perf: skip radial bins computation when PYAUTO_WORKSPACE_SMALL_DATASETS=1

Early-return a uniform size-2 array from
over_sample_size_via_radial_bins_from(), avoiding the numba JIT
compilation and radial distance computation on small test grids.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: 2 people

autoarray/operators/over_sampling/over_sample_util.py

@@ -232,6 +232,9 @@ def over_sample_size_via_radial_bins_from(
     """
     Returns an adaptive sub-grid size based on the radial distance of every pixel from the centre of the mask.
 
+    When ``PYAUTO_WORKSPACE_SMALL_DATASETS=1`` returns a uniform size-2 array
+    immediately, skipping the expensive radial-bin computation and numba JIT.
+
     The adaptive sub-grid size is computed as follows:
 
     1) Compute the radial distance of every pixel in the mask from the centre of the mask (or input centres).
@@ -264,6 +267,11 @@ def over_sample_size_via_radial_bins_from(
     the centre of the mask.
     """
 
+    import os
+
+    if os.environ.get("PYAUTO_WORKSPACE_SMALL_DATASETS") == "1":
+        return Array2D(values=np.full(grid.shape_slim, 2.0), mask=grid.mask)
+
     if centre_list is None:
         centre_list = [grid.mask.mask_centre]