normalize by max

Author: mohammedahmed18

codeflash/code_utils/code_utils.py

@@ -62,11 +62,11 @@ def choose_weights(**importance: float) -> list[float]:
     return [v / total for v in importance.values()]
 
 
-def normalize(values: list[float]) -> list[float]:
-    mn, mx = min(values), max(values)
-    if mx == mn:
+def normalize_by_max(values: list[float]) -> list[float]:
+    mx = max(values)
+    if mx == 0:
         return [0.0] * len(values)
-    return [(v - mn) / (mx - mn) for v in values]
+    return [v / mx for v in values]
 
 
 def create_score_dictionary_from_metrics(weights: list[float], *metrics: list[float]) -> dict[int, int]:

codeflash/optimization/function_optimizer.py

@@ -38,7 +38,7 @@
     file_name_from_test_module_name,
     get_run_tmp_file,
     module_name_from_file_path,
-    normalize,
+    normalize_by_max,
     restore_conftest,
     unified_diff_strings,
 )
@@ -198,8 +198,8 @@ def _process_refinement_results(self) -> OptimizedCandidate | None:
             runtime_w, diff_w = REFINED_CANDIDATE_RANKING_WEIGHTS
             weights = choose_weights(runtime=runtime_w, diff=diff_w)
 
-            runtime_norm = normalize(runtimes_list)
-            diffs_norm = normalize(diff_lens_list)
+            runtime_norm = normalize_by_max(runtimes_list)
+            diffs_norm = normalize_by_max(diff_lens_list)
             # the lower the better
             score_dict = create_score_dictionary_from_metrics(weights, runtime_norm, diffs_norm)
             top_n_candidates = int((TOP_N_REFINEMENTS * len(runtimes_list)) + 0.5)