From 77e7d6979d5aa9801ca917f4ae49bffc43d5b2c9 Mon Sep 17 00:00:00 2001 From: Brendan Collins Date: Sat, 20 Jun 2026 02:51:39 -0700 Subject: [PATCH 1/2] Add missing morphology accessor methods (#3399) Expose morph_gradient, morph_white_tophat, and morph_black_tophat on both the DataArray and Dataset .xrs accessors, matching the four base morphology ops already present. Add accessor tests for the morphology family and guard all seven methods in the expected-methods checks. --- xrspatial/accessor.py | 24 ++++++++++++++++ xrspatial/tests/test_accessor.py | 47 ++++++++++++++++++++++++++++++++ 2 files changed, 71 insertions(+) diff --git a/xrspatial/accessor.py b/xrspatial/accessor.py index 47f9892b9..5ba6fa064 100644 --- a/xrspatial/accessor.py +++ b/xrspatial/accessor.py @@ -882,6 +882,18 @@ def morph_closing(self, **kwargs): from .morphology import morph_closing return morph_closing(self._obj, **kwargs) + def morph_gradient(self, **kwargs): + from .morphology import morph_gradient + return morph_gradient(self._obj, **kwargs) + + def morph_white_tophat(self, **kwargs): + from .morphology import morph_white_tophat + return morph_white_tophat(self._obj, **kwargs) + + def morph_black_tophat(self, **kwargs): + from .morphology import morph_black_tophat + return morph_black_tophat(self._obj, **kwargs) + # ---- Proximity / Distance ---- def proximity(self, **kwargs): @@ -1523,6 +1535,18 @@ def morph_closing(self, **kwargs): from .morphology import morph_closing return morph_closing(self._obj, **kwargs) + def morph_gradient(self, **kwargs): + from .morphology import morph_gradient + return morph_gradient(self._obj, **kwargs) + + def morph_white_tophat(self, **kwargs): + from .morphology import morph_white_tophat + return morph_white_tophat(self._obj, **kwargs) + + def morph_black_tophat(self, **kwargs): + from .morphology import morph_black_tophat + return morph_black_tophat(self._obj, **kwargs) + # ---- Diffusion ---- def diffuse(self, **kwargs): diff --git a/xrspatial/tests/test_accessor.py b/xrspatial/tests/test_accessor.py index 315e83033..2f1862fcc 100644 --- a/xrspatial/tests/test_accessor.py +++ b/xrspatial/tests/test_accessor.py @@ -88,6 +88,8 @@ def test_dataarray_accessor_has_expected_methods(elevation): 'natural_breaks', 'equal_interval', 'quantile', 'reclassify', 'binary', 'percentiles', 'focal_mean', + 'morph_erode', 'morph_dilate', 'morph_opening', 'morph_closing', + 'morph_gradient', 'morph_white_tophat', 'morph_black_tophat', 'proximity', 'allocation', 'direction', 'cost_distance', 'a_star_search', 'zonal_stats', 'zonal_apply', 'zonal_crosstab', 'crop', 'trim', @@ -111,6 +113,8 @@ def test_dataset_accessor_has_expected_methods(): 'natural_breaks', 'equal_interval', 'quantile', 'reclassify', 'binary', 'percentiles', 'focal_mean', + 'morph_erode', 'morph_dilate', 'morph_opening', 'morph_closing', + 'morph_gradient', 'morph_white_tophat', 'morph_black_tophat', 'proximity', 'allocation', 'direction', 'cost_distance', 'ndvi', 'evi', 'arvi', 'savi', 'nbr', 'sipi', 'rasterize', @@ -222,6 +226,49 @@ def test_da_arvi(nir, red, blue): xr.testing.assert_identical(result, expected) +# --------------------------------------------------------------------------- +# 4b. DataArray morphology — accessor matches direct call +# --------------------------------------------------------------------------- + +_MORPH_KERNEL = np.ones((3, 3), dtype=np.uint8) + + +def test_da_morph_erode(elevation): + from xrspatial.morphology import morph_erode + expected = morph_erode(elevation, kernel=_MORPH_KERNEL) + result = elevation.xrs.morph_erode(kernel=_MORPH_KERNEL) + xr.testing.assert_identical(result, expected) + + +def test_da_morph_gradient(elevation): + from xrspatial.morphology import morph_gradient + expected = morph_gradient(elevation, kernel=_MORPH_KERNEL) + result = elevation.xrs.morph_gradient(kernel=_MORPH_KERNEL) + xr.testing.assert_identical(result, expected) + + +def test_da_morph_white_tophat(elevation): + from xrspatial.morphology import morph_white_tophat + expected = morph_white_tophat(elevation, kernel=_MORPH_KERNEL) + result = elevation.xrs.morph_white_tophat(kernel=_MORPH_KERNEL) + xr.testing.assert_identical(result, expected) + + +def test_da_morph_black_tophat(elevation): + from xrspatial.morphology import morph_black_tophat + expected = morph_black_tophat(elevation, kernel=_MORPH_KERNEL) + result = elevation.xrs.morph_black_tophat(kernel=_MORPH_KERNEL) + xr.testing.assert_identical(result, expected) + + +def test_ds_morph_gradient(elevation): + from xrspatial.morphology import morph_gradient + ds = xr.Dataset({'elev': elevation}) + expected = morph_gradient(ds, kernel=_MORPH_KERNEL) + result = ds.xrs.morph_gradient(kernel=_MORPH_KERNEL) + xr.testing.assert_identical(result, expected) + + # --------------------------------------------------------------------------- # 5. Dataset single-input — accessor matches direct call # --------------------------------------------------------------------------- From cbebb6454b3c11f694c16c59efc9e461ba7ba2fd Mon Sep 17 00:00:00 2001 From: Brendan Collins Date: Sat, 20 Jun 2026 03:03:50 -0700 Subject: [PATCH 2/2] Record morphology api-consistency sweep state (#3399) --- .claude/sweep-api-consistency-state.csv | 29 +++++++++++++------------ 1 file changed, 15 insertions(+), 14 deletions(-) diff --git a/.claude/sweep-api-consistency-state.csv b/.claude/sweep-api-consistency-state.csv index fbdfda8cb..63e9ae23c 100644 --- a/.claude/sweep-api-consistency-state.csv +++ b/.claude/sweep-api-consistency-state.csv @@ -1,14 +1,15 @@ -module,last_inspected,issue,severity_max,categories_found,notes -focal,2026-06-10,3215;3216,MEDIUM,3;4,"Sweep 2026-06-10 (deep-sweep-api-consistency-focal-2026-06-10). 2 MEDIUM findings filed, fixed on branches -01/-02 off this one. (#3215, MEDIUM Cat 4 cross-backend default parity, branch -01) apply() default func=_calc_mean is an @ngjit CPU function but the cupy/dask+cupy paths launch func as a CUDA kernel via _focal_stats_func_cupy func[griddim, blockdim], so apply(cupy_agg, kernel) raises TypeError 'CPUDispatcher' object is not subscriptable (dask+cupy builds the graph and fails at compute). Prior 2026-05-29 sweep dispositioned this LOW as 'documented in the docstring', but the docstring covers explicit funcs -- the default itself is unusable on 2 of 4 backends. Fix: func=None sentinel resolved per backend (_calc_mean CPU, _focal_mean_cuda GPU), explicit-func behavior unchanged; same PR adds the missing name= param to the apply() docstring (signature has name='focal_apply'; mean/focal_stats/hotspots document theirs). (#3216, MEDIUM Cat 3, branch -02) hotspots() docstring lists 3 backends but dask_cupy_func=_hotspots_dask_cupy is dispatched and works; kernel param documented as binary ('values of 1 indicate the kernel') while hotspots accepts weighted kernels and the Gi* formula in the same docstring uses weights w_ij (apply/focal_stats reject non-binary via _validate_binary_kernel, hotspots deliberately does not). Docs-only fix. LOW documented, not fixed: among the 4 focal publics only mean() has @supports_dataset (Dataset-support drift; feature gap, not an API bug). Cross-cutting, notes only per template: emerging_hotspots(raster=), viewshed(raster=), calc_cellsize(raster) still use raster while focal standardized on agg with a DeprecationWarning shim (#2689/PR #2699); library-wide first-arg drift, belongs to those modules' sweeps. No Cat 1 in-module (agg canonical, raster alias warns, both-args raises). No Cat 2 return drift (mean/apply/hotspots 2D same-type, focal_stats 3D (stats,y,x) as documented). No Cat 5 orphan API (apply/focal_stats/hotspots documented in focal.rst autosummary and consumed via xrspatial.focal module path; only mean re-exported top-level; emerging_hotspots top-level vs hotspots module-level asymmetry noted, additive export would be a design call, not filed). cuda-validated: CUDA_AVAILABLE=True on this host; mean/apply/focal_stats/hotspots smoke-tested on cupy with kwarg parity; the apply default crash reproduced on GPU; hotspots weighted-kernel acceptance verified empirically." -geotiff,2026-06-12,3263;3265,MEDIUM,3;5,"Re-sweep 2026-06-12 (deep-sweep-api-consistency-geotiff-2026-06-12); prior pass 2026-06-09 (#3086). Scope: surface changes since 2026-06-09 (pack/unpack fixes #3171-#3241, SUPPORTED_FEATURES reader.unpack/writer.pack/reader.coregister, coregister docs #3248) plus a fresh 5-category pass on open_geotiff/to_geotiff. 