def hdf5_adddata(hdf, sname, meta, debug=False, chk_meta_only=False):
""" Append XQ-100 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))
xq100_grp = hdf.create_group(sname)
if len(meta) != 300:
pdb.set_trace()
# Checks
if sname != 'XQ-100':
raise IOError("Expecting XQ-100!!")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 20000 # Just needs to be large enough
data = init_data(max_npix, include_co=True)
# Init
spec_set = hdf[sname].create_dataset('spec',
data=data,
chunks=True,
maxshape=(None, ),
compression='gzip')
spec_set.resize((nspec, ))
Rlist = []
wvminlist = []
wvmaxlist = []
npixlist = []
speclist = []
gratinglist = []
telelist = []
instrlist = []
# Loop
maxpix = 0
for jj, row in enumerate(meta):
#
print("XQ-100: Reading {:s}".format(row['SPEC_FILE']))
spec = lsio.readspec(row['SPEC_FILE'])
# Parse name
fname = row['SPEC_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)
# Continuum
# 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.to('AA').value
data['co'][0][:npix] = spec.co.value
# Meta
head = spec.header
speclist.append(str(fname))
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
telelist.append(head['TELESCOP'])
instrlist.append(head['INSTRUME'])
gratinglist.append(head['DISPELEM'])
npixlist.append(npix)
if gratinglist[-1] == 'NIR': # From Lopez+16
Rlist.append(4350.)
elif gratinglist[-1] == 'VIS':
Rlist.append(7450.)
elif gratinglist[-1] == 'UVB':
Rlist.append(5300.)
else:
pdb.set_trace()
raise ValueError("UH OH")
# 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(gratinglist, name='DISPERSER'))
meta.add_column(Column(telelist, name='TELESCOPE'))
meta.add_column(Column(instrlist, name='INSTR'))
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(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/2016arXiv160708776L',
bib='lopez+16')
]
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
def hdf5_adddata(hdf, sname, meta, debug=False, chk_meta_only=False, sdss_hdf=None, **kwargs):
""" Add SDSS data to the DB
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))
if sdss_hdf is not None:
print("Using previously generated {:s} dataset...".format(sname))
sdss_hdf.copy(sname, hdf)
return
sdss_grp = hdf.create_group(sname)
# Load up
# Checks
if sname != 'SDSS_DR7':
raise IOError("Not expecting this survey..")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 4000 # Just needs to be large enough
data = init_data(max_npix, include_co=True)
# Init
spec_set = hdf[sname].create_dataset('spec', data=data, chunks=True,
maxshape=(None,), compression='gzip')
spec_set.resize((nspec,))
# Read Zhu continua, wave file
cfile = os.getenv('RAW_IGMSPEC')+'/SDSS/ALLQSO_SPEC_106_continuum_nointerp.fits'
zhu_conti = Table.read(cfile)
wvfile = cfile.replace('continuum','wave')
zhu_wave = Table.read(wvfile)
#
wvminlist = []
wvmaxlist = []
npixlist = []
speclist = []
# Loop
maxpix = 0
for jj,row in enumerate(meta):
full_file = get_specfil(row)
if not os.path.isfile(full_file):
full_file = get_specfil(row, dr7=True)
# Extract
#print("SDSS: Reading {:s}".format(full_file))
# Parse name
fname = full_file.split('/')[-1]
# Generate full file
spec = lsio.readspec(full_file)
# 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','co']:
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
# Continuum
mtc = (zhu_conti['PLATE'] == row['PLATE']) & (zhu_conti['FIBER']==row['FIBER'])
mtw = (zhu_wave['PLATE'] == row['PLATE']) & (zhu_wave['FIBER']==row['FIBER'])
if np.sum(mtc) == 1:
imin = np.argmin(np.abs(zhu_wave['WAVE'][0][:,np.where(mtw)[1]]-spec.wavelength[0].value))
data['co'][0][:npix] = zhu_conti['CONTINUUM'][0][imin:npix+imin,np.where(mtc)[1]].flatten()
elif np.sum(mtc) > 1:
print("Multiple continua for plate={:d}, row={:d}. Taking the first".format(row['PLATE'], row['FIBER']))
imin = np.argmin(np.abs(zhu_wave['WAVE'][0][:,np.where(mtw)[1][0]]-spec.wavelength[0].value))
data['co'][0][:npix] = zhu_conti['CONTINUUM'][0][imin:npix+imin,np.where(mtc)[1][0]].flatten()
elif np.sum(mtc) == 0:
print("No SDSS continuum for plate={:d}, row={:d}".format(row['PLATE'], row['FIBER']))
#from xastropy.xutils import xdebug as xdb
#xdb.set_trace()
#xdb.xplot(data['wave'][0], data['flux'][0], data['co'][0])
# Meta
speclist.append(str(fname))
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
# 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(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(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/2010AJ....139.2360S',
bib='sdss_qso_dr7'),
]
jrefs = ltu.jsonify(refs)
hdf[sname]['meta'].attrs['Refs'] = json.dumps(jrefs)
#
return
def hdf5_writter(path, reso, lowl, highl, outputname):
'''
:param path: path to the spectra file
:param lowl float: lower limit for request redshift
:param highl float: higher limit for request redshift
:param reso: delta v in km/s to rebin the data
:param outputname: the name for the output file
:return: hdf5file
'''
outfil = str(outputname)
hdf = h5py.File(outfil, 'w')
#
gdict = {}
# creating group
for z in np.arange(lowl, highl, 0.05):
# hdf.create_group('z'+str(z)+'-'+str(z+0.05))
print(z)
spectest1 = []
spec2 = []
spectest1, spec2 = reading_data(path, reso, z, z + 0.05)
print(np.round(z, 2), len(spectest1.z))
# hdf_append = h5py.File('tmp'+str(z)+'.hdf', 'w')
# hdf.create_group('z' + str(z) + '-' + str(z + 0.05))
f = hdf.create_group('z' + str(np.round(z, 2)) + '-' +
str(np.round(z + 0.05, 2)))
npix = len(spec2.wavelength)
data = sdb_u.init_data(npix)
nspec = len(spectest1.z)
print(npix)
#creat dataset
spec_set = hdf['z' + str(np.round(z, 2)) + '-' +
str(np.round(z + 0.05, 2))].create_dataset(
'spec',
data=data,
chunks=True,
maxshape=(None, ),
compression='gzip')
spec_set.resize((nspec, ))
for ii in range(nspec):
data['flux'][0][:npix] = spec2[ii].flux # Should be flux values
data['sig'][0][:npix] = spec2[ii].sig # SHould be sigma values
# print (spec[ii].sig)
data['wave'][0][:npix] = spec2[
ii].wavelength # Should be wavelength values
# Fill
spec_set[ii] = data
# hdf.copy('z'+str(z)+'-'+str(z+0.05), hdf_append['z'+str(z)+'-'+str(z+0.05)])
# making meta data
# hdfnew = h5py.File('z2.8_specdb_test1.hdf', 'w')
# group = 'z2.8-2.85'
# _ = hdfnew.create_group(group)
group = 'z' + str(np.round(z, 2)) + '-' + str(np.round(z + 0.05, 2))
id_key = 'DESI_ID'
maindb, tkeys = spbu.start_maindb(id_key)
meta = Table()
meta['zem_GROUP'] = spectest1.z
meta['RA_GROUP'] = spectest1.ra
meta['DEC_GROUP'] = spectest1.dec
meta['EPOCH'] = 2000.
