Add raster-based dasymetric mapping module#936
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Adds disaggregate(), pycnophylactic(), and validate_disaggregation() for redistributing zone-level values onto finer raster grids. disaggregate supports three methods (binary, weighted, limiting_variable) across all four backends (numpy, cupy, dask+numpy, dask+cupy). pycnophylactic implements Tobler's smooth interpolation with iterative Laplacian smoothing and mass correction (numpy/cupy). validate_disaggregation checks that zone totals are preserved within tolerance across all backends. 51 tests covering known values, conservation, edge cases, cross-backend parity, and input validation.
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Closes #930.
Summary
disaggregate()for redistributing zone-level values (e.g. population per census tract) onto a finer raster grid using ancillary weights. Three methods:'binary','weighted','limiting_variable'. All four backends supported for binary/weighted; limiting_variable is numpy-only.pycnophylactic()implementing Tobler's (1979) smooth interpolation — iterative Laplacian smoothing with mass correction that preserves zone totals. Numpy and cupy (CPU fallback) supported; dask raisesNotImplementedErrorsince the algorithm is inherently iterative.validate_disaggregation()to check that zone totals in a result match the input values within tolerance. Works across all four backends..xrsfordisaggregateandpycnophylactic.Test plan
pytest xrspatial/tests/test_dasymetric.py -v— 51 tests passsum(result[zone]) == values[zone])from xrspatial import disaggregate, pycnophylactic, validate_disaggregation