functio al

ece.py

@@ -75,8 +75,7 @@ def create_bins(n_bins=10, scheme="equal-range", bin_range=None, P=None):
         if P is None:
             bin_range = [0, 1]  # no way to know range
         else:
-            if scheme == "equal-range":
-                bin_range = [min(P), max(P)]
+            bin_range = [min(P), max(P)]
 
     if scheme == "equal-range":
         bins = np.linspace(bin_range[0], bin_range[1], n_bins + 1)  # equal range
@@ -168,13 +167,12 @@ def CE_estimate(y_correct, P, bins=None, p=1, proxy="upper-edge"):
 
     empirical_acc, bin_edges, bin_assignment = manual_binned_statistic(P, y_correct, bins)
     bin_numbers, weights_ece = np.unique(bin_assignment, return_counts=True)
-    anindices = bin_numbers - 1  # reduce bin counts; left edge; indexes right BY DEFAULT
+    anindices = bin_numbers - 1  # reduce bin counts; left edge; indexes right by default
 
     # Expected calibration error
     if p < np.inf:  # L^p-CE
         CE = np.average(
-            abs(empirical_acc[anindices] - calibrated_acc[anindices]) ** p,
-            weights=weights_ece,  # weighted average 1/binfreq
+            abs(empirical_acc[anindices] - calibrated_acc[anindices]) ** p, weights=weights_ece
         )
     elif np.isinf(p):  # max-ECE
         CE = np.max(abs(empirical_acc[anindices] - calibrated_acc[anindices]))
@@ -193,8 +191,6 @@ def top_1_CE(Y, P, **kwargs):
 
 @evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
 class ECE(evaluate.EvaluationModule):
-    """TODO: Short description of my evaluation module."""
-
     """
     0. create binning scheme [discretization of f]
     1. build histogram P(f(X))
@@ -203,15 +199,11 @@ class ECE(evaluate.EvaluationModule):
     4. apply L^p norm distance and weights
     """
 
-    # have to add to initialization here?
-    # create bins using the params
-    # create proxy
-
     def __init__(self, n_bins=10, bin_range=None, scheme="equal-range", proxy="upper-edge", p=1):
-        super().__init__(self)
+        #super().__init__(self)
 
-        self.bin_range = bin_range
         self.n_bins = n_bins
+        self.bin_range = bin_range
         self.scheme = scheme
         self.proxy = proxy
         self.p = p
@@ -245,8 +237,7 @@ class ECE(evaluate.EvaluationModule):
 
     def _compute(self, predictions, references):
         """Returns the scores"""
-
-        ECE = top_1_CE(references, predictions)
+        ECE = top_1_CE(references, predictions, **self.__dict__)
         return {
             "ECE": ECE,
         }
@@ -274,7 +265,3 @@ def test_ECE():
 
 if __name__ == "__main__":
     test_ECE()
-
-
-#        if scheme == "equal-mass":
-# raise AssertionError("Need to calculate based on P") #so cannot instantiate yet