import cdspyreadme from astropy.io import fits from astropy.table import Table def make_euds_cds(infile1=None,outfile1=None,infile2=None,outfile2=None,fluxlim=None): print("Reading {}".format(infile1)) ######################### """ Read eUDS catalog """ ######################### tablemaker = cdspyreadme.CDSTablesMaker() r = Table.read(infile1) tab=Table([ r['ID_SRC'], # 0 r['NAME'], # 1 r['RA'], # 2 r['DEC'], # 3 r['RADEC_ERR'], # 4 Positional error (68% confidence) r['EXT'], # 5 Source extent r['EXT_ERR'], # 6 Extent uncertainty r['EXT_LIKE'], # 7 r['DET_LIKE'], # 8 r['ML_RATE'], # 9 r['ML_RATE_ERR'], # 10 r['ML_CTS'], # 11 r['ML_CTS_ERR'], # 12 r['ML_FLUX'], # 13 r['ML_FLUX_ERR'], # 14 r['ML_EXP'], # 15 r['ML_BKG'], # 16 r['DR12_IAU_NAME'] , # 17 4XMM J021738.8-051257 r['DET_LIKE_1'] , # 18 r['ML_RATE_1'] , # 19 r['ML_RATE_ERR_1'] , # 20 r['ML_CTS_1'] , # 21 r['ML_CTS_ERR_1'] , # 22 r['ML_FLUX_1'] , # 23 r['ML_FLUX_ERR_1'] , # 24 r['ML_EXP_1'] , # 25 r['ML_BKG_1'] , # 26 r['DET_LIKE_2'] , # 27 r['ML_RATE_2'] , # 28 r['ML_RATE_ERR_2'] , # 29 r['ML_CTS_2'] , # 30 r['ML_CTS_ERR_2'] , # 31 r['ML_FLUX_2'] , # 32 r['ML_FLUX_ERR_2'] , # 33 r['ML_EXP_2'] , # 34 r['ML_BKG_2'] , # 35 r['DET_LIKE_3'] , # 36 r['ML_RATE_3'] , # 37 r['ML_RATE_ERR_3'] , # 38 r['ML_CTS_3'] , # 39 r['ML_CTS_ERR_3'] , # 40 r['ML_FLUX_3'] , # 41 r['ML_FLUX_ERR_3'] , # 42 r['ML_EXP_3'] , # 43 r['ML_BKG_3'] , # 44 r['DET_LIKE_4'] , # 45 r['ML_RATE_4'] , # 46 r['ML_RATE_ERR_4'] , # 47 r['ML_CTS_4'] , # 48 r['ML_CTS_ERR_4'] , # 49 r['ML_FLUX_4'] , # 50 r['ML_FLUX_ERR_4'] , # 51 r['ML_EXP_4'] , # 52 r['ML_BKG_4'] , # 53 ]) table = tablemaker.addTable(tab, name=outfile1, description="eUDS X-ray catalog, converted from eUDS.fits") col = table.get_column('ID_SRC') # 0 col.name="SrcID" col.set_format("I3") col.description="Source ID (ID_SRC)" col = table.get_column('NAME') # 1 col.name="Name" col.set_format("A21") col.description="Source name, eUDS JHHMMSS.s+DDMMSS" col = table.get_column('RA') # 2 col.set_format("F10.6") col.name="RAdeg" col.description="RA (J2000) (RA)" col = table.get_column('DEC') # 3 col.name="DEdeg" col.set_format("F10.6") col.description="Dec (J2000) (RA)" col = table.get_column('RADEC_ERR') # 4 Positional error (68% confidence) col.set_format("F6.3") col.name="ePos" col.description="Positional uncertainty (RADEC_ERR)" col = table.get_column('EXT') # 5 Source extent col.set_format("F5.2") col.name="Ext" col.description="Source extent (EXT)" col = table.get_column('EXT_ERR') # 6 Extent uncertainty col.set_format("F5.2") col.name="e_Ext" col.description="Extent error (EXT_ERR)" col = table.get_column('EXT_LIKE') # 7 col.set_format("F10.6") col.name="ExtLike" col.description="Extent likelihood (EXT_LIKE)" col = table.get_column('DET_LIKE') # 8 col.set_format("F12.6") col.name="DetLike" col.description="Detection likelihood measured by PSF-fitting; 0.3-2.3 keV (DET_LIKE)" col = table.get_column('ML_RATE') # 9 col.name="MLRate" col.set_format("F8.6") col.description="Source count rate measured by PSF-fitting; 0.3-2.3 keV (ML_RATE)" col = table.get_column('ML_RATE_ERR') # 10 col.name="e_MLRate" col.set_format("F8.6") col.description="1 sigma count rate error; 0.3-2.3 keV (ML_RATE_ERR)" col = table.get_column('ML_CTS') # 11 col.name="MLCts" col.set_format("F11.6") col.description="Source net counts measured from count rate; 0.3-2.3 keV (ML_CTS)" col = table.get_column('ML_CTS_ERR') # 12 col.name="e_MLCts" col.set_format("F11.6") col.description="1 sigma counts error; 0.3-2.3 keV (ML_CTS_ERR)" col = table.get_column('ML_FLUX') # 13 col.name="MLFlux" col.set_format("E12.6") col.description="Source flux converted from count rate; 0.3-2.3 keV (ML_FLUX)" col = table.get_column('ML_FLUX_ERR') # 14 col.name="e_MLFlux" col.set_format("E12.6") col.description="1 sigma flux error; 0.3-2.3 keV (ML_FLUX_ERR)" col = table.get_column('ML_EXP') # 15 col.name="MLExp" col.set_format("E12.6") col.description="Vignetted exposure value; 0.3-2.3 keV (ML_EXP)" col = table.get_column('ML_BKG') # 16 col.name="MLBkg" col.set_format("F12.6") col.description="Background at the source position; 0.3-2.3 keV (ML_BKG)" col = table.get_column('DR12_IAU_NAME') # 17 4XMM J021738.8-051257 col.name="DR12Name" col.set_format("A21") col.description="4XMM-DR12 source name used for forced photometry (DR12_IAU_NAME)" col = table.get_column('DET_LIKE_1') # 18 col.name="DetLike1" col.set_format("F12.6") col.description="Detection likelihood measured by PSF-fitting; 0.3-0.6 keV (DET_LIKE_1)" col = table.get_column('ML_RATE_1') # 19 col.name="MLRate1" col.set_format("F8.6") col.description="Source count rate measured by PSF-fitting; 0.3-0.6 keV (ML_RATE_1)" col = table.get_column('ML_RATE_ERR_1') # 20 col.name="e_MLRate1" col.set_format("F8.6") col.description="1 sigma count rate error; 0.3-0.6 keV (ML_RATE_ERR_1)" col = table.get_column('ML_CTS_1') # 21 col.name="MLCts1" col.set_format("F11.6") col.description="Source net counts measured from count rate; 0.3-0.6 keV (ML_CTS_1)" col = table.get_column('ML_CTS_ERR_1') # 22 col.name="e_MLCts1" col.set_format("F11.6") col.description="1 sigma counts error; 0.3-0.6 keV (ML_CTS_ERR_1)" col = table.get_column('ML_FLUX_1') # 23 col.name="MLFlux1" col.set_format("E12.6") col.description="Source flux converted from count rate; 0.3-0.6 keV (ML_FLUX_1)" col = table.get_column('ML_FLUX_ERR_1') # 24 col.name="e_MLFlux1" col.set_format("E12.6") col.description="1 sigma flux error; 0.3-0.6 keV (ML_FLUX_ERR_1)" col = table.get_column('ML_EXP_1') # 25 col.name="MLExp1" col.set_format("E12.6") col.description="Vignetted exposure value; 0.3-0.6 keV (ML_EXP_1)" col = table.get_column('ML_BKG_1') # 26 col.name="MLBkg1" col.set_format("F12.6") col.description="Background at the source position; 0.3-0.6 keV (ML_BKG_1)" col = table.get_column('DET_LIKE_2') # 27 col.name="DetLike2" col.set_format("F12.6") col.description="Detection likelihood measured by PSF-fitting; 0.6-2.3 keV (DET_LIKE_2)" col = table.get_column('ML_RATE_2') # 28 col.name="MLRate2" col.set_format("F8.6") col.description="Source count rate measured by PSF-fitting; 0.6-2.3 keV (ML_RATE_2)" col = table.get_column('ML_RATE_ERR_2') # 29 col.name="e_MLRate2" col.set_format("F8.6") col.description="1 sigma count rate error; 0.6-2.3 keV (ML_RATE_ERR_2)" col = table.get_column('ML_CTS_2') # 30 col.name="MLCts2" col.set_format("F11.6") col.description="Source net counts measured from count rate; 0.6-2.3 keV (ML_CTS_2)" col = table.get_column('ML_CTS_ERR_2') # 31 col.name="e_MLCts2" col.set_format("F11.6") col.description="1 sigma counts error; 0.6-2.3 keV (ML_CTS_ERR_2)" col = table.get_column('ML_FLUX_2') # 32 col.name="MLFlux2" col.set_format("E12.6") col.description="Source flux converted from count rate; 0.6-2.3 keV (ML_FLUX_2)" col = table.get_column('ML_FLUX_ERR_2') # 33 col.name="e_MLFlux2" col.set_format("E12.6") col.description="1 sigma flux error; 0.6-2.3 keV (ML_FLUX_ERR_2)" col = table.get_column('ML_EXP_2') # 34 col.name="MLExp2" col.set_format("E12.6") col.description="Vignetted exposure value; 0.6-2.3 keV (ML_EXP_2)" col = table.get_column('ML_BKG_2') # 35 col.name="MLBkg2" col.set_format("F12.6") col.description="Background at the source position; 0.6-2.3 keV (ML_BKG_2)" col = table.get_column('DET_LIKE_3') # 36 col.name="DetLike3" col.set_format("F12.6") col.description="Detection likelihood measured by PSF-fitting; 2.3-5 keV (DET_LIKE_3)" col = table.get_column('ML_RATE_3') # 37 col.name="MLRate3" col.set_format("F8.6") col.description="Source count rate measured by PSF-fitting; 2.3-5 keV (ML_RATE_3)" col = table.get_column('ML_RATE_ERR_3') # 38 col.name="e_MLRate3" col.set_format("F8.6") col.description="1 sigma count rate error; 2.3-5 keV (ML_RATE_ERR_3)" col = table.get_column('ML_CTS_3') # 39 col.name="MLCts3" col.set_format("F11.6") col.description="Source net counts measured from count rate; 2.3-5 keV (ML_CTS_3)" col = table.get_column('ML_CTS_ERR_3') # 40 col.name="e_MLCts3" col.set_format("F11.6") col.description="1 sigma counts error; 2.3-5 keV (ML_CTS_ERR_3)" col = table.get_column('ML_FLUX_3') # 41 col.name="MLFlux3" col.set_format("E12.6") col.description="Source flux converted from count rate; 2.3-5 keV (ML_FLUX_3)" col = table.get_column('ML_FLUX_ERR_3') # 42 col.name="e_MLFlux3" col.set_format("E12.6") col.description="1 sigma flux error; 2.3-5 keV (ML_FLUX_ERR_3)" col = table.get_column('ML_EXP_3') # 43 col.name="MLExp3" col.set_format("E12.6") col.description="Vignetted exposure value; 2.3-5 keV (ML_EXP_3)" col = table.get_column('ML_BKG_3') # 44 col.name="MLBkg3" col.set_format("F12.6") col.description="Background at the source position; 2.3-5 keV (ML_BKG_3)" col = table.get_column('DET_LIKE_4') # 45 col.name="DetLike4" col.set_format("F12.6") col.description="Detection likelihood measured by PSF-fitting; 5-8 keV (DET_LIKE_4)" col = table.get_column('ML_RATE_4') # 46 col.name="MLRate4" col.set_format("F8.6") col.description="Source count rate measured by PSF-fitting; 5-8 keV (ML_RATE_4)" col = table.get_column('ML_RATE_ERR_4') # 47 col.name="e_MLRate4" col.set_format("F8.6") col.description="1 sigma count rate error; 5-8 keV (ML_RATE_ERR_4)" col = table.get_column('ML_CTS_4') # 48 col.name="MLCts4" col.set_format("F11.6") col.description="Source net counts measured from count rate; 5-8 keV (ML_CTS_4)" col = table.get_column('ML_CTS_ERR_4') # 49 col.name="e_MLCts4" col.set_format("F11.6") col.description="1 sigma counts error; 5-8 keV (ML_CTS_ERR_4)" col = table.get_column('ML_FLUX_4') # 50 col.name="MLFLux4" col.set_format("E12.6") col.description="Source flux converted from count rate; 5-8 keV (ML_FLUX_4)" col = table.get_column('ML_FLUX_ERR_4') # 51 col.name="e_MLFlux4" col.set_format("E12.6") col.description="1 sigma flux error; 5-8 keV (ML_FLUX_ERR_4)" col = table.get_column('ML_EXP_4') # 52 col.name="MLExp4" col.set_format("E12.6") col.description="Vignetted exposure value; 5-8 keV (ML_EXP_4)" col = table.get_column('ML_BKG_4') # 53 col.name="MLBkg4" col.set_format("F12.6") col.description="Background at the source position; 5-8 keV (ML_BKG_4)" ##################################### """ Read 4XMM-DR12 forced catalog """ ##################################### print("Reading {}".format(infile2)) r = Table.read(infile2) tab2=Table([ r['DR12_IAU_NAME'], # 0 r['DR12_SRCID'], # 1 r['DR12_RA'], # 2 r['DR12_DEC'], # 3 r['DR12_RADEC_ERR'], # 4 r['DET_LIKE_0'] , # 5 r['DET_LIKE_1'] , # 6 r['DET_LIKE_2'] , # 7 r['DET_LIKE_3'] , # 8 r['DET_LIKE_4'] , # 9 r['ML_RATE_0'] , # 10 r['ML_RATE_1'] , # 11 r['ML_RATE_2'] , # 12 r['ML_RATE_3'] , # 13 r['ML_RATE_4'] , # 14 r['ML_RATE_ERR_0'] , # 15 r['ML_RATE_ERR_1'] , # 16 r['ML_RATE_ERR_2'] , # 17 r['ML_RATE_ERR_3'] , # 18 r['ML_RATE_ERR_4'] , # 19 r['ML_CTS_0'] , # 20 r['ML_CTS_1'] , # 21 r['ML_CTS_2'] , # 22 r['ML_CTS_3'] , # 23 r['ML_CTS_4'] , # 24 r['ML_CTS_ERR_0'] , # 25 r['ML_CTS_ERR_1'] , # 26 r['ML_CTS_ERR_2'] , # 27 r['ML_CTS_ERR_3'] , # 28 r['ML_CTS_ERR_4'] , # 29 r['ML_FLUX_0'] , # 30 r['ML_FLUX_1'] , # 31 r['ML_FLUX_2'] , # 32 r['ML_FLUX_3'] , # 33 r['ML_FLUX_4'] , # 34 r['ML_FLUX_ERR_0'] , # 35 r['ML_FLUX_ERR_1'] , # 36 r['ML_FLUX_ERR_2'] , # 37 r['ML_FLUX_ERR_3'] , # 38 r['ML_FLUX_ERR_4'] , # 39 r['ML_EXP_0'] , # 40 r['ML_EXP_1'] , # 41 r['ML_EXP_2'] , # 42 r['ML_EXP_3'] , # 43 r['ML_EXP_4'] , # 44 r['ML_BKG_0'] , # 45 r['ML_BKG_1'] , # 46 r['ML_BKG_2'] , # 47 r['ML_BKG_3'] , # 48 r['ML_BKG_4'] , # 49 r['CONF'], # 50 ]) table2 = tablemaker.addTable(tab2, name=outfile2, description="eUDS forced photometry of 4XMM-DR12 sources, converted from eUDS_4XMM-DR12.fits") col = table2.get_column('DR12_IAU_NAME') # 0 col.name="DR12Name" col.set_format("A21") col.description="4XMM-DR12 source IAU name (DR12_IAU_NAME)" col = table2.get_column('DR12_SRCID') # 1 col.name="DR12SrcID" col.set_format("I15") col.description="Source ID (64-bit integer, DR12_SRCID)" col = table2.get_column('DR12_RA') # 2 col.name="RAdeg" col.set_format("F10.6") col.description="Right ascension (J2000, DR12_RA)" col = table2.get_column('DR12_DEC') # 3 col.name="DEdeg" col.set_format("F10.6") col.description="Declination (J2000, DR12_DEC)" col = table2.get_column('DR12_RADEC_ERR') # 4 col.name="ePos" col.set_format("F6.3") col.description="Positional error (DR12_RADEC_ERR)" col = table2.get_column('DET_LIKE_0') # 5 col.name="DetLike0" col.set_format("F12.6") col.description="Detection likelihood; 0.3-2.3 keV (DET_LIKE_0)" col = table2.get_column('DET_LIKE_1') # 6 col.name="DetLike1" col.set_format("F12.6") col.description="Detection likelihood; 0.3-0.6 keV (DET_LIKE_1)" col = table2.get_column('DET_LIKE_2') # 7 col.name="DetLike2" col.set_format("F12.6") col.description="Detection likelihood; 0.6-2.3 keV (DET_LIKE_2)" col = table2.get_column('DET_LIKE_3') # 8 col.name="DetLike3" col.set_format("F12.6") col.description="Detection likelihood; 2.3-5 keV (DET_LIKE_3)" col = table2.get_column('DET_LIKE_4') # 9 col.name="DetLike4" col.set_format("F12.6") col.description="Detection likelihood; 5-8 keV (DET_LIKE_4)" col = table2.get_column('ML_RATE_0') # 10 col.name="MLRate0" col.set_format("F10.6") col.description="Source count rate measured by PSF-fitting; 0.3-2.3 keV (ML_RATE_0)" col = table2.get_column('ML_RATE_1') # 11 col.name="MLRate1" col.set_format("F10.6") col.description="Source count rate measured by PSF-fitting; 0.3-0.6 keV (ML_RATE_1)" col = table2.get_column('ML_RATE_2') # 12 col.name="MLRate2" col.set_format("F10.6") col.description="Source count rate measured by PSF-fitting; 0.6-2.3 keV (ML_RATE_2)" col = table2.get_column('ML_RATE_3') # 13 col.name="MLRate3" col.set_format("F10.6") col.description="Source count rate measured by PSF-fitting; 2.3-5 keV (ML_RATE_3)" col = table2.get_column('ML_RATE_4') # 14 col.name="MLRate4" col.set_format("F10.6") col.description="Source count rate measured by PSF-fitting; 5-8 keV (ML_RATE_4)" col = table2.get_column('ML_RATE_ERR_0') # 15 col.name="e_MLRate0" col.set_format("F10.6") col.description="1 sigma count rate error; 0.3-2.3 keV (ML_RATE_ERR_0)" col = table2.get_column('ML_RATE_ERR_1') # 16 col.name="e_MLRate1" col.set_format("F10.6") col.description="1 sigma count rate error; 0.3-0.6 keV (ML_RATE_ERR_1)" col = table2.get_column('ML_RATE_ERR_2') # 17 col.name="e_MLRate2" col.set_format("F10.6") col.description="1 sigma count rate error; 0.6-2.3 keV (ML_RATE_ERR_2)" col = table2.get_column('ML_RATE_ERR_3') # 18 col.name="e_MLRate3" col.set_format("F10.6") col.description="1 sigma count rate error; 2.3-5 keV (ML_RATE_ERR_3)" col = table2.get_column('ML_RATE_ERR_4') # 19 col.name="e_MLRate4" col.set_format("F10.6") col.description="1 sigma count rate error; 5-8 keV (ML_RATE_ERR_4)" col = table2.get_column('ML_CTS_0') # 20 col.name="MLCts0" col.set_format("F11.6") col.description="Source net counts measured from count rate; 0.3-2.3 keV (ML_CTS_0)" col = table2.get_column('ML_CTS_1') # 21 col.name="MLCts1" col.set_format("F11.6") col.description="Source net counts measured from count rate; 0.3-0.6 keV (ML_CTS_1)" col = table2.get_column('ML_CTS_2') # 22 col.name="MLCts2" col.set_format("F11.6") col.description="Source net counts measured from count rate; 0.6-2.3 keV (ML_CTS_2)" col = table2.get_column('ML_CTS_3') # 23 col.name="MLCts3" col.set_format("F11.6") col.description="Source net counts measured from count rate; 2.3-5 keV (ML_CTS_3)" col = table2.get_column('ML_CTS_4') # 24 col.name="MLCts4" col.set_format("F11.6") col.description="Source net counts measured from count rate; 5-8 keV (ML_CTS_4)" col = table2.get_column('ML_CTS_ERR_0') # 25 col.name="e_MLCts0" col.set_format("F12.6") col.description="1 sigma counts error; 0.3-2.3 keV (ML_CTS_ERR_0)" col = table2.get_column('ML_CTS_ERR_1') # 26 col.name="e_MLCts1" col.set_format("F12.6") col.description="1 sigma counts error; 0.3-0.6 keV (ML_CTS_ERR_1)" col = table2.get_column('ML_CTS_ERR_2') # 27 col.name="e_MLCts2" col.set_format("F12.6") col.description="1 sigma counts error; 0.6-2.3 keV (ML_CTS_ERR_2)" col = table2.get_column('ML_CTS_ERR_3') # 28 col.name="e_MLCts3" col.set_format("F12.6") col.description="1 sigma counts error; 2.3-5 keV (ML_CTS_ERR_3)" col = table2.get_column('ML_CTS_ERR_4') # 29 col.name="e_MLCts4" col.set_format("F12.6") col.description="1 sigma counts error; 5-8 keV (ML_CTS_ERR_4)" col = table2.get_column('ML_FLUX_0') # 30 col.name="MLFlux0" col.set_format("E12.6") col.description="Source flux converted from count rate; 0.3-2.3 keV (ML_FLUX_0)" col = table2.get_column('ML_FLUX_1') # 31 col.name="MLFlux1" col.set_format("E12.6") col.description="Source flux converted from count rate; 0.3-0.6 keV (ML_FLUX_1)" col = table2.get_column('ML_FLUX_2') # 32 col.name="MLFlux2" col.set_format("E12.6") col.description="Source flux converted from count rate; 0.6-2.3 keV (ML_FLUX_2)" col = table2.get_column('ML_FLUX_3') # 33 col.name="MLFlux3" col.set_format("E12.6") col.description="Source flux converted from count rate; 2.3-5 keV (ML_FLUX_3)" col = table2.get_column('ML_FLUX_4') # 34 col.name="MLFlux4" col.set_format("E12.6") col.description="Source flux converted from count rate; 5-8 keV (ML_FLUX_4)" col = table2.get_column('ML_FLUX_ERR_0') # 35 col.name="e_MLFlux0" col.set_format("E12.6") col.description="1 sigma flux error; 0.3-2.3 keV (ML_FLUX_ERR_0)" col = table2.get_column('ML_FLUX_ERR_1') # 36 col.name="e_MLFlux1" col.set_format("E12.6") col.description="1 sigma flux error; 0.3-0.6 keV (ML_FLUX_ERR_1)" col = table2.get_column('ML_FLUX_ERR_2') # 37 col.name="e_MLFlux2" col.set_format("E12.6") col.description="1 sigma flux error; 0.6-2.3 keV (ML_FLUX_ERR_2)" col = table2.get_column('ML_FLUX_ERR_3') # 38 col.name="e_MLFlux3" col.set_format("E12.6") col.description="1 sigma flux error; 2.3-5 keV (ML_FLUX_ERR_3)" col = table2.get_column('ML_FLUX_ERR_4') # 39 col.name="e_MLFlux4" col.set_format("E12.6") col.description="1 sigma flux error; 5-8 keV (ML_FLUX_ERR_4)" col = table2.get_column('ML_EXP_0') # 40 col.name="MLExp0" col.set_format("E10.6") col.description="Vignetted exposure value; 0.3-2.3 keV (ML_EXP_0)" col = table2.get_column('ML_EXP_1') # 41 col.name="MLExp1" col.set_format("E10.6") col.description="Vignetted exposure value; 0.3-0.6 keV (ML_EXP_1)" col = table2.get_column('ML_EXP_2') # 42 col.name="MLExp2" col.set_format("E10.6") col.description="Vignetted exposure value; 0.6-2.3 keV (ML_EXP_2)" col = table2.get_column('ML_EXP_3') # 43 col.name="MLExp3" col.set_format("E10.6") col.description="Vignetted exposure value; 2.3-5 keV (ML_EXP_3)" col = table2.get_column('ML_EXP_4') # 44 col.name="MLExp4" col.set_format("E10.6") col.description="Vignetted exposure value; 5-8 keV (ML_EXP_4)" col = table2.get_column('ML_BKG_0') # 45 col.name="MLBkg0" col.set_format("F12.6") col.description="Background at the source position; 0.3-2.3 keV (ML_BKG_0)" col = table2.get_column('ML_BKG_1') # 46 col.name="MLBkg1" col.set_format("F12.6") col.description="Background at the source position; 0.3-0.6 keV (ML_BKG_1)" col = table2.get_column('ML_BKG_2') # 47 col.name="MLBkg2" col.set_format("F12.6") col.description="Background at the source position; 0.6-2.3 keV (ML_BKG_2)" col = table2.get_column('ML_BKG_3') # 48 col.name="MLBkg3" col.set_format("F12.6") col.description="Background at the source position; 2.3-5 keV (ML_BKG_3)" col = table2.get_column('ML_BKG_4') # 