API Reference#

Resamplers#

healpix_resample.NearestResampler(*args[, Npt])

Nearest-neighbour HEALPix resampler — no sparse matrices.

healpix_resample.BilinearResampler(*args, ...)

healpix_resample.PSFResampler(lon_deg, ...)

healpix_resample.CellPointResampler(*args, ...)

Resample input lat-lon points as HEALPix "cell-points".

healpix_resample.GroupByResampler([reduce])

Base class#

KNeighborsResampler is the base class inherited by all resamplers above. Use it directly only if you need to implement a custom weighting scheme via comp_matrix().

healpix_resample.knn.KNeighborsResampler(...)

GPU-friendly sparse HEALPix regridding via local Gaussian weights + CG deconvolution.

Output#

All resamplers return a ResampleResults dataclass.

healpix_resample.base.ResampleResults(...[, ...])

Proxy to resampling results.

Internals#

These functions are not part of the public API but are documented here for contributors. healpix_weighted_nearest() is called internally by all resamplers to build the sparse operators. conjugate_gradient() and least_squares_cg() are used internally by PSFResampler.

healpix_resample.knn.healpix_weighted_nearest(...)

Retourne:

healpix_resample.psf.conjugate_gradient(A_mv, b)

Solve A x = b with Conjugate Gradient where A is SPD, using only matvec A_mv(v).

healpix_resample.psf.least_squares_cg(M, MT, ...)

Solve for delta in a damped least-squares problem without forming dense matrices.