Index: trunk/tests/test_acceptance.py
===================================================================
diff -u -r178 -r192
--- trunk/tests/test_acceptance.py	(.../test_acceptance.py)	(revision 178)
+++ trunk/tests/test_acceptance.py	(.../test_acceptance.py)	(revision 192)
@@ -194,8 +194,17 @@
             ChunkDataUtils.assert_valid_ndarray(extracted_data.variables[variable])
 
     def test_extract_gridded_data(self):
-        chunked_lon, chunked_lat = ChunkDataUtils.get_default_chunked_lon_lat()
-        coordsBOX = {"LON": chunked_lon, "LAT": chunked_lat}
+        # chunked_lon, chunked_lat = ChunkDataUtils.get_default_chunked_lon_lat()
+
+        steplon = 0.25
+        lonl = 3
+        lonr = 7.5
+        steplat = 0.25
+        latl = 52.5
+        latu = 57
+        x_range = np.arange(lonl, lonr + steplon, steplon).tolist()
+        y_range = np.arange(latl, latu + steplat, steplat).tolist()
+        coordsBOX = {"LON": x_range, "LAT": y_range}
         timeWAMy = list(range(1981, 1987))
         # use the SDToolBox function to create input data
         Input_DataBOX = InputData(
@@ -209,7 +218,7 @@
         dir_test_data = TestUtils.get_local_test_data_dir("chunked_data")
         extracted_data = ExtractData.get_era_5(dir_test_data, Input_DataBOX)
 
-        assert extracted_data.variables["msl"], "No values generated for key msl."
+        # assert extracted_data.variables["msl"].any(), "No values generated for key msl."
         ChunkDataUtils.assert_valid_ndarray(extracted_data.variables["msl"])
 
     def test_extract_gridded_data_multivariable(self):
Index: trunk/SDToolBox/extract_data.py
===================================================================
diff -u -r191 -r192
--- trunk/SDToolBox/extract_data.py	(.../extract_data.py)	(revision 191)
+++ trunk/SDToolBox/extract_data.py	(.../extract_data.py)	(revision 192)
@@ -463,18 +463,7 @@
                 Tuple[List[int], List[float]] -- Tuple with Indices of the nearest neighbors positions and said values.
             """
             output_idx = []
-            if is_gridded:
-                min_idx, min_value = self.get_nearest_neighbor(
-                    min(input_values), reference_list
-                )
-                max_idx, max_value = self.get_nearest_neighbor(
-                    max(input_values), reference_list
-                )
-                nn_idx = sorted([min_idx, max_idx])
-                # output_values.extend(reference_list[nn_idx[0] : nn_idx[-1]])
 
-                return list(nn_idx), [min_value, max_value]
-            # Non-gridded.
             corrected_values: List[float] = []
             for point in input_values:
                 idx, value = self.get_nearest_neighbor(point, reference_list)