49 col.name="MLBkg4" col.set_format("F12.6") col.description="Background at the source position; 5-8 keV (ML_BKG_4)" col = table2.get_column('CONF') # 50 col.name="Conf" col.set_format("I1") col.description="True if source is located within 60 arcsec from another source with 0.3-2.3 keV flux > 1E−14 erg/s/cm**2 (CONF)" tablemaker.writeCDSTables() # Customize ReadMe output tablemaker.title = "eUDS: The SRG/eROSITA X-ray Survey of the UKIDSS Ultra Deep Survey Field. Catalogue of Sources." tablemaker.author = 'Krivonos R.' tablemaker.authors="Gilfanov M., Medvedev P., Sazonov S., Sunyaev R." tablemaker.date = 2024 tablemaker.bibcode = "2024MNRAS.528.1264K" tablemaker.keywords = "catalogues - surveys - X-ray: general" tablemaker.abstract = "The eROSITA X-ray telescope on board the Spectrum-Roentgen-Gamma (SRG) spacecraft observed the field of the UKIDSS Ultra-Deep Survey (UDS) in August-September 2019, during its flight to Sun-Earth L2 point. The resulting eROSITA UDS (or eUDS) survey was thus the first eROSITA X-ray imaging survey, which demonstrated the capability of the telescope to perform uniform observations of large sky areas. With a moderate single-camera exposure of 150 ks, eUDS covered ∼5 deg^2^ with the limiting flux ranging between 4*10^-15^ and 5*10^-14^erg/cm^2^/s in the 0.3-2.3 keV band. We present a catalogue of 647 sources detected at likelihood >10 (∼4sigma) during the eUDS. The catalogue provides information on the source fluxes in the main energy band 0.3-2.3 keV and forced photometry in a number of bands between 0.3 and 8 keV. Using the deeper 4XMM-DR12 catalogue, we have identified 22 strongly variable objects that have brightened or faded by at least a factor of ten during the eROSITA observations compared to previous observations by XMM-Newton. We also provide a catalogue of 22 sources detected by eROSITA in the hard energy band of 2.3-5 keV." tablemaker.more_description = "The catalogue (fits/eUDS.fits) contains 647 sources detected in the 0.3-2.3 keV band using eSASS adopting a detection likelihood threshold of 10. The catalogue provides information on the source fluxes in the main energy band 0: 0.3-2.3 keV and forced photometry in 1: 0.3-0.6, 2: 0.6-2.3, 3: 2.3-5.0 and 4: 5.0-8.0 keV bands. The catalogue of forced PSF-fitting fluxes (fits/eUDS_4XMM-DR12.fits) contains 3603 XMM-Newton sources from 4XMM-DR12 catalogue with the eUDS exposure of more than 100 s. The catalogue provides information on the source forced photometry in the energy bands 0: 0.3-2.3, 1: 0.3-0.6, 2: 0.6-2.3, 3: 2.3-5.0 and 4: 5.0-8.0 keV. To warn about the potential impact of spatial confusion with a nearby bright source, we added a confusion flag (see original paper for details)." tablemaker.putRef("J/A+A/661/A1","The eFEDS X-ray catalogs (Brunner+, 2022)") tablemaker.putRef("J/A+A/661/A38","SRG/ART-XC 1st year all-sky X-ray survey (Pavlinsky+, 2022)") tablemaker.putRef("https://www.srg.cosmos.ru/eUDS","eUDS catalog") #tablemaker.makeReadMe() with open("ReadMe.tmp","w") as fd: tablemaker.makeReadMe(out=fd) make_euds_cds(infile1="../uds/products/eUDS.fits",outfile1='table1.dat', infile2="../uds/products/eUDS_4XMM-DR12.fits",outfile2='table2.dat')