2 MEDIUM findings filed and fixed on branches -01/-02 off this one. (#3263, MEDIUM Cat 3, PR #3269, branch -01) open_geotiff unpack docstring said 'A source without scale / offset metadata is a no-op', but unpack=True folds into the masking gate (_finalize_eager_read: mask_and_scale implies masking, rioxarray parity), so a sentinel-bearing uint16 source still comes back float64 with NaN holes; verified identical on all 4 backends (not a parity bug), only a source with neither scale/offset nor a sentinel reads unchanged. Docs-only fix + test_unpack_noop_doc_3263.py pinning wording (scoped to the unpack paragraph) and behavior. (#3265, MEDIUM Cat 5, PR #3273, branch -02) exception-export drift: VRTUnsupportedError (raised 10+ times in _vrt_validation.py on public .vrt reads, documented in geotiff_safe_io.rst which steered users to the private _errors module), CloudSizeLimitError (importable but not in __all__, sibling UnsafeURLError IS exported), and PixelSafetyLimitError (raised by the [stable] max_pixels cap, only importable from _layout/_reader) were the only 3 exceptions raised on public open_geotiff paths missing from the public surface (other 17 exported). Additive fix: import + __all__ + :class: roles in safe_io doc + trigger-point docs naming the exceptions in max_pixels/max_cloud_bytes param docs and geotiff.rst; test_exception_exports_3265.py pins export, identity with private definitions, and a functional max_pixels raise. Clean elsewhere: docstring/signature parity exact on both publics (programmatic check + 218 existing contract tests); no Cat 1 (signatures unchanged since 2026-06-09; pack/unpack pair deliberate), no Cat 2 (DataArray / path returns unchanged), no Cat 4 (shared allow_* defaults match reader/writer; gpu False-vs-None auto-detect documented). SUPPORTED_FEATURES tiers (reader.unpack/writer.pack/reader.coregister experimental) agree with docstring tier markers. coregister= itself lives on accessor.py (excluded module) -- only its SUPPORTED_FEATURES registration is in geotiff, consistent. cuda-validated: CUDA_AVAILABLE=True; open_geotiff smoke-tested with identical kwargs on numpy/cupy/dask/dask+cupy (cpu/gpu pixel parity), to_geotiff gpu=True, cupy pack=True write (#3240 fix confirmed), deprecated aliases mask_and_scale/name/mask_nodata all warn. Both PRs reviewed (COMMENTED) with findings fixed in follow-up commits c14844a8/af3c8a66; branches up to date with origin/main; left for user merge per REVIEW_REQUIRED." -hydro-d8,2026-05-29,2709,HIGH,1;5,"Sweep 2026-05-29 (deep-sweep-api-consistency-hydro-d8-2026-05-29). Scope = the 13 D8-variant files only; dinf/mfd read for reference but not modified. 1 HIGH Cat 1 + 1 MEDIUM Cat 5 fixed in this branch (#2709, PR #2716). HIGH Cat 1: stream_order_d8 named its strahler/shreve selector `ordering` while sibling stream_order_dinf/stream_order_mfd use `method`; both names live in the public API and the __init__.py _StreamOrderDispatch special-cases the drift (translates ordering->method for non-d8). Fix adds `method` as an accepted alias on stream_order_d8 (case-insensitive; takes precedence; conflicting ordering+method raises ValueError), keeping `ordering` working so the out-of-scope dispatcher (passes ordering=) and existing callers are unaffected. Full rename to `method` deferred because deprecating `ordering` would warn on every stream_order(routing='d8') call via the dispatcher I cannot touch in this scope. MEDIUM Cat 5: basins_d8 (watershed_d8.py) is a backward-compat wrapper whose docstring said 'use basin instead' but emitted no warning; added DeprecationWarning(stacklevel=2). Tests added for alias parity/precedence/conflict/case-insensitivity and for the basins_d8 warning. Findings documented but NOT filed per template: (LOW Cat 1 cross-module, out of scope) dinf siblings name the first arg `flow_dir_dinf` (stream_link/flow_path/hand/watershed_dinf) while all D8 funcs use the cleaner `flow_dir`; D8 is the better convention so no D8 change -- the drift lives in the dinf files. (LOW Cat 4 defensive-validation drift) hand_d8 validates np.isfinite(threshold) but stream_link_d8/stream_order_d8 (same threshold: float = 100 param) do not; not user-facing signature surprise, document only. No Cat 2 return drift (every D8 public fn returns xr.DataArray with coords/dims/attrs preserved; Dataset in -> Dataset out via @supports_dataset). No Cat 3 missing-hints beyond fill_d8 z_limit (optional, no hint) which mirrors its sibling style. All 13 D8 funcs are re-exported in xrspatial/hydro/__init__.py (no orphan API). cuda-validated: CUDA_AVAILABLE=True on this host; method-alias parity smoke-tested on a cupy DataArray. CI: ubuntu/windows/3.12 GitHub Actions green; macOS-3.14 + ReadTheDocs slow but no failures. NOTE: the /review-pr review comment could not be posted to GitHub (auto-mode permission denial on gh pr review); review findings were applied to code instead (case-insensitive conflict check + str|None hint, commit f8467320)." -interpolate,2026-06-12,3285,MEDIUM,2,"Sweep 2026-06-12 (deep-sweep-api-consistency-interpolate-2026-06-12). Scope: idw/_idw.py, kriging/_kriging.py, spline/_spline.py, shared _validation.py. 1 MEDIUM Cat 2 finding filed as #3285, fixed on branch -01 off this one: kriging(return_variance=True) singular-matrix fallback (_kriging.py:499) returns prediction, prediction.copy() so the variance DataArray keeps the prediction's name instead of f'{name}_variance' (normal path :523 names it correctly); reproduced by monkeypatching _build_kriging_matrix to None; anything keying on .name (xr.merge, Dataset build) silently collapses the pair. One-line fix + regression test on the singular path. Clean elsewhere: Cat 1 in-module exact (idw/kriging/spline share x, y, z, template positionals and name= default ''; template matches kde's template=); docstring/signature parity exact on all 3 publics (every param documented, Returns sections match incl. kriging's tuple); Cat 4 no default drift (power=2.0, k=None, fill_value=nan, variogram_model='spherical', nlags=15, smoothing=0.0, all single-owner params); Cat 5 no orphan API (all 3 re-exported in xrspatial/__init__.py and autosummaried in docs/source/reference/interpolation.rst; tests touch private helpers only via module paths). Cross-cutting, notes only per template: fill_value (idw) vs fill (rasterize) for the uncovered-pixel value is library-wide drift (idw matches numpy's fill_value convention, left alone); public functions are untyped module-wide (consistent internally, drifts from typed kde/rasterize/proximity siblings -- annotation pass would span the whole module, LOW, not filed); kde's keyword-only style is the library minority so interpolate's positional style matches the rasterize/proximity majority. GPU k-nearest rejection (NotImplementedError) is deliberate and documented in the k param docstring. cuda-validated: CUDA_AVAILABLE=True on this host; idw/kriging/spline smoke-tested with full kwargs on numpy AND cupy DataArrays (variance name parity confirmed on both), dask+numpy and dask+cupy graph construction verified without compute." -mcda,2026-06-10,3148,HIGH,1;2;3;5,"Sweep 2026-06-10 (deep-sweep-api-consistency-mcda-2026-06-10). Fixed in this branch (#3148): (HIGH Cat 1) owa() named its criterion-weight dict criterion_weights while wlc/wpm/sensitivity use weights (same semantics, same _validate_weights); renamed to weights with keyword-only