For an AXS catalog loaded as
axs_catalog = AxsCatalog(spark) table = AxsCatalog(spark).load('table_name')
all the existing info methods , eg. .get_table_info() , .describe(), .explain() provide automatically- made information. Now that more and more tables are made, crossmatched, etc., it would be really nice to be able to add a user-made info that explains how a table was created from a user perspective. Eg., when making the table from a crossmatch, crossmatch = ztf_lc.crossmatch(sdss_lc, r=2*Constants.ONE_ASEC).\ save_axs_table(fname, info), with info being a string that a user can define (eg. table.info = 'ztf DR1 LCs within S82, nobs > 1, all filters, crossmatch to S82 Quasars within 2 asec), accessible by .info(). It is up to users to keep it going, but I would definitely do that to all tables I make, to avoid asking on slack all the time eg. who made gaia_500b_28e_10800z and what does it contain...
For an AXS catalog loaded as
axs_catalog = AxsCatalog(spark) table = AxsCatalog(spark).load('table_name')all the existing info methods , eg.
.get_table_info(),.describe(),.explain()provide automatically- made information. Now that more and more tables are made, crossmatched, etc., it would be really nice to be able to add a user-made info that explains how a table was created from a user perspective. Eg., when making the table from a crossmatch,crossmatch = ztf_lc.crossmatch(sdss_lc, r=2*Constants.ONE_ASEC).\ save_axs_table(fname, info), with info being a string that a user can define (eg.table.info = 'ztf DR1 LCs within S82, nobs > 1, all filters, crossmatch to S82 Quasars within 2 asec), accessible by.info(). It is up to users to keep it going, but I would definitely do that to all tables I make, to avoid asking on slack all the time eg. who madegaia_500b_28e_10800zand what does it contain...