def GetStarData(starname):
"""
Return a dictionary with the SimBad data for a given star.
"""
link = sim.buildLink(starname)
star = sim.simbad(link)
return star
def classify_file(filename, astroquery=True):
"""
This function uses the fits header information and the Simbad database to classify the object
:param filename: The filename of the observation to be classified
:return:
"""
# Read in the header and get the object name
header = fits.getheader(filename)
object = header['object']
print object
# Default values
plx = 30.0
# Make a Simbad object
if astroquery:
sim = Simbad()
sim.add_votable_fields('plx', 'sp')
data = sim.query_object(object)
plx = data['PLX_VALUE'].item()
spt_full = data['SP_TYPE'].item()
spt = spt_full[0] + re.search(r'\d*\.?\d*', spt_full[1:]).group()
else:
link = pySIMBAD.buildLink(object)
data = pySIMBAD.simbad(link)
plx = data.Parallax()
spt_full = data.SpectralType().split()[0]
spt = spt_full[0] + re.search(r'\d*\.?\d*', spt_full[1:]).group()
d = {'Object': object,
'plx': plx,
'SpT': spt,
'exptime': header['exptime']}
return d
def classify_file(filename, astroquery=True):
"""
This function uses the fits header information and the Simbad database to classify the object
:param filename: The filename of the observation to be classified
:return:
"""
# Read in the header and get the object name
header = fits.getheader(filename)
object = header['object']
print object
# Default values if I can't get it any other way
plx = 30.0
MS = SpectralTypeRelations.MainSequence()
# Make a Simbad object
if astroquery:
sim = Simbad()
sim.add_votable_fields('plx', 'sp', 'flux(V)')
data = sim.query_object(object)
spt_full = data['SP_TYPE'].item()
# spt = spt_full[0] + re.search(r'\d*\.?\d*', spt_full[1:]).group()
spt = spt_full
if data['PLX_VALUE'].mask:
if not data['FLUX_V'].mask:
# Fall back to photometric parallax
Vmag_obs = data['FLUX_V'].item()
Vmag_abs = MS.GetAbsoluteMagnitude(spt, color='V')
plx = 10 ** (3.0 + (Vmag_abs - Vmag_obs - 5.0) / 5.0)
else:
plx = data['PLX_VALUE'].item()
else:
link = pySIMBAD.buildLink(object)
data = pySIMBAD.simbad(link)
plx = data.Parallax()
spt_full = data.SpectralType().split()[0]
spt = spt_full[0] + re.search(r'\d*\.?\d*', spt_full[1:]).group()
if 'exptime' not in header.keys():
header['exptime'] = 30.0
d = {'Object': object,
'plx': plx,
'SpT': spt,
'exptime': header['exptime']}
return d
