# generate sed array
seds = arr[:, 2].reshape((ages.size, ls.size)).transpose()
# convert from angstroms to hertz
vs = c / ls
# convert from ergs/s/A to ergs/s/Hz
seds *= ls.reshape((ls.size, 1))**2.0 / c
# and now from ergs/s/Hz to ergs/s/Hz/cm^2.0
seds /= (4.0 * math.pi *
utils.convert_length(10, incoming='pc', outgoing='cm')**2.0)
# sort in frequency space
sinds = vs.argsort()
# did the masses get passed?
if filemass:
data = utils.rascii(filemass, silent=True)
mass_interp = interpolate.interp1d(data[:, 0] * 1e9, data[:, 1])
masses = mass_interp(ages)
# generate fits frame with sed in it
primary_hdu = pyfits.PrimaryHDU(seds[sinds, :])
primary_hdu.header.update('units', 'ergs/s/cm^2/Hz')
primary_hdu.header.update('has_seds', True)
primary_hdu.header.update('nfilters', 0)
primary_hdu.header.update('nzfs', 0)
# store meta data
if sfh and met and imf:
primary_hdu.header.update('has_meta', True)
primary_hdu.header.update('model', 'M05', comment='meta data')
primary_hdu.header.update('met', met, comment='meta data')
if parts.count( 'z' ): met = parts[ parts.index( 'z' ) + 1 ] # imf for (check,val) in zip( ['krou','salp','chab'], ['Kroupa', 'Salpeter', 'Chabrier'] ): if parts.count( check ): imf = val break if not os.path.isfile( filein ): raise ValueError( 'Input file does not exist or is not readable!' ) if not os.path.isfile( filemass ): raise ValueError( 'Mass file does not exist or is not readable!' ) # read ised file ( seds, ages, vs ) = utils.read_ised( filein ) # read age-mass relationship mass = utils.rascii( filemass, silent=True ) # each line in the mass file should exactly correspond to the age, with the exception of the first age (which is zero) # check that the numbers of lines are the same, and if so assume that the correspondence is perfect. # otherwise, interpolate if mass[:,0].size == ages.size-1: masses = np.append( 0, mass[:,6] ) else: masses = np.zeros( ages.size ) interp = interpolate.interp1d( 10.0**mass[:,0], mass[:,6] ) masses[1:] = interp( ages[1:] ) # generate fits frame with sed in it primary_hdu = pyfits.PrimaryHDU(seds) primary_hdu.header.update( 'units', 'ergs/s/cm^2/Hz' ) primary_hdu.header.update( 'has_seds', True ) primary_hdu.header.update( 'nfilters', 0 )
for (check,val) in zip( ['krou','salp','chab'], ['Kroupa', 'Salpeter', 'Chabrier'] ): if parts.count( check ): imf = val break if parts.count( 'n' ): n = parts[ parts.index( 'n' ) + 1 ] ae = False if parts.count( 'ae' ): ae = True # does the file with masses exist? has_masses = False mass_file = glob.glob( 'MLR*.txt' ) if len( mass_file ): # read it in! print 'Loading masses from %s' % mass_file[0] data = utils.rascii( mass_file[0], silent=True ) masses = data[:,10:14].sum( axis=1 ) has_masses = True files = glob.glob( 'SPEC*agb*' ) nages = len( files ) ages = [] for (i,file) in enumerate(files): ls = [] this = [] # extract the age from the filename and convert to years m = re.search( 't60*(\d+)$', file ) ages.append( int( m.group(1) )*1e6 )
def __init__(self, filename, units='a', cosmology=None, vega=False, solar=False):
# load additional modules. Yes, this is strange. But this way astro_filter_light can inherit astro_filter.
# this is necessary because astro_filter_light is intended to work without any of these modules
import scipy.interpolate as interpolate
import scipy.integrate
global interpolate
global scipy
# check that we were passed a file and it exists
if type(filename) == type(''):
if not os.path.isfile(filename): raise ValueError('The specified filter transmission file does not exist!')
# read it in
file = utils.rascii(filename)
elif filename is None:
# very basic load - no filter response curve
self.npts = 0
self.to_vega = vega
self.has_vega = True
if cosmology is not None: self.cosmo = cosmology
self.solar = solar
self.has_solar = not np.isnan(solar)
return
else:
# is this a numpy array?
if type(filename) == type(np.array([])):
file = filename
else:
raise ValueError('Please pass the filename for the filter transmission file!')
ls = file[:,0]
# calculate wavelengths in both angstroms and hertz
units = units.lower()
if units == 'hz':
vs = ls
ls = utils.to_lambda(vs, units='a')
else:
vs = utils.to_hertz(ls, units=units)
ls = utils.convert_length(ls, incoming=units, outgoing='a')
# store everything sorted
sind = vs.argsort()
self.vs = vs[sind] # frequencies
self.tran = file[sind,1] # corresponding transmission
self.ls = ls[sind[::-1]] # wavelengths (angstroms)
self.tran_ls = self.tran[::-1] # corresponding transmission
self.npts = self.vs.size
# frequency widths of each datapoint
self.diffs = np.roll(self.vs, -1) - self.vs
self.diffs[-1] = self.diffs[-2]
# calculate filter properties and store in the object
self.calc_filter_properties()
# normalization for calculating ab mags for this filter
self.ab_flux = self.ab_source_flux*scipy.integrate.simps(self.tran/self.vs, self.vs)
# store the cosmology object if passed
if cosmology is not None: self.cosmo = cosmology
# calculate ab-to-vega conversion if vega spectrum was passed
if type(vega) == type(np.array([])): self.set_vega_conversion(vega)
# calculate solar magnitude if solar spectrum was passed
if type(solar) == type(np.array([])): self.set_solar_magnitude(solar)
self.zfs = np.array([])
self.zf_grids = []
['Kroupa', 'Salpeter', 'Chabrier']):
if parts.count(check):
imf = val
break
if parts.count('n'):
n = parts[parts.index('n') + 1]
ae = False
if parts.count('ae'): ae = True
# does the file with masses exist?
has_masses = False
mass_file = glob.glob('MLR*.txt')
if len(mass_file):
# read it in!
print(('Loading masses from %s' % mass_file[0]))
data = utils.rascii(mass_file[0], silent=True)
masses = data[:, 10:14].sum(axis=1)
has_masses = True
files = glob.glob('SPEC*agb*')
nages = len(files)
ages = []
for (i, file) in enumerate(files):
ls = []
this = []
# extract the age from the filename and convert to years
m = re.search('t60*(\d+)$', file)
ages.append(int(m.group(1)) * 1e6)