criterion_weights deprecation shim (DeprecationWarning; both names -> TypeError; positional callers untouched). (MEDIUM Cat 2) boolean_overlay annotated criteria as dict-only while every sibling combiner takes xr.Dataset; Dataset already worked via the Mapping interface -- now annotated/documented as xr.Dataset | dict. (MEDIUM Cat 3) ahp_weights docstring Raises claimed ValueError on incomplete comparisons but code warns (UserWarning) and defaults missing pairs to 1 -- docstring now documents Warns behaviour. (MEDIUM Cat 5) ConsistencyResult returned by public ahp_weights but absent from xrspatial/mcda __all__ and docs/source/reference/mcda.rst -- exported and documented. Documented, NOT fixed here: (MEDIUM Cat 2, deferred to parallel sweep-metadata sibling to avoid duplicate PR) constrain() drops attrs via xr.where while the other nine public functions preserve them. (LOW Cat 2) ahp_weights returns (weights, ConsistencyResult) tuple vs rank_weights bare dict -- intentional, documented in both docstrings, no fix. (LOW Cat 4) name=None inherit-input-name (standardize/constrain) vs literal-name defaults (combiners) -- defensible split, document only. Pre-existing backend bugs surfaced by the mandated cupy smoke (accuracy/test-coverage lane, recorded in #3148 body): owa fails on cupy (numpy order-weights array mixed into cupy multiply, combine.py ~336-340) and on ANY dask backend at graph construction (da.sort does not exist, combine.py:356, despite the owa MemoryError message recommending dask); sensitivity(method=monte_carlo) fails on cupy (template.values implicit-conversion guard). constrain on cupy blocked by the known library-wide cupy 13.6 + xarray xr.where astype incompat (dependency-pin issue), not mcda-specific. cuda-validated: CUDA_AVAILABLE=True; all 10 public functions smoke-tested on cupy DataArrays; owa weights=/criterion_weights= shim verified on numpy AND cupy entry points (cupy execution stops at the pre-existing mixed-array bug, signature acceptance confirmed)." -polygonize,2026-06-12,3306;3307,MEDIUM,1;3,"Re-sweep 2026-06-12 (deep-sweep-api-consistency-polygonize-2026-06-12); prior pass 2026-05-19 (#2148). 2 MEDIUM findings filed and fixed on branches -01/-02 off this one. (#3306, MEDIUM Cat 3, branch -01) column_name docstring says 'Only used if return_type is geopandas or spatialpandas' but _to_geojson also consumes it as the per-feature property key (verified: properties={'myval': 1}); docs-only fix + test pinning geojson property naming. (#3307, MEDIUM sibling-behavior drift, branch -02) return_type is the only polygonize parameter validated AFTER the computation: invalid value runs the full backend (spy-verified 1 invocation before raise) while sibling contours() validates up front and lists allowed values; fix hoists the check into the top validation block with an allowed-values message (existing test matches on prefix, unaffected). Re-confirmed prior dispositions, still documented-only per cross-module rule: (HIGH Cat 1 cross-module) connectivity (polygonize, matches GDAL/rasterio/skimage) vs neighborhood (sieve.py, zonal.regions) for the identical 4|8 rook/queen concept -- rename shim belongs in sieve/zonal, out of polygonize scope; (LOW Cat 1 cross-cutting) raster (polygonize/sieve/clip_polygon) vs agg (contours/terrain family) first-arg drift, library-wide, not filed per-module. No new Cat 2 (return_type dispatch shapes match docstring Returns section exactly); no Cat 4 (atol/rtol mirror numpy.isclose, connectivity=4 == sieve neighborhood=4); Cat 5 LOW documented-only: module has no __all__ and the non-underscore internals generated_jit + Turn leak via import-star; polygonize re-exported in __init__.py and accessor, no orphan API. Docstring/signature parity otherwise exact (all 10 params documented, all annotated). Open polygonize issues #3292/#3293 checked -- no overlap with these findings. cuda-validated: CUDA_AVAILABLE=True on this host; polygonize smoke-tested with identical full kwargs on numpy, cupy (int + float atol/rtol=0), and dask+cupy; no backend signature drift." -proximity,2026-06-09,3090;3091,HIGH,2;3,"Sweep 2026-06-09 (deep-sweep-api-consistency-proximity-2026-06-09). 1 HIGH Cat 2 finding (#3090): dask+numpy (and unbounded dask+cupy, which converts to it) KDTree path violates the documented lowest-flat-index tie-break in allocation()/direction() whenever the raster has >1 chunk column. _collect_region_targets concatenates targets chunk-major (iy outer, ix inner) so the tree's target order is not global row-major; _kdtree_query_lowest_index then ties to the wrong target. Existing tie-break tests put both targets in the same raster row where chunk order coincides with row-major, so they pass. Repro: 5x5, targets 2@(1,3) and 3@(2,2), chunks (5,3), pixel (2,3) tied at d=1 -> numpy gives 2, dask gives 3. Bounded map_overlap paths are fine (local row-major order is offset-invariant). 1 MEDIUM Cat 3 finding (#3091): all 3 public docstrings claim numpy + dask+numpy support only while cupy/dask+cupy backends exist, are dispatched, and are tested (the tie-break paragraphs in the same docstrings name all 4 backends); direction() opens with a stray copy-pasted slope line ('downward slope direction') plus a doubled 'the the'; allocation example output reads as float64 but the function returns float32; stale '# convert to have same type as of input @raster' comment. Within-module Cat 1/4/5 clean: proximity/allocation/direction share an identical signature (raster, x='x', y='y', target_values=None, max_distance=np.inf, distance_metric='EUCLIDEAN'); consistent with surface_distance siblings (raster/x/y/target_values/max_distance); all 6 public symbols (incl. euclidean/manhattan/great_circle_distance) re-exported in __init__.py, no orphan API. Cross-cutting, documented not filed: sibling distance modules (surface_distance, cost_distance, balanced_allocation) use mutable default target_values: list = [] while proximity uses the None sentinel - the mutable-default fix belongs to those modules; proximity's target_values: list = None hint would be more precise as Optional[list] (LOW, matches library style). cuda-validated: CUDA_AVAILABLE=True on this host; proximity/allocation/direction smoke-tested with identical kwargs on numpy, cupy, dask+numpy, dask+cupy (proximity parity passed; allocation/direction parity failure is finding #3090)." -rasterize,2026-06-09,3089,HIGH,1,"Sweep 2026-06-09 (deep-sweep-api-consistency-rasterize-2026-06-09). 1 HIGH Cat 1 fixed in this branch (#3089): rasterize(use_cuda=) vs open_geotiff(gpu=) named the identical GPU-backend opt-in differently; these are the only two public entry points with an explicit GPU boolean (no input array to dispatch on; both pair it with chunks= for dask) and both names were live in the public API at once. Fix renames the positional param to gpu (same slot, positional callers unaffected) and appends use_cuda=None as a deprecated alias: DeprecationWarning on use, TypeError when combined with gpu=True. Docstring, GPU merge warning text, CuPy ImportError text, and polygon_clip.py's internal dask+cupy caller updated (guarded so a legacy use_cuda in rasterize_kw does not collide with the new default); all rasterize test call sites migrated to gpu=; regression tests in test_rasterize_gpu_alias_3089.py pin slot position, warning, TypeError, backend parity, and the warning-free clip_polygon path. Re-inspection after the 2026-05-21 pass (#2250); prior cross-module notes (clip_polygon nodata vs fill, name default drift, polygonize column_name vs column) still documented-only. Docstring/signature parity verified programmatically (17/17 params, order matches). New params since last pass (check_crs, max_pixels) consistent with geotiff naming (max_pixels matches geotiff's). No Cat 2/4/5 findings. LOW noted, not fixed (other module's docs): docs/source/user_guide/focal.ipynb claims convolve_2d takes use_cuda, which it does not. cuda-validated: CUDA_AVAILABLE=True; numpy/cupy/dask+numpy/dask+cupy smoke-tested with identical kwargs, values equal." -reproject,2026-06-09,3095;3097,HIGH,1;2;3,"Sweep 2026-06-09 (deep-sweep-api-consistency-reproject-2026-06-09). 