refactor score_less_than_thresh in _binclf_one_curve_python

src/anomalib/metrics/per_image/binclf_curve_numpy.py

@@ -13,6 +13,7 @@
 import itertools
 import logging
 from dataclasses import dataclass
+from functools import partial
 from typing import ClassVar
 
 import numpy as np
@@ -140,24 +141,21 @@ def _binclf_one_curve_python(scores: ndarray, gts: ndarray, threshs: ndarray) ->
     num_neg = current_count_fp = scores_negatives.size
     fps = np.empty((num_th,), dtype=np.int64)
 
-    def score_less_than_thresh(thresh):  # noqa: ANN001, ANN202
-        def func(score) -> bool:  # noqa: ANN001
-            return score < thresh
-
-        return func
+    def score_less_than_thresh(score: float, thresh: float) -> bool:
+        return score < thresh
 
     # it will progressively drop the scores that are below the current thresh
     for thresh_idx, thresh in enumerate(threshs):
         # UPDATE POSITIVES
         # < becasue it is the same as ~(>=)
-        num_drop = sum(1 for _ in itertools.takewhile(score_less_than_thresh(thresh), scores_positives))
+        num_drop = sum(1 for _ in itertools.takewhile(partial(score_less_than_thresh, thresh=thresh), scores_positives))
         scores_positives = scores_positives[num_drop:]
         current_count_tp -= num_drop
         tps[thresh_idx] = current_count_tp
 
         # UPDATE NEGATIVES
         # same with the negatives
-        num_drop = sum(1 for _ in itertools.takewhile(score_less_than_thresh(thresh), scores_negatives))
+        num_drop = sum(1 for _ in itertools.takewhile(partial(score_less_than_thresh, thresh=thresh), scores_negatives))
         scores_negatives = scores_negatives[num_drop:]
         current_count_fp -= num_drop
         fps[thresh_idx] = current_count_fp