test scalar output

aeon/testing/estimator_checking/_yield_estimator_checks.py

@@ -609,7 +609,8 @@ def _equal_outputs(output1, output2):
     """Test whether two outputs from an estimator are logically identical.
 
     Valid data structures are:
-    1. numpy array: stores an equal length collection or series
+    1. float
+    2. numpy array: stores an equal length collection or series
     2. dict: a histogram of counts, usually of discrete series
     3. pd.DataFrame: series stored in dataframe
     4. list: stores unequal length series in a format 1-3
@@ -618,6 +619,8 @@ def _equal_outputs(output1, output2):
     """
     if type(output1) is not type(output2):
         return False
+    if np.issubdtype(type(output1), np.floating):
+        return np.isclose(output1, output2)
     if isinstance(output1, np.ndarray):  # 1. X an equal length collection or series
         return np.allclose(output1, output2, equal_nan=True)
     if isinstance(output1, dict):  # 2. X a dictionary, dense collection or series