arrakis.cutout

Produce cutouts from RACS cubes

Attributes

`T`
`TQDM_OUT`

Classes

CutoutArgs

Arguments for cutout function

Functions

`big_cutout`(→ list[pymongo.UpdateOne])
`cli`(→ None)	Command-line interface
`cutout_image`(→ pymongo.UpdateOne)	Perform a cutout.
`cutout_islands`(→ None)	Flow to cutout islands in parallel.
`cutout_parser`(→ argparse.ArgumentParser)
`cutout_weight`(→ pymongo.UpdateOne)
`get_args`(→ CutoutArgs \| None)	Get arguments for cutout function
`main`(→ None)	Main script
`make_cutout`(lock, host, epoch, source, comps, outdir, ...)

Module Contents

class arrakis.cutout.CutoutArgs[source]

Bases: NamedTuple

Arguments for cutout function

dec_high: float[source]: Upper DEC bound in degrees

dec_low: float[source]: Lower DEC bound in degrees

outdir: pathlib.Path[source]: Output directory

ra_left: float[source]: Upper RA bound in degrees

ra_right: float[source]: Lower RA bound in degrees

arrakis.cutout.big_cutout(sources: pandas.DataFrame, comps: pandas.DataFrame, beam_num: int, stoke: str, datadir: pathlib.Path, outdir: pathlib.Path, host: str, epoch: int, field: str, pad: float = 3, username: str | None = None, password: str | None = None, limit: int | None = None, dryrun: bool = False) → list[pymongo.UpdateOne][source]

arrakis.cutout.cli() → None[source]: Command-line interface

arrakis.cutout.cutout_image(lock: threading.Lock, image_name: pathlib.Path, data_in_mem: numpy.ndarray, old_header: astropy.io.fits.Header, cube: spectral_cube.SpectralCube, source_id: str, cutout_args: CutoutArgs | None, field: str, beam_num: int, stoke: str, pad: float = 3, dryrun: bool = False) → pymongo.UpdateOne[source]

Perform a cutout.

Returns:: Update query for MongoDB
Return type:: pymongo.UpdateOne

arrakis.cutout.cutout_islands(field: str, directory: pathlib.Path, host: str, epoch: int, sbid: int | None = None, username: str | None = None, password: str | None = None, pad: float = 3, stokeslist: list[str] | None = None, dryrun: bool = True, limit: int | None = None) → None[source]

Flow to cutout islands in parallel.

Parameters:

field (str) – RACS field name.
directory (Path) – Directory to store cutouts.
host (str) – MongoDB host.
username (str, optional) – Mongo username. Defaults to None.
password (str, optional) – Mongo password. Defaults to None.
pad (int, optional) – Number of beamwidths to pad cutouts. Defaults to 3.
stokeslist (List[str], optional) – Stokes parameters to cutout. Defaults to None.
dryrun (bool, optional) – Do everything except write FITS files. Defaults to True.

arrakis.cutout.cutout_parser(parent_parser: bool = False) → argparse.ArgumentParser[source]

arrakis.cutout.cutout_weight(image_name: pathlib.Path, source_id: str, cutout_args: CutoutArgs | None, field: str, stoke: str, beam_num: int, dryrun=False) → pymongo.UpdateOne[source]

arrakis.cutout.get_args(comps: pandas.DataFrame, source: pandas.Series, outdir: pathlib.Path) → CutoutArgs | None[source]

Get arguments for cutout function

Parameters:

comps (pd.DataFrame) – List of mongo entries for RACS components in island
beam (Dict) – Mongo entry for the RACS beam
island_id (str) – RACS island ID
outdir (Path) – Input directory

Raises:

e – Exception
Exception – Problems with coordinates

Returns:

List of cutout arguments for cutout function

Return type:

List[CutoutArgs]

arrakis.cutout.main(args: argparse.Namespace) → None[source]

Main script

Parameters:: args (argparse.Namespace) – Command-line args

arrakis.cutout.make_cutout(lock: threading.Lock, host: str, epoch: int, source: pandas.Series, comps: pandas.DataFrame, outdir: pathlib.Path, image_name: pathlib.Path, data_in_mem: numpy.ndarray, old_header: astropy.io.fits.Header, cube: spectral_cube.SpectralCube, field: str, beam_num: int, stoke: str, pad: float = 3, username: str | None = None, password: str | None = None, dryrun: bool = False)[source]

arrakis.cutout.T[source]

arrakis.cutout.TQDM_OUT[source]