def json_to_sdss_dlasurvey(json_file, sdss_survey, add_pf=True, debug=False):
""" Convert JSON output file to a DLASurvey object
Assumes SDSS bookkeeping for sightlines (i.e. PLATE, FIBER)
Parameters
----------
json_file : str
Full path to the JSON results file
sdss_survey : DLASurvey
SDSS survey, usually human (e.g. JXP for DR5)
add_pf : bool, optional
Add plate/fiber to DLAs in sdss_survey
Returns
-------
ml_survey : LLSSurvey
Survey object for the LLS
"""
print("Loading SDSS Survey from JSON file {:s}".format(json_file))
# imports
from pyigm.abssys.dla import DLASystem
from pyigm.abssys.lls import LLSSystem
# Fiber key
for fkey in ['FIBER', 'FIBER_ID', 'FIB']:
if fkey in sdss_survey.sightlines.keys():
break
# Read
ml_results = ltu.loadjson(json_file)
use_platef = False
if 'plate' in ml_results[0].keys():
use_platef = True
else:
if 'id' in ml_results[0].keys():
use_id = True
# Init
#idict = dict(plate=[], fiber=[], classification_confidence=[], # FOR v2
# classification=[], ra=[], dec=[])
idict = dict(ra=[], dec=[])
if use_platef:
for key in ['plate', 'fiber', 'mjd']:
idict[key] = []
ml_tbl = Table()
ml_survey = LLSSurvey()
systems = []
in_ml = np.array([False]*len(sdss_survey.sightlines))
# Loop
for obj in ml_results:
# Sightline
for key in idict.keys():
idict[key].append(obj[key])
# DLAs
#if debug:
# if (obj['plate'] == 1366) & (obj['fiber'] == 614):
# sv_coord = SkyCoord(ra=obj['ra'], dec=obj['dec'], unit='deg')
# print("GOT A MATCH IN RESULTS FILE")
for idla in obj['dlas']:
"""
dla = DLASystem((sdss_survey.sightlines['RA'][mt[0]],
sdss_survey.sightlines['DEC'][mt[0]]),
idla['spectrum']/(1215.6701)-1., None,
idla['column_density'])
"""
if idla['z_dla'] < 1.8:
continue
isys = LLSSystem((obj['ra'],obj['dec']),
idla['z_dla'], None, NHI=idla['column_density'], zem=obj['z_qso'])
isys.confidence = idla['dla_confidence']
if use_platef:
isys.plate = obj['plate']
isys.fiber = obj['fiber']
elif use_id:
plate, fiber = [int(spl) for spl in obj['id'].split('-')]
isys.plate = plate
isys.fiber = fiber
# Save
systems.append(isys)
# Connect to sightlines
ml_coord = SkyCoord(ra=idict['ra'], dec=idict['dec'], unit='deg')
s_coord = SkyCoord(ra=sdss_survey.sightlines['RA'], dec=sdss_survey.sightlines['DEC'], unit='deg')
idx, d2d, d3d = match_coordinates_sky(s_coord, ml_coord, nthneighbor=1)
used = d2d < 1.*u.arcsec
for iidx in np.where(~used)[0]:
print("Sightline RA={:g}, DEC={:g} was not used".format(sdss_survey.sightlines['RA'][iidx],
sdss_survey.sightlines['DEC'][iidx]))
# Add plate/fiber to statistical DLAs
if add_pf:
dla_coord = sdss_survey.coord
idx2, d2d, d3d = match_coordinates_sky(dla_coord, s_coord, nthneighbor=1)
if np.min(d2d.to('arcsec').value) > 1.:
raise ValueError("Bad match to sightlines")
for jj,igd in enumerate(np.where(sdss_survey.mask)[0]):
dla = sdss_survey._abs_sys[igd]
try:
dla.plate = sdss_survey.sightlines['PLATE'][idx2[jj]]
except IndexError:
pdb.set_trace()
dla.fiber = sdss_survey.sightlines[fkey][idx2[jj]]
# Finish
ml_survey._abs_sys = systems
if debug:
ml2_coord = ml_survey.coord
minsep = np.min(sv_coord.separation(ml2_coord))
minsep2 = np.min(sv_coord.separation(s_coord))
tmp = sdss_survey.sightlines[used]
t_coord = SkyCoord(ra=tmp['RA'], dec=tmp['DEC'], unit='deg')
minsep3 = np.min(sv_coord.separation(t_coord))
pdb.set_trace()
ml_survey.sightlines = sdss_survey.sightlines[used]
for key in idict.keys():
ml_tbl[key] = idict[key]
ml_survey.ml_tbl = ml_tbl
# Return
return ml_survey
