def conversion(value, from_units, to_units):
try:
return Decimal(str(convert_length(value, from_units,
to_units))).quantize(
Decimal('.01'))
except ValueError:
return None
def conversion(value, from_units, to_units):
try:
if isinstance(value, (list, tuple)):
q = int(value[0]) * pq.ft # convert feet / inches into centimeters
value = float(q.rescale(pq.inch) + float(value[1]) * pq.inch)
return Decimal(str(convert_length(value, from_units, to_units))).quantize(Decimal('.01'))
except ValueError:
return None
def conversion(value, from_units, to_units):
try:
if isinstance(value, (list, tuple)):
q = int(
value[0]) * pq.ft # convert feet / inches into centimeters
value = float(q.rescale(pq.inch) + float(value[1]) * pq.inch)
return Decimal(str(convert_length(value, from_units,
to_units))).quantize(
Decimal('.01'))
except ValueError:
return None
def _get_FIELD_display(cls, field):
if isinstance(field, HeightField):
value = getattr(cls, field.attname)
if value:
if cls.units != DATABASE_UNITS:
value = round(convert_length(value, DATABASE_UNITS, cls.units), 2)
q = float(value) * pq.inch # rescale inches to feet and inches
return _('%s ft %s in' % (
int(q.rescale(pq.ft)), int(float((q.rescale(pq.ft) % pq.ft).rescale(pq.inch)))))
else:
return _('%s cm' % value)
return value
return super(self.model, cls)._get_FIELD_display(field)
def _get_FIELD_display(cls, field):
if isinstance(field, HeightField):
value = getattr(cls, field.attname)
if value:
if cls.units != DATABASE_UNITS:
value = round(
convert_length(value, DATABASE_UNITS, cls.units),
2)
q = float(
value
) * pq.inch # rescale inches to feet and inches
return _('%s ft %s in' %
(int(q.rescale(pq.ft)),
int(
float((q.rescale(pq.ft) % pq.ft).rescale(
pq.inch)))))
else:
return _('%s cm' % value)
return value
return super(self.model, cls)._get_FIELD_display(field)
def conversion(value, from_units, to_units):
try:
return Decimal(str(convert_length(value, from_units, to_units))).quantize(Decimal('.01'))
except ValueError:
return None
break
# tau?
if sfh:
tau = parts[sfh_index + 1] if sfh == 'Exponential' else ''
# metallicity
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
# speed of light
c = utils.convert_length(utils.c, incoming='m', outgoing='a')
# read in model
fi = open(filein, 'r')
res = []
for line in fi:
if line[0] == '#': continue
res.extend(line.strip().split())
fi.close()
# convert to float and return original shape (m, 3)
arr = np.array(res).reshape((-1, 3)).astype('float')
# grab unique ages
ages = np.unique(arr[:, 0]) * 1e9
# and unique ls
ls = np.unique(arr[:, 1])
sfh_index = parts.index( check ) break # tau? if sfh: tau = parts[sfh_index+1] if sfh == 'Exponential' else '' # metallicity 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 # speed of light c = utils.convert_length( utils.c, incoming='m', outgoing='a' ) # read in model fi = open( filein, 'r' ) res = [] for line in fi: if line[0] == '#': continue res.extend( line.strip().split() ) fi.close() # convert to float and return original shape (m, 3) arr = np.array( res ).reshape( (-1,3) ).astype( 'float' ) # grab unique ages ages = np.unique( arr[:,0] )*1e9 # and unique ls ls = np.unique( arr[:,1] )
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 = []
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 # read in wavelengths ls = [] fp = open( lambdas, 'r' ) ls = np.array( [ line.strip() for line in fp ] ).astype( 'float' ) fp.close() nls = ls.size # conversion from Lo/Hz to ergs/s/Hz/cm^2.0 conv = 3.826e33/(4.0*math.pi*utils.convert_length( 10, incoming='pc', outgoing='cm' )**2.0) vs = utils.convert_length( utils.c, incoming='m', outgoing='a' )/ls # now read in the model file fp = open( filein, 'r' ) ages = [] masses = [] c = 0 while True: # each age takes up two lines descr = fp.readline() if not descr: break if descr[0] == '#': continue # skip the first data line (it just gives the number of ages)
seds = np.empty((nls, nages))
# convert to ergs/s/angstrom
seds[:, i] = np.array(this) / 4.3607e-33 / 1e10
# convert to numpy
ages = np.array(ages)
ls = np.array(ls) * 10.0
# make sure we are sorted in age
sinds = ages.argsort()
ages = ages[sinds]
seds = seds[:, sinds]
# speed of light
c = utils.convert_length(utils.c, incoming='m', outgoing='a')
# 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()
# generate fits frame with sed in it
primary_hdu = pyfits.PrimaryHDU(seds[sinds, :])
primary_hdu.header.update('units', 'ergs/s/cm^2/Hz')