small update to support unrealistic perfect classification

ece.py

@@ -104,7 +104,7 @@ def create_bins(n_bins=10, scheme="equal-range", bin_range=None, P=None):
 def discretize_into_bins(P, bins):
 
     contains_rightmost = bool(bins[-1] > 1)  # outlier bins
-    contains_leftmost = bool(bins[0] == 0)  # beyond [before] bin_range[0]
+    contains_leftmost = bool(bins[0] <= 0)  # beyond [before] bin_range[0]
     # bins_with_left_edge = np.insert(bins, 0, 0, axis=0)
 
     oneDbins = np.digitize(
@@ -112,7 +112,6 @@ def discretize_into_bins(P, bins):
     )  # since bins contains extra righmost (& leftmost bins)
     if contains_leftmost:
         oneDbins -= 1
-    # oneDbins = np.digitize(P, bins) - 1  # since bins contains extra righmost (& leftmost bins)
 
     # Fix to scipy.binned_dd_statistic:
     # Tie-breaking to the left for rightmost bin
@@ -245,8 +244,8 @@ class ECE(evaluate.EvaluationModule):
             # Homepage of the module for documentation
             homepage="https://huggingface.co/spaces/jordyvl/ece",
             # Additional links to the codebase or references
-            codebase_urls=["http://github.com/path/to/codebase/of/new_module"],
-            reference_urls=["http://path.to.reference.url/new_module"],
+            codebase_urls=[""],
+            reference_urls=[""],
         )
 
     def init_kwargs(
@@ -341,32 +340,27 @@ def test_equalmass_binning():
         scheme="equal-mass",
         bin_range=None,
         proxy="upper-edge",
-        # proxy="center",
         p=1,
         detail=True,
     )
     bins = create_bins(
         n_bins=kwargs["n_bins"], scheme=kwargs["scheme"], bin_range=kwargs["bin_range"], P=probs
     )
-
     test_ECE(**kwargs)
 
-    """
+
+def test_perfect_predictions(K=3):
+    references = [0, 1, 2]
     res = ECE()._compute(
-        references=[0, 1, 2],
-        predictions=[[0.63, 0.2, 0.2], [0, 0.95, 0.05], [0.72, 0.1, 0.2]],
+        references=references,
+        predictions=np.eye(K)[references],
         detail=True,
     )
     print(f"ECE: {res['ECE']}\n {res}")
-    """
-    # need to provide lens
-
-    import pdb
-
-    pdb.set_trace()  # breakpoint 94583f9f //
 
 
 if __name__ == "__main__":
+    test_perfect_predictions()
     test_equalmass_binning()
     test_deterministic()
     test_ECE()