def sdss_redshifts():
"""
Enter the directory and build a redshift table
based on the spectra present
Returns:
"""
embed(header='THIS NEEDS HELP')
#
all_folders = glob.glob(db_path + '/SDSS/*')
for folder in all_folders:
Jnames = []
# Grab the list of spectra files
spec_files = glob.glob(os.path.join(folder, 'J*_spec.fits'))
# Generate the name list
Jnames += [
os.path.basename(ifile).split('_')[0] for ifile in spec_files
]
# Coords
coords = SkyCoord(Jnames,
unit=(units.hourangle, units.deg)) # from DES
# Setup
done = np.zeros_like(coords.ra.value, dtype=bool)
zs = np.zeros_like(coords.ra.value)
# Loop me
while np.any(~done):
# Grab the first not done
i0 = np.where(~done)[0][0]
coord = coords[i0]
# Grab the SDSS data
sdssSurvey = sdss.SDSS_Survey(coord, 10 * units.arcmin)
#
sub_coords = coords[~done]
sep = coord.separation(sub_coords)
doidx = np.where(sep < 10 * units.arcmin)[0]
dothem = coords[doidx]
# Now match
catalog = sdssSurvey.get_catalog()
sdss_coords = SkyCoord(ra=catalog['ra'],
dec=catalog['dec'],
unit='deg')
idx, d2d, d3d = match_coordinates_sky(dothem,
sdss_coords,
nthneighbor=1)
# Fill
zs[doidx] = catalog['z_spec'][idx]
done[np.where(dothem)] = True
# Write the catalog
tbl = Table()
tbl['RA'] = coords.ra.value
tbl['DEC'] = coords.dec.value
tbl['ZEM'] = zs
tbl['ZEM_SOURCE'] = 'SDSS'
tbl['ZQ'] = 4
tbl.write(os.path.join(folder, 'z_SDSS.ascii'),
overwrite=True,
format='ascii.fixed_width')
def build_host_180916(run_ppxf=False, build_photom=False, build_cigale=False):
""" Build the host galaxy data for FRB 180916
All of the data currently comes from Marcote et al. 2020
https://ui.adsabs.harvard.edu/abs/2020Natur.577..190M/abstract
CIGALE will be published in Kasper et al. 2020
Args:
build_photom (bool, optional):
"""
frbname = '180916'
gal_coord = SkyCoord('J015800.28+654253.0',
unit=(units.hourangle, units.deg))
# Instantiate
host180916 = frbgalaxy.FRBHost(gal_coord.ra.value, gal_coord.dec.value,
frbname)
# Load redshift table
#ztbl = Table.read(os.path.join(db_path, 'CRAFT', 'Bhandari2019', 'z_SDSS.ascii'),
# format='ascii.fixed_width')
#z_coord = SkyCoord(ra=ztbl['RA'], dec=ztbl['DEC'], unit='deg')
#idx, d2d, _ = match_coordinates_sky(gal_coord, z_coord, nthneighbor=1)
#if np.min(d2d) > 0.5*units.arcsec:
# embed(header='190608')
# Redshift -- SDSS
#host180916.set_z(ztbl[idx]['ZEM'], 'spec')
# Redshift
host180916.set_z(0.0337, 'spec')
# Morphology
#host190608.parse_galfit(os.path.join(photom_path, 'CRAFT', 'Bannister2019',
# 'HG180924_galfit_DES.log'), 0.263)
# Photometry
EBV = nebular.get_ebv(gal_coord)['meanValue'] #
print("EBV={} for the host of {}".format(EBV, frbname))
# SDSS
# Grab the table (requires internet)
photom_file = os.path.join(db_path, 'CHIME', 'Marcote2020',
'marcote2020_photom.ascii')
if build_photom:
# SDSS
search_r = 1 * units.arcsec
sdss_srvy = sdss.SDSS_Survey(gal_coord, search_r)
sdss_tbl = sdss_srvy.get_catalog(print_query=True)
sdss_tbl['Name'] = host180916.name
photom = frbphotom.merge_photom_tables(sdss_tbl, photom_file)
# WISE
wise_srvy = wise.WISE_Survey(gal_coord, search_r)
wise_tbl = wise_srvy.get_catalog(print_query=True)
wise_tbl['Name'] = host180916.name
photom = frbphotom.merge_photom_tables(wise_tbl, photom, debug=True)
# Write
photom.write(photom_file,
format=frbphotom.table_format,
overwrite=True)
# Parse
photom = Table.read(photom_file, format=frbphotom.table_format)
# Dust correction
frbphotom.correct_photom_table(photom, EBV)
# Parse
host180916.parse_photom(photom)
# CIGALE
cigale_file = os.path.join(db_path, 'CHIME', 'Marcote2020',
'HG180619_CIGALE.fits')
if build_cigale:
cut_photom = photom.copy()
# Remove WISE
#for column in cut_photom.keys():
# if 'WISE' in column:
# cut_photom.remove_column(column)
# Run
cigale.host_run(cut_photom, host180916, cigale_file=cigale_file)
host180916.parse_cigale(cigale_file)
# PPXF
#results_file = os.path.join(db_path, 'CRAFT', 'Bhandari2019', 'HG190608_SDSS_ppxf.ecsv')
#if run_ppxf:
# meta, spectrum = host190608.get_metaspec(instr='SDSS')
# spec_fit = None
# ppxf.run(spectrum, 2000., host190608.z, results_file=results_file, spec_fit=spec_fit, chk=True)
#host190608.parse_ppxf(results_file)
# Derived quantities
# AV
#host190608.calc_nebular_AV('Ha/Hb')
# SFR
#host190608.calc_nebular_SFR('Ha')
#host.derived['SFR_nebular_err'] = -999.