2 findings filed and fixed: #3095 -> PR #3125, #3097 -> PR #3134 (branches -01/-02 off this one). (HIGH Cat 2, #3095) merge() raises TypeError ('Implicit conversion to a NumPy array is not allowed') on cupy-backed inputs while sibling reproject() supports numpy/cupy/dask+numpy/dask+cupy; crash site _merge_inmemory info['raster'].values (__init__.py:2572); dask-of-cupy fails the same way at compute via _merge_block_adapter -> _reproject_chunk_numpy/np.asarray. _merge.py has a complete _merge_arrays_cupy that is imported in __init__.py:38 but never called (dead GPU plumbing; the unused import alone is lint issue #3083 from the style sweep). Fix: host round-trip on entry (same pattern as _apply_vertical_shift), GPU result out, docstring documents backend handling. (MEDIUM Cat 3, #3097) _vertical.py Returns docstrings claim 'same type as input/height' but geoid_height(DataArray) returns np.ndarray (verified empirically) and the four conversion wrappers return np.float64/np.ndarray; geoid_height converts scalars to Python float but the wrappers do not (sibling scalar-return drift). Docs-only fix. Documented but NOT fixed: (LOW Cat 1) itrf_transform(src=/tgt=) abbreviations vs source_/target_ elsewhere -- prior 2026-05-29 sweep already weighed this and left it as-is (frames, not CRSes); filed #3099 before noticing the prior disposition, then closed it as not-planned to avoid churn. (LOW Cat 5) module docstring 'Public API' section lists only reproject/merge while __all__ exports 10 names (vertical+itrf funcs invisible in help() header; docs/source/reference/reproject.rst autosummary likewise lists only reproject/merge). Cross-cutting, notes only per template: raster/rasters (reproject) vs agg (terrain family) vs source (geotiff); chunk_size (reproject/merge) vs chunks (open_geotiff); resampling+resolution (reproject/merge/accessor) vs method+target_resolution (resample.py -- resample is the outlier, belongs to a resample-module pass, already in resample row's notes). No Cat 4 default drift (resampling='bilinear'/transform_precision=16/chunk_size=None/bounds_policy='auto'/model='EGM96' consistent across siblings). reproject()/merge() kwarg parity smoke-tested on numpy AND cupy DataArrays (merge cupy crash found exactly there). cuda-validated: CUDA_AVAILABLE=True on this host. CI: all GitHub Actions checks green on both PRs; RTD flapped (pending on #3125, fail on #3134 -- repo-wide backlog, change not docs-rendered); PRs left BLOCKED on REVIEW_REQUIRED for the user to merge." -resample,2026-05-27,2544,MEDIUM,3,"Sweep 2026-05-27 (deep-sweep-api-consistency-resample-2026-05-27). 1 MEDIUM Cat 3 finding fixed in this branch (#2544): resample() was the only public symbol in xrspatial.resample without type annotations on any parameter or return; siblings slope/aspect/hillshade/curvature all annotate `agg: xr.DataArray` and `-> xr.DataArray`. Fix adds annotations matching the docstring (agg: xr.DataArray; scale_factor / target_resolution: float | tuple[float, float] | None; method: str; nodata: float | None; name: str) and a `-> xr.DataArray` return type, plus a docstring note that the @supports_dataset decorator accepts Dataset too. Regression test test_resample_signature_annot_2544.py pins every param and the return annotation. Other findings documented but not filed per template: (MEDIUM Cat 1 cross-module) `method` (resample) vs `resampling` (reproject/merge) -- same conceptual parameter, different name, cross-cutting rename, needs design issue. (LOW Cat 1 cross-cutting) first-arg `agg` (resample/slope/aspect/...) vs `raster` (reproject/rasterize/polygonize/sieve) -- library-wide drift, not per-module. (LOW Cat 5) ALL_METHODS imported by tests but not in __all__ (module has no __all__); borderline orphan but used for test parametrisation only. No Cat 2 (returns xr.DataArray as documented). No Cat 4 mutable defaults. resample is exported in xrspatial/__init__.py. cuda-validated: cupy backend smoke-tested with nearest, bilinear, and average on host with CUDA_AVAILABLE=True." -slope,2026-05-29,2681,MEDIUM,3,"Sweep 2026-05-29 (deep-sweep-api-consistency-slope-2026-05-29). 1 MEDIUM Cat 3 finding fixed in this branch (#2681, PR #2687): slope() annotated name as `str` while every terrain-family sibling (aspect/northness/eastness in aspect.py, curvature in curvature.py) uses Optional[str]. name flows into xr.DataArray(name=name) which accepts None, so slope(agg, name=None) already worked at runtime -- the annotation was just wrong and inconsistent. Fix widens to Optional[str] and imports Optional (module previously imported only Union). Non-breaking (type-hint widening), no deprecation shim. Added test_name_annotation_matches_terrain_family (pins parity vs the 4 siblings via get_type_hints, unwrapping @supports_dataset) and test_name_none_accepted (slope(agg, name=None).name is None). Full test_slope.py passes (43). No backend logic touched -- numpy/cupy/dask+numpy/dask+cupy paths unchanged; public signature is shared across backends via ArrayTypeFunctionMapping. Other categories: no Cat 1 in-module rename (slope/aspect share identical public param names agg/name/method/z_unit/boundary); no Cat 2 return drift (returns xr.DataArray/Dataset via @supports_dataset, same coords/dims/attrs convention as siblings); no Cat 4 default drift (name/method='planar'/z_unit='meter'/boundary='nan' match across the family); no Cat 5 orphan API (slope re-exported in __init__.py, documented, no __all__ but consistent with module convention). Cross-cutting (documented, not filed per template): first-arg `agg` (slope/aspect/curvature) vs `raster` (reproject/rasterize/polygonize) is library-wide drift. cuda-validated: CUDA_AVAILABLE=True on this host; cupy slope smoke-tested (planar) and signature parity confirmed between numpy and cupy entry points." -visibility,2026-06-10,3183,MEDIUM,3;5,"Sweep 2026-06-10 (deep-sweep-api-consistency-visibility-2026-06-10). 2 MEDIUM findings filed as issue #3183, fixed in this branch. (MEDIUM Cat 5) output-name convention drift: viewshed() sets a fixed output name and exposes name=, but cumulative_viewshed (visibility.py:289) and visibility_frequency built/returned DataArrays with name=None. Fix adds name='cumulative_viewshed'/'visibility_frequency' params (Optional[str]) and sets result.name; additive, non-breaking, no shim. coords/attrs were already preserved on both. (MEDIUM Cat 3) line_of_sight (visibility.py:162) annotated frequency_mhz: float = None; default contradicts the float hint and the docstring already says optional. Fix -> Optional[float] (imported typing.Optional). Tests added: cumulative/frequency default+custom name. No Cat 1 naming drift: observer_elev/target_elev/max_distance/x/y and the x0/y0/x1/y1 two-point extension match viewshed and the observers dict keys. No Cat 2 arbitrary return drift: line_of_sight -> Dataset fits its per-sample multi-variable result; the two cumulative funcs -> DataArray like viewshed. No Cat 4 default drift (observer_elev=0/target_elev=0/max_distance=None match). No Cat 5 orphan API: all 3 funcs re-exported in __init__.py; no __all__ but consistent with module convention. cuda-validated: CUDA_AVAILABLE=True on this host; cupy entry points accept the new name= kwarg and the line_of_sight Optional hint. PRE-EXISTING backend bug (out of scope, not an api-consistency issue, NOT filed here): cumulative_viewshed on a cupy raster raises TypeError 'Unsupported type numpy.ndarray' in the count + (vs_data != INVISIBLE) accumulation (numpy accumulator vs cupy viewshed result); reproduced on origin/main without this branch's changes -- a backend-parity gap for a future backend-parity sweep." -zonal,2026-06-10,3188,MEDIUM,1;3;5,"Re-sweep 2026-06-10 (deep-sweep-api-consistency-zonal-2026-06-10). Prior sweep's HIGH zones_ids/zone_ids typo confirmed already fixed on main (#2521). Several previously-documented MEDIUM Cat 3 items also fixed on main since 2026-05-27: crosstab layer docstring now says default=None; hypsometric_integral now has param+return annotations; apply now has -> xr.DataArray. Two remaining safe Cat 3 fixes filed+PR'd this run (issue #3188 / PR #3196): (1) crosstab zone_ids/cat_ids annotated List[...]