Remove workaround and use new scipp.bin dim arg

Author: SimonHeybrock

src/ess/powder/grouping.py

@@ -2,8 +2,6 @@
 # Copyright (c) 2023 Scipp contributors (https://github.com/scipp)
 """Grouping and merging of pixels / voxels."""
 
-import scipp as sc
-
 from .types import (
     DspacingBins,
     DspacingData,
@@ -14,28 +12,11 @@
 )
 
 
-def _drop_grouping_and_bin(
-    data: sc.DataArray, *, dims_to_reduce: tuple[str, ...] | None = None, edges: dict
-) -> sc.DataArray:
-    all_pixels = data if dims_to_reduce == () else data.bins.concat(dims_to_reduce)
-    # all_pixels may just have a single bin now, which currently yields
-    # inferior performance when binning (no/bad multi-threading?).
-    # We operate on the content buffer for better multi-threaded performance.
-    if all_pixels.ndim == 0:
-        return (
-            all_pixels.value.bin(**edges)
-            .assign_coords(all_pixels.coords)
-            .assign_masks(all_pixels.masks)
-        )
-    else:
-        return all_pixels.bin(**edges)
-
-
 def focus_data_dspacing(
     data: DspacingData[RunType], dspacing_bins: DspacingBins
 ) -> FocussedDataDspacing[RunType]:
     return FocussedDataDspacing[RunType](
-        _drop_grouping_and_bin(data, edges={dspacing_bins.dim: dspacing_bins})
+        data.bin({dspacing_bins.dim: dspacing_bins}, dim=data.dims)
     )
 
 
@@ -45,9 +26,7 @@ def focus_data_dspacing_and_two_theta(
     twotheta_bins: TwoThetaBins,
 ) -> FocussedDataDspacingTwoTheta[RunType]:
     return FocussedDataDspacingTwoTheta[RunType](
-        data.bin({twotheta_bins.dim: twotheta_bins}).bin(
-            {dspacing_bins.dim: dspacing_bins}
-        )
+        data.bin({twotheta_bins.dim: twotheta_bins, dspacing_bins.dim: dspacing_bins})
     )