Add kernel density estimation (KDE)#1170
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_extract_transect was calling .compute() on the full dask array just to read a handful of transect cells. Now uses vindex fancy indexing so only the relevant chunks are materialized. cumulative_viewshed was allocating a full-size np.zeros count array and calling .values on each viewshed result, forcing materialization every iteration. Now accumulates lazily with da.zeros and dask array addition when the input is dask-backed.
The dask Tier B memory guard underestimated peak usage at 280 bytes/pixel. Actual peak during lexsort reaches ~360 bytes/pixel (sorted + unsorted event_list coexist) plus 8 bytes/pixel for the computed raster. Updated estimate to 368 bytes/pixel to prevent borderline OOM. Also use astype(copy=False) to skip the float64 copy when data is already float64.
Implements kde() and line_density() for point-to-raster and line-to-raster density surfaces. Supports Gaussian, Epanechnikov, and quartic kernels with automatic bandwidth selection via Silverman's rule. All four backends: numpy, cupy, dask+numpy, dask+cupy.
35 tests covering correctness, edge cases, kernel types, bandwidth selection, weights, and cross-backend parity (dask+numpy, cupy). Removes hard cutoff from GPU Gaussian kernel to avoid box-vs-circle mismatch with CPU.
Creates docs/source/reference/kde.rst with autosummary entries for kde() and line_density(). Adds both functions to __init__.py and the docs toctree.
Covers Gaussian/Epanechnikov/quartic kernels, bandwidth effects, weighted KDE, and line density with synthetic earthquake and road network data.
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The repo has
rasterize()for burning discrete values onto a grid but nothing for continuous density surfaces. This adds that.Closes #1143
Summary
kde()turns point coordinates into a density raster. Gaussian, Epanechnikov, and quartic kernels. Automatic bandwidth (Silverman's rule) or manual. Optional per-point weights. All four backends: numpy, cupy, dask+numpy, dask+cupy.line_density()does the same for line segments. numpy only for now.examples/user_guide/49_KDE.ipynb) with earthquake cluster and road network examples.docs/source/reference/kde.rstadded, README feature matrix updated.Test plan
pytest xrspatial/tests/test_kde.py-- 35/35 passingjupyter nbconvert --executemake html