Skarabina
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skarabina: a basic 1GC radio astronomy RFI flagger
Author: Tim Molteno (tim@elec.ac.nz)
Intended to reduce I/O costs by performing the standard flagging during 1GC efficiently, and with low memory requirements. Skarabina can also do averaging to reduce data volume, and measurement set analysis to recommend image size.
Documentation
See doc/ for full documentation:
Install
pip install skarabina
See INSTALL.md for detailed instructions, including aarch64 / NVIDIA DGX Spark setup.
Quick start
# Flag and clean (including autocorrelations)
skarabina --ms raw.ms --flag-autos --flag-nan --flag-uv-above 4000 \
--time-average-factor 3 --optimize --msout clean.ms --clobber
# Keep a subset of scans, then average
skarabina --ms raw.ms --scan 1,12,14 --flag-nan \
--frequency-average-factor 8 --msout kept.ms --clobber
# Analyze
skarabina-analyze --ms raw.ms --image-fov 2.5
--field-of-view (flagging/summary) and --image-fov (analysis) both take the
field of view as a full width, so the same value can be passed to both. The
summary's fringe-rotation limit uses the distance from the phase centre to the
edge, i.e. half of it.
Build
Install uv, then:
uv sync
uv build
Stimela
_include:
- (skarabina_cargo):
- skarabina.yml
my-recipe:
info: "Print a flagging summary using skarabina"
inputs:
ms: MS
steps:
flag-summary:
cab: skarabina
params:
ms: =recipe.ms
summary: true
1 maintainer
Metadata
1 maintainer
Release files for skarabina 1.0.11
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| File | Size | Uploaded | |
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|---|---|---|---|---|
| skarabina-1.0.11-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 476.1 kB
Release files / skarabina-1.0.11.tar.gz
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