Fixes #560: weighted A* pathfinding with friction surface#862
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brendancol merged 3 commits intomasterfrom Feb 23, 2026
Merged
Fixes #560: weighted A* pathfinding with friction surface#862brendancol merged 3 commits intomasterfrom
brendancol merged 3 commits intomasterfrom
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Replace the O(h*w) open-list scan with a binary min-heap (reused from cost_distance) and add optional friction weighting to a_star_search(). Edge costs now use cellsize-scaled spatial distances instead of pixel- space distances, and when a friction surface is provided the cost model matches cost_distance (geometric_distance * mean_friction_of_endpoints).
Sparse dask A* loads chunks on demand via LRU cache so pathfinding works on datasets that don't fit in RAM. CuPy falls back to the existing numpy kernel with CPU↔GPU transfers.
Add backend support table to docstring and user guide notebook, dask out-of-core example, and CPU-fallback symbol in README matrix.
This was referenced Feb 23, 2026
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Summary
_a_star_searchwith O(log n) heap operations (reused fromcost_distance)a_star_search()accepts an optionalfrictionDataArray; edge costs becomegeometric_distance × mean_friction_of_endpoints, matching thecost_distance()cost modelcost_distance()Test plan
pytest xrspatial/tests/test_pathfinding.py -v— 10 tests pass (4 existing updated for cellsize scaling + 6 new weighted tests)pytest xrspatial/tests/test_cost_distance.py -v— 19 tests unchanged, all passjupyter nbconvert --execute docs/source/user_guide/pathfinding.ipynb— executes cleanly, cost_distance validation printsMatch: True