Function reference

1 Pipeline API

Stateful Combiner object and rejection objects.

Combiner Stateful pipeline holder for (scale/zero, reject, combine) workflows.
SigClip Iterative sigma-clipping rejection.
CcdClip CCD noise-model clipping.
LinearClip Center-relative linear clipping.
MinMaxClip Reject the smallest and largest unmasked values at each pixel.
PClip IRAF-style percentile clipping.
Rejector Base class for rejection objects.
SampleFlags Per-sample rejection/provenance flags.
OutputFlags Per-output rejection status flags.
resolve_zero_scale Resolve a numeric, string, or callable zero/scale input.

2 Kernel API

Advanced one-operation primitives for custom pipeline layers.

kernels.nanaverage Return the NaN-aware weighted average along the stack axis.
kernels.grow_mask Dilate a stack mask over spatial axes by an exact Euclidean radius.
kernels.sigclip Sigma-clipping rejection.
kernels.sigclip_1d Sigma-clipping rejection (1-D variant).
kernels.sigclip_mask Sigma-clipping rejection (mask-only variant).
kernels.sigclip_combine Sigma-clipping rejection (output-only variant).
kernels.sigclip_combine_1d Sigma-clipping rejection (1-D output-only variant).
kernels.ccdclip CCD noise-model clipping.
kernels.ccdclip_1d CCD noise-model clipping (1-D variant).
kernels.ccdclip_mask CCD noise-model clipping (mask-only variant).
kernels.ccdclip_mask_1d CCD noise-model clipping (1-D mask-only variant).
kernels.ccdclip_combine CCD noise-model clipping (output-only variant).
kernels.ccdclip_combine_1d CCD noise-model clipping (1-D output-only variant).
kernels.linearclip Center-relative linear clipping (low + low_scale * center <= value <= upp + upp_scale * center).
kernels.linearclip_1d Center-relative linear clipping (low + low_scale * center <= value <= upp + upp_scale * center) (1-D variant).
kernels.minmax Reject the n_min smallest and n_max largest unmasked values at each pixel. Single-pass.
kernels.minmax_1d Reject the n_min smallest and n_max largest unmasked values at each pixel. Single-pass (1-D variant).
kernels.minmax_mask Reject the n_min smallest and n_max largest unmasked values at each pixel. Single-pass (mask-only variant).
kernels.minmax_mask_1d Reject the n_min smallest and n_max largest unmasked values at each pixel. Single-pass (1-D mask-only variant).
kernels.minmax_combine Reject the n_min smallest and n_max largest unmasked values at each pixel. Single-pass (output-only variant).
kernels.minmax_combine_1d Reject the n_min smallest and n_max largest unmasked values at each pixel. Single-pass (1-D output-only variant).
kernels.pclip IRAF-style percentile clipping at each pixel.
kernels.pclip_1d IRAF-style percentile clipping at each pixel (1-D variant).
kernels.pclip_mask IRAF-style percentile clipping at each pixel (mask-only variant).
kernels.pclip_mask_1d IRAF-style percentile clipping at each pixel (1-D mask-only variant).
kernels.pclip_combine IRAF-style percentile clipping at each pixel (output-only variant).
kernels.pclip_combine_1d IRAF-style percentile clipping at each pixel (1-D output-only variant).

3 Compatibility API

IRAF-style compact wrapper.

ndcombine Combine an image stack with optional normalization and rejection.
place_into_padded Place N-D arrays into a padded stack using integer offsets.