=None -> wrapped in Optional[...] to match stats()/crop(); (2) crosstab nodata_values docstring said 'Cells with nodata' (copy-paste from apply) -> now references nodata_values. Non-breaking, 17 crosstab tests pass. Documented-not-fixed: (MEDIUM Cat 1) nodata vs nodata_values drift across stats/crosstab (nodata_values, default None, filters VALUES raster) vs apply/hypsometric_integral (nodata, default 0, filters ZONES raster) -- names differ but so do the concepts and defaults, so a blanket rename would conflate two distinct meanings; needs a design decision, not a mechanical shim. (MEDIUM Cat 5) get_full_extent has a public-style docstring+example but is not in __init__.py -- borderline orphan, minor utility, left as-is. (LOW Cat 3) crop() lacks a return type annotation while stats/crosstab/apply/regions/trim annotate theirs. Cross-cutting (not filed): first-arg name varies (stats/crosstab/crop use zones; regions/trim use raster) but regions/trim operate on the raster itself so the name matches the role; library-wide agg vs raster vs values naming spans 20+ modules, out of per-module scope. cuda-validated: CUDA_AVAILABLE=True on this host." \ No newline at end of file +module,last_inspected,issue,severity_max,categories_found,notes +focal,2026-06-10,3215;3216,MEDIUM,3;4,"Sweep 2026-06-10 (deep-sweep-api-consistency-focal-2026-06-10). 2 MEDIUM findings filed, fixed on branches -01/-02 off this one. (#3215, MEDIUM Cat 4 cross-backend default parity, branch -01) apply() default func=_calc_mean is an @ngjit CPU function but the cupy/dask+cupy paths launch func as a CUDA kernel via _focal_stats_func_cupy func[griddim, blockdim], so apply(cupy_agg, kernel) raises TypeError 'CPUDispatcher' object is not subscriptable (dask+cupy builds the graph and fails at compute). Prior 2026-05-29 sweep dispositioned this LOW as 'documented in the docstring', but the docstring covers explicit funcs -- the default itself is unusable on 2 of 4 backends. Fix: func=None sentinel resolved per backend (_calc_mean CPU, _focal_mean_cuda GPU), explicit-func behavior unchanged; same PR adds the missing name= param to the apply() docstring (signature has name='focal_apply'; mean/focal_stats/hotspots document theirs). (#3216, MEDIUM Cat 3, branch -02) hotspots() docstring lists 3 backends but dask_cupy_func=_hotspots_dask_cupy is dispatched and works; kernel param documented as binary ('values of 1 indicate the kernel') while hotspots accepts weighted kernels and the Gi* formula in the same docstring uses weights w_ij (apply/focal_stats reject non-binary via _validate_binary_kernel, hotspots deliberately does not). Docs-only fix. LOW documented, not fixed: among the 4 focal publics only mean() has @supports_dataset (Dataset-support drift; feature gap, not an API bug). Cross-cutting, notes only per template: emerging_hotspots(raster=), viewshed(raster=), calc_cellsize(raster) still use raster while focal standardized on agg with a DeprecationWarning shim (#2689/PR #2699); library-wide first-arg drift, belongs to those modules' sweeps. No Cat 1 in-module (agg canonical, raster alias warns, both-args raises). No Cat 2 return drift (mean/apply/hotspots 2D same-type, focal_stats 3D (stats,y,x) as documented). No Cat 5 orphan API (apply/focal_stats/hotspots documented in focal.rst autosummary and consumed via xrspatial.focal module path; only mean re-exported top-level; emerging_hotspots top-level vs hotspots module-level asymmetry noted, additive export would be a design call, not filed). cuda-validated: CUDA_AVAILABLE=True on this host; mean/apply/focal_stats/hotspots smoke-tested on cupy with kwarg parity; the apply default crash reproduced on GPU; hotspots weighted-kernel acceptance verified empirically." +geotiff,2026-06-12,3263;3265,MEDIUM,3;5,"Re-sweep 2026-06-12 (deep-sweep-api-consistency-geotiff-2026-06-12); prior pass 2026-06-09 (#3086). Scope: surface changes since 2026-06-09 (pack/unpack fixes #3171-#3241, SUPPORTED_FEATURES reader.unpack/writer.pack/reader.coregister, coregister docs #3248) plus a fresh 5-category pass on open_geotiff/to_geotiff. 2 MEDIUM findings filed and fixed on branches -01/-02 off this one. (#3263, MEDIUM Cat 3, PR #3269, branch -01) open_geotiff unpack docstring said 'A source without scale / offset metadata is a no-op', but unpack=True folds into the masking gate (_finalize_eager_read: mask_and_scale implies masking, rioxarray parity), so a sentinel-bearing uint16 source still comes back float64 with NaN holes; verified identical on all 4 backends (not a parity bug), only a source with neither scale/offset nor a sentinel reads unchanged. Docs-only fix + test_unpack_noop_doc_3263.py pinning wording (scoped to the unpack paragraph) and behavior. (#3265, MEDIUM Cat 5, PR #3273, branch -02) exception-export drift: VRTUnsupportedError (raised 10+ times in _vrt_validation.py on public .vrt reads, documented in geotiff_safe_io.rst which steered users to the private _errors module), CloudSizeLimitError (importable but not in __all__, sibling UnsafeURLError IS exported), and PixelSafetyLimitError (raised by the [stable] max_pixels cap, only importable from _layout/_reader) were the only 3 exceptions raised on public open_geotiff paths missing from the public surface (other 17 exported). Additive fix: import + __all__ + :class: roles in safe_io doc + trigger-point docs naming the exceptions in max_pixels/max_cloud_bytes param docs and geotiff.rst; test_exception_exports_3265.py pins export, identity with private definitions, and a functional max_pixels raise. Clean elsewhere: docstring/signature parity exact on both publics (programmatic check + 218 existing contract tests); no Cat 1 (signatures unchanged since 2026-06-09; pack/unpack pair deliberate), no Cat 2 (DataArray / path returns unchanged), no Cat 4 (shared allow_* defaults match reader/writer; gpu False-vs-None auto-detect documented). SUPPORTED_FEATURES tiers (reader.unpack/writer.pack/reader.coregister experimental) agree with docstring tier markers. coregister= itself lives on accessor.py (excluded module) -- only its SUPPORTED_FEATURES registration is in geotiff, consistent. cuda-validated: CUDA_AVAILABLE=True; open_geotiff smoke-tested with identical kwargs on numpy/cupy/dask/dask+cupy (cpu/gpu pixel parity), to_geotiff gpu=True, cupy pack=True write (#3240 fix confirmed), deprecated aliases mask_and_scale/name/mask_nodata all warn. Both PRs reviewed (COMMENTED) with findings fixed in follow-up commits c14844a8/af3c8a66; branches up to date with origin/main; left for user merge per REVIEW_REQUIRED." +hydro-d8,2026-05-29,2709,HIGH,1;5,"Sweep 2026-05-29 (deep-sweep-api-consistency-hydro-d8-2026-05-29). Scope = the 13 D8-variant files only; dinf/mfd read for reference but not modified. 