Refactor run_and_check_enhancement

satpy/tests/enhancement_tests/test_enhancements.py

@@ -32,35 +32,57 @@
 # - tmp_path
 
 
-def run_and_check_enhancement(func, data, expected, match_dtype=False, **kwargs):
+def run_and_check_enhancement(func, data, expected, **kwargs):
     """Perform basic checks that apply to multiple tests."""
+    pre_attrs = data.attrs
+    img = _get_enhanced_image(func, data, **kwargs)
+
+    _assert_image(img, pre_attrs, func.__name__, "palettes" in kwargs)
+    _assert_image_data(img, expected)
+
+
+def _get_enhanced_image(func, data, **kwargs):
     from trollimage.xrimage import XRImage
 
-    pre_attrs = data.attrs
     img = XRImage(data)
     func(img, **kwargs)
 
+    return img
+
+
+def _assert_image(img, pre_attrs, func_name, has_palette):
+    assert isinstance(img.data, xr.DataArray)
     assert isinstance(img.data.data, da.Array)
+
     old_keys = set(pre_attrs.keys())
     # It is OK to have "enhancement_history" added
     new_keys = set(img.data.attrs.keys()) - {"enhancement_history"}
     # In case of palettes are used, _FillValue is added.
     # Colorize doesn't add the fill value, so ignore that
-    if "palettes" in kwargs and func.__name__ != "colorize":
+    if has_palette and func_name != "colorize":
         assert "_FillValue" in new_keys
         # Remove it from further comparisons
         new_keys = new_keys - {"_FillValue"}
     assert old_keys == new_keys
 
-    res_data_arr = img.data
-    assert isinstance(res_data_arr, xr.DataArray)
-    assert isinstance(res_data_arr.data, da.Array)
-    res_data = res_data_arr.data.compute()  # mimics what xrimage geotiff writing does
+
+def _assert_image_data(img, expected, dtype=None):
+    # Compute the data to mimic what xrimage geotiff writing does
+    res_data = img.data.data.compute()
     assert not isinstance(res_data, da.Array)
     np.testing.assert_allclose(res_data, expected, atol=1.e-6, rtol=0)
-    if match_dtype:
-        assert res_data_arr.dtype == data.dtype
-        assert res_data.dtype == data.dtype
+    if dtype:
+        assert img.data.dtype == dtype
+        assert res_data.dtype == dtype
+
+
+def run_and_check_enhancement_with_dtype(func, data, expected, **kwargs):
+    """Perform basic checks that apply to multiple tests."""
+    pre_attrs = data.attrs
+    img = _get_enhanced_image(func, data, **kwargs)
+
+    _assert_image(img, pre_attrs, func.__name__, "palettes" in kwargs)
+    _assert_image_data(img, expected, dtype=data.dtype)
 
 
 def identical_decorator(func):
@@ -120,7 +142,7 @@ def test_cira_stretch(self, dtype):
         expected = np.array([[
             [np.nan, -7.04045974, -7.04045974, 0.79630132, 0.95947296],
             [1.05181359, 1.11651012, 1.16635571, 1.20691137, 1.24110186]]], dtype=dtype)
-        run_and_check_enhancement(cira_stretch, self.ch1.astype(dtype), expected, match_dtype=True)
+        run_and_check_enhancement_with_dtype(cira_stretch, self.ch1.astype(dtype), expected)
 
     def test_reinhard(self):
         """Test the reinhard algorithm."""