def hdf5_adddata(hdf, sname, meta, debug=False, chk_meta_only=False):
""" Append KODIAQ data to the h5 file
Parameters
----------
hdf : hdf5 pointer
IDs : ndarray
int array of IGM_ID values in mainDB
sname : str
Survey name
chk_meta_only : bool, optional
Only check meta file; will not write
Returns
-------
"""
# Add Survey
print("Adding {:s} survey to DB".format(sname))
kodiaq_grp = hdf.create_group(sname)
# Load up
# Checks
if sname != 'KODIAQ_DR2':
raise IOError("Not expecting this survey..")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 60000 # Just needs to be large enough
# Init
data = init_data(max_npix, include_co=False)
spec_set = hdf[sname].create_dataset('spec', data=data, chunks=True,
maxshape=(None,), compression='gzip')
spec_set.resize((nspec,))
# Lists
Rlist = []
wvminlist = []
wvmaxlist = []
gratinglist = []
npixlist = []
speclist = []
# Loop
path = os.getenv('RAW_IGMSPEC')+'/KODIAQ2/Data/'
maxpix = 0
for jj,row in enumerate(meta):
# Generate full file
full_file = path+row['qso']+'/'+row['pi_date']+'/'+row['spec_prefix']+'_f.fits'
# Extract
print("KODIAQ: Reading {:s}".format(full_file))
hduf = fits.open(full_file)
head = hduf[0].header
spec = lsio.readspec(full_file)
# Parse name
fname = full_file.split('/')[-1]
# npix
npix = spec.npix
if npix > max_npix:
raise ValueError("Not enough pixels in the data... ({:d})".format(npix))
else:
maxpix = max(npix,maxpix)
# Some fiddling about
for key in ['wave','flux','sig']:
data[key] = 0. # Important to init (for compression too)
data['flux'][0][:npix] = spec.flux.value
data['sig'][0][:npix] = spec.sig.value
data['wave'][0][:npix] = spec.wavelength.value
# Meta
speclist.append(str(fname))
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
if 'XDISPERS' in head.keys():
if head['XDISPERS'].strip() == 'UV':
gratinglist.append('BLUE')
else:
gratinglist.append('RED')
else: # Original, earl data
gratinglist.append('RED')
npixlist.append(npix)
try:
Rlist.append(set_resolution(head))
except ValueError:
pdb.set_trace()
# Only way to set the dataset correctly
if chk_meta_only:
continue
spec_set[jj] = data
#
print("Max pix = {:d}".format(maxpix))
# Add columns
meta.add_column(Column([2000.]*nspec, name='EPOCH'))
meta.add_column(Column(speclist, name='SPEC_FILE'))
meta.add_column(Column(npixlist, name='NPIX'))
meta.add_column(Column(wvminlist, name='WV_MIN'))
meta.add_column(Column(wvmaxlist, name='WV_MAX'))
meta.add_column(Column(Rlist, name='R'))
meta.add_column(Column(gratinglist, name='DISPERSER'))
meta.add_column(Column(np.arange(nspec,dtype=int),name='GROUP_ID'))
# Add HDLLS meta to hdf5
if chk_meta(meta):
if chk_meta_only:
pdb.set_trace()
hdf[sname]['meta'] = meta
else:
raise ValueError("meta file failed")
# References
refs = [dict(url='http://adsabs.harvard.edu/abs/2017AJ....154..114O',
bib='kodiaq')
]
jrefs = ltu.jsonify(refs)
hdf[sname]['meta'].attrs['Refs'] = json.dumps(jrefs)
#
return
def mk_meta(files,
ztbl,
fname=False,
stype='QSO',
skip_badz=False,
mdict=None,
parse_head=None,
debug=False,
chkz=False,
mtbl_file=None,
verbose=False,
specdb=None,
sdb_key=None,
**kwargs):
""" Generate a meta Table from an input list of files
Parameters
----------
files : list
List of FITS files
ztbl : Table
Table of redshifts. Must include RA, DEC, ZEM, ZEM_SOURCE
Used for RA/DEC if fname=False; then requires SPEC_FILE too
fname : bool, optional
Attempt to parse RA/DEC from the file name
Format must be
SDSSJ######(.##)+/-######(.#)[x]
where x cannot be a #. or +/-
stype : str, optional
Description of object type (e.g. 'QSO', 'Galaxy', 'SN')
specdb : SpecDB, optional
Database object to grab ID values from
Requires sdb_key
sdb_key : str, optional
ID key in SpecDB object
skip_badz : bool, optional
Skip spectra without a parseable redshift (using the Myers catalog)
parse_head : dict, optional
Parse header for meta info with this dict
mdict : dict, optional
Input meta data in dict form e.g. mdict=dict(INSTR='ESI')
chkz : bool, optional
If any sources have no parseable redshift, hit a set_trace
mtbl_file : str
Filename of input meta table. Current allowed extensions are _meta.ascii or _meta.fits
and they must be readable by Table.read(). The values in this table will overwrite
any others generated. Table must include a SPEC_FILE column to link meta data
Returns
-------
meta : Table
Meta table
"""
if specdb is not None:
if sdb_key is None:
raise IOError("Must specify sdb_key if you are passing in specdb")
Rdicts = defs.get_res_dicts()
#
coordlist = []
snames = []
for ifile in files:
sname = ifile.split('/')[-1]
snames.append(sname)
if fname:
# Starting index
if 'SDSSJ' in ifile:
i0 = ifile.find('SDSSJ') + 4
else:
i0 = ifile.rfind('J') + 1
# Find end (ugly)
for ii in range(i0 + 1, 99999):
if ifile[ii] in ('0', '1', '2', '3', '4', '5', '6', '7', '8',
'9', '.', '+', '-'):
continue
else:
i1 = ii
break
# Deal with .fits
if ifile[i1 - 1] == '.':
i1 -= 1
# Get coord
try:
coord = ltu.radec_to_coord(ifile[i0:i1])
except (UnboundLocalError, ValueError):
pdb.set_trace()
else:
mt = np.where(ztbl['SPEC_FILE'] == sname)[0]
if len(mt) != 1:
raise IndexError("NO MATCH FOR {:s}".format(sname))
coord = ltu.radec_to_coord((ztbl['RA'][mt], ztbl['DEC'][mt]))[0]
coordlist.append(coord)
ras = np.array([coord.ra.degree for coord in coordlist])
decs = np.array([coord.dec.degree for coord in coordlist])
coords = SkyCoord(ra=ras, dec=decs, unit='deg')
# Generate maindb Table
#maindb, tkeys = spbu.start_maindb(private=True)
# Fill
meta = Table()
meta['RA_GROUP'] = coords.ra.deg
meta['DEC_GROUP'] = coords.dec.deg
meta['STYPE'] = [str(stype)] * len(meta)
zem, zsource = spzu.zem_from_radec(meta['RA_GROUP'], meta['DEC_GROUP'],
ztbl, **kwargs)
badz = zem <= 0.
if np.sum(badz) > 0:
if skip_badz:
warnings.warn(
"Skipping {:d} entries without a parseable redshift".format(
np.sum(badz)))
else:
if chkz: # Turn this on to hit a stop instead of an Exception
pdb.set_trace()
else:
raise ValueError(
"{:d} entries without a parseable redshift".format(
np.sum(badz)))
meta['zem_GROUP'] = zem
meta['sig_zem'] = 0. # Need to add
meta['flag_zem'] = zsource
# Cut
meta = meta[~badz]
# specdb IDs
if sdb_key is not None:
meta[sdb_key] = [-9999] * len(meta)
if sdb_key not in meta.keys():
meta[sdb_key] = [-9999] * len(meta)
c_igmsp = SkyCoord(ra=specdb.qcat.cat['RA'],
dec=specdb.qcat.cat['DEC'],
unit='deg')
c_new = SkyCoord(ra=meta['RA_GROUP'],
dec=meta['DEC_GROUP'],
unit='deg')
# Find new sources
idx, d2d, d3d = match_coordinates_sky(c_new, c_igmsp, nthneighbor=1)
cdict = defs.get_cat_dict()
mtch = d2d < cdict['match_toler']
meta[sdb_key][mtch] = specdb.qcat.cat[sdb_key][idx[mtch]]
# Stack (primarily as a test)
'''
try:
maindb = vstack([maindb,meta], join_type='exact')
except:
pdb.set_trace()
'''
# SPEC_FILE
meta['SPEC_FILE'] = np.array(files)[~badz]
root_names = np.array(snames)[~badz]
# Try Header?
if parse_head is not None:
# Setup to store
plist = {}
for key in parse_head.keys():
plist[key] = []
# Loop on files
for sfile in meta['SPEC_FILE']:
if verbose:
print('Parsing {:s}'.format(sfile))
try:
head = fits.open(sfile)[0].header
except FileNotFoundError: # Try for compressed
head = fits.open(sfile + '.gz')[0].header
for key, item in parse_head.items():
# R
if key == 'R':
if parse_head[key] is True:
try:
plist[key].append(spbu.set_resolution(head))
except ValueError:
if mdict is not None:
try:
plist[key].append(mdict['R'])
except KeyError:
pdb.set_trace()
else:
pdb.set_trace()
plist[key].append(0.)
else:
raise ValueError("Set something else for R")
elif key == 'DATE-OBS':
if 'MJD' in item:
tval = Time(head[item],
format='mjd',
out_subfmt='date')
else:
tval = Time(head[item].replace('/', '-'),
format='isot',
out_subfmt='date')
plist[key].append(tval.iso)
else:
plist[key].append(head[item])
# INSTRUMENT SPECIFIC
try:
instr = head['INSTRUME']
except KeyError:
instr = 'none'
if 'LRIS' in instr:
if 'DISPERSER' not in plist.keys():
plist['DISPERSER'] = []
plist['INSTR'] = []
plist['R'] = []
try:
det = head['DETECTOR']
except KeyError:
if head['OUTFILE'] == 'lred':
det = 'LRIS-R'
else:
det = 'LRIS-B'
if 'LRIS-R' in det:
plist['DISPERSER'].append(head['GRANAME'])
plist['INSTR'].append('LRISr')
else:
plist['DISPERSER'].append(head['GRISNAME'])
plist['INSTR'].append('LRISb')
# Resolution
res = Rdicts[plist['INSTR'][-1]][plist['DISPERSER'][-1]]
try:
sname = head['SLITNAME']
except KeyError:
swidth = 1.
else:
swidth = defs.slit_width(sname, LRIS=True)
plist['R'].append(res / swidth)
# Finish
for key in plist.keys():
meta[key] = plist[key]
# mdict
if mdict is not None:
for key, item in mdict.items():
meta[key] = [item] * len(meta)
# EPOCH
if 'EPOCH' not in meta.keys():
warnings.warn("EPOCH not defined. Filling with 2000.")
meta['EPOCH'] = 2000.
# GROUP ID
meta['GROUP_ID'] = np.arange(len(meta)).astype(int)
# Fill in empty columns with warning
mkeys = meta.keys()
req_clms = defs.get_req_clms(sdb_key=sdb_key)
for clm in req_clms:
if clm not in mkeys:
if clm not in ['NPIX', 'WV_MIN', 'WV_MAX']: # File in ingest_spec
warnings.warn(
"Meta Column {:s} not defined. Filling with DUMMY".format(
clm))
if clm == 'DATE-OBS':
meta[clm] = ['9999-1-1'] * len(meta)
else:
meta[clm] = ['DUMMY'] * len(meta)
# Input meta table
if mtbl_file is not None:
# Read
if '_meta.ascii' in mtbl_file:
imtbl = Table.read(mtbl_file, format='ascii')
elif '_meta.fits' in mtbl_file:
imtbl = Table.read(mtbl_file)
else:
raise IOError(
"Input meta table must have either an ascii or fits extension")
# Check length
if len(imtbl) != len(meta):
raise IOError(
"Input meta table must have same length as self-generated one")
# Check for SPEC_FILE
if 'SPEC_FILE' not in imtbl.keys():
raise ValueError("Input meta table must include SPEC_FILE column")
# Loop to get indices
idx = []
for row in imtbl:
imt = np.where(root_names == row['SPEC_FILE'])[0]
if len(imt) == 0:
print("No match to spec file {:s}. Will ignore".format(
row['SPEC_FILE']))
elif len(imt) == 1:
idx.append(imt[0])
else:
raise ValueError(
"Two entries with the same SPEC_FILE. Something went wrong.."
)
idx = np.array(idx)
# Loop on keys
for key in imtbl.keys():
# Skip?
if key in ['SPEC_FILE']:
continue
if key in meta.keys():
pdb.set_trace()
else:
# Add Column
meta.add_column(imtbl[key][idx])
# Return
if debug:
meta[['RA_GROUP', 'DEC_GROUP', 'SPEC_FILE']].pprint(max_width=120)
pdb.set_trace()
return meta
def hdf5_adddata(hdf,
sname,
hdla100_meta,
debug=False,
chk_meta_only=False,
mk_test_file=False):
""" Append HDLA100 data to the h5 file
Parameters
----------
hdf : hdf5 pointer
IDs : ndarray
int array of IGM_ID values in mainDB
sname : str
Survey name
chk_meta_only : bool, optional
Only check meta file; will not write
mk_test_file : bool, optional
Generate the debug test file for Travis??
Returns
-------
"""
from specdb import defs
# Add Survey
print("Adding {:s} survey to DB".format(sname))
hdlls_grp = hdf.create_group(sname)
# Load up
Rdicts = defs.get_res_dicts()
# Checks
if sname != 'HDLA100':
raise IOError("Not expecting this survey..")
# Build spectra (and parse for meta)
#if mk_test_file:
# hdla100_full = hdlls_full[0:3]
max_npix = 192000 # Just needs to be large enough
data = init_data(max_npix, include_co=False)
# Init
spec_set = hdf[sname].create_dataset('spec',
data=data,
chunks=True,
maxshape=(None, ),
compression='gzip')
nspec = len(hdla100_meta)
spec_set.resize((nspec, ))
Rlist = []
wvminlist = []
wvmaxlist = []
dateobslist = []
npixlist = []
gratinglist = []
# Loop
for jj, row in enumerate(hdla100_meta):
kk = jj
# Extract
f = os.getenv('RAW_IGMSPEC') + '/HDLA100/' + row['SPEC_FILE']
spec = lsio.readspec(f)
# Parse name
fname = f.split('/')[-1]
# npix
head = spec.header
npix = spec.npix
if npix > max_npix:
raise ValueError(
"Not enough pixels in the data... ({:d})".format(npix))
# Some fiddling about
for key in ['wave', 'flux', 'sig']:
data[key] = 0. # Important to init (for compression too)
data['flux'][0][:npix] = spec.flux.value
data['sig'][0][:npix] = spec.sig.value
data['wave'][0][:npix] = spec.wavelength.value
# Meta
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
try:
Rlist.append(set_resolution(head))
except ValueError:
raise ValueError("Header is required for {:s}".format(fname))
else:
if '/' in head['DATE-OBS']:
spl = head['DATE-OBS'].split('/')
t = Time(datetime.datetime(
int(spl[2]) + 1900, int(spl[1]), int(spl[0])),
format='datetime')
else:
t = Time(head['DATE-OBS'], format='isot', out_subfmt='date')
dateobslist.append(t.iso)
# Grating
try:
gratinglist.append(head['XDISPERS'])
except KeyError:
try:
yr = t.value.year
except AttributeError:
yr = int(t.value[0:4])
if yr <= 1997:
gratinglist.append('RED')
else:
pdb.set_trace()
# Only way to set the dataset correctly
if chk_meta_only:
continue
spec_set[kk] = data
# Add columns
nmeta = len(hdla100_meta)
hdla100_meta.add_column(Column([2000.] * nmeta, name='EPOCH'))
hdla100_meta.add_column(Column(npixlist, name='NPIX'))
hdla100_meta.add_column(
Column([str(date) for date in dateobslist], name='DATE-OBS'))
hdla100_meta.add_column(Column(wvminlist, name='WV_MIN'))
hdla100_meta.add_column(Column(wvmaxlist, name='WV_MAX'))
hdla100_meta.add_column(Column(Rlist, name='R'))
hdla100_meta.add_column(
Column(np.arange(nmeta, dtype=int), name='GROUP_ID'))
hdla100_meta.add_column(Column(gratinglist, name='DISPERSER'))
hdla100_meta['INSTR'] = ['HIRES'] * nspec
hdla100_meta['TELESCOPE'] = ['Keck-I'] * nspec
#hdla100_meta.rename_column('Z_QSO', 'zem')
# Add HDLLS meta to hdf5
if chk_meta(hdla100_meta):
if chk_meta_only:
pdb.set_trace()
hdf[sname]['meta'] = hdla100_meta
else:
raise ValueError("meta file failed")
# References
refs = [
dict(url='http://adsabs.harvard.edu/abs/2013ApJ...769...54N',
bib='neeleman+13'),
]
jrefs = ltu.jsonify(refs)
hdf[sname]['meta'].attrs['Refs'] = json.dumps(jrefs)
#
return
def hdf5_adddata(hdf,
sname,
meta,
debug=False,
chk_meta_only=False,
mk_test_file=False):
""" Append HD-LLS data to the h5 file
Parameters
----------
hdf : hdf5 pointer
IDs : ndarray
int array of IGM_ID values in mainDB
sname : str
Survey name
chk_meta_only : bool, optional
Only check meta file; will not write
mk_test_file : bool, optional
Generate the debug test file for Travis??
Returns
-------
"""
from specdb import defs
# Add Survey
print("Adding {:s} survey to DB".format(sname))
hdlls_grp = hdf.create_group(sname)
# Load up
Rdicts = defs.get_res_dicts()
mike_meta = grab_meta_mike()
mike_coord = SkyCoord(ra=mike_meta['RA_GROUP'],
dec=mike_meta['DEC_GROUP'],
unit='deg')
# Checks
if sname != 'HD-LLS_DR1':
raise IOError("Not expecting this survey..")
full_coord = SkyCoord(ra=meta['RA_GROUP'],
dec=meta['DEC_GROUP'],
unit='deg')
# Build spectra (and parse for meta)
if mk_test_file:
meta = meta[0:3]
nspec = len(meta)
max_npix = 210000 # Just needs to be large enough
data = init_data(max_npix, include_co=False)
# Init
full_idx = np.zeros(len(meta), dtype=int)
spec_set = hdf[sname].create_dataset('spec',
data=data,
chunks=True,
maxshape=(None, ),
compression='gzip')
spec_set.resize((nspec, ))
Rlist = []
wvminlist = []
wvmaxlist = []
dateobslist = []
npixlist = []
instrlist = []
gratinglist = []
telelist = []
# Loop
members = glob.glob(os.getenv('RAW_IGMSPEC') + '/{:s}/*fits'.format(sname))
kk = -1
for jj, member in enumerate(members):
if 'HD-LLS_DR1.fits' in member:
continue
kk += 1
# Extract
f = member
hdu = fits.open(f)
# Parse name
fname = f.split('/')[-1]
mt = np.where(meta['SPEC_FILE'] == fname)[0]
if mk_test_file and (jj >= 3):
continue
if len(mt) != 1:
pdb.set_trace()
raise ValueError("HD-LLS: No match to spectral file?!")
else:
print('loading {:s}'.format(fname))
full_idx[kk] = mt[0]
# npix
head = hdu[0].header
# Some fiddling about
for key in ['wave', 'flux', 'sig']:
data[key] = 0. # Important to init (for compression too)
# Double check
if kk == 0:
assert hdu[1].name == 'ERROR'
assert hdu[2].name == 'WAVELENGTH'
# Write
spec = lsio.readspec(f) # Handles dummy pixels in ESI
npix = spec.npix
if npix > max_npix:
raise ValueError(
"Not enough pixels in the data... ({:d})".format(npix))
data['flux'][0][:npix] = spec.flux.value
data['sig'][0][:npix] = spec.sig.value
data['wave'][0][:npix] = spec.wavelength.value
#data['flux'][0][:npix] = hdu[0].data
#data['sig'][0][:npix] = hdu[1].data
#data['wave'][0][:npix] = hdu[2].data
# Meta
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
if 'HIRES' in fname:
instrlist.append('HIRES')
telelist.append('Keck-I')
gratinglist.append('BOTH')
try:
Rlist.append(set_resolution(head))
except ValueError:
# A few by hand (pulled from Table 1)
if 'J073149' in fname:
Rlist.append(Rdicts['HIRES']['C5'])
tval = datetime.datetime.strptime('2006-01-04', '%Y-%m-%d')
elif 'J081435' in fname:
Rlist.append(Rdicts['HIRES']['C1'])
tval = datetime.datetime.strptime('2006-12-26',
'%Y-%m-%d') # 2008 too
elif 'J095309' in fname:
Rlist.append(Rdicts['HIRES']['C1'])
tval = datetime.datetime.strptime('2005-03-18', '%Y-%m-%d')
elif 'J113418' in fname:
Rlist.append(Rdicts['HIRES']['C5'])
tval = datetime.datetime.strptime('2006-01-05', '%Y-%m-%d')
elif 'J135706' in fname:
Rlist.append(Rdicts['HIRES']['C5'])
tval = datetime.datetime.strptime('2007-04-28', '%Y-%m-%d')
elif 'J155556.9' in fname:
Rlist.append(Rdicts['HIRES']['C5'])
tval = datetime.datetime.strptime('2005-04-15', '%Y-%m-%d')
elif 'J212329' in fname:
Rlist.append(Rdicts['HIRES']['E3'])
tval = datetime.datetime.strptime('2006-08-20', '%Y-%m-%d')
else:
pdb.set_trace()
else:
tval = datetime.datetime.strptime(head['DATE-OBS'], '%Y-%m-%d')
dateobslist.append(datetime.datetime.strftime(tval, '%Y-%m-%d'))
elif 'ESI' in fname:
instrlist.append('ESI')
telelist.append('Keck-II')
gratinglist.append('ECH')
try:
Rlist.append(set_resolution(head))
except ValueError:
print("Using R=6,000 for ESI")
Rlist.append(6000.)
try:
tval = datetime.datetime.strptime(head['DATE'], '%Y-%m-%d')
except KeyError:
if ('J223438.5' in fname) or ('J231543' in fname):
tval = datetime.datetime.strptime('2004-09-11', '%Y-%m-%d')
else:
pdb.set_trace()
dateobslist.append(datetime.datetime.strftime(tval, '%Y-%m-%d'))
elif 'MIKE' in fname: # APPROXIMATE
if 'MIKEr' in fname:
instrlist.append('MIKEr')
gratinglist.append('RED')
elif 'MIKEb' in fname:
instrlist.append('MIKEb')
gratinglist.append('BLUE')
else:
instrlist.append('MIKE')
gratinglist.append('BOTH')
telelist.append('Magellan')
sep = full_coord[mt[0]].separation(mike_coord)
imin = np.argmin(sep)
if sep[imin] > 1. * u.arcsec:
pdb.set_trace()
raise ValueError("Bad separation in MIKE")
# R and Date
Rlist.append(25000. / mike_meta['Slit'][imin])
tval = datetime.datetime.strptime(mike_meta['DATE-OBS'][imin],
'%Y-%b-%d')
dateobslist.append(datetime.datetime.strftime(tval, '%Y-%m-%d'))
elif 'MAGE' in fname: # APPROXIMATE
instrlist.append('MagE')
if 'Clay' in head['TELESCOP']:
telelist.append('Magellan/Clay')
else:
telelist.append('Magellan/Baade')
gratinglist.append('N/A')
Rlist.append(set_resolution(head))
dateobslist.append(head['DATE-OBS'])
else: # MagE
raise ValueError("UH OH")
# Only way to set the dataset correctly
if chk_meta_only:
continue
spec_set[kk] = data
# Add columns
meta = meta[full_idx]
nmeta = len(meta)
meta.add_column(Column([2000.] * nmeta, name='EPOCH'))
meta.add_column(Column(npixlist, name='NPIX'))
meta.add_column(
Column([str(date) for date in dateobslist], name='DATE-OBS'))
meta.add_column(Column(wvminlist, name='WV_MIN'))
meta.add_column(Column(wvmaxlist, name='WV_MAX'))
meta.add_column(Column(Rlist, name='R'))
meta.add_column(Column(np.arange(nmeta, dtype=int), name='GROUP_ID'))
meta.add_column(Column(gratinglist, name='GRATING'))
meta.add_column(Column(instrlist, name='INSTR'))
meta.add_column(Column(telelist, name='TELESCOPE'))
# v02
meta.rename_column('GRATING', 'DISPERSER')
# Add HDLLS meta to hdf5
if chk_meta(meta):
if chk_meta_only:
pdb.set_trace()
hdf[sname]['meta'] = meta
else:
raise ValueError("meta file failed")
# References
refs = [
dict(url='http://adsabs.harvard.edu/abs/2015ApJS..221....2P',
bib='prochaska+15'),
]
jrefs = ltu.jsonify(refs)
hdf[sname]['meta'].attrs['Refs'] = json.dumps(jrefs)
#
return
def hdf5_adddata(hdf, sname, meta, debug=False, chk_meta_only=False,
mk_test_file=False):
""" Append HD-LLS data to the h5 file
Parameters
----------
hdf : hdf5 pointer
IDs : ndarray
int array of IGM_ID values in mainDB
sname : str
Survey name
chk_meta_only : bool, optional
Only check meta file; will not write
mk_test_file : bool, optional
Generate the debug test file for Travis??
Returns
-------
"""
from specdb import defs
# Add Survey
print("Adding {:s} survey to DB".format(sname))
hdlls_grp = hdf.create_group(sname)
# Load up
Rdicts = defs.get_res_dicts()
mike_meta = grab_meta_mike()
mike_coord = SkyCoord(ra=mike_meta['RA_GROUP'], dec=mike_meta['DEC_GROUP'], unit='deg')
# Checks
if sname != 'HD-LLS_DR1':
raise IOError("Not expecting this survey..")
full_coord = SkyCoord(ra=meta['RA_GROUP'], dec=meta['DEC_GROUP'], unit='deg')
# Build spectra (and parse for meta)
if mk_test_file:
meta = meta[0:3]
nspec = len(meta)
max_npix = 210000 # Just needs to be large enough
data = init_data(max_npix, include_co=False)
# Init
full_idx = np.zeros(len(meta), dtype=int)
spec_set = hdf[sname].create_dataset('spec', data=data, chunks=True,
maxshape=(None,), compression='gzip')
spec_set.resize((nspec,))
Rlist = []
wvminlist = []
wvmaxlist = []
dateobslist = []
npixlist = []
instrlist = []
gratinglist = []
telelist = []
# Loop
members = glob.glob(os.getenv('RAW_IGMSPEC')+'/{:s}/*fits'.format(sname))
kk = -1
for jj,member in enumerate(members):
if 'HD-LLS_DR1.fits' in member:
continue
kk += 1
# Extract
f = member
hdu = fits.open(f)
# Parse name
fname = f.split('/')[-1]
mt = np.where(meta['SPEC_FILE'] == fname)[0]
if mk_test_file and (jj>=3):
continue
if len(mt) != 1:
pdb.set_trace()
raise ValueError("HD-LLS: No match to spectral file?!")
else:
print('loading {:s}'.format(fname))
full_idx[kk] = mt[0]
# npix
head = hdu[0].header
# Some fiddling about
for key in ['wave','flux','sig']:
data[key] = 0. # Important to init (for compression too)
# Double check
if kk == 0:
assert hdu[1].name == 'ERROR'
assert hdu[2].name == 'WAVELENGTH'
# Write
spec = lsio.readspec(f) # Handles dummy pixels in ESI
npix = spec.npix
if npix > max_npix:
raise ValueError("Not enough pixels in the data... ({:d})".format(npix))
data['flux'][0][:npix] = spec.flux.value
data['sig'][0][:npix] = spec.sig.value
data['wave'][0][:npix] = spec.wavelength.value
#data['flux'][0][:npix] = hdu[0].data
#data['sig'][0][:npix] = hdu[1].data
#data['wave'][0][:npix] = hdu[2].data
# Meta
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
if 'HIRES' in fname:
instrlist.append('HIRES')
telelist.append('Keck-I')
gratinglist.append('BOTH')
try:
Rlist.append(set_resolution(head))
except ValueError:
# A few by hand (pulled from Table 1)
if 'J073149' in fname:
Rlist.append(Rdicts['HIRES']['C5'])
tval = datetime.datetime.strptime('2006-01-04', '%Y-%m-%d')
elif 'J081435' in fname:
Rlist.append(Rdicts['HIRES']['C1'])
tval = datetime.datetime.strptime('2006-12-26', '%Y-%m-%d') # 2008 too
elif 'J095309' in fname:
Rlist.append(Rdicts['HIRES']['C1'])
tval = datetime.datetime.strptime('2005-03-18', '%Y-%m-%d')
elif 'J113418' in fname:
Rlist.append(Rdicts['HIRES']['C5'])
tval = datetime.datetime.strptime('2006-01-05', '%Y-%m-%d')
elif 'J135706' in fname:
Rlist.append(Rdicts['HIRES']['C5'])
tval = datetime.datetime.strptime('2007-04-28', '%Y-%m-%d')
elif 'J155556.9' in fname:
Rlist.append(Rdicts['HIRES']['C5'])
tval = datetime.datetime.strptime('2005-04-15', '%Y-%m-%d')
elif 'J212329' in fname:
Rlist.append(Rdicts['HIRES']['E3'])
tval = datetime.datetime.strptime('2006-08-20', '%Y-%m-%d')
else:
pdb.set_trace()
else:
tval = datetime.datetime.strptime(head['DATE-OBS'], '%Y-%m-%d')
dateobslist.append(datetime.datetime.strftime(tval,'%Y-%m-%d'))
elif 'ESI' in fname:
instrlist.append('ESI')
telelist.append('Keck-II')
gratinglist.append('ECH')
try:
Rlist.append(set_resolution(head))
except ValueError:
print("Using R=6,000 for ESI")
Rlist.append(6000.)
try:
tval = datetime.datetime.strptime(head['DATE'], '%Y-%m-%d')
except KeyError:
if ('J223438.5' in fname) or ('J231543' in fname):
tval = datetime.datetime.strptime('2004-09-11', '%Y-%m-%d')
else:
pdb.set_trace()
dateobslist.append(datetime.datetime.strftime(tval,'%Y-%m-%d'))
elif 'MIKE' in fname: # APPROXIMATE
if 'MIKEr' in fname:
instrlist.append('MIKEr')
gratinglist.append('RED')
elif 'MIKEb' in fname:
instrlist.append('MIKEb')
gratinglist.append('BLUE')
else:
instrlist.append('MIKE')
gratinglist.append('BOTH')
telelist.append('Magellan')
sep = full_coord[mt[0]].separation(mike_coord)
imin = np.argmin(sep)
if sep[imin] > 1.*u.arcsec:
pdb.set_trace()
raise ValueError("Bad separation in MIKE")
# R and Date
Rlist.append(25000. / mike_meta['Slit'][imin])
tval = datetime.datetime.strptime(mike_meta['DATE-OBS'][imin], '%Y-%b-%d')
dateobslist.append(datetime.datetime.strftime(tval,'%Y-%m-%d'))
elif 'MAGE' in fname: # APPROXIMATE
instrlist.append('MagE')
if 'Clay' in head['TELESCOP']:
telelist.append('Magellan/Clay')
else:
telelist.append('Magellan/Baade')
gratinglist.append('N/A')
Rlist.append(set_resolution(head))
dateobslist.append(head['DATE-OBS'])
else: # MagE
raise ValueError("UH OH")
# Only way to set the dataset correctly
if chk_meta_only:
continue
spec_set[kk] = data
# Add columns
meta = meta[full_idx]
nmeta = len(meta)
meta.add_column(Column([2000.]*nmeta, name='EPOCH'))
meta.add_column(Column(npixlist, name='NPIX'))
meta.add_column(Column([str(date) for date in dateobslist], name='DATE-OBS'))
meta.add_column(Column(wvminlist, name='WV_MIN'))
meta.add_column(Column(wvmaxlist, name='WV_MAX'))
meta.add_column(Column(Rlist, name='R'))
meta.add_column(Column(np.arange(nmeta,dtype=int),name='GROUP_ID'))
meta.add_column(Column(gratinglist, name='GRATING'))
meta.add_column(Column(instrlist, name='INSTR'))
meta.add_column(Column(telelist, name='TELESCOPE'))
# v02
meta.rename_column('GRATING', 'DISPERSER')
# Add HDLLS meta to hdf5
if chk_meta(meta):
if chk_meta_only:
pdb.set_trace()
hdf[sname]['meta'] = meta
else:
raise ValueError("meta file failed")
# References
refs = [dict(url='http://adsabs.harvard.edu/abs/2015ApJS..221....2P',
bib='prochaska+15'),
]
jrefs = ltu.jsonify(refs)
hdf[sname]['meta'].attrs['Refs'] = json.dumps(jrefs)
#
return
def hdf5_adddata(hdf, sname, hdla100_meta, debug=False, chk_meta_only=False,
mk_test_file=False):
""" Append HDLA100 data to the h5 file
Parameters
----------
hdf : hdf5 pointer
IDs : ndarray
int array of IGM_ID values in mainDB
sname : str
Survey name
chk_meta_only : bool, optional
Only check meta file; will not write
mk_test_file : bool, optional
Generate the debug test file for Travis??
Returns
-------
"""
from specdb import defs
# Add Survey
print("Adding {:s} survey to DB".format(sname))
hdlls_grp = hdf.create_group(sname)
# Load up
Rdicts = defs.get_res_dicts()
# Checks
if sname != 'HDLA100':
raise IOError("Not expecting this survey..")
# Build spectra (and parse for meta)
#if mk_test_file:
# hdla100_full = hdlls_full[0:3]
max_npix = 192000 # Just needs to be large enough
data = init_data(max_npix, include_co=False)
# Init
spec_set = hdf[sname].create_dataset('spec', data=data, chunks=True,
maxshape=(None,), compression='gzip')
nspec = len(hdla100_meta)
spec_set.resize((nspec,))
Rlist = []
wvminlist = []
wvmaxlist = []
dateobslist = []
npixlist = []
gratinglist = []
# Loop
for jj,row in enumerate(hdla100_meta):
kk = jj
# Extract
f = os.getenv('RAW_IGMSPEC')+'/HDLA100/'+row['SPEC_FILE']
spec = lsio.readspec(f)
# Parse name
fname = f.split('/')[-1]
# npix
head = spec.header
npix = spec.npix
if npix > max_npix:
raise ValueError("Not enough pixels in the data... ({:d})".format(npix))
# Some fiddling about
for key in ['wave','flux','sig']:
data[key] = 0. # Important to init (for compression too)
data['flux'][0][:npix] = spec.flux.value
data['sig'][0][:npix] = spec.sig.value
data['wave'][0][:npix] = spec.wavelength.value
# Meta
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
try:
Rlist.append(set_resolution(head))
except ValueError:
raise ValueError("Header is required for {:s}".format(fname))
else:
if '/' in head['DATE-OBS']:
spl = head['DATE-OBS'].split('/')
t = Time(datetime.datetime(int(spl[2])+1900, int(spl[1]), int(spl[0])), format='datetime')
else:
t = Time(head['DATE-OBS'], format='isot', out_subfmt='date')
dateobslist.append(t.iso)
# Grating
try:
gratinglist.append(head['XDISPERS'])
except KeyError:
try:
yr = t.value.year
except AttributeError:
yr = int(t.value[0:4])
if yr <= 1997:
gratinglist.append('RED')
else:
pdb.set_trace()
# Only way to set the dataset correctly
if chk_meta_only:
continue
spec_set[kk] = data
# Add columns
nmeta = len(hdla100_meta)
hdla100_meta.add_column(Column([2000.]*nmeta, name='EPOCH'))
hdla100_meta.add_column(Column(npixlist, name='NPIX'))
hdla100_meta.add_column(Column([str(date) for date in dateobslist], name='DATE-OBS'))
hdla100_meta.add_column(Column(wvminlist, name='WV_MIN'))
hdla100_meta.add_column(Column(wvmaxlist, name='WV_MAX'))
hdla100_meta.add_column(Column(Rlist, name='R'))
hdla100_meta.add_column(Column(np.arange(nmeta,dtype=int),name='GROUP_ID'))
hdla100_meta.add_column(Column(gratinglist, name='DISPERSER'))
hdla100_meta['INSTR'] = ['HIRES']*nspec
hdla100_meta['TELESCOPE'] = ['Keck-I']*nspec
#hdla100_meta.rename_column('Z_QSO', 'zem')
# Add HDLLS meta to hdf5
if chk_meta(hdla100_meta):
if chk_meta_only:
pdb.set_trace()
hdf[sname]['meta'] = hdla100_meta
else:
raise ValueError("meta file failed")
# References
refs = [dict(url='http://adsabs.harvard.edu/abs/2013ApJ...769...54N',
bib='neeleman+13'),
]
jrefs = ltu.jsonify(refs)
hdf[sname]['meta'].attrs['Refs'] = json.dumps(jrefs)
#
return