2374 lo l2 integrate cg correction for hf maps - prepare for lo integration (#2381)

* Add method to HiLoBasePointingSet for calculating the ram pixel mask

* Update CG correction code to call update_ram_mask method

* Move ram_mask calculation to corrections.py module

* self review updates

* Convert CG correction functions to take xarray.Dataset as input and output

* Update Hi L2 to only use HiPointintSet class for map projection purposes

* PR feedback

* Try to fix test failing in github by correctly handling NaNs in float -> int64 conversion

* Try again to fix github tests

* Fix bug that was causing test failures
Improve test so that bug would be caught locally

Author: tmplummer

imap_processing/ena_maps/ena_maps.py

@@ -7,7 +7,7 @@
 from abc import ABC, abstractmethod
 from enum import Enum
 from pathlib import Path
-from typing import TypeVar
+from typing import ClassVar, TypeVar
 
 import astropy_healpix.healpy as hp
 import numpy as np
@@ -653,24 +653,26 @@ class HiPointingSet(LoHiBasePointingSet):
         Hi L1C pointing set data loaded in a xarray.DataArray.
     """
 
+    # class variable that stores the mapping of variables that need to be
+    # renamed to match L2 variables
+    l1c_to_l2_var_mapping: ClassVar[dict[str, str]] = {
+        "exposure_times": "exposure_factor",
+        "background_rates": "bg_rates",
+        "background_rates_uncertainty": "bg_rates_unc",
+    }
+
     def __init__(self, dataset: xr.Dataset | str | Path):
         super().__init__(dataset, spice_reference_frame=geometry.SpiceFrame.IMAP_HAE)
 
         self.spatial_coords = ("spin_angle_bin",)
 
-        # Rename some PSET vars to match L2 variables
-        self.data = self.data.rename(
-            {
-                "exposure_times": "exposure_factor",
-                "background_rates": "bg_rates",
-                "background_rates_uncertainty": "bg_rates_unc",
-            }
-        )
-
-        # Add obs_date variable to be used in determining a map mean obs_date
-        self.data["obs_date"] = xr.full_like(
-            self.data["exposure_factor"], self.data["epoch"].values[0]
-        )
+        # Rename some PSET vars to match L2 variables (if necessary)
+        rename_dict = {
+            key: value
+            for key, value in self.l1c_to_l2_var_mapping.items()
+            if key in self.data
+        }
+        self.data = self.data.rename(rename_dict)
 
         # Update az_el_points using the base class method
         self.update_az_el_points()