arrakis.init_database

Create the Arrakis database

Attributes

TQDM_OUT

Functions

beam_database(→ pymongo.results.InsertManyResult)

Insert beams into the database

beam_inf(→ pymongo.results.InsertManyResult)

Get the beam information

cat2beams(→ Tuple[numpy.ndarray, numpy.ndarray, ...)

Find the separations between sources in the master catalogue and the RACS beams

cli()

Command-line interface

field_database(...)

Reset and load the field database

get_beams(→ List[Dict])

Get beams from the master catalogue

get_catalogue(→ astropy.table.Table)

Get the RACS catalogue for a given epoch

main(→ None)

Main script

ndix_unique(→ Tuple[numpy.ndarray, List[numpy.ndarray]])

Find the N-dimensional array of indices of the unique values in x

read_racs_database(→ astropy.table.Table)

Read the RACS database from CSVs or postgresql

source2beams(→ astropy.table.Table)

Find RACS beams that contain a given source position

source_database(...)

Insert sources into the database

Module Contents

arrakis.init_database.beam_database(database_path: pathlib.Path, islandcat: astropy.table.Table, host: str, epoch: int, username: str | None = None, password: str | None = None) → pymongo.results.InsertManyResult[source]

Insert beams into the database

Parameters:

  • islandcat (Table) – Island catalogue table.

  • host (str) – MongoDB host IP.

  • username (str, optional) – Mongo username. Defaults to None.

  • password (str, optional) – Mongo host. Defaults to None.

  • epoch (int, optional) – RACS epoch to use. Defaults to 0.

Returns:

Result of the insert.

Return type:

InsertManyResult

arrakis.init_database.beam_inf(database: astropy.table.Table, survey_dir: pathlib.Path, host: str, epoch: int, username: str | None = None, password: str | None = None) → pymongo.results.InsertManyResult[source]

Get the beam information

arrakis.init_database.cat2beams(mastercat: astropy.table.Table, database: astropy.table.Table, max_sep: float = 1) → Tuple[numpy.ndarray, numpy.ndarray, astropy.coordinates.Angle][source]

Find the separations between sources in the master catalogue and the RACS beams

Parameters:

  • mastercat (Table) – Master catalogue table.

  • database (Table) – RACS database table.

  • max_sep (float, optional) – Maxium source separation in degrees. Defaults to 1.

Returns:

Output of astropy.coordinates.search_around_sky

Return type:

Tuple[np.ndarray, np.ndarray, Angle]

arrakis.init_database.cli()[source]

Command-line interface

arrakis.init_database.field_database(survey_dir: pathlib.Path, host: str, epoch: int, username: str | None = None, password: str | None = None) → Tuple[pymongo.results.InsertManyResult, pymongo.results.InsertManyResult][source]

Reset and load the field database

Parameters:

  • survey_dir (Path) – Path to RACS database (i.e. ‘askap_surveys/racs’ repo).

  • host (str) – Mongo host

  • epoch (int, optional) – RACS epoch number.

  • username (Union[str, None]) – Mongo username

  • password (Union[str, None]) – Mongo password

Returns:

Field and beam info insert object.

Return type:

Tuple[InsertManyResult, InsertManyResult]

arrakis.init_database.get_beams(mastercat: astropy.table.Table, database: astropy.table.Table, epoch: int = 0) → List[Dict][source]

Get beams from the master catalogue

Parameters:

  • mastercat (Table) – Master catalogue table.

  • database (Table) – RACS database table.

Returns:

List of beam dictionaries.

Return type:

List[Dict]

arrakis.init_database.get_catalogue(survey_dir: pathlib.Path, epoch: int = 0) → astropy.table.Table[source]

Get the RACS catalogue for a given epoch

Parameters:

epoch (int, optional) – Epoch number. Defaults to 0.

Returns:

RACS catalogue table.

Return type:

Table

arrakis.init_database.main(load: bool = False, islandcat: str | None = None, compcat: str | None = None, database_path: pathlib.Path | None = None, host: str = 'localhost', username: str | None = None, password: str | None = None, field: bool = False, epochs: List[int] = 0, force: bool = False) → None[source]

Main script

Parameters:

  • load (bool, optional) – Load the database. Defaults to False.

  • islandcat (Union[str, None], optional) – Island catalogue. Defaults to None.

  • compcat (Union[str, None], optional) – Component catalogue. Defaults to None.

  • host (str, optional) – Mongo host. Defaults to “localhost”.

  • username (Union[str, None], optional) – Mongo username. Defaults to None.

  • password (Union[str, None], optional) – Mongo password. Defaults to None.

  • field (bool, optional) – Load the field database. Defaults to False.

  • epochs (List[int], optional) – Epochs to load. Defaults to [0].

  • force (bool, optional) – Force overwrite of database. Defaults to False.

Raises:

ValueError – If load is True and islandcat or compcat are None.

arrakis.init_database.ndix_unique(x: numpy.ndarray) → Tuple[numpy.ndarray, List[numpy.ndarray]][source]

Find the N-dimensional array of indices of the unique values in x From https://stackoverflow.com/questions/54734545/indices-of-unique-values-in-array

Parameters:

x (np.ndarray) – Array of values.

Returns:

  • 1D-array of sorted unique values

  • Array of arrays. Each array contains the indices where a given value in x is found

Return type:

Tuple[np.ndarray, np.ndarray]

arrakis.init_database.read_racs_database(survey_dir: pathlib.Path, epoch: int, table: str) → astropy.table.Table[source]

Read the RACS database from CSVs or postgresql

Parameters:

  • survey_dir (Path) – Path to RACS database (i.e. ‘askap_surveys/racs’ repo).

  • epoch (int) – RACS epoch number.

  • table (str) – Table name.

Returns:

RACS database table.

Return type:

Table

arrakis.init_database.source2beams(ra: float, dec: float, database: astropy.table.Table, max_sep: float = 1) → astropy.table.Table[source]

Find RACS beams that contain a given source position

Parameters:

  • ra (float) – RA of source in degrees.

  • dec (float) – DEC of source in degrees.

  • database (dict) – RACS database table.

  • max_sep (float, optional) – Maximum seperation of source to beam centre in degrees. Defaults to 1.

Returns:

Subset of RACS databsae table containing beams that contain the source.

Return type:

Table

arrakis.init_database.source_database(islandcat: astropy.table.Table, compcat: astropy.table.Table, host: str, epoch: int, username: str | None = None, password: str | None = None) → Tuple[pymongo.results.InsertManyResult, pymongo.results.InsertManyResult][source]

Insert sources into the database

Following https://medium.com/analytics-vidhya/how-to-upload-a-pandas-dataframe-to-mongodb-ffa18c0953c1

Parameters:

  • islandcat (Table) – Island catalogue table.

  • compcat (Table) – Component catalogue table.

  • host (str) – MongoDB host IP.

  • username (str, optional) – Mongo username. Defaults to None.

  • password (str, optional) – Mongo host. Defaults to None.

Returns:

Results for the islands and components inserts.

Return type:

Tuple[InsertManyResult, InsertManyResult]

arrakis.init_database.TQDM_OUT[source]