# Vet all
host180916.vet_all()
# Write -- BUT DO NOT ADD TO REPO (YET)
path = resource_filename('frb', 'data/Galaxies/{}'.format(frbname))
host180916.write_to_json(path=path)
def build_host_190608(run_ppxf=False, build_photom=False):
""" Build the host galaxy data for FRB 190608
All of the data comes from Bhandrari+2020, ApJL, in press
Args:
build_photom (bool, optional):
"""
frbname = '190608'
gal_coord = SkyCoord('J221604.90-075356.0',
unit=(units.hourangle,
units.deg)) # Cherie; 07-Mar-2019
# Instantiate
host190608 = frbgalaxy.FRBHost(gal_coord.ra.value, gal_coord.dec.value,
frbname)
# Load redshift table
ztbl = Table.read(os.path.join(db_path, 'CRAFT', 'Bhandari2019',
'z_SDSS.ascii'),
format='ascii.fixed_width')
z_coord = SkyCoord(ra=ztbl['RA'], dec=ztbl['DEC'], unit='deg')
idx, d2d, _ = match_coordinates_sky(gal_coord, z_coord, nthneighbor=1)
if np.min(d2d) > 0.5 * units.arcsec:
embed(header='190608')
# Redshift -- SDSS
host190608.set_z(ztbl[idx]['ZEM'], 'spec')
# Morphology
#host190608.parse_galfit(os.path.join(photom_path, 'CRAFT', 'Bannister2019',
# 'HG180924_galfit_DES.log'), 0.263)
# Photometry
# SDSS
# Grab the table (requires internet)
photom_file = os.path.join(db_path, 'CRAFT', 'Bhandari2019',
'bhandari2019_photom.ascii')
if build_photom:
# VLT
search_r = 1 * units.arcsec
# SDSS
sdss_srvy = sdss.SDSS_Survey(gal_coord, search_r)
sdss_tbl = sdss_srvy.get_catalog(print_query=True)
sdss_tbl['Name'] = 'HG190608'
photom = frbphotom.merge_photom_tables(sdss_tbl, photom_file)
# WISE
wise_srvy = wise.WISE_Survey(gal_coord, search_r)
wise_tbl = wise_srvy.get_catalog(print_query=True)
wise_tbl['Name'] = 'HG190608'
# Write
photom = frbphotom.merge_photom_tables(wise_tbl, photom, debug=True)
photom.write(photom_file,
format=frbphotom.table_format,
overwrite=True)
# Parse
host190608.parse_photom(
Table.read(photom_file, format=frbphotom.table_format))
# PPXF
results_file = os.path.join(db_path, 'CRAFT', 'Bhandari2019',
'HG190608_SDSS_ppxf.ecsv')
if run_ppxf:
meta, spectrum = host190608.get_metaspec(instr='SDSS')
spec_fit = None
ppxf.run(spectrum,
2000.,
host190608.z,
results_file=results_file,
spec_fit=spec_fit,
chk=True)
host190608.parse_ppxf(results_file)
# Derived quantities
# AV
host190608.calc_nebular_AV('Ha/Hb')
# SFR
host190608.calc_nebular_SFR('Ha')
#host.derived['SFR_nebular_err'] = -999.
# CIGALE
host190608.parse_cigale(
os.path.join(db_path, 'CRAFT', 'Bhandari2019', 'HG190608_CIGALE.fits'))
# Vet all
host190608.vet_all()
# Write
path = resource_filename('frb', 'data/Galaxies/{}'.format(frbname))
host190608.write_to_json(path=path)