1 HIGH Cat 1 + 1 MEDIUM Cat 5 fixed in this branch (#2709, PR #2716). HIGH Cat 1: stream_order_d8 named its strahler/shreve selector `ordering` while sibling stream_order_dinf/stream_order_mfd use `method`; both names live in the public API and the __init__.py _StreamOrderDispatch special-cases the drift (translates ordering->method for non-d8). Fix adds `method` as an accepted alias on stream_order_d8 (case-insensitive; takes precedence; conflicting ordering+method raises ValueError), keeping `ordering` working so the out-of-scope dispatcher (passes ordering=) and existing callers are unaffected. Full rename to `method` deferred because deprecating `ordering` would warn on every stream_order(routing='d8') call via the dispatcher I cannot touch in this scope. MEDIUM Cat 5: basins_d8 (watershed_d8.py) is a backward-compat wrapper whose docstring said 'use basin instead' but emitted no warning; added DeprecationWarning(stacklevel=2). Tests added for alias parity/precedence/conflict/case-insensitivity and for the basins_d8 warning. Findings documented but NOT filed per template: (LOW Cat 1 cross-module, out of scope) dinf siblings name the first arg `flow_dir_dinf` (stream_link/flow_path/hand/watershed_dinf) while all D8 funcs use the cleaner `flow_dir`; D8 is the better convention so no D8 change -- the drift lives in the dinf files. (LOW Cat 4 defensive-validation drift) hand_d8 validates np.isfinite(threshold) but stream_link_d8/stream_order_d8 (same threshold: float = 100 param) do not; not user-facing signature surprise, document only. No Cat 2 return drift (every D8 public fn returns xr.DataArray with coords/dims/attrs preserved; Dataset in -> Dataset out via @supports_dataset). No Cat 3 missing-hints beyond fill_d8 z_limit (optional, no hint) which mirrors its sibling style. All 13 D8 funcs are re-exported in xrspatial/hydro/__init__.py (no orphan API). cuda-validated: CUDA_AVAILABLE=True on this host; method-alias parity smoke-tested on a cupy DataArray. CI: ubuntu/windows/3.12 GitHub Actions green; macOS-3.14 + ReadTheDocs slow but no failures. NOTE: the /review-pr review comment could not be posted to GitHub (auto-mode permission denial on gh pr review); review findings were applied to code instead (case-insensitive conflict check + str|None hint, commit f8467320)." +interpolate,2026-06-12,3285,MEDIUM,2,"Sweep 2026-06-12 (deep-sweep-api-consistency-interpolate-2026-06-12). Scope: idw/_idw.py, kriging/_kriging.py, spline/_spline.py, shared _validation.py. 1 MEDIUM Cat 2 finding filed as #3285, fixed on branch -01 off this one: kriging(return_variance=True) singular-matrix fallback (_kriging.py:499) returns prediction, prediction.copy() so the variance DataArray keeps the prediction's name instead of f'{name}_variance' (normal path :523 names it correctly); reproduced by monkeypatching _build_kriging_matrix to None; anything keying on .name (xr.merge, Dataset build) silently collapses the pair. One-line fix + regression test on the singular path. Clean elsewhere: Cat 1 in-module exact (idw/kriging/spline share x, y, z, template positionals and name= default ''; template matches kde's template=); docstring/signature parity exact on all 3 publics (every param documented, Returns sections match incl. kriging's tuple); Cat 4 no default drift (power=2.0, k=None, fill_value=nan, variogram_model='spherical', nlags=15, smoothing=0.0, all single-owner params); Cat 5 no orphan API (all 3 re-exported in xrspatial/__init__.py and autosummaried in docs/source/reference/interpolation.rst; tests touch private helpers only via module paths). Cross-cutting, notes only per template: fill_value (idw) vs fill (rasterize) for the uncovered-pixel value is library-wide drift (idw matches numpy's fill_value convention, left alone); public functions are untyped module-wide (consistent internally, drifts from typed kde/rasterize/proximity siblings -- annotation pass would span the whole module, LOW, not filed); kde's keyword-only style is the library minority so interpolate's positional style matches the rasterize/proximity majority. GPU k-nearest rejection (NotImplementedError) is deliberate and documented in the k param docstring. cuda-validated: CUDA_AVAILABLE=True on this host; idw/kriging/spline smoke-tested with full kwargs on numpy AND cupy DataArrays (variance name parity confirmed on both), dask+numpy and dask+cupy graph construction verified without compute." +mcda,2026-06-10,3148,HIGH,1;2;3;5,"Sweep 2026-06-10 (deep-sweep-api-consistency-mcda-2026-06-10). Fixed in this branch (#3148): (HIGH Cat 1) owa() named its criterion-weight dict criterion_weights while wlc/wpm/sensitivity use weights (same semantics, same _validate_weights); renamed to weights with keyword-only criterion_weights deprecation shim (DeprecationWarning; both names -> TypeError; positional callers untouched). (MEDIUM Cat 2) boolean_overlay annotated criteria as dict-only while every sibling combiner takes xr.Dataset; Dataset already worked via the Mapping interface -- now annotated/documented as xr.Dataset | dict. (MEDIUM Cat 3) ahp_weights docstring Raises claimed ValueError on incomplete comparisons but code warns (UserWarning) and defaults missing pairs to 1 -- docstring now documents Warns behaviour. (MEDIUM Cat 5) ConsistencyResult returned by public ahp_weights but absent from xrspatial/mcda __all__ and docs/source/reference/mcda.rst -- exported and documented. Documented, NOT fixed here: (MEDIUM Cat 2, deferred to parallel sweep-metadata sibling to avoid duplicate PR) constrain() drops attrs via xr.where while the other nine public functions preserve them. (LOW Cat 2) ahp_weights returns (weights, ConsistencyResult) tuple vs rank_weights bare dict -- intentional, documented in both docstrings, no fix. (LOW Cat 4) name=None inherit-input-name (standardize/constrain) vs literal-name defaults (combiners) -- defensible split, document only. Pre-existing backend bugs surfaced by the mandated cupy smoke (accuracy/test-coverage lane, recorded in #3148 body): owa fails on cupy (numpy order-weights array mixed into cupy multiply, combine.py ~336-340) and on ANY dask backend at graph construction (da.sort does not exist, combine.py:356, despite the owa MemoryError message recommending dask); sensitivity(method=monte_carlo) fails on cupy (template.values implicit-conversion guard). constrain on cupy blocked by the known library-wide cupy 13.6 + xarray xr.where astype incompat (dependency-pin issue), not mcda-specific. cuda-validated: CUDA_AVAILABLE=True; all 10 public functions smoke-tested on cupy DataArrays; owa weights=/criterion_weights= shim verified on numpy AND cupy entry points (cupy execution stops at the pre-existing mixed-array bug, signature acceptance confirmed)." +morphology,2026-06-20,3399,MEDIUM,5,"Sweep 2026-06-20 (deep-sweep-api-consistency-morphology-2026-06-20). 1 MEDIUM Cat 5 finding filed as #3399, fixed in this branch (PR #3409). Cat 5 accessor-parity gap: all 7 public morphology functions are exported in xrspatial/__init__.py, documented, and tested, but the .xrs accessor exposed only morph_erode/dilate/opening/closing on both XrsSpatialDataArrayAccessor and XrsSpatialDatasetAccessor; morph_gradient/white_tophat/black_tophat were missing (da.xrs.morph_gradient -> AttributeError while da.xrs.morph_erode works). Root cause: base 4 ops landed #949 + accessors #1042; derived 3 ops landed later #1026 and the accessor was never updated. Fix adds the 3 forwarding methods to both accessor classes (mechanical, matches existing pattern) plus accessor tests (none existed for morph before) and guards all 7 method names in the expected-methods checks. Clean elsewhere: Cat 1 no in-module naming drift -- all 7 publics share the exact signature (agg, kernel=None, boundary='nan', name=''), verified programmatically; matches kernel-op siblings convolution_2d/focal.apply/hotspots which also use agg/kernel/boundary/name. Cat 2 no return drift (all 7 return xr.DataArray with coords/dims/attrs preserved via _dispatch / @supports_dataset). Cat 3 docstring/signature parity exact on all 7 (every param documented, Returns sections all DataArray). Cat 4 no default drift (kernel=None->3x3 ones, boundary='nan' uniform across all 7). Cross-cutting, notes only per template: convolution_2d orders name before boundary while morphology orders boundary before name (both keyword-defaulted, cosmetic); focal.apply/hotspots accept a keyword-only raster= alias for agg but that alias is focal-only (not a library convention) so morphology lacking it is not drift; library-wide first-arg agg vs raster drift spans 20+ modules, out of per-module scope. cuda-validated: CUDA_AVAILABLE=True on this host; all 7 publics smoke-tested with identical kwargs on numpy AND cupy DataArrays (shape parity, no signature drift between numpy/cupy entry points). PR reviewed (COMMENTED), no findings; branch merged with origin/main (clean), left BLOCKED on REVIEW_REQUIRED for user merge." +polygonize,2026-06-12,3306;3307,MEDIUM,1;3,"Re-sweep 2026-06-12 (deep-sweep-api-consistency-polygonize-2026-06-12); prior pass 2026-05-19 (#2148). 