Fuse hypsometric_integral dask path to a single graph evaluation#1212
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brendancol merged 1 commit intomasterfrom Apr 16, 2026
Merged
Fuse hypsometric_integral dask path to a single graph evaluation#1212brendancol merged 1 commit intomasterfrom
brendancol merged 1 commit intomasterfrom
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_hi_dask_numpy did two blocking dask.compute() calls (_unique_finite_zones at one step, _hi_reduce at the next), so the caller paid for two full input scans before the lazy map_blocks output was even returned. _hi_reduce also np.stacked the per-block partials into an (n_blocks, n_zones, 4) array on the scheduler; at 240k blocks * 1000 zones that is ~7.7 GB resident in a single scheduler task. Have each block discover its own local unique zones and return a dict mapping zone id -> (min, max, sum, count). _hi_reduce stream-merges the partial dicts into a global hi_lookup so scheduler peak memory scales with the number of distinct zones, not n_blocks * n_zones. The up-front _unique_finite_zones pass is gone and the whole dask path collapses to a single graph evaluation.
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Summary
_hi_block_statsnow discovers its own local unique zones and returns a dict ofzone_id -> (min, max, sum, count), so there is no up-front_unique_finite_zonespass._hi_reducestream-merges the per-block dicts into a single hi_lookup. Scheduler peak memory now scales with the number of distinct zones instead ofn_blocks * n_zones.dask.compute()calls to one.Motivation
On the previous implementation the dask+numpy path did two full graph evaluations before the user ever called
.compute()on the result:_unique_finite_zones(zones_data)to discover zones globally._hi_reduceon all per-block partials to build the hi_lookup dict.On top of that,
_hi_reducebuiltnp.stack(partials_list)producing an(n_blocks, n_zones, 4)float64 array in a single scheduler task — at 240,000 blocks * 1000 zones that is ~7.7 GB held on the scheduler.The streaming dict-merge keeps scheduler memory proportional to the number of distinct zones (tens of KB for typical inputs) and halves the wall time for the dask backend.
Benchmark
Synthetic input: 512×512 float64, chunks=128 (16 blocks), 20 integer zones.
Test plan
pytest xrspatial/tests/test_hypsometric_integral.py— 29 tests passpytest xrspatial/tests/test_zonal.py— full zonal suite pass