diff --git a/electronic_checks.py b/electronic_checks.py
index 5bd1af4e75e0b52b0f4db8dbde95e991579ca5fd..b41d1f809c88fdf9954e9d59d81d187be4093a0b 100644
--- a/electronic_checks.py
+++ b/electronic_checks.py
@@ -6,18 +6,19 @@ import itertools
 electronic_checks = BaseCheckList()
 
 def find_bb_outliers(frame, parameters, bb):
+    """
+    Find outliers in blackbody temperatures.
+    Annotate any problems, and set quality flags for each thermistor
+    """
     window_length = parameters.get('window_length', 50)
 
     if bb == 'HBB':
         delta_thresh = .001
-        bbb_outliers = np.array(list(_scan_for_outliers(frame, '{}bottomTemp'.format(bb), delta_thresh)))
-        bba_outliers = np.array(list(_scan_for_outliers(frame, '{}apexTemp'.format(bb), delta_thresh)))
-        bbt_outliers = np.array(list(_scan_for_outliers(frame, '{}topTemp'.format(bb), delta_thresh)))
     else:
         delta_thresh = .01
-        bbb_outliers = np.array(list(_scan_for_outliers(frame, '{}bottomTemp'.format(bb), delta_thresh)))
-        bba_outliers = np.array(list(_scan_for_outliers(frame, '{}apexTemp'.format(bb), delta_thresh)))
-        bbt_outliers = np.array(list(_scan_for_outliers(frame, '{}topTemp'.format(bb), delta_thresh)))
+    bbb_outliers = np.array(list(_scan_for_outliers(frame, '{}bottomTemp'.format(bb), delta_thresh)))
+    bba_outliers = np.array(list(_scan_for_outliers(frame, '{}apexTemp'.format(bb), delta_thresh)))
+    bbt_outliers = np.array(list(_scan_for_outliers(frame, '{}topTemp'.format(bb), delta_thresh)))
 
     variable_qcs = pd.DataFrame({
         'qc_{}bottomTemp'.format(bb) : bbb_outliers * 1,
@@ -53,12 +54,17 @@ def _find_6sigma_outliers(frame, window_length, estimation_func=_compute_robust_
     return estimation_func(frame, window_length) > 6
 
 def _scan_for_outliers(frame, variable, delta_thresh):
+    """
+    Check for temperature changes exceeding the delta_thresh rate in degK / sec
+    """
     last = None
     for i, row in frame.iterrows():
+        # First row cannot be an outlier
         if last is None:
             yield False
             last = row
         else:
+            # Compare each row to previous non-outlier row
             time_diff = (row.datetime - last.datetime).total_seconds()
             variable_diff = row[variable] - last[variable]
             if abs(variable_diff / time_diff) < delta_thresh: