sdapy.snerun.snelist.parse_meta_all

snelist.parse_meta_all(kwargs, objid)

properly read a list of meta infomations from self.meta, i.e. coordinates self.ra, self.dec, redshift self.z, distance self.dist, distance module self.dm, mkily way extinction self.mkwebv, host galaxy extinction self.hostebv, type self.sntype and peak time self.jdpeak. If ra dec missed, user should manully input lightcurve later instead of build-in sources. If redshift missed, will make all analysis in obervational frame instead of rest frame. If distance missed, will calculate it from redshift with a standard cosmology (astropy.cosmology.Planck13). If milky way E(B-V) missed, will check if A_V available, if not, make sure you had dustmaps.sfd installed, and SFD dust map is downloaded propoerly with dustmaps, Otherwise will ignore milky way extinction. If host galaxy E(B-V) missed, will check if A_V available, otherwise temporarily assign 0 to host E(B-V), which can be updated later from colour comparison or Na Id fittings. Type is used by colour comparison (which template colour should be compared) and line measurements (which line should be fitted), if missed, will make trouble in these 2 parts. jdpeak is can be decided by snobject in many ways, but a prior input is important to guess the JD range to query photometry. (https://github.com/saberyoung/HAFFET/blob/master/sdapy/data/default_par.txt)

Parameters

kwargsKeyword Arguments

optional parameters, will use idkey, rakey, deckey, zkey,

distkey, dmkey, mkwebvkey, mkwavkey, hostebvkey, hostavkey, typekey, peaktkey, idkey, and rv

objidstr

object ID string

See also

snelist.parse_meta, snelist.parse_meta_one

Examples

>>> from sdapy import snerun
>>> a = snerun.snelist()
>>> a.parse_meta(withnew='skip', source='BTS', metafile=None, syntax='type in ["Ib","Ic"]')
meta 154 objs
>>> a.parse_meta_all(a.read_kwargs(), 'ZTF21abmlldj') 
>>> a.z
0.0944
>>> a.ra
'00:29:30.87'
>>> a.dm
38.25085889208277