2 MEDIUM findings filed and fixed on branches -01/-02 off this one. (#3306, MEDIUM Cat 3, branch -01) column_name docstring says 'Only used if return_type is geopandas or spatialpandas' but _to_geojson also consumes it as the per-feature property key (verified: properties={'myval': 1}); docs-only fix + test pinning geojson property naming. (#3307, MEDIUM sibling-behavior drift, branch -02) return_type is the only polygonize parameter validated AFTER the computation: invalid value runs the full backend (spy-verified 1 invocation before raise) while sibling contours() validates up front and lists allowed values; fix hoists the check into the top validation block with an allowed-values message (existing test matches on prefix, unaffected). Re-confirmed prior dispositions, still documented-only per cross-module rule: (HIGH Cat 1 cross-module) connectivity (polygonize, matches GDAL/rasterio/skimage) vs neighborhood (sieve.py, zonal.regions) for the identical 4|8 rook/queen concept -- rename shim belongs in sieve/zonal, out of polygonize scope; (LOW Cat 1 cross-cutting) raster (polygonize/sieve/clip_polygon) vs agg (contours/terrain family) first-arg drift, library-wide, not filed per-module. No new Cat 2 (return_type dispatch shapes match docstring Returns section exactly); no Cat 4 (atol/rtol mirror numpy.isclose, connectivity=4 == sieve neighborhood=4); Cat 5 LOW documented-only: module has no __all__ and the non-underscore internals generated_jit + Turn leak via import-star; polygonize re-exported in __init__.py and accessor, no orphan API. Docstring/signature parity otherwise exact (all 10 params documented, all annotated). Open polygonize issues #3292/#3293 checked -- no overlap with these findings. cuda-validated: CUDA_AVAILABLE=True on this host; polygonize smoke-tested with identical full kwargs on numpy, cupy (int + float atol/rtol=0), and dask+cupy; no backend signature drift." +proximity,2026-06-09,3090;3091,HIGH,2;3,"Sweep 2026-06-09 (deep-sweep-api-consistency-proximity-2026-06-09). 1 HIGH Cat 2 finding (#3090): dask+numpy (and unbounded dask+cupy, which converts to it) KDTree path violates the documented lowest-flat-index tie-break in allocation()/direction() whenever the raster has >1 chunk column. _collect_region_targets concatenates targets chunk-major (iy outer, ix inner) so the tree's target order is not global row-major; _kdtree_query_lowest_index then ties to the wrong target. Existing tie-break tests put both targets in the same raster row where chunk order coincides with row-major, so they pass. Repro: 5x5, targets 2@(1,3) and 3@(2,2), chunks (5,3), pixel (2,3) tied at d=1 -> numpy gives 2, dask gives 3. Bounded map_overlap paths are fine (local row-major order is offset-invariant). 1 MEDIUM Cat 3 finding (#3091): all 3 public docstrings claim numpy + dask+numpy support only while cupy/dask+cupy backends exist, are dispatched, and are tested (the tie-break paragraphs in the same docstrings name all 4 backends); direction() opens with a stray copy-pasted slope line ('downward slope direction') plus a doubled 'the the'; allocation example output reads as float64 but the function returns float32; stale '# convert to have same type as of input @raster' comment. Within-module Cat 1/4/5 clean: proximity/allocation/direction share an identical signature (raster, x='x', y='y', target_values=None, max_distance=np.inf, distance_metric='EUCLIDEAN'); consistent with surface_distance siblings (raster/x/y/target_values/max_distance); all 6 public symbols (incl. euclidean/manhattan/great_circle_distance) re-exported in __init__.py, no orphan API. Cross-cutting, documented not filed: sibling distance modules (surface_distance, cost_distance, balanced_allocation) use mutable default target_values: list = [] while proximity uses the None sentinel - the mutable-default fix belongs to those modules; proximity's target_values: list = None hint would be more precise as Optional[list] (LOW, matches library style). cuda-validated: CUDA_AVAILABLE=True on this host; proximity/allocation/direction smoke-tested with identical kwargs on numpy, cupy, dask+numpy, dask+cupy (proximity parity passed; allocation/direction parity failure is finding #3090)." +rasterize,2026-06-09,3089,HIGH,1,"Sweep 2026-06-09 (deep-sweep-api-consistency-rasterize-2026-06-09). 1 HIGH Cat 1 fixed in this branch (#3089): rasterize(use_cuda=) vs open_geotiff(gpu=) named the identical GPU-backend opt-in differently; these are the only two public entry points with an explicit GPU boolean (no input array to dispatch on; both pair it with chunks= for dask) and both names were live in the public API at once. Fix renames the positional param to gpu (same slot, positional callers unaffected) and appends use_cuda=None as a deprecated alias: DeprecationWarning on use, TypeError when combined with gpu=True. Docstring, GPU merge warning text, CuPy ImportError text, and polygon_clip.py's internal dask+cupy caller updated (guarded so a legacy use_cuda in rasterize_kw does not collide with the new default); all rasterize test call sites migrated to gpu=; regression tests in test_rasterize_gpu_alias_3089.py pin slot position, warning, TypeError, backend parity, and the warning-free clip_polygon path. Re-inspection after the 2026-05-21 pass (#2250); prior cross-module notes (clip_polygon nodata vs fill, name default drift, polygonize column_name vs column) still documented-only. Docstring/signature parity verified programmatically (17/17 params, order matches). New params since last pass (check_crs, max_pixels) consistent with geotiff naming (max_pixels matches geotiff's). No Cat 2/4/5 findings. LOW noted, not fixed (other module's docs): docs/source/user_guide/focal.ipynb claims convolve_2d takes use_cuda, which it does not. cuda-validated: CUDA_AVAILABLE=True; numpy/cupy/dask+numpy/dask+cupy smoke-tested with identical kwargs, values equal." +reproject,2026-06-09,3095;3097,HIGH,1;2;3,"Sweep 2026-06-09 (deep-sweep-api-consistency-reproject-2026-06-09). 2 findings filed and fixed: #3095 -> PR #3125, #3097 -> PR #3134 (branches -01/-02 off this one). (HIGH Cat 2, #3095) merge() raises TypeError ('Implicit conversion to a NumPy array is not allowed') on cupy-backed inputs while sibling reproject() supports numpy/cupy/dask+numpy/dask+cupy; crash site _merge_inmemory info['raster'].values (__init__.py:2572); dask-of-cupy fails the same way at compute via _merge_block_adapter -> _reproject_chunk_numpy/np.asarray. _merge.py has a complete _merge_arrays_cupy that is imported in __init__.py:38 but never called (dead GPU plumbing; the unused import alone is lint issue #3083 from the style sweep). Fix: host round-trip on entry (same pattern as _apply_vertical_shift), GPU result out, docstring documents backend handling. (MEDIUM Cat 3, #3097) _vertical.py Returns docstrings claim 'same type as input/height' but geoid_height(DataArray) returns np.ndarray (verified empirically) and the four conversion wrappers return np.float64/np.ndarray; geoid_height converts scalars to Python float but the wrappers do not (sibling scalar-return drift). Docs-only fix. Documented but NOT fixed: (LOW Cat 1) itrf_transform(src=/tgt=) abbreviations vs source_/target_ elsewhere -- prior 2026-05-29 sweep already weighed this and left it as-is (frames, not CRSes); filed #3099 before noticing the prior disposition, then closed it as not-planned to avoid churn. (LOW Cat 5) module