Add tests for Raster.get_mask (#529)

geoutils/raster/raster.py

@@ -2136,14 +2136,14 @@ def get_nanarray(self, return_mask: bool = False) -> NDArrayNum | tuple[NDArrayN
 
     def get_mask(self) -> NDArrayBool:
         """
-        Get mask from the raster.
-
-        The mask is always returned as a boolean array, even if there is no mask to .data and thus .data.mask = a
-        single False value, nomask property of masked arrays.
+        Get mask of invalid values from the raster.
 
         If the raster is not loaded, reads only the mask from disk to optimize memory usage.
 
-        :return:
+        The mask is always returned as a boolean array, even if there is no mask associated to .data (nomask property
+        of masked arrays).
+
+        :return: The mask of invalid values in the raster.
         """
         # If it is loaded, use NumPy's getmaskarray function to deal with False values
         if self.is_loaded:

tests/test_raster.py

@@ -357,6 +357,24 @@ def test_load_only_mask(self, example: str) -> None:
         assert not r_notloaded.is_loaded
         assert np.array_equal(mask_notloaded, mask_loaded)
 
+    @pytest.mark.parametrize("example", [landsat_b4_path, aster_dem_path, landsat_rgb_path])  # type: ignore
+    def test_get_mask(self, example: str) -> None:
+        """
+        Test that getting mask works properly (similar to _load_only_mask).
+        """
+
+        # Load raster with and without loading
+        r_loaded = gu.Raster(example, load_data=True)
+        r_notloaded = gu.Raster(example)
+
+        # Get the mask for the two options
+        mask_loaded = r_loaded.get_mask()
+        mask_notloaded = r_notloaded.get_mask()
+
+        # Data should not be loaded and masks should be equal
+        assert not r_notloaded.is_loaded
+        assert np.array_equal(mask_notloaded, mask_loaded)
+
     @pytest.mark.parametrize("example", [landsat_b4_path, aster_dem_path])  # type: ignore
     def test_to_rio_dataset(self, example: str):
         """Test the export to a rasterio dataset"""