meta['sig_zem'] = 0.
meta['flag_zem'] = np.string_('DESI')
meta['STYPE'] = np.string_('QSO')
# Observation
meta['SPEC_FILE'] = np.array(spectest1.filename, dtype=float)
meta['DATE-OBS'] = spectest1.date
#
meta['GROUP_ID'] = np.arange(len(meta)).astype(int)
# Spectrograph
meta['R'] = 3000.
meta['TELESCOPE'] = np.string_('KPNO-4m')
meta['DISPERSER'] = np.string_('ALL')
meta['INSTR'] = np.string_('DESI')
meta['WV_MIN'] = 3800. # Should be the right value
meta['WV_MAX'] = 9900. # Should be the right value
meta['NPIX'] = 8000 # Should be the right value
meta['PLATE'] = np.array(np.tile(1, len(spectest1.id)), dtype=int)
meta['FIBERID'] = spectest1.id
meta['MOCK_ID'] = spectest1.id
flag_g = spbu.add_to_group_dict(group, gdict)
maindb = spbu.add_ids(maindb,
meta,
flag_g,
tkeys,
'DESI_ID',
first=(flag_g == flag_g))
hdf[group]['meta'] = meta
zpri = spb_defs.z_priority()
print(flag_g)
spbu.write_hdf(hdf,
str('DESI_v05'),
maindb,
zpri,
gdict,
str('v0.1'),
Publisher='jding')
hdf.close()
def hdf5_adddata(hdf, sname, meta, debug=False, chk_meta_only=False, boss_hdf=None, **kwargs):
""" Add BOSS data to the DB
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
boss_hdf : str, optional
Returns
-------
"""
# Add Survey
print("Adding {:s} survey to DB".format(sname))
if boss_hdf is not None:
print("Using previously generated {:s} dataset...".format(sname))
boss_hdf.copy(sname, hdf)
return
boss_grp = hdf.create_group(sname)
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 4650 # Just needs to be large enough
data = init_data(max_npix, include_co=True)
# Init
spec_set = hdf[sname].create_dataset('spec', data=data, chunks=True,
maxshape=(None,), compression='gzip')
spec_set.resize((nspec,))
wvminlist = []
wvmaxlist = []
speclist = []
npixlist = []
# Loop
maxpix = 0
for jj,row in enumerate(meta):
# Generate full file
full_file = get_specfil(row)
if full_file == 'None':
continue
# Read
spec = lsio.readspec(full_file)
# npix
npix = spec.npix
# Kludge for higest redshift systems
if npix < 10:
full_file = get_specfil(row, hiz=True)
try:
spec = lsio.readspec(full_file)
except:
print("Missing: {:s}".format(full_file))
npix = spec.npix
elif npix > max_npix:
raise ValueError("Not enough pixels in the data... ({:d})".format(npix))
else:
maxpix = max(npix,maxpix)
# Parse name
fname = full_file.split('/')[-1]
# Fill
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
# GZ Continuum -- packed in with spectrum, generated by my IDL script
try:
co = spec.co.value
except AttributeError:
co = np.zeros_like(spec.flux.value)
# KG Continuum
KG_file = get_specfil(row, KG=True)
if os.path.isfile(KG_file) and (npix>1): # Latter is for junk in GZ file. Needs fixing
hduKG = fits.open(KG_file)
KGtbl = hduKG[1].data
wvKG = 10.**KGtbl['LOGLAM']
try:
assert (wvKG[0]-spec.wavelength[0].value) < 1e-5
except:
pdb.set_trace()
gdpix = np.where(wvKG < (1+row['zem_GROUP'])*1200.)[0]
co[gdpix] = KGtbl['CONT'][gdpix]
data['co'][0][:npix] = co
# Meta
speclist.append(str(fname))
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
if chk_meta_only:
continue
# Only way to set the dataset correctly
spec_set[jj] = data
#
print("Max pix = {:d}".format(maxpix))
# Add columns
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(np.arange(nspec,dtype=int),name='GROUP_ID'))
meta.add_column(Column([2000.]*len(meta), name='EPOCH'))
# Add HDLLS meta to hdf5
if chk_meta(meta):
if chk_meta_only:
pdb.set_trace()
hdf[sname]['meta'] = meta
else:
pdb.set_trace()
raise ValueError("meta file failed")
# References
refs = [dict(url='http://adsabs.harvard.edu/abs/2015ApJS..219...12A',
bib='boss_qso_dr12'),
]
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,
sdss_hdf=None,
**kwargs):
""" Add SDSS data to the DB
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))
if sdss_hdf is not None:
print("Using previously generated {:s} dataset...".format(sname))
sdss_hdf.copy(sname, hdf)
return
sdss_grp = hdf.create_group(sname)
# Load up
# Checks
if sname != 'SDSS_DR7':
raise IOError("Not expecting this survey..")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 4000 # Just needs to be large enough
data = init_data(max_npix, include_co=True)
# Init
spec_set = hdf[sname].create_dataset('spec',
data=data,
chunks=True,
maxshape=(None, ),
compression='gzip')
spec_set.resize((nspec, ))
# Read Zhu continua, wave file
cfile = os.getenv(
'RAW_IGMSPEC') + '/SDSS/ALLQSO_SPEC_106_continuum_nointerp.fits'
zhu_conti = Table.read(cfile)
wvfile = cfile.replace('continuum', 'wave')
zhu_wave = Table.read(wvfile)
#
wvminlist = []
wvmaxlist = []
npixlist = []
speclist = []
# Loop
maxpix = 0
for jj, row in enumerate(meta):
full_file = get_specfil(row)
if not os.path.isfile(full_file):
full_file = get_specfil(row, dr7=True)
# Extract
#print("SDSS: Reading {:s}".format(full_file))
# Parse name
fname = full_file.split('/')[-1]
# Generate full file
spec = lsio.readspec(full_file)
# 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', 'co']:
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
# Continuum
mtc = (zhu_conti['PLATE'] == row['PLATE']) & (zhu_conti['FIBER']
== row['FIBER'])
mtw = (zhu_wave['PLATE'] == row['PLATE']) & (zhu_wave['FIBER']
== row['FIBER'])
if np.sum(mtc) == 1:
imin = np.argmin(
np.abs(zhu_wave['WAVE'][0][:, np.where(mtw)[1]] -
spec.wavelength[0].value))
data['co'][0][:npix] = zhu_conti['CONTINUUM'][0][
imin:npix + imin, np.where(mtc)[1]].flatten()
elif np.sum(mtc) > 1:
print(
"Multiple continua for plate={:d}, row={:d}. Taking the first"
.format(row['PLATE'], row['FIBER']))