docstring 'Public API' section lists only reproject/merge while __all__ exports 10 names (vertical+itrf funcs invisible in help() header; docs/source/reference/reproject.rst autosummary likewise lists only reproject/merge). Cross-cutting, notes only per template: raster/rasters (reproject) vs agg (terrain family) vs source (geotiff); chunk_size (reproject/merge) vs chunks (open_geotiff); resampling+resolution (reproject/merge/accessor) vs method+target_resolution (resample.py -- resample is the outlier, belongs to a resample-module pass, already in resample row's notes). No Cat 4 default drift (resampling='bilinear'/transform_precision=16/chunk_size=None/bounds_policy='auto'/model='EGM96' consistent across siblings). reproject()/merge() kwarg parity smoke-tested on numpy AND cupy DataArrays (merge cupy crash found exactly there). cuda-validated: CUDA_AVAILABLE=True on this host. CI: all GitHub Actions checks green on both PRs; RTD flapped (pending on #3125, fail on #3134 -- repo-wide backlog, change not docs-rendered); PRs left BLOCKED on REVIEW_REQUIRED for the user to merge." +resample,2026-05-27,2544,MEDIUM,3,"Sweep 2026-05-27 (deep-sweep-api-consistency-resample-2026-05-27). 1 MEDIUM Cat 3 finding fixed in this branch (#2544): resample() was the only public symbol in xrspatial.resample without type annotations on any parameter or return; siblings slope/aspect/hillshade/curvature all annotate `agg: xr.DataArray` and `-> xr.DataArray`. Fix adds annotations matching the docstring (agg: xr.DataArray; scale_factor / target_resolution: float | tuple[float, float] | None; method: str; nodata: float | None; name: str) and a `-> xr.DataArray` return type, plus a docstring note that the @supports_dataset decorator accepts Dataset too. Regression test test_resample_signature_annot_2544.py pins every param and the return annotation. Other findings documented but not filed per template: (MEDIUM Cat 1 cross-module) `method` (resample) vs `resampling` (reproject/merge) -- same conceptual parameter, different name, cross-cutting rename, needs design issue. (LOW Cat 1 cross-cutting) first-arg `agg` (resample/slope/aspect/...) vs `raster` (reproject/rasterize/polygonize/sieve) -- library-wide drift, not per-module. (LOW Cat 5) ALL_METHODS imported by tests but not in __all__ (module has no __all__); borderline orphan but used for test parametrisation only. No Cat 2 (returns xr.DataArray as documented). No Cat 4 mutable defaults. resample is exported in xrspatial/__init__.py. cuda-validated: cupy backend smoke-tested with nearest, bilinear, and average on host with CUDA_AVAILABLE=True." +slope,2026-05-29,2681,MEDIUM,3,"Sweep 2026-05-29 (deep-sweep-api-consistency-slope-2026-05-29). 1 MEDIUM Cat 3 finding fixed in this branch (#2681, PR #2687): slope() annotated name as `str` while every terrain-family sibling (aspect/northness/eastness in aspect.py, curvature in curvature.py) uses Optional[str]. name flows into xr.DataArray(name=name) which accepts None, so slope(agg, name=None) already worked at runtime -- the annotation was just wrong and inconsistent. Fix widens to Optional[str] and imports Optional (module previously imported only Union). Non-breaking (type-hint widening), no deprecation shim. Added test_name_annotation_matches_terrain_family (pins parity vs the 4 siblings via get_type_hints, unwrapping @supports_dataset) and test_name_none_accepted (slope(agg, name=None).name is None). Full test_slope.py passes (43). No backend logic touched -- numpy/cupy/dask+numpy/dask+cupy paths unchanged; public signature is shared across backends via ArrayTypeFunctionMapping. Other categories: no Cat 1 in-module rename (slope/aspect share identical public param names agg/name/method/z_unit/boundary); no Cat 2 return drift (returns xr.DataArray/Dataset via @supports_dataset, same coords/dims/attrs convention as siblings); no Cat 4 default drift (name/method='planar'/z_unit='meter'/boundary='nan' match across the family); no Cat 5 orphan API (slope re-exported in __init__.py, documented, no __all__ but consistent with module convention). Cross-cutting (documented, not filed per template): first-arg `agg` (slope/aspect/curvature) vs `raster` (reproject/rasterize/polygonize) is library-wide drift. cuda-validated: CUDA_AVAILABLE=True on this host; cupy slope smoke-tested (planar) and signature parity confirmed between numpy and cupy entry points." +visibility,2026-06-10,3183,MEDIUM,3;5,"Sweep 2026-06-10 (deep-sweep-api-consistency-visibility-2026-06-10). 2 MEDIUM findings filed as issue #3183, fixed in this branch. (MEDIUM Cat 5) output-name convention drift: viewshed() sets a fixed output name and exposes name=, but cumulative_viewshed (visibility.py:289) and visibility_frequency built/returned DataArrays with name=None. Fix adds name='cumulative_viewshed'/'visibility_frequency' params (Optional[str]) and sets result.name; additive, non-breaking, no shim. coords/attrs were already preserved on both. (MEDIUM Cat 3) line_of_sight (visibility.py:162) annotated frequency_mhz: float = None; default contradicts the float hint and the docstring already says optional. Fix -> Optional[float] (imported typing.Optional). Tests added: cumulative/frequency default+custom name. No Cat 1 naming drift: observer_elev/target_elev/max_distance/x/y and the x0/y0/x1/y1 two-point extension match viewshed and the observers dict keys. No Cat 2 arbitrary return drift: line_of_sight -> Dataset fits its per-sample multi-variable result; the two cumulative funcs -> DataArray like viewshed. No Cat 4 default drift (observer_elev=0/target_elev=0/max_distance=None match). No Cat 5 orphan API: all 3 funcs re-exported in __init__.py; no __all__ but consistent with module convention. cuda-validated: CUDA_AVAILABLE=True on this host; cupy entry points accept the new name= kwarg and the line_of_sight Optional hint. PRE-EXISTING backend bug (out of scope, not an api-consistency issue, NOT filed here): cumulative_viewshed on a cupy raster raises TypeError 'Unsupported type numpy.ndarray' in the count + (vs_data != INVISIBLE) accumulation (numpy accumulator vs cupy viewshed result); reproduced on origin/main without this branch's changes -- a backend-parity gap for a future backend-parity sweep." +zonal,2026-06-10,3188,MEDIUM,1;3;5,"Re-sweep 2026-06-10 (deep-sweep-api-consistency-zonal-2026-06-10). Prior sweep's HIGH zones_ids/zone_ids typo confirmed already fixed on main (#2521). Several previously-documented MEDIUM Cat 3 items also fixed on main since 2026-05-27: crosstab layer docstring now says default=None; hypsometric_integral now has param+return annotations; apply now has -> xr.DataArray. Two remaining safe Cat 3 fixes filed+PR'd this run (issue #3188 / PR #3196): (1) crosstab zone_ids/cat_ids annotated List[...]=None -> wrapped in Optional[...] to match stats()/crop(); (2) crosstab nodata_values docstring said 'Cells with nodata' (copy-paste from apply) -> now references nodata_values. Non-breaking, 17 crosstab tests pass. Documented-not-fixed: (MEDIUM Cat 1) nodata vs nodata_values drift across stats/crosstab (nodata_values, default None, filters VALUES raster) vs apply/hypsometric_integral (nodata, default 0, filters ZONES raster) -- names differ but so do the concepts and defaults, so a blanket rename would conflate two distinct meanings; needs a design decision, not a mechanical shim. (MEDIUM Cat 5) get_full_extent has a public-style docstring+example but is not in __init__.py -- borderline orphan, minor utility, left as-is. (LOW Cat 3) crop() lacks a return type annotation while stats/crosstab/apply/regions/trim annotate theirs. Cross-cutting (not filed): first-arg name varies (stats/crosstab/crop use zones; regions/trim use raster) but regions/trim operate on the raster itself so the name matches the role; library-wide agg vs raster vs values naming spans 20+ modules, out of per-module scope. cuda-validated: CUDA_AVAILABLE=True on this host."