--- a/COBRAxy/flux_to_map.py	Wed Nov 06 21:00:17 2024 +0000
+++ b/COBRAxy/flux_to_map.py	Wed Nov 06 21:02:00 2024 +0000
@@ -733,13 +733,12 @@
     
     return tmp, max_z_score
 
-def computeEnrichment(metabMap :ET.ElementTree, class_pat :Dict[str, List[List[float]]], ids :List[str]) -> List[Tuple[str, str, dict, float]]:
+def computeEnrichment(class_pat :Dict[str, List[List[float]]], ids :List[str]) -> List[Tuple[str, str, dict, float]]:
     """
     Compares clustered data based on a given comparison mode and applies enrichment-based styling on the
     provided metabolic map.
 
     Args:
-        metabMap : SVG map to modify.
         class_pat : the clustered data.
         ids : ids for data association.
         
@@ -749,10 +748,7 @@
 
     Raises:
         sys.exit : if there are less than 2 classes for comparison
-    
-    Side effects:
-        metabMap : mut
-        ids : mut
+
     """
     class_pat = { k.strip() : v for k, v in class_pat.items() }
     #TODO: simplfy this stuff vvv and stop using sys.exit (raise the correct utils error)
@@ -765,8 +761,6 @@
         for i, j in it.combinations(class_pat.keys(), 2):
             comparisonDict, max_z_score = compareDatasetPair(class_pat.get(i), class_pat.get(j), ids)
             enrichment_results.append((i, j, comparisonDict, max_z_score))
-            
-            
     
     elif ARGS.comparison == "onevsrest":
         for single_cluster in class_pat.keys():
@@ -1030,7 +1024,7 @@
         computeEnrichmentMeanMedian(core_map, class_pat, ids, ARGS.color_map)
 
 
-    enrichment_results = computeEnrichment(core_map, class_pat, ids)
+    enrichment_results = computeEnrichment(class_pat, ids)
     for i, j, comparisonDict, max_z_score in enrichment_results:
         map_copy = copy.deepcopy(core_map)
         temp_thingsInCommon(comparisonDict, map_copy, max_z_score, i, j)