Added exclude to correct_baseline_average.

glotaran/io/preprocessor/pipeline.py

@@ -65,19 +65,24 @@ def correct_baseline_value(self, value: float) -> PreProcessingPipeline:
         return self
 
     def correct_baseline_average(
-        self, selection: dict[str, slice | list[int] | int]
+        self,
+        selection: dict[str, slice | list[int] | int] | None = None,
+        exclude: dict[str, slice | list[int] | int] | None = None,
     ) -> PreProcessingPipeline:
         """Correct a dataset by subtracting the average over a part of the data.
 
         Parameters
         ----------
-        selection: dict[str, slice | list[int] | int]
+        selection: dict[str, slice | list[int] | int] | None
             The selection to average as dictionary of dimension and indexer.
             The indexer can be a slice, a list or an integer value.
+        exclude: dict[str, slice | list[int] | int] | None
+            Excluded regions from the average as dictionary of dimension and indexer.
+            The indexer can be a slice, a list or an integer value.
 
         Returns
         -------
         PreProcessingPipeline
         """
-        self._push_action(CorrectBaselineAverage(selection=selection))
+        self._push_action(CorrectBaselineAverage(exclude=exclude, selection=selection))
         return self

glotaran/io/preprocessor/preprocessor.py

@@ -58,7 +58,8 @@ class CorrectBaselineAverage(PreProcessor):
     """Corrects a dataset by subtracting the average over a part of the data."""
 
     action: Literal["baseline-average"] = "baseline-average"
-    selection: dict[str, slice | list[int] | int]
+    selection: dict[str, slice | list[int] | int] | None = None
+    exclude: dict[str, slice | list[int] | int] | None = None
 
     def apply(self, data: xr.DataArray) -> xr.DataArray:
         """Apply the pre-processor.
@@ -72,5 +73,5 @@ def apply(self, data: xr.DataArray) -> xr.DataArray:
         -------
         xr.DataArray
         """
-        selection = data.sel(self.selection)
+        selection = data.sel(self.selection or {}).drop_sel(self.exclude or {})
         return data - (selection.sum() / selection.size)

glotaran/io/preprocessor/test/test_preprocessor.py

@@ -15,12 +15,21 @@ def test_correct_baseline_value():
 @pytest.mark.parametrize("indexer", (slice(0, 2), [0, 1]))
 def test_correct_baseline_average(indexer: slice | list[int]):
     pl = PreProcessingPipeline()
-    pl.correct_baseline_average({"dim_0": 0, "dim_1": indexer})
+    pl.correct_baseline_average(selection={"dim_0": 0, "dim_1": indexer})
     data = xr.DataArray([[1.1, 0.9]])
     result = pl.apply(data)
     assert (result == data - 1).all()
 
 
+def test_correct_baseline_average_exclude():
+    pl = PreProcessingPipeline()
+    pl.correct_baseline_average(exclude={"dim_1": 1})
+    data = xr.DataArray([[1.1, 0.9]])
+    result = pl.apply(data)
+    print(result)
+    assert (result == data - 1.1).all()
+
+
 def test_to_from_dict():
     pl = PreProcessingPipeline()
     pl.correct_baseline_value(1)
@@ -29,7 +38,7 @@ def test_to_from_dict():
     assert pl_dict == {
         "actions": [
             {"action": "baseline-value", "value": 1.0},
-            {"action": "baseline-average", "selection": {"dim_1": slice(0, 2)}},
+            {"action": "baseline-average", "selection": {"dim_1": slice(0, 2)}, "exclude": None},
         ]
     }
     assert PreProcessingPipeline.parse_obj(pl_dict) == pl