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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

Release files for skarabina 1.0.4

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Source distribution for skarabina 1.0.4
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Table of built distributions (wheels) for skarabina 1.0.4
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