False. If you want the history to be saved, "
+                "run self.config(saveHistory=True)."
+            )
+
+        return self._history
+
     @staticmethod
     def _validateInputs(
         I1: Image,