imin = np.argmin(
np.abs(zhu_wave['WAVE'][0][:, np.where(mtw)[1][0]] -
spec.wavelength[0].value))
data['co'][0][:npix] = zhu_conti['CONTINUUM'][0][
imin:npix + imin, np.where(mtc)[1][0]].flatten()
elif np.sum(mtc) == 0:
print("No SDSS continuum for plate={:d}, row={:d}".format(
row['PLATE'], row['FIBER']))
#from xastropy.xutils import xdebug as xdb
#xdb.set_trace()
#xdb.xplot(data['wave'][0], data['flux'][0], data['co'][0])
# Meta
speclist.append(str(fname))
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
# 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(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(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/2010AJ....139.2360S',
bib='sdss_qso_dr7'),
]
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):
""" Append ESI 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
-------
"""
from specdb import defs
# Add Survey
print("Adding {:s} survey to DB".format(sname))
esidla_grp = hdf.create_group(sname)
# Load up
Rdicts = defs.get_res_dicts()
# Checks
if sname != 'ESI_DLA':
raise IOError("Expecting ESI_DLA!!")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 50000 # 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')
spec_set.resize((nspec,))
Rlist = []
wvminlist = []
wvmaxlist = []
npixlist = []
speclist = []
# Loop
maxpix = 0
for jj,row in enumerate(meta):
#
specfile = os.getenv('RAW_IGMSPEC')+'/HighzESIDLA/{:s}a_xF.fits'.format(
row['Name'])
print("ESI_DLA: Reading {:s}".format(specfile))
spec = lsio.readspec(specfile)
# Parse name
fname = specfile.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)
# Continuum
# 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.to('AA').value
#data['co'][0][:npix] = spec.co.value
# Meta
head = spec.header
speclist.append(str(fname))
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
try:
Rlist.append(Rdicts['ESI'][head['SLMSKNAM']])
except KeyError:
if row['Slit'] == 0.75:
Rlist.append(Rdicts['ESI']['0.75_arcsec'])
elif row['Slit'] == 0.5:
Rlist.append(Rdicts['ESI']['0.50_arcsec'])
else:
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(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(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/2012ApJ...755...89R',
bib='rafelski+12'),
dict(url='http://adsabs.harvard.edu/abs/2014ApJ...782L..29R',
bib='rafelski+14'),
]
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,
boss_hdf=None,
**kwargs):
""" Add BOSS data to the DB
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
boss_hdf : str, optional
Returns
-------
"""
# Add Survey
print("Adding {:s} survey to DB".format(sname))
if boss_hdf is not None:
print("Using previously generated {:s} dataset...".format(sname))
boss_hdf.copy(sname, hdf)
return
boss_grp = hdf.create_group(sname)
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 4660 # 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')
spec_set.resize((nspec, ))
wvminlist = []
wvmaxlist = []
speclist = []
npixlist = []
# Loop
maxpix = 0
bad_spec = np.array([False] * len(meta))
for jj in range(len(meta)):
# Generate full file
full_file = get_specfil(jj, meta)
if full_file == 'None':
continue
# Read
try:
spec = lsio.readspec(full_file, masking='edges')
except:
print("Failed on full_file: {:s}, {:d}".format(full_file, jj))
bad_spec[jj] = True
continue
# npix
npix = spec.npix
if npix < 10:
print("Not enough pixels in file: {:s}, {:d}".format(
full_file, jj))
bad_spec[jj] = True
continue
'''
# Kludge for higest redshift systems
if npix < 10:
full_file = get_specfil(jj, meta, hiz=True)
try:
spec = lsio.readspec(full_file)
except:
print("Missing: {:s}".format(full_file))
npix = spec.npix
elif npix > max_npix:
raise ValueError("Not enough pixels in the data... ({:d})".format(npix))
else:
maxpix = max(npix,maxpix)
'''
maxpix = max(npix, maxpix)
# Parse name
fname = full_file.split('/')[-1]
# Fill
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
'''
# GZ Continuum -- packed in with spectrum, generated by my IDL script
try:
co = spec.co.value
except AttributeError:
co = np.zeros_like(spec.flux.value)
# KG Continuum
KG_file = get_specfil(row, KG=True)
if os.path.isfile(KG_file) and (npix>1): # Latter is for junk in GZ file. Needs fixing
hduKG = fits.open(KG_file)
KGtbl = hduKG[1].data
wvKG = 10.**KGtbl['LOGLAM']
try:
assert (wvKG[0]-spec.wavelength[0].value) < 1e-5
except:
pdb.set_trace()
gdpix = np.where(wvKG < (1+row['zem_GROUP'])*1200.)[0]
co[gdpix] = KGtbl['CONT'][gdpix]
data['co'][0][:npix] = co
'''
# Meta
speclist.append(str(fname))
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
if chk_meta_only:
continue
# Only way to set the dataset correctly
spec_set[jj] = data
# Deal with null spec -- Should only be done once, saved and then ready to go
if np.any(bad_spec):
bad_meta = meta[bad_spec]
pdb.set_trace()
print("Max pix = {:d}".format(maxpix))
# Add columns
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(np.arange(nspec, dtype=int), name='GROUP_ID'))
meta.add_column(Column([2000.] * len(meta), name='EPOCH'))
# Add HDLLS meta to hdf5
if chk_meta(meta):
if chk_meta_only:
pdb.set_trace()
hdf[sname]['meta'] = meta
else:
pdb.set_trace()
raise ValueError("meta file failed")
# References
refs = [
dict(url='http://adsabs.harvard.edu/abs/2015ApJS..219...12A',
bib='boss_qso_dr12'),
]
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):
""" Add 2QZ data to the DB
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))
tqz_grp = hdf.create_group(sname)
# Checks
if sname != '2QZ':
raise IOError("Not expecting this survey..")
# Add zem
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 4000 # 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')
spec_set.resize((nspec,))
wvminlist = []
wvmaxlist = []
npixlist = []
speclist = []
# Loop
maxpix = 0
for jj,row in enumerate(meta):
full_file = get_specfil(row)
# Parse name
fname = full_file.split('/')[-1]
# Read
hdu = fits.open(full_file)
head0 = hdu[0].header
wave = lsio.setwave(head0)
flux = hdu[0].data
var = hdu[2].data
sig = np.zeros_like(flux)
gd = var > 0.
if np.sum(gd) == 0:
print("{:s} has a bad var array. Not including".format(fname))
pdb.set_trace()
continue
sig[gd] = np.sqrt(var[gd])
# npix
spec = XSpectrum1D.from_tuple((wave,flux,sig))
npix = spec.npix
spec.meta['headers'][0] = head0
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]))
npixlist.append(npix)
# 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(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(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/2004MNRAS.349.1397C',
bib='2QZ')
]
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 HSTQSO 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
-------
"""
# Add Survey
print("Adding {:s} survey to DB".format(sname))
hstz2_grp = hdf.create_group(sname)
# Checks
if sname != 'HSTQSO':
raise IOError("Not expecting this survey..")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 80000 # 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')
spec_set.resize((nspec, ))
wvminlist = []
wvmaxlist = []
npixlist = []
Rlist = []
# Loop
#path = os.getenv('RAW_IGMSPEC')+'/KODIAQ_data_20150421/'
path = os.getenv('RAW_IGMSPEC') + '/HSTQSO/'
maxpix = 0
for jj, row in enumerate(meta):
# Generate full file
full_file = path + row['SPEC_FILE'] + '.gz'
# Extract
print("HSTQSO: Reading {:s}".format(full_file))
hduf = fits.open(full_file)
head0 = hduf[0].header
spec = lsio.readspec(full_file, masking='edges')
# 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
if 'FOS-L' in fname:
Rlist.append(300.)
elif 'FOS-H' in fname:
Rlist.append(14000.)
elif 'STIS' in fname:
if row['DISPERSER'] == 'G230L':
Rlist.append(700.)
elif row['DISPERSER'] == 'G140L':
Rlist.append(1200.)
else:
raise ValueError("Bad STIS grating")
elif 'hsla' in fname: # COS
Rlist.append(18000.)
row['DATE-OBS'] = hduf[1].data['DATEOBS'][0][0]
else:
pdb.set_trace()
raise ValueError("Missing instrument!")
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
if chk_meta_only:
continue
# Only way to set the dataset correctly
spec_set[jj] = data
#
print("Max pix = {:d}".format(maxpix))
# Add columns
meta.add_column(Column([2000.] * nspec, name='EPOCH'))
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(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/2011ApJ...736...42R',
bib='ribuado11'),
dict(url='http://adsabs.harvard.edu/abs/2016ApJ...818..113N',
bib='neeleman16'),
]
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):
""" Append ESI 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
-------
"""
from specdb import defs
# Add Survey
print("Adding {:s} survey to DB".format(sname))
esidla_grp = hdf.create_group(sname)
# Load up
Rdicts = defs.get_res_dicts()
# Checks
if sname != 'ESI_DLA':
raise IOError("Expecting ESI_DLA!!")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 50000 # 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')
spec_set.resize((nspec, ))
Rlist = []
wvminlist = []
wvmaxlist = []
npixlist = []
speclist = []
# Loop
maxpix = 0
for jj, row in enumerate(meta):
#
specfile = os.getenv(
'RAW_IGMSPEC') + '/HighzESIDLA/{:s}a_xF.fits'.format(row['Name'])
print("ESI_DLA: Reading {:s}".format(specfile))
spec = lsio.readspec(specfile)
# Parse name
fname = specfile.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)
# Continuum
# 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.to('AA').value
#data['co'][0][:npix] = spec.co.value
# Meta
head = spec.header
speclist.append(str(fname))
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
try:
Rlist.append(Rdicts['ESI'][head['SLMSKNAM']])
except KeyError:
if row['Slit'] == 0.75:
Rlist.append(Rdicts['ESI']['0.75_arcsec'])
elif row['Slit'] == 0.5:
Rlist.append(Rdicts['ESI']['0.50_arcsec'])
else:
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(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(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/2012ApJ...755...89R',
bib='rafelski+12'),
dict(url='http://adsabs.harvard.edu/abs/2014ApJ...782L..29R',
bib='rafelski+14'),
]
jrefs = ltu.jsonify(refs)
hdf[sname]['meta'].attrs['Refs'] = json.dumps(jrefs)
#
return
def hdf5_adddata(hdf,
sname,
musodla_meta,
debug=False,
chk_meta_only=False,
mk_test_file=False):
""" Append MUSoDLA 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.build.utils import chk_meta
# Add Survey
print("Adding {:s} survey to DB".format(sname))
hdlls_grp = hdf.create_group(sname)
# Checks
if sname != 'MUSoDLA':
raise IOError("Not expecting this survey..")
# Build spectra (and parse for meta)
max_npix = 230000 # 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(musodla_meta)
spec_set.resize((nspec, ))
wvminlist = []
wvmaxlist = []
npixlist = []
# Loop
for jj, row in enumerate(musodla_meta):
kk = jj
# Extract
f = os.getenv('RAW_IGMSPEC') + '/MUSoDLA/data/' + row['SPEC_FILE']
try:
spec = lsio.readspec(f, masking='edges')
except:
pdb.set_trace()
# 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
if 'MagE' in f:
if fname in ['J2122-0014_MagE.ascii', 'J0011+1446_MagE.ascii']:
data['sig'][0][:npix] = spec.sig.value # Special cases..
else:
data['sig'][0][:npix] = 1. / np.sqrt(spec.sig.value) # IVAR
else:
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)
# Only way to set the dataset correctly
if chk_meta_only:
continue
spec_set[kk] = data
# Add columns
nmeta = len(musodla_meta)
musodla_meta.add_column(Column([2000.] * nmeta, name='EPOCH'))
musodla_meta.add_column(Column(npixlist, name='NPIX'))
musodla_meta.add_column(Column(wvminlist, name='WV_MIN'))
musodla_meta.add_column(Column(wvmaxlist, name='WV_MAX'))
musodla_meta.add_column(
Column(np.arange(nmeta, dtype=int), name='GROUP_ID'))
# Add HDLLS meta to hdf5
if chk_meta(musodla_meta):
if chk_meta_only:
pdb.set_trace()
hdf[sname]['meta'] = musodla_meta
else:
raise ValueError("meta file failed")
# References
refs = [
dict(url='http://adsabs.harvard.edu/abs/2013MNRAS.435..482J',
bib='regina+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):
""" 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 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 COS-Halos 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
-------
"""
# Add Survey
print("Adding {:s} survey to DB".format(sname))
chalos_grp = hdf.create_group(sname)
# Load up
# Checks
if sname != 'COS-Halos':
raise IOError("Not expecting this survey..")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 160000 # 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')
spec_set.resize((nspec, ))
wvminlist = []
wvmaxlist = []
npixlist = []
speclist = []
# Loop
path = os.getenv('RAW_IGMSPEC') + '/COS-Halos/'
maxpix = 0
for jj, row in enumerate(meta):
# Generate full file
coord = ltu.radec_to_coord((row['RA_GROUP'], row['DEC_GROUP']))
if row['INSTR'].strip() == 'COS':
full_file = path + '/J{:s}{:s}_nbin3_coadd.fits.gz'.format(
coord.ra.to_string(unit=u.hour, sep='', pad=True)[0:4],
coord.dec.to_string(sep='', pad=True, alwayssign=True)[0:5])
else: # HIRES
full_file = path + '/HIRES/J{:s}{:s}_f.fits.gz'.format(
coord.ra.to_string(unit=u.hour, sep='', pad=True)[0:4],
coord.dec.to_string(sep='', pad=True, alwayssign=True)[0:5])
# Extract
print("COS-Halos: Reading {:s}".format(full_file))
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]))
npixlist.append(npix)
if chk_meta_only:
continue
# Only way to set the dataset correctly
spec_set[jj] = data
#
print("Max pix = {:d}".format(maxpix))
# Add columns
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(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/2013ApJ...777...59T',
bib='tumlinson+13'),
dict(url='http://adsabs.harvard.edu/abs/2013ApJS..204...17W',
bib='werk+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):
""" Add 2QZ data to the DB
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))
tqz_grp = hdf.create_group(sname)
# Checks
if sname != '2QZ':
raise IOError("Not expecting this survey..")
# Add zem
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 4000 # 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')
spec_set.resize((nspec, ))
wvminlist = []
wvmaxlist = []
npixlist = []
speclist = []
# Loop
maxpix = 0
for jj, row in enumerate(meta):
full_file = get_specfil(row)
# Parse name
fname = full_file.split('/')[-1]
# Read
hdu = fits.open(full_file)
head0 = hdu[0].header
wave = lsio.setwave(head0)
flux = hdu[0].data
var = hdu[2].data
sig = np.zeros_like(flux)
gd = var > 0.
if np.sum(gd) == 0:
print("{:s} has a bad var array. Not including".format(fname))
pdb.set_trace()
continue
sig[gd] = np.sqrt(var[gd])
# npix
spec = XSpectrum1D.from_tuple((wave, flux, sig))
npix = spec.npix
spec.meta['headers'][0] = head0
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]))
npixlist.append(npix)
# 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(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(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/2004MNRAS.349.1397C',
bib='2QZ')
]
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):
""" Append GGG data to the h5 file
Parameters
----------
hdf : hdf5 pointer
sname : str
Survey name
meta : Table
chk_meta_only : bool, optional
Only check meta file; will not write
Returns
-------
"""
# Add Survey
print("Adding {:s} survey to DB".format(sname))
_ = hdf.create_group(sname)
# Load up
if sname != 'ESI_z6':
raise IOError("Not expecting this survey..")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 30000 # Just needs to be large enough
# Init
data = init_data(max_npix, include_co=True)
spec_set = hdf[sname].create_dataset('spec',
data=data,
chunks=True,
maxshape=(None, ),
compression='gzip')
spec_set.resize((nspec, ))
Rlist = []
wvminlist = []
wvmaxlist = []
npixlist = []
speclist = []
gratinglist = []
telelist = []
dateobslist = []
instrlist = []
# Loop
maxpix = 0
for jj, row in enumerate(meta):
# Generate full file
full_file, spec = read_spec(row)
# 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
data['co'][0][:npix] = spec.co.value
# Meta
#head = spec.header
speclist.append(str(fname))
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
#telelist.append(head['OBSERVAT'])
#instrlist.append(head['INSTRUME'])
#tval = Time(head['DATE'], format='isot', out_subfmt='date')
#dateobslist.append(tval.iso)
npixlist.append(npix)
# 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(speclist, name='SPEC_FILE'))
#meta.add_column(Column(telelist, name='TELESCOPE'))
#meta.add_column(Column(instrlist, name='INSTR'))
#meta.add_column(Column(dateobslist, name='DATE-OBS'))
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(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/2014MNRAS.445.1745W',
bib='worseck+14')
]
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 HST/FUSE 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
-------
"""
Rdicts = defs.get_res_dicts()
# Add Survey
print("Adding {:s} survey to DB".format(sname))
hstc_grp = hdf.create_group(sname)
# Checks
if sname != 'UVpSM4':
raise IOError("Not expecting this survey..")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 40000 # Just needs to be large enough
# Init
data = init_data(max_npix, include_co=True)
spec_set = hdf[sname].create_dataset('spec',
data=data,
chunks=True,
maxshape=(None, ),
compression='gzip')
spec_set.resize((nspec, ))
Rlist = []
wvminlist = []
wvmaxlist = []
npixlist = []
gratinglist = []
datelist = []
badf = []
badstis = []
badghrs = []
# Loop
path = os.getenv('RAW_IGMSPEC') + '/HST_Cooksey/'
maxpix = 0
for jj, row in enumerate(meta):
# Generate full file
full_file = path + '{:s}/{:s}/{:s}'.format(row['QSO'], row['INSTR'],
row['SPEC_FILE'])
# Extract
if row['INSTR'] == 'FUSE':
hext = 1
else:
hext = 0
print("HST_Cooksey: Reading {:s}".format(full_file))
try:
spec = lsio.readspec(full_file, head_exten=hext, masking='edges')
except: # BAD HEADER
hdu = fits.open(full_file)
head1 = hdu[1].header
hdu[1].verify('fix')
tbl = Table(hdu[1].data)
spec = lsio.readspec(tbl, masking='edges')
spec.meta['headers'][spec.select] = head1
# Continuum
cfile = full_file.replace('.fits', '_c.fits')
if os.path.isfile(cfile):
# Watch that mask!
gdp = ~spec.data['flux'][spec.select].mask
spec.data['co'][spec.select][gdp] = (
fits.open(cfile)[0].data)[gdp]
# 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', 'co']:
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
if spec.co_is_set:
try:
data['co'][0][:npix] = spec.co.value
except ValueError:
pdb.set_trace()
# Meta
datet = None
if row['INSTR'] == 'FUSE':
if 'HISTORY' in spec.header.keys():
ncards = len(spec.header['HISTORY'])
flg_H = True
else:
flg_H = False
hdu = fits.open(full_file)
head0 = hdu[0].header
ncards = len(head0)
# Is this a good one?
if 'APER_ACT' in head0:
pass
else: # Need to fight harder for the header
# Look for untrim
untrim = full_file + '.untrim'
if not os.path.isfile(untrim):
pdb.set_trace()
# Read
hduu = fits.open(untrim)
if 'PKS2005' in untrim: # One extra kludge..
head0 = hduu[1].header
flg_H = True
ncards = len(head0['HISTORY'])
else:
head0 = hduu[0].header
ncards = len(head0)
spec.meta['headers'][spec.select] = head0
# Read from history
for ss in range(ncards):
if flg_H:
try:
card = Header.fromstring(spec.header['HISTORY'][ss])
except:
pdb.set_trace()
try:
ckey = list(card.keys())[0]
except IndexError:
continue
else:
card0 = card[0]
else:
ckey, card0 = list(spec.header.keys())[ss], spec.header[ss]
# Parse
if ckey == 'APERTURE':
aper = card0
elif ckey == 'DETECTOR':
det = card0
elif ckey == 'APER_ACT': # Extracted aperture
ext_ap = card0
elif ckey == 'DATE': # Extracted aperture
datet = card0
gratinglist.append(ext_ap + det)
elif row['INSTR'] == 'STIS':
try:
datet = spec.header['DATE']
except KeyError: # handful of kludged coadds
if 'HISTORY' not in spec.header.keys():
# Grab from the other extension, e.g. PKS0405
hdu = fits.open(full_file)
head1 = hdu[1].header
spec.meta['headers'][0] = head1
for ihist in spec.header['HISTORY']:
if 'TDATEOBS' in ihist:
idash = ihist.find('-')
datet = ihist[idash - 4:idash + 6]
# Grating from name
i0 = full_file.rfind('_')
i1 = full_file.rfind('.fits')
gratinglist.append(full_file[i0 + 1:i1])
if datet is None:
pdb.set_trace()
else:
gratinglist.append(spec.header['OPT_ELEM'])
elif row['INSTR'] == 'GHRS':
# Date
try:
tmp = spec.header['DATE-OBS']
except KeyError:
# Pull header from parallel file
iM = full_file.find('M_1')
if iM <= 0:
iM = full_file.find('L_1')
ofile = full_file[:iM + 1] + '_F.fits'
if not os.path.isfile(ofile):
if 'NGC4151' in ofile: # Kludge
ofile = ofile.replace('G160M', 'G160Mmd')
elif 'PKS2155-304_GHRS_G140L' in ofile: # Kludge
ofile = ofile.replace('G140L', 'G140Llo')
elif 'PKS2155-304_GHRS_G160M' in ofile: # Kludge
ofile = ofile.replace('G160M', 'G160Mmd')
else:
pdb.set_trace()
hdu = fits.open(ofile)
head0 = hdu[0].header
spec.meta['headers'][spec.select] = head0
# Reformat
prs = tmp.split('/')
if prs[2][0] == '9':
yr = '19' + prs[2]
else:
yr = '20' + prs[2]
datet = yr + '-' + prs[1] + '-{:02d}'.format(int(prs[0]))
# Grating
gratinglist.append(spec.header['GRATING'])
else:
pdb.set_trace()
if datet is None:
try:
datet = spec.header['DATE-OBS']
except KeyError:
print("Missing Header for file: {:s}".format(full_file))
badf.append(full_file)
datet = '9999-9-9'
t = Time(datet, format='isot',
out_subfmt='date') # Fixes to YYYY-MM-DD
datelist.append(t.iso)
try:
Rlist.append(Rdicts[row['INSTR']][gratinglist[-1]])
except KeyError:
print(gratinglist[-1])
pdb.set_trace()
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
if chk_meta_only:
continue
# Only way to set the dataset correctly
spec_set[jj] = data
#
if (len(badstis)) > 0:
raise ValueError("Somehow have a bad STIS header..")
if len(badf) > 0:
print("We still have bad FUSE headers")
pdb.set_trace()
if len(badghrs) > 0:
print("We still have bad GHRS headers")
pdb.set_trace()
print("Max pix = {:d}".format(maxpix))
# Add columns
meta.add_column(Column(npixlist, name='NPIX'))
meta.add_column(Column(wvminlist, name='WV_MIN'))
meta.add_column(Column(Rlist, name='R'))
meta.add_column(Column(gratinglist, name='DISPERSER'))
meta.add_column(Column(wvmaxlist, name='WV_MAX'))
meta.add_column(Column(datelist, name='DATE-OBS'))
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:
pdb.set_trace()
raise ValueError("meta file failed")
# References
refs = [
dict(url='http://adsabs.harvard.edu/abs/2010ApJ...708..868C',
bib='cooksey10')
]
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 COS-Halos 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
-------
"""
# Add Survey
print("Adding {:s} survey to DB".format(sname))
chalos_grp = hdf.create_group(sname)
# Load up
# Checks
if sname != 'COS-Halos':
raise IOError("Not expecting this survey..")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 160000 # 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')
spec_set.resize((nspec,))
wvminlist = []
wvmaxlist = []
npixlist = []
speclist = []
# Loop
path = os.getenv('RAW_IGMSPEC')+'/COS-Halos/'
maxpix = 0
for jj,row in enumerate(meta):
# Generate full file
coord = ltu.radec_to_coord((row['RA_GROUP'],row['DEC_GROUP']))
if row['INSTR'].strip() == 'COS':
full_file = path+'/J{:s}{:s}_nbin3_coadd.fits.gz'.format(coord.ra.to_string(unit=u.hour,sep='',pad=True)[0:4],
coord.dec.to_string(sep='',pad=True,alwayssign=True)[0:5])
else: # HIRES
full_file = path+'/HIRES/J{:s}{:s}_f.fits.gz'.format(coord.ra.to_string(unit=u.hour,sep='',pad=True)[0:4], coord.dec.to_string(sep='',pad=True,alwayssign=True)[0:5])
# Extract
print("COS-Halos: Reading {:s}".format(full_file))
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]))
npixlist.append(npix)
if chk_meta_only:
continue
# Only way to set the dataset correctly
spec_set[jj] = data
#
print("Max pix = {:d}".format(maxpix))
# Add columns
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(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/2013ApJ...777...59T',
bib='tumlinson+13'),
dict(url='http://adsabs.harvard.edu/abs/2013ApJS..204...17W',
bib='werk+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):
""" Append UVES_Dall 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
-------
"""
from specdb import defs
# Add Survey
print("Adding {:s} survey to DB".format(sname))
uvesdall_grp = hdf.create_group(sname)
# Load up
Rdicts = defs.get_res_dicts()
# Checks
if sname != 'UVES_Dall':
raise IOError("Expecting UVES_Dall!!")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 150000 # Just needs to be large enough
data = init_data(max_npix, include_co=True)
# Init
spec_set = hdf[sname].create_dataset('spec', data=data, chunks=True,
maxshape=(None,), compression='gzip')
spec_set.resize((nspec,))
wvminlist, wvmaxlist, npixlist, speclist = [], [], [], []
# Loop
maxpix = 0
for jj,row in enumerate(meta):
# Read
specfile = os.getenv('RAW_IGMSPEC')+'/UVES_Dall/{:s}_flux.dat'.format(row['NAME'])
print("UVES_Dall: Reading {:s}".format(specfile))
spec = Table.read(specfile,format='ascii.fast_no_header',guess=False)#, data_start=1)
# Parse name
fname = specfile.split('/')[-1]
# npix
npix = len(spec['col1'])
if npix > max_npix:
raise ValueError("Not enough pixels in the data... ({:d})".format(npix))
else:
maxpix = max(npix,maxpix)
# Continuum
# Some fiddling about
for key in ['wave','flux','sig','co']:
data[key] = 0. # Important to init (for compression too)
data['flux'][0][:npix] = spec['col2']
data['sig'][0][:npix] = spec['col3']
data['wave'][0][:npix] = spec['col1']
data['co'][0][:npix] = spec['col4']
# Meta
speclist.append(str(fname))
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
# 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(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(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/2008A%26A...491..465D',
bib='dallaglio+08'),
]
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):
""" Append XQ-100 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))
xq100_grp = hdf.create_group(sname)
if len(meta) != 300:
pdb.set_trace()
# Checks
if sname != 'XQ-100':
raise IOError("Expecting XQ-100!!")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 20000 # Just needs to be large enough
data = init_data(max_npix, include_co=True)
# Init
spec_set = hdf[sname].create_dataset('spec', data=data, chunks=True,
maxshape=(None,), compression='gzip')
spec_set.resize((nspec,))
Rlist = []
wvminlist = []
wvmaxlist = []
npixlist = []
speclist = []
gratinglist = []
telelist = []
instrlist = []
# Loop
maxpix = 0
for jj,row in enumerate(meta):
#
print("XQ-100: Reading {:s}".format(row['SPEC_FILE']))
spec = lsio.readspec(row['SPEC_FILE'])
# Parse name
fname = row['SPEC_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)
# Continuum
# 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.to('AA').value
data['co'][0][:npix] = spec.co.value
# Meta
head = spec.header
speclist.append(str(fname))
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
telelist.append(head['TELESCOP'])
instrlist.append(head['INSTRUME'])
gratinglist.append(head['DISPELEM'])
npixlist.append(npix)
if gratinglist[-1] == 'NIR': # From Lopez+16
Rlist.append(4350.)
elif gratinglist[-1] == 'VIS':
Rlist.append(7450.)
elif gratinglist[-1] == 'UVB':
Rlist.append(5300.)
