def get_table(teff=None,
logg=None,
ebv=None,
vrad=None,
star=None,
wave_units='AA',
flux_units='erg/cm2/s/AA/sr',
**kwargs):
"""
Retrieve the specific intensity of a model atmosphere.
ebv is reddening
vrad is radial velocity: positive is redshift, negative is blueshift (km/s!)
extra kwargs are for reddening
You get limb angles, wavelength and a table. The shape of the table is
(N_wave,N_mu).
WARNING: wave and flux units cannot be specificed for the moment.
>>> mu,wave,table = get_table(10000,4.0)
>>> p = pl.figure()
>>> ax1 = pl.subplot(221)
>>> p = pl.title('E(B-V)=0, vrad=0')
>>> ax = pl.gca()
>>> ax.set_color_cycle([pl.cm.spectral(i) for i in np.linspace(0,1,len(mu))])
>>> p = pl.loglog(wave,table)
>>> p = pl.xlim(700,15000)
>>> p = pl.ylim(1e3,1e8)
>>> mu,wave,table = get_table(10000,4.0,ebv=0.5)
>>> p = pl.subplot(222,sharex=ax1,sharey=ax1)
>>> p = pl.title('E(B-V)=0.5, vrad=0')
>>> ax = pl.gca()
>>> ax.set_color_cycle([pl.cm.spectral(i) for i in np.linspace(0,1,len(mu))])
>>> p = pl.loglog(wave,table)
>>> p = pl.xlim(700,15000)
>>> p = pl.ylim(1e3,1e8)
>>> mu,wave,table = get_table(10000,4.0,vrad=-1000.)
>>> p = pl.subplot(223,sharex=ax1,sharey=ax1)
>>> p = pl.title('E(B-V)=0., vrad=-10000.')
>>> ax = pl.gca()
>>> ax.set_color_cycle([pl.cm.spectral(i) for i in np.linspace(0,1,len(mu))])
>>> p = pl.loglog(wave,table)
>>> p = pl.xlim(700,15000)
>>> p = pl.ylim(1e3,1e8)
>>> mu,wave,table = get_table(10000,4.0,vrad=-1000.,ebv=0.5)
>>> p = pl.subplot(224,sharex=ax1,sharey=ax1)
>>> p = pl.title('E(B-V)=0.5, vrad=-10000.')
>>> ax = pl.gca()
>>> ax.set_color_cycle([pl.cm.spectral(i) for i in np.linspace(0,1,len(mu))])
>>> p = pl.loglog(wave,table)
>>> p = pl.xlim(700,15000)
>>> p = pl.ylim(1e3,1e8)
>>> mu,wave,table = get_table(10050,4.12)
>>> p = pl.figure()
>>> pl.gca().set_color_cycle([pl.cm.spectral(i) for i in np.linspace(0,1,len(mu))])
>>> p = pl.loglog(wave,table)
@param teff: effective temperature (K)
@type teff: float
@param logg: log surface gravity (cgs, dex)
@type logg: float
@param ebv: reddening (mag)
@type ebv: float
@param vrad: radial velocity (for doppler shifting) (km/s)
@type vrad: float
@return: mu angles, wavelengths, table (Nwave x Nmu)
@rtype: array, array, array
"""
#-- get the FITS-file containing the tables
gridfile = get_file(**kwargs)
#-- read the file:
ff = pyfits.open(gridfile)
teff = float(teff)
logg = float(logg)
#-- if we have a grid model, no need for interpolation
try:
#-- extenstion name as in fits files prepared by Steven
mod_name = "T%05d_logg%01.02f" % (teff, logg)
mod = ff[mod_name]
mu = np.array(mod.columns.names[1:], float)
table = np.array(mod.data.tolist())[:, 1:]
wave = mod.data.field('wavelength')
logger.debug('Model LD taken directly from file (%s)' %
(os.path.basename(gridfile)))
except KeyError:
mu, wave, teffs, loggs, flux, flux_grid = get_grid_mesh(**kwargs)
logger.debug('Model LD interpolated from grid %s (%s)' %
(os.path.basename(gridfile), kwargs))
wave = wave + 0.
table = flux_grid(np.log10(teff), logg) + 0.
ff.close()
#-- velocity shift if necessary
if vrad is not None and vrad != 0:
cc = constants.cc / 1000. #speed of light in km/s
for i in range(len(mu)):
flux_shift = tools.doppler_shift(wave, vrad, flux=table[:, i])
table[:, i] = flux_shift - 5. * vrad / cc * table[:, i]
#-- redden if necessary
if ebv is not None and ebv > 0:
for i in range(len(mu)):
table[:, i] = reddening.redden(table[:, i],
wave=wave,
ebv=ebv,
rtype='flux',
**kwargs)
#-- that's it!
return mu, wave, table
def get_table(teff=None, logg=None, vrad=0, vrot=0, **kwargs):
"""
Retrieve synthetic spectrum.
Wavelengths in angstrom, fluxes in eddington flux: erg/s/cm2/A.
It is possible to rotationally broaden the spectrum by supplying at least
'vrot' and optionally also other arguments for the rotation.rotin function.
Supply vrot in km/s
It is possibility to include a radial velocity shift in the spectrum. Supply
'vrad' in km/s. (+vrad means redshift). Uses spectra.tools.doppler_shift
"""
gridfