def nebular(self, params, outwave):
"""If the emission_rest_wavelengths parameter is present, return a
nebular emission line spectrum. Currently uses several approximations
for the velocity broadening. Currently does *not* affect photometry.
Only provides samples of the nebular spectrum at outwave, so will not
be correct for total power unless outwave densley samples the emission
dispersion.
:returns nebspec:
The nebular emission in the observed frame, at the wavelengths
specified by the obs['wavelength'].
"""
if 'emission_rest_wavelengths' not in params:
return 0.
mu = vac2air(params['emission_rest_wavelengths'])
# try to get a nebular redshift, otherwise use stellar redshift,
# otherwise use no redshift
a1 = params.get('zred_emission', self.params.get('zred', 0.0)) + 1.0
A = params.get('emission_luminosity', 0.)
sigma = params.get('emission_disp', 10.)
if params.get('smooth_velocity', False):
# This is an approximation to get the dispersion in terms of
# wavelength at the central line wavelength, but should work much
# of the time
sigma = mu * sigma / 2.998e5
return gauss(outwave, mu * a1, A, sigma * a1)
def load_obs(objname=None,
noisefactor=1.0,
calibrated=False,
mask=True,
broaden_obs=False,
wlo=3750.,
whi=7500.,
**extras):
assert objname == 'M67'
bmag = 7.5 #hack
obs = {}
dat = np.loadtxt(os.path.join(sdir, 'data/m67_nobs.dat'))
obs['wavelength'] = observate.vac2air(dat[:, 0])
obs['spectrum'] = dat[:, 1]
obs['unc'] = dat[:, 2]
obs['filters'] = observate.load_filters(['sdss_g0'])
obs['maggies'] = np.array([10**(-0.4 * bmag)])
obs['maggies_unc'] = 0.05 * obs['maggies']
# mask
obs['mask'] = (obs['wavelength'] > wlo) & (obs['wavelength'] < whi)
#adjust uncertainties
obs['unc'] *= noisefactor
obs['noisefactor'] = noisefactor
obs['spec_calibrated'] = calibrated
return obs
def nebular(self, params, outwave):
"""If the emission_rest_wavelengths parameter is present, return a
nebular emission line spectrum. Currently uses several approximations
for the velocity broadening. Currently does *not* affect photometry.
Only provides samples of the nebular spectrum at outwave, so will not
be correct for total power unless outwave densley samples the emission
dispersion.
:returns nebspec:
The nebular emission in the observed frame, at the wavelengths
specified by the obs['wavelength'].
"""
if 'emission_rest_wavelengths' not in params:
return 0.
mu = vac2air(params['emission_rest_wavelengths'])
# try to get a nebular redshift, otherwise use stellar redshift,
# otherwise use no redshift
a1 = params.get('zred_emission', self.params.get('zred', 0.0)) + 1.0
A = params.get('emission_luminosity', 0.)
sigma = params.get('emission_disp', 10.)
if params.get('smooth_velocity', False):
# This is an approximation to get the dispersion in terms of
# wavelength at the central line wavelength, but should work much
# of the time
sigma = mu * sigma / 2.998e5
return gauss(outwave, mu * a1, A, sigma * a1)
def process_component(self, i, outwave, filters):
"""Basically do all the COMPSP stuff for one component.
"""
cspec = self.basis_spec[i, :].copy()
cphot = 0
inwave = self.ssp.wavelengths
if self.safe:
cspec = np.interp(self.params['outwave'], vac2air(inwave),
cspec / a)
cphot = 10**(-0.4 * getSED(inwave, cspec / a, filters))
return cspec, cphot
# Dust attenuation
tage = self.params['tage'][i]
tesc = self.params.get('dust_tesc', 0.01)
dust1 = self.params.get('dust1', 0.0)
dust2 = self.params['dust2']
a = (1 + self.params.get('zred', 0.0))
dust = (tage < tesc) * dust1 + dust2
att = self.params['dust_curve'][0](inwave, **self.params)
cspec *= np.exp(-att * dust)
if filters is not None:
cphot = 10**(-0.4 * getSED(inwave * a, cspec / a, filters))
# Wavelength scale. Broadening and redshifting and placing on output
# wavelength grid
if self.params.get('lsf', [None])[0] is not None:
cspec = smoothspec(
vac2air(inwave) * a, cspec / a, self.params['sigma_smooth'],
**self.params)
else:
sigma = self.params.get('sigma_smooth', 0.0)
cspec = self.ssp.smoothspec(inwave, cspec, sigma)
cspec = np.interp(self.params['outwave'], vac2air(inwave * a),
cspec / a)
return cspec, cphot
def process_component(self, i, outwave, filters):
"""Basically do all the COMPSP stuff for one component.
"""
cspec = self.basis_spec[i, :].copy()
cphot = 0
inwave = self.ssp.wavelengths
if self.safe:
cspec = np.interp(self.params['outwave'], vac2air(inwave), cspec/a)
cphot = 10**(-0.4 * getSED(inwave, cspec/a, filters))
return cspec, cphot
# Dust attenuation
tage = self.params['tage'][i]
tesc = self.params.get('dust_tesc', 0.01)
dust1 = self.params.get('dust1', 0.0)
dust2 = self.params['dust2']
a = (1 + self.params.get('zred', 0.0))
dust = (tage < tesc) * dust1 + dust2
att = self.params['dust_curve'][0](inwave, **self.params)
cspec *= np.exp(-att*dust)
if filters is not None:
cphot = 10**(-0.4 * getSED(inwave*a, cspec / a, filters))
# Wavelength scale. Broadening and redshifting and placing on output
# wavelength grid
if self.params.get('lsf', [None])[0] is not None:
cspec = smoothspec(vac2air(inwave) * a, cspec / a,
self.params['sigma_smooth'], **self.params)
else:
sigma = self.params.get('sigma_smooth', 0.0)
cspec = self.ssp.smoothspec(inwave, cspec, sigma)
cspec = np.interp(self.params['outwave'], vac2air(inwave * a), cspec/a)
return cspec, cphot
def load_obs(objname=None, noisefactor=1.0, calibrated=False,
mask=True, broaden_obs=False, wlo=3750., whi=7500.,
**extras):
assert objname == 'M67'
bmag = 7.5 # hack
obs = {}
dat = np.loadtxt(os.path.join(sdir, 'data/m67_nobs.dat'))
obs['wavelength'] = observate.vac2air(dat[:, 0])
obs['spectrum'] = dat[:, 1]
obs['unc'] = dat[:, 2]
obs['filters'] = observate.load_filters(['sdss_g0'])
obs['maggies'] = np.array([10**(-0.4 * bmag)])
obs['maggies_unc'] = 0.05 * obs['maggies']
# mask
obs['mask'] = (obs['wavelength'] > wlo) & (obs['wavelength'] < whi)
#adjust uncertainties
obs['unc'] *= noisefactor
obs['noisefactor'] = noisefactor
obs['spec_calibrated'] = calibrated
return obs
def get_spectrum(self, outwave=None, filters=None, peraa=False, **kwargs):
"""Return an attenuated, smoothed, distance dimmed stellar spectrum and SED.
:returns spec:
The spectrum on the outwave grid (assumed in air), in AB maggies.
If peraa is True then the spectrum is erg/s/cm^2/AA.
:returns phot:
Observed frame photometry in units of AB maggies. If ``lumdist``
is not present in the parameters then these are absolute maggies,
otherwise they are apparent.
:returns x:
A blob of extra quantities (e.g. mass, uncertainty)
"""
self.update(**kwargs)
# star spectrum (in Lsun/Hz)
wave, spec, unc = self.get_star_spectrum(**self.params)
spec *= self.normalize()
# dust
if 'dust_curve' in self.params:
att = self.params['dust_curve'](self._wave, **self.params)
spec *= np.exp(-att)
# Redshifting + Wavelength solution. We also convert to in-air.
a = 1 + self.params.get('zred', 0)
b = 0.0
if 'wavecal_coeffs' in self.params:
x = wave - wave.min()
x = 2.0 * (x / x.max()) - 1.0
c = np.insert(self.params['wavecal_coeffs'], 0, 0)
# assume coeeficients give shifts in km/s
b = chebval(x, c) / (lightspeed*1e-13)
wa, sa = vac2air(wave) * (a + b), spec * a
if outwave is None:
outwave = wa
# Broadening, interpolation onto output wavelength grid
if 'sigma_smooth' in self.params:
smspec = self.smoothspec(wa, sa, self.params['sigma_smooth'],
outwave=outwave, **self.params)
elif outwave is not wa:
smspec = np.interp(outwave, wa, sa, left=0, right=0)
else:
smspec = sa
# Photometry (observed frame absolute maggies)
if filters is not None:
mags = getSED(wa, sa * lightspeed / wa**2 * to_cgs, filters)
phot = np.atleast_1d(10**(-0.4 * mags))
else:
phot = 0.0
# Distance dimming. Default to 10pc distance (i.e. absolute)
dfactor = (self.params.get('lumdist', 1e-5) * 1e5)**2
if peraa:
# spectrum will be in erg/s/cm^2/AA
smspec *= to_cgs / dfactor * lightspeed / outwave**2
else:
# Spectrum will be in maggies
smspec *= to_cgs / dfactor / 1e3 / (3631*jansky_mks)
# Convert from absolute maggies to apparent maggies
phot /= dfactor
return smspec, phot, None
def get_spectrum(self, outwave=None, filters=None, peraa=False, **kwargs):
"""Return an attenuated, smoothed, distance dimmed stellar spectrum and SED.
:returns spec:
The spectrum on the outwave grid (assumed in air), in AB maggies.
If peraa is True then the spectrum is erg/s/cm^2/AA.
:returns phot:
Observed frame photometry in units of AB maggies. If ``lumdist``
is not present in the parameters then these are absolute maggies,
otherwise they are apparent.
:returns x:
A blob of extra quantities (e.g. mass, uncertainty)
"""
self.update(**kwargs)
# star spectrum (in Lsun/Hz)
wave, spec, unc = self.get_star_spectrum(**self.params)
spec *= self.normalize()
# dust
if 'dust_curve' in self.params:
att = self.params['dust_curve'](self._wave, **self.params)
spec *= np.exp(-att)
# Redshifting + Wavelength solution. We also convert to in-air.
a = 1 + self.params.get('zred', 0)
b = 0.0
if 'wavecal_coeffs' in self.params:
x = wave - wave.min()
x = 2.0 * (x / x.max()) - 1.0
c = np.insert(self.params['wavecal_coeffs'], 0, 0)
# assume coeeficients give shifts in km/s
b = chebval(x, c) / (lightspeed*1e-13)
wa, sa = vac2air(wave) * (a + b), spec * a
if outwave is None:
outwave = wa
# Broadening, interpolation onto output wavelength grid
if 'sigma_smooth' in self.params:
smspec = self.smoothspec(wa, sa, self.params['sigma_smooth'],
outwave=outwave, **self.params)
elif outwave is not wa:
smspec = np.interp(outwave, wa, sa, left=0, right=0)
else:
smspec = sa
# Photometry (observed frame absolute maggies)
if filters is not None:
mags = getSED(wa, sa * lightspeed / wa**2 * to_cgs, filters)
phot = np.atleast_1d(10**(-0.4 * mags))
else:
phot = 0.0
# Distance dimming. Default to 10pc distance (i.e. absolute)
dfactor = (self.params.get('lumdist', 1e-5) * 1e5)**2
if peraa:
# spectrum will be in erg/s/cm^2/AA
smspec *= to_cgs / dfactor * lightspeed / outwave**2
else:
# Spectrum will be in maggies
smspec *= to_cgs / dfactor / 1e3 / (3631*jansky_mks)
# Convert from absolute maggies to apparent maggies
phot /= dfactor
return smspec, phot, None