fix energy calibration and hextof notebook

sed/calibrator/energy.py

@@ -1987,7 +1987,7 @@ def residual(pars, time, data, binwidth, binning, energy_scale):
         value=E0_pars.get("value", min(vals)),
         min=E0_pars.get("min", -np.inf),
         max=E0_pars.get("max", np.inf),
-        vary=d_pars.get("vary", True),
+        vary=E0_pars.get("vary", True),
     )
     fit = Minimizer(
         residual,
@@ -2225,6 +2225,7 @@ def apply_energy_offset(
     df: Union[pd.DataFrame, dask.dataframe.DataFrame],
     columns: Union[str, Sequence[str]],
     signs: Union[int, Sequence[int]],
+    subtract_mean: Union[bool, Sequence[bool]] = True,
     energy_column: str = None,
     reductions: Union[str, Sequence[str]] = None,
     config: dict = None,
@@ -2255,9 +2256,12 @@ def apply_energy_offset(
         columns = [columns]
     if isinstance(signs, int):
         signs = [signs]
+    if len(signs) != len(columns):
+        raise ValueError("signs and columns must have the same length.")
+    if isinstance(subtract_mean, bool):
+        subtract_mean = [subtract_mean] * len(columns)
     if reductions is None:
         reductions = [None] * len(columns)
-
     columns_: List[str] = []
     reductions_: List[str] = []
     to_roll: List[str] = []
@@ -2280,6 +2284,7 @@ def apply_energy_offset(
         target_column=energy_column,
         offset_columns=columns_,
         signs=signs,
+        subtract_mean=subtract_mean,
         reductions=reductions_,
         inplace=True,
     )

sed/core/dfops.py

@@ -331,6 +331,7 @@ def apply_offset_from_columns(
     offset_columns: Union[str, Sequence[str]],
     signs: Union[int, Sequence[int]],
     reductions: Union[str, Sequence[str]],
+    subtract_mean: Union[bool, Sequence[bool]],
     inplace: bool = True,
 ) -> Union[pd.DataFrame, dask.dataframe.DataFrame]:
     """Apply an offset to a column based on the values of other columns.
@@ -359,10 +360,12 @@ def apply_offset_from_columns(
     if len(signs) != len(offset_columns):
         raise ValueError("signs and offset_columns must have the same length!")
 
-    for col, sign, red in zip(offset_columns, signs, reductions):
+    for col, sign, red, submean in zip(offset_columns, signs, reductions, subtract_mean):
         assert col in df.columns, f"{col} not in dataframe!"
         if red is not None:
             df[target_column] = df[target_column] + sign * df[col].agg(red)
         else:
             df[target_column] = df[target_column] + sign * df[col]
+        if submean:
+            df[target_column] = df[target_column] - sign * df[col].mean()
     return df

sed/core/processor.py

@@ -1168,6 +1168,7 @@ def apply_energy_offset(
         columns: Union[str, Sequence[str]] = None,
         signs: Union[int, Sequence[int]] = None,
         reductions: Union[str, Sequence[str]] = None,
+        subtract_mean: Union[bool, Sequence[bool]] = None,
     ) -> None:
         """Shift the energy axis of the dataframe by a given amount.
 
@@ -1190,22 +1191,27 @@ def apply_energy_offset(
                 f"Energy column {energy_column} not found in dataframe! "
                 "Run energy calibration first",
             )
-        self._dataframe, metadata = energy.apply_energy_offset(
-            df=self._dataframe,
-            columns=columns,
-            energy_column=energy_column,
-            signs=signs,
-            reductions=reductions,
-            config=self._config,
-        )
-        self._dataframe[energy_column] += constant
-        metadata["offset"] = constant
-        self._attributes.add(
-            metadata,
-            "apply_energy_offset",
-            # TODO: allow only appending when no offset along this column(s) was applied
-            duplicate_policy="append",
-        )
+        metadata = {}
+        if columns is not None:
+            self._dataframe, metadata = energy.apply_energy_offset(
+                df=self._dataframe,
+                columns=columns,
+                energy_column=energy_column,
+                signs=signs,
+                reductions=reductions,
+                subtract_mean=subtract_mean,
+                config=self._config,
+            )
+        if constant is not None:
+            self._dataframe[energy_column] += constant
+            metadata["offset"] = constant
+        if len(metadata) > 0:
+            self._attributes.add(
+                metadata,
+                "apply_energy_offset",
+                # TODO: allow only appending when no offset along this column(s) was applied
+                duplicate_policy="append",
+            )
 
     def append_tof_ns_axis(
         self,