else:
pdb.set_trace()
raise ValueError("UH OH")
# 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(gratinglist, name='DISPERSER'))
meta.add_column(Column(telelist, name='TELESCOPE'))
meta.add_column(Column(instrlist, name='INSTR'))
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(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/2016arXiv160708776L',
bib='lopez+16')]
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):
""" Append GGG data to the h5 file
Parameters
----------
hdf : hdf5 pointer
sname : str
Survey name
meta : Table
chk_meta_only : bool, optional
Only check meta file; will not write
Returns
-------
"""
# Add Survey
print("Adding {:s} survey to DB".format(sname))
ggg_grp = hdf.create_group(sname)
# Load up
if sname != 'GGG':
raise IOError("Not expecting this survey..")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 1600 # 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,))
Rlist = []
wvminlist = []
wvmaxlist = []
npixlist = []
speclist = []
gratinglist = []
telelist = []
dateobslist = []
instrlist = []
# Loop
path = os.getenv('RAW_IGMSPEC')+'/GGG/'
maxpix = 0
for jj,row in enumerate(meta):
# Generate full file
if jj >= nspec//2:
full_file = path+row['name']+'_R400.fits.gz'
gratinglist.append('R400')
else:
full_file = path+row['name']+'_B600.fits.gz'
gratinglist.append('B600')
# Extract
print("GGG: Reading {:s}".format(full_file))
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
head = spec.header
speclist.append(str(fname))
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
telelist.append(head['OBSERVAT'])
instrlist.append(head['INSTRUME'])
tval = Time(head['DATE'], format='isot', out_subfmt='date')
dateobslist.append(tval.iso)
npixlist.append(npix)
if 'R400' in fname:
Rlist.append(833.)
else:
Rlist.append(940.)
# 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(speclist, name='SPEC_FILE'))
meta.add_column(Column(gratinglist, name='GRATING'))
meta.add_column(Column(telelist, name='TELESCOPE'))
meta.add_column(Column(instrlist, name='INSTR'))
meta.add_column(Column(dateobslist, name='DATE-OBS'))
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(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/2014MNRAS.445.1745W',
bib='worseck+14')]
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 HSTQSO 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
-------
"""
# Add Survey
print("Adding {:s} survey to DB".format(sname))
hstz2_grp = hdf.create_group(sname)
# Checks
if sname != 'HSTQSO':
raise IOError("Not expecting this survey..")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 80000 # 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')
spec_set.resize((nspec,))
wvminlist = []
wvmaxlist = []
npixlist = []
Rlist = []
# Loop
#path = os.getenv('RAW_IGMSPEC')+'/KODIAQ_data_20150421/'
path = os.getenv('RAW_IGMSPEC')+'/HSTQSO/'
maxpix = 0
for jj,row in enumerate(meta):
# Generate full file
full_file = path+row['SPEC_FILE']+'.gz'
# Extract
print("HSTQSO: Reading {:s}".format(full_file))
hduf = fits.open(full_file)
head0 = hduf[0].header
spec = lsio.readspec(full_file, masking='edges')
# 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
if 'FOS-L' in fname:
Rlist.append(300.)
elif 'FOS-H' in fname:
Rlist.append(14000.)
elif 'STIS' in fname:
if row['DISPERSER'] == 'G230L':
Rlist.append(700.)
elif row['DISPERSER'] == 'G140L':
Rlist.append(1200.)
else:
raise ValueError("Bad STIS grating")
elif 'hsla' in fname: # COS
Rlist.append(18000.)
row['DATE-OBS'] = hduf[1].data['DATEOBS'][0][0]
else:
pdb.set_trace()
raise ValueError("Missing instrument!")
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
if chk_meta_only:
continue
# Only way to set the dataset correctly
spec_set[jj] = data
#
print("Max pix = {:d}".format(maxpix))
# Add columns
meta.add_column(Column([2000.]*nspec, name='EPOCH'))
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(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/2011ApJ...736...42R',
bib='ribuado11'),
dict(url='http://adsabs.harvard.edu/abs/2016ApJ...818..113N',
bib='neeleman16'),
]
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):
""" Append UVES_Dall 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
-------
"""
from specdb import defs
# Add Survey
print("Adding {:s} survey to DB".format(sname))
uvesdall_grp = hdf.create_group(sname)
# Load up
Rdicts = defs.get_res_dicts()
# Checks
if sname != 'UVES_Dall':
raise IOError("Expecting UVES_Dall!!")
# Build spectra (and parse for meta)
nspec = len(meta)
max_npix = 150000 # Just needs to be large enough
data = init_data(max_npix, include_co=True)
# Init
spec_set = hdf[sname].create_dataset('spec',
data=data,
chunks=True,
maxshape=(None, ),
compression='gzip')
spec_set.resize((nspec, ))
wvminlist, wvmaxlist, npixlist, speclist = [], [], [], []
# Loop
maxpix = 0
for jj, row in enumerate(meta):
# Read
specfile = os.getenv(
'RAW_IGMSPEC') + '/UVES_Dall/{:s}_flux.dat'.format(row['NAME'])
print("UVES_Dall: Reading {:s}".format(specfile))
spec = Table.read(specfile, format='ascii.fast_no_header',
guess=False) #, data_start=1)
# Parse name
fname = specfile.split('/')[-1]
# npix
npix = len(spec['col1'])
if npix > max_npix:
raise ValueError(
"Not enough pixels in the data... ({:d})".format(npix))
else:
maxpix = max(npix, maxpix)
# Continuum
# Some fiddling about
for key in ['wave', 'flux', 'sig', 'co']:
data[key] = 0. # Important to init (for compression too)
data['flux'][0][:npix] = spec['col2']
data['sig'][0][:npix] = spec['col3']
data['wave'][0][:npix] = spec['col1']
data['co'][0][:npix] = spec['col4']
# Meta
speclist.append(str(fname))
wvminlist.append(np.min(data['wave'][0][:npix]))
wvmaxlist.append(np.max(data['wave'][0][:npix]))
npixlist.append(npix)
# 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(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(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/2008A%26A...491..465D',
bib='dallaglio+08'),
]
jrefs = ltu.jsonify(refs)
hdf[sname]['meta'].attrs['Refs'] = json.dumps(jrefs)
#
return
