Add balanced service area partitioning (#939)#943
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Per-source cost-distance with iterative bias adjustment to produce territories of roughly equal cost-weighted area.
Covers two-source, three-source, single-source, no-source, NaN barrier, asymmetric friction, target_values, and validation errors.
Covers standard vs balanced comparison, asymmetric friction, three sources, tolerance tuning, and barriers.
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Summary
balanced_allocation()which partitions a cost surface into territories of roughly equal cost-weighted areacost_distanceper source, then iteratively adjusts additive biases until territory weights convergecost_distance, no custom kernelsCloses #939
What changed
xrspatial/balanced_allocation.py-- new module with thebalanced_allocationfunctionxrspatial/__init__.py-- exportxrspatial/tests/test_balanced_allocation.py-- 12 tests (two/three/single/no sources, NaN barriers, asymmetric friction, target_values, validation errors)docs/source/reference/proximity.rst-- API docs entryexamples/user_guide/15_Balanced_Allocation.ipynb-- user guide notebookREADME.md-- feature matrix rowTest plan
pytest xrspatial/tests/test_balanced_allocation.py -k "not cupy"-- 12/12 pass