note on -derivative matching np.gradient

NREL · Feb 16, 2024 · 6f7f877 · 6f7f877
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commit 6f7f877
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diff --git a/sup3r/postprocessing/file_handling.py b/sup3r/postprocessing/file_handling.py
@@ -306,7 +306,7 @@ def enforce_limits(features, data):
 
             max = H5_ATTRS[dset_name].get('max', np.inf)
             min = H5_ATTRS[dset_name].get('min', -np.inf)
-            logger.debug(f'Enforcing range of ({max}, {min} for "{fn}")')
+            logger.debug(f'Enforcing range of ({min}, {max} for "{fn}")')
             maxs.append(max)
             mins.append(min)
 

diff --git a/sup3r/utilities/loss_metrics.py b/sup3r/utilities/loss_metrics.py
@@ -127,7 +127,10 @@ class MaterialDerivativeLoss(tf.keras.losses.Loss):
     LOSS_METRIC = MeanAbsoluteError()
 
     def _derivative(self, x, axis=1):
-        """Custom derivative function for compatibility with tensorflow
+        """Custom derivative function for compatibility with tensorflow.
+
+        NOTE: Matches np.gradient by using the central difference
+        approximation.
 
         Parameters
         ----------
@@ -204,8 +207,8 @@ def __call__(self, x1, x2):
         """
         hub_heights = x1.shape[-1] // 2
 
-        msg = (f'The {self.__class__} is meant to be used on spatiotemporal '
-               'data only. Received tensor(s) that are not 5D')
+        msg = (f'The {self.__class__.__name__} is meant to be used on '
+               'spatiotemporal data only. Received tensor(s) that are not 5D')
         assert len(x1.shape) == 5 and len(x2.shape) == 5, msg
 
         x1_div = tf.stack(