def ned_query(ra, dec):
# getting skycoordinate object
co = coordinates.SkyCoord(ra=ra,
dec=dec,
unit=(u.deg, u.deg),
frame='icrs')
search_radius = 0.01 * u.deg
# this search radius is smaller than Fermi LAT resolution (please check)
# get table with all objects inside the search radius
result_table = Ned.query_region(co,
radius=search_radius,
equinox='J2000.0')
result_table = Ned.query_object("NGC 224")
print('names of the columns are ', result_table.colnames)
print('to get an impression, here the whole table:')
print(result_table)
# get all the object names to get speific data
object_names = result_table['Object Name']
print('identified objects = ', object_names)
# get table with positions of the first object as an example:
position_table = Ned.get_table(object_names[0], table='positions')
# position table is something you normally don't need but might be interesting
# This should always work'
# print('position table: ', position_table)
spectra = Ned.get_spectra("3c 273")
return result_table, spectra
def getNEDSpectra(df, path, verbose=0):
hostNames = np.array(df.dropna(subset=['NED_name'])['NED_name'])
transientNames = np.array(df.dropna(subset=['NED_name'])['TransientName'])
for j in np.arange(len(hostNames)):
try:
spectra = Ned.get_spectra(hostNames[j])
except:
continue
if spectra:
for i in np.arange(len(spectra)):
fn = re.sub(r"^\s+", "", hostNames[j])
a = find_all("%s_%.02i.fits" % (fn, i), path)
sp = spectra[i]
if not a:
if verbose:
print("Saving spectrum %i for %s, host of %s." %
(i, hostNames[j], transientNames[j]))
try:
sp.writeto(path + "/%s_%.02i.fits" % (fn, i),
output_verify='ignore')
except:
if verbose:
print("Error in saving host spectrum for %s." %
transientNames[j])
elif verbose:
# if verbose:
print("host spectrum for %s already downloaded!" %
transientNames[j])
def load_spectra(self):
"""Load reference spectra from Pysynphot database or NED database.
If the object redshift is >0.2, the LAMBDA_MIN and LAMBDA_MAX parameters
are redshifted accordingly.
Examples
--------
>>> s = Star('3C273')
>>> print(s.spectra[0][:4])
[0.0000000e+00 2.5048577e-14 2.4238061e-14 2.4088789e-14]
>>> s = Star('HD111980')
>>> print(s.spectra[0][:4])
[2.16890002e-13 2.66480010e-13 2.03540011e-13 2.38780004e-13]
>>> s = Star('PKS1510-089')
>>> print(s.redshift)
0.36
>>> print(f'{parameters.LAMBDA_MIN:.1f}, {parameters.LAMBDA_MAX:.1f}')
408.0, 1496.0
>>> print(s.spectra[0][:4])
[117.34012 139.27621 87.38032 143.0816 ]
"""
self.wavelengths = [] # in nm
self.spectra = []
# first try with pysynphot
file_names = []
is_calspec = False
if os.getenv("PYSYN_CDBS") is not None:
dirname = os.path.expandvars('$PYSYN_CDBS/calspec/')
for fname in os.listdir(dirname):
if os.path.isfile(os.path.join(dirname, fname)):
if self.label.lower().replace(' ', '') in fname.lower():
file_names.append(os.path.join(dirname, fname))
if len(file_names) > 0:
is_calspec = True
self.emission_spectrum = False
self.hydrogen_only = False
self.lines = Lines(HYDROGEN_LINES + ATMOSPHERIC_LINES +
STELLAR_LINES,
redshift=self.redshift,
emission_spectrum=self.emission_spectrum,
hydrogen_only=self.hydrogen_only)
for k, f in enumerate(file_names):
if '_mod_' in f:
continue
if self.verbose:
self.my_logger.info('\n\tLoading %s' % f)
data = S.FileSpectrum(f, keepneg=True)
if isinstance(data.waveunits, S.units.Angstrom):
self.wavelengths.append(data.wave / 10.)
self.spectra.append(data.flux * 10.)
else:
self.wavelengths.append(data.wave)
self.spectra.append(data.flux)
# TODO DM-33731: the use of self.label in parameters.STAR_NAMES:
# below works for running but breaks a test so needs fixing for DM
elif 'HD' in self.label: # or self.label in parameters.STAR_NAMES: # it is a star
self.emission_spectrum = False
self.hydrogen_only = False
self.lines = Lines(ATMOSPHERIC_LINES + HYDROGEN_LINES +
STELLAR_LINES,
redshift=self.redshift,
emission_spectrum=self.emission_spectrum,
hydrogen_only=self.hydrogen_only)
elif 'PNG' in self.label:
self.emission_spectrum = True
self.lines = Lines(ATMOSPHERIC_LINES + ISM_LINES + HYDROGEN_LINES,
redshift=self.redshift,
emission_spectrum=self.emission_spectrum,
hydrogen_only=self.hydrogen_only)
else: # maybe a quasar, try with NED query
from astroquery.ned import Ned
hdulists = Ned.get_spectra(self.label, show_progress=False)
if len(hdulists) > 0:
self.emission_spectrum = True
self.hydrogen_only = False
if self.redshift > 0.2:
self.hydrogen_only = True
parameters.LAMBDA_MIN *= 1 + self.redshift
parameters.LAMBDA_MAX *= 1 + self.redshift
self.lines = Lines(ATMOSPHERIC_LINES + ISM_LINES +
HYDROGEN_LINES,
redshift=self.redshift,
emission_spectrum=self.emission_spectrum,
hydrogen_only=self.hydrogen_only)
for k, h in enumerate(hdulists):
if h[0].header['NAXIS'] == 1:
self.spectra.append(h[0].data)
else:
for d in h[0].data:
self.spectra.append(d)
wave_n = len(h[0].data)
if h[0].header['NAXIS'] == 2:
wave_n = len(h[0].data.T)
wave_step = h[0].header['CDELT1']
wave_start = h[0].header['CRVAL1'] - (
h[0].header['CRPIX1'] - 1) * wave_step
wave_end = wave_start + wave_n * wave_step
waves = np.linspace(wave_start, wave_end, wave_n)
is_angstrom = False
for key in list(h[0].header.keys()):
if 'angstrom' in str(h[0].header[key]).lower():
is_angstrom = True
if is_angstrom:
waves *= 0.1
if h[0].header['NAXIS'] > 1:
for i in range(h[0].header['NAXIS'] + 1):
self.wavelengths.append(waves)
else:
self.wavelengths.append(waves)
self.build_sed()
self.my_logger.debug(
f"\n\tTarget label: {self.label}"
f"\n\tCalspec? {is_calspec}"
f"\n\tNumber of spectra: {len(self.spectra)}"
f"\n\tRedshift: {self.redshift}"
f"\n\tEmission spectrum ? {self.emission_spectrum}"
f"\n\tLines: {[l.label for l in self.lines.lines]}")
def load_spectra(self):
self.wavelengths = [] # in nm
self.spectra = []
# first try with pysynphot
file_names = []
if os.getenv("PYSYN_CDBS") is not None:
dirname = os.path.expandvars('$PYSYN_CDBS/calspec/')
for fname in os.listdir(dirname):
if os.path.isfile(dirname + fname):
if self.label.lower() in fname.lower():
file_names.append(dirname + fname)
if len(file_names) > 0:
self.emission_spectrum = False
self.hydrogen_only = True
for k, f in enumerate(file_names):
if '_mod_' in f:
continue
if self.verbose:
print 'Loading %s' % f
data = S.FileSpectrum(f, keepneg=True)
if isinstance(data.waveunits, S.units.Angstrom):
self.wavelengths.append(data.wave / 10.)
self.spectra.append(data.flux * 10.)
else:
self.wavelengths.append(data.wave)
self.spectra.append(data.flux)
else:
if 'PNG' not in self.label:
# Try with NED query
# print 'Loading target %s from NED...' % self.label
ned = Ned.query_object(self.label)
hdulists = Ned.get_spectra(self.label)
self.redshift = ned['Redshift'][0]
self.emission_spectrum = True
self.hydrogen_only = False
if self.redshift > 0.2:
self.hydrogen_only = True
parameters.LAMBDA_MIN *= 1 + self.redshift
parameters.LAMBDA_MAX *= 1 + self.redshift
for k, h in enumerate(hdulists):
if h[0].header['NAXIS'] == 1:
self.spectra.append(h[0].data)
else:
for d in h[0].data:
self.spectra.append(d)
wave_n = len(h[0].data)
if h[0].header['NAXIS'] == 2:
wave_n = len(h[0].data.T)
wave_step = h[0].header['CDELT1']
wave_start = h[0].header['CRVAL1'] - (
h[0].header['CRPIX1'] - 1) * wave_step
wave_end = wave_start + wave_n * wave_step
waves = np.linspace(wave_start, wave_end, wave_n)
is_angstrom = False
for key in h[0].header.keys():
if 'angstrom' in str(h[0].header[key]).lower():
is_angstrom = True
if is_angstrom:
waves *= 0.1
if h[0].header['NAXIS'] > 1:
for i in range(h[0].header['NAXIS'] + 1):
self.wavelengths.append(waves)
else:
self.wavelengths.append(waves)
else:
self.emission_spectrum = True
self.build_sed()
def test6():
spectra = Ned.get_spectra("3c 273")
print spectra
