Datasets

agasc_gaia.datasets.get_agasc_summary(file_in='agasc1p7.h5')

Loads the AGASC and the Tycho2 and GSC 2.3 catalogs and joins them, using GSC 1.1 IDs as intermediates.

The final result is sorted by agasc_id. This is convenient for later use, so one does not have to join this table with others, but one can use np.searchsorted, which is faster.

This function does the following:

• determine the Tycho2, Tycho2-TDSC, and GSC1.1 IDs (Tycho2 is cross-matched with TDSC so we have the Tycho2-TDSC IDs)

• add a random index to each AGASC entry. This is useful for cross-validation later on.

• add a column ‘R’ with the estimated angular distance moved since its epoch to the Gaia reference epoch

• add the GSC2.3 ID using the vivzier 2.3 catalog

• add observed magnitudes from AGASC supplement

• add boolean flags to denote stars that are guide/acq candidates

• remove a duplicated entry in the AGASC catalog

• For tycho stars, take the original Tycho RA/dec instead of the ones at 2000 epoch

• sort the final result by agasc_id

agasc_gaia.datasets.get_agasc_summary_csv()

Return a subset of the agasc summary table, in CSV format to be uploaded to Gaia.

agasc_gaia.datasets.get_background_agasc_summary_csv()

Return a subset of the agasc summary table, with positions randomly shifted 1.5 degree, in CSV format to be uploaded to Gaia.

agasc_gaia.datasets.get_gsc11(download=False)

Loads the GSC 1.1 catalog.

agasc_gaia.datasets.get_gsc23()

Loads the GSC 2.3 catalog.

agasc_gaia.datasets.get_plain_agasc()

Loads the AGASC catalog and adds Tycho IDs.

agasc_gaia.datasets.get_potential_duplicates()

Return a list of potential duplicate stars in AGASC.

Two stars are considered potential duplicates if they are within 1 arcsec of each other and their positions are from different base catalogs. To decide which one of the two might be a duplicate, they are sorted by pos_catid using the following precedence order (from high to low):

• 5: Tycho-2

• 6: GSC-ACT

• 4: ACT

• 3: Tycho-1

• 2: PPM

• 1: GSC1.1

• 0: No catalog

Two stars within 1 arcsec from the same catalog does occur, because there are binaries and such. But two stars within 1 arcsec and from different catalogs is unlikely unless there was an update of positions, and only one star of a multiple system was updated. Most probably, this coincidence happened when two datasets were merged without first removing cross-matches.

Galaxies, non-stars and potential artifacts are excluded from this list. All the other classes are kept.

Parameters:

agascTable

The AGASC summary table.

Returns:

Table

A table with potential duplicate pairs of stars. The second star in the pair corresponds to potential duplicates. The first star in the pair can be a duplicate but it not always is.

agasc_gaia.datasets.get_tdsc()

Loads the TDSC catalog.

agasc_gaia.datasets.get_tycho()

Loads the Tycho catalog.

agasc_gaia.datasets.get_tycho2_tdsc()

Cross-match the positions of Tycho2 and TDSC and return a union table.

The union table includes a “tdsc_id”, which is the ID in TDSC. This is not always the same as the Tycho2 ID (hence this function).

agasc_gaia.datasets.tycho2_tdsc_get_best_matches(matches)

Given a list of matches (TYC3 values from Tycho2 and TDSC), return the best matches.

The goodness of the match is determined by the xmatch_weight column.

The algorithm is the following: - sort the matches by xmatch_weight in reverse order - iterate over matches, adding pairs that have not been added yet.

agasc_gaia.datasets.tycho2_tdsc_mag_diff_prob(mag_diff)

Magnitude difference probability used to match Tycho2 and TDSC.

agasc_gaia.datasets.tycho2_tdsc_separation_prob(separation)

Separation probability used to match Tycho2 and TDSC.

agasc_gaia.datasets.tycho_id(t1, t2, t3)

Fast function to assemble Tycho ID strings.