pr comments and logger statements

Author: lacoak21

imap_processing/cdf/config/imap_ultra_l1b_variable_attrs.yaml

@@ -553,9 +553,10 @@ quality_statistics:
   LABLAXIS: quality_statistics
   # TODO: come back to format
   UNITS: " "
+  DEPEND_0: spin_number
 
 energy_range_edges:
-  CATDESC: Energy range edges used for culling data at l1b.
+  CATDESC: Energy range edges used for culling data.
   DISPLAY_TYPE: no_plot
   FIELDNAM: Energy Range Edges
   FILLVAL: -1.0e+31
@@ -565,9 +566,10 @@ energy_range_edges:
   VALIDMIN: 0.0
   VALIDMAX: 5000
   VAR_TYPE: support_data
+  DEPEND_0: energy_range_edges_dim
 
 energy_range_flags:
-  CATDESC: Bit flags describing culling energy ranges applied at l1b.
+  CATDESC: Bit flags describing culling energy ranges.
   DISPLAY_TYPE: no_plot
   FIELDNAM: Energy Range Flags
   FILLVAL: 0
@@ -576,4 +578,5 @@ energy_range_flags:
   UNITS: " "
   VALIDMIN: 1
   VALIDMAX: 65534
-  VAR_TYPE: support_data
+  VAR_TYPE: support_data
+  DEPEND_0: energy_range_flags_dim

imap_processing/ultra/l1b/ultra_l1b_culling.py

@@ -674,7 +674,11 @@ def flag_low_voltage(
     # For each low voltage ind, flag the corresponding flag
     quality_flags[lv_spin_inds] = True
 
-    #  TODO add log summary.
+    num_culled: int = np.sum(quality_flags)
+    logger.info(
+        f"High energy culling removed {num_culled} spin bins across all energy "
+        f"channels. Voltage threshold: {voltage_threshold} V."
+    )
 
     return quality_flags
 
@@ -752,7 +756,12 @@ def flag_high_energy(
         quality_flags[:, ~mask] = flagged[:, ~mask]
     else:
         quality_flags = flagged
-    # TODO add log summary. E.g Tim's hi goodtimes code
+
+    num_culled: int = np.sum(quality_flags)
+    logger.info(
+        f"High energy culling removed {num_culled} spin bins across {n_energy_bins} "
+        f"energy channels. Energy thresholds: {energy_thresholds.flatten()}, "
+    )
 
     return quality_flags
 
@@ -889,7 +898,7 @@ def flag_statistical_outliers(
                     convergence[e_idx] = True
 
     num_culled: int = np.sum(quality_stats)
-    logger.debug(
+    logger.info(
         f"Statistical culling removed {num_culled} spin bins across {n_energy_bins}"
         f" energy channels. Convergence: {convergence} after "
         f"{iterations} iterations."

imap_processing/ultra/utils/ultra_l1_utils.py

@@ -1,5 +1,6 @@
 """Create dataset."""
 
+import numpy as np
 import xarray as xr
 
 from imap_processing.cdf.imap_cdf_manager import ImapCdfAttributes
@@ -186,15 +187,29 @@ def create_dataset(  # noqa: PLR0912
                 attrs=cdf_manager.get_variable_attributes(key, check_schema=False),
             )
         elif key in {"energy_range_edges"}:
+            dataset["energy_range_edges_dim"] = xr.DataArray(
+                np.arange(len(data)),
+                dims=["energy_range_edges_dim"],
+                attrs=cdf_manager.get_variable_attributes(
+                    "energy_range_edges_dim", check_schema=False
+                ),
+            )
             dataset[key] = xr.DataArray(
                 data,
-                dims=["energy_range_edges"],
+                dims=["energy_range_edges_dim"],
                 attrs=cdf_manager.get_variable_attributes(key, check_schema=False),
             )
         elif key in {"energy_range_flags"}:
+            dataset["energy_range_flags_dim"] = xr.DataArray(
+                np.arange(len(data)),
+                dims=["energy_range_flags_dim"],
+                attrs=cdf_manager.get_variable_attributes(
+                    "energy_range_flags_dim", check_schema=False
+                ),
+            )
             dataset[key] = xr.DataArray(
                 data,
-                dims=["energy_range_flags"],
+                dims=["energy_range_flags_dim"],
                 attrs=cdf_manager.get_variable_attributes(key, check_schema=False),
             )
         else: