proximity: style cleanup (flake8 F841/E128, isort, mutable default)

.claude/sweep-style-state.csv

@@ -1,6 +1,7 @@
 module,last_inspected,issue,severity_max,categories_found,notes
 geotiff,2026-05-27,2481,HIGH,1;3;4,"Bundled 387 flake8 + ~30 isort fixes since #2285/#2430. F401 x9, F811 x6, F841 x3. E501 x250 (mostly wrapped, 3 file-scope imports keep noqa: E402+E501). E252 x62, blank-line cluster, E128/E127 indents. importorskip imports use # noqa: E402. Cat 5 grep clean."
 polygonize,2026-05-27,2534,HIGH,1;3;4,"F401 line 58 (is_cupy_array unused, not re-exported). E127 lines 83/88 (overload continuation indent in generated_jit). isort: 5-line .utils import block collapses to one line at 100-char limit. Cat 2 clean. Cat 5 grep clean."
+proximity,2026-05-29,2725,HIGH,1;3;4;5,"F841 line 1274 original_chunks dead local in unbounded dask+cupy branch (refactor leftover). Cat 5 mutable default target_values: list = [] in proximity/allocation/direction -> None sentinel, normalized to [] in body (never mutated, behaviour preserved). E128 line 291 np.where continuation under-indent in _vectorized_calc_direction. isort: re-sorted xrspatial import block + blank line after inline import cupy as cp. flake8+isort clean after fix; 69 proximity tests pass + new parametrized regression test. Pre-existing E127 (test_proximity.py 726/752) + test-file isort drift left untouched (out of module scope)."
 rasterize,2026-05-27,2503,HIGH,1;3,F401 line 15 + F811 line 1193 (paired: local import warnings shadowed unused module-level import); E306 line 1775 (nested @cuda.jit). isort clean. Cat 5 grep clean. Fix in PR #2507.
 resample,2026-05-27,2543,MEDIUM,4,isort drift only: 4 multi-line parenthesised imports collapsed to single/one-per-line under line_length=100 (top-of-file scipy.ndimage + xrspatial.utils; local cupyx imports in _nan_aware_interp_cupy and _interp_block_cupy); two blank-line nits after import math in _run_dask_numpy/_run_dask_cupy. flake8 clean. Cat 5 grep clean. 169 resample tests pass.
 zonal,2026-05-27,2522,HIGH,1;3;4,"F401 not_implemented_func (line 42, only present on import line). E501 line 455 (dd.concat one-liner, 117 chars) wrapped across 3 lines. isort: consolidated xrspatial.utils block (merged has_dask_array, dropped not_implemented_func, alphabetised, trimmed extra blank line). Cat 5 grep clean. 125 zonal tests pass."

xrspatial/proximity.py

@@ -24,13 +24,10 @@
     class cupy(object):
         ndarray = False
 
-from xrspatial.pathfinding import _available_memory_bytes
-from xrspatial.utils import (
-    _validate_raster,
-    cuda_args, get_dataarray_resolution, has_cuda_and_cupy,
-    is_cupy_array, is_dask_cupy, ngjit,
-)
 from xrspatial.dataset_support import supports_dataset
+from xrspatial.pathfinding import _available_memory_bytes
+from xrspatial.utils import (_validate_raster, cuda_args, get_dataarray_resolution,
+                             has_cuda_and_cupy, is_cupy_array, is_dask_cupy, ngjit)
 
 EUCLIDEAN = 0
 GREAT_CIRCLE = 1
@@ -288,7 +285,7 @@ def _vectorized_calc_direction(x1, x2, y1, y2):
     dy = y2 - y1
     d = np.arctan2(-dy, dx) * 57.29578
     result = np.where(d < 0, 90.0 - d,
-             np.where(d > 90.0, 360.0 - d + 90.0, 90.0 - d))
+                      np.where(d > 90.0, 360.0 - d + 90.0, 90.0 - d))
     result[(x1 == x2) & (y1 == y2)] = 0.0
     return result.astype(np.float32)
 
@@ -1269,9 +1266,9 @@ def _process_dask(raster, xs, ys):
             was_dask_cupy = has_cuda_and_cupy() and is_dask_cupy(raster)
             if was_dask_cupy:
                 import cupy as cp
+
                 # Unbounded: convert to dask+numpy for KDTree/line-sweep
                 # (KDTree is CPU-only; O(N log T) beats brute-force O(NT))
-                original_chunks = raster.data.chunks
                 raster = raster.copy(
                     data=raster.data.map_blocks(
                         lambda x: x.get(), dtype=raster.dtype,
@@ -1344,7 +1341,7 @@ def proximity(
     raster: xr.DataArray,
     x: str = "x",
     y: str = "y",
-    target_values: list = [],
+    target_values: list = None,
     max_distance: float = np.inf,
     distance_metric: str = "EUCLIDEAN",
 ) -> xr.DataArray:
@@ -1460,6 +1457,9 @@ def proximity(
           * x        (x) int64 0 1 2 3 4
     """
 
+    if target_values is None:
+        target_values = []
+
     _validate_raster(raster, func_name='proximity', name='raster')
 
     proximity_img = _process(
@@ -1487,7 +1487,7 @@ def allocation(
     raster: xr.DataArray,
     x: str = "x",
     y: str = "y",
-    target_values: list = [],
+    target_values: list = None,
     max_distance: float = np.inf,
     distance_metric: str = "EUCLIDEAN",
 ):
@@ -1600,6 +1600,9 @@ def allocation(
           * x        (x) int64 0 1 2 3 4
     """
 
+    if target_values is None:
+        target_values = []
+
     _validate_raster(raster, func_name='allocation', name='raster')
 
     allocation_img = _process(
@@ -1627,7 +1630,7 @@ def direction(
     raster: xr.DataArray,
     x: str = "x",
     y: str = "y",
-    target_values: list = [],
+    target_values: list = None,
     max_distance: float = np.inf,
     distance_metric: str = "EUCLIDEAN",
 ):
@@ -1746,6 +1749,9 @@ def direction(
           * x        (x) int64 0 1 2 3 4
     """
 
+    if target_values is None:
+        target_values = []
+
     _validate_raster(raster, func_name='direction', name='raster')
 
     direction_img = _process(

xrspatial/tests/test_proximity.py

@@ -961,3 +961,26 @@ def test_no_scipy_dask_unbounded_memory_guard():
                 proximity(raster, x='lon', y='lat')
     finally:
         prox_mod.cKDTree = original_ckdtree
+
+
+@pytest.mark.parametrize("func", [proximity, allocation, direction])
+def test_target_values_none_default_matches_empty_list(func):
+    # target_values default switched from [] to a None sentinel; passing
+    # None (the default) must behave exactly like passing an empty list.
+    data = np.asarray([[0., 0., 0., 0., 0.],
+                       [0., 0., 0., 1., 0.],
+                       [0., 0., 0., 0., 0.],
+                       [0., 0., 2., 0., 0.],
+                       [0., 0., 0., 0., 0.]])
+    n, m = data.shape
+    raster = xr.DataArray(data, dims=['y', 'x'])
+    raster['y'] = np.arange(n)[::-1]
+    raster['x'] = np.arange(m)
+
+    default_result = func(raster)
+    explicit_result = func(raster, target_values=[])
+
+    np.testing.assert_array_equal(
+        np.nan_to_num(default_result.data),
+        np.nan_to_num(explicit_result.data),
+    )