change arg name to empty_bucket_value and add replacement check

pyresample/bucket/__init__.py

@@ -202,8 +202,7 @@ def _get_indices(self):
         target_shape = self.target_area.shape
         self.idxs = self.y_idxs * target_shape[1] + self.x_idxs
 
-    def get_sum(self, data, fill_value=np.nan, skipna=True,
-                set_empty_bucket_to=0):
+    def get_sum(self, data, fill_value=np.nan, skipna=True, empty_bucket_value=0):
         """Calculate sums for each bin with drop-in-a-bucket resampling.
 
         Parameters
@@ -215,12 +214,12 @@ def get_sum(self, data, fill_value=np.nan, skipna=True,
             Default: np.nan
         skipna : boolean (optional)
             If True, skips missing values (as marked by NaN or `fill_value`) for the sum calculation
-            (similarly to Numpy's `nansum`). Buckets containing only missing values are set to `set_empty_bucket_to`.
+            (similarly to Numpy's `nansum`). Buckets containing only missing values are set to `empty_bucket_value`.
             If False, sets the bucket to fill_value if one or more missing values are present in the bucket
             (similarly to Numpy's `sum`).
-            In both cases, empty buckets are set to `set_empty_bucket_to`.
+            In both cases, empty buckets are set to `empty_bucket_value`.
             Default: True
-        set_empty_bucket_to : float
+        empty_bucket_value : float
             Set empty buckets to the given value. Empty buckets are considered as the buckets with value 0.
             Note that a bucket could become 0 as the result of a sum
             of positive and negative values. If the user needs to identify these zero-buckets reliably,
@@ -255,7 +254,9 @@ def get_sum(self, data, fill_value=np.nan, skipna=True,
 
         # TODO remove following line in favour of weights = data when dask histogram bug (issue #6935) is fixed
         sums = self._mask_bins_with_nan_if_not_skipna(skipna, data, out_size, sums, fill_value)
-        sums = da.where(sums == 0, set_empty_bucket_to, sums)
+
+        if empty_bucket_value != 0:
+            sums = da.where(sums == 0, empty_bucket_value, sums)
 
         return sums.reshape(self.target_area.shape)
 

pyresample/test/test_bucket.py

@@ -205,24 +205,24 @@ def test_get_sum_non_default_fill_value_skipna_true(self):
         self.assertEqual(np.count_nonzero(result == 255), 0)
         self.assertEqual(np.nanmin(result), 0)
 
-    def test_nonzero_set_empty_bucket_to_number(self):
-        """Test drop-in-a-bucket sum for non-zero set_empty_bucket_to np.nan."""
+    def test_nonzero_empty_bucket_value_number(self):
+        """Test drop-in-a-bucket sum for non-zero empty_bucket_value set as number."""
         data = da.from_array(np.array([[2., np.nan], [5., np.nan]]),
                              chunks=self.chunks)
 
-        result = self._get_sum_result(data, skipna=True, set_empty_bucket_to=4095)
+        result = self._get_sum_result(data, skipna=True, empty_bucket_value=4095)
         # 5 is untouched in a single bin
         self.assertEqual(np.count_nonzero(result == 5.), 1)
         # all-nan and rest is 4095
         self.assertEqual(np.count_nonzero(result == 4095), 2048 * 2560 - 2)
         self.assertEqual(np.nanmin(result), 2)
 
-    def test_nonzero_set_empty_bucket_to_npnan(self):
-        """Test drop-in-a-bucket sum for non-zero set_empty_bucket_to np.nan."""
+    def test_nonzero_empty_bucket_valueo_npnan(self):
+        """Test drop-in-a-bucket sum for non-zero empty_bucket_value set as np.nan."""
         data = da.from_array(np.array([[2., np.nan], [5., np.nan]]),
                              chunks=self.chunks)
 
-        result = self._get_sum_result(data, skipna=True, set_empty_bucket_to=np.nan)
+        result = self._get_sum_result(data, skipna=True, empty_bucket_value=np.nan)
         # 5 is untouched in a single bin
         self.assertEqual(np.count_nonzero(result == 5.), 1)
         # all-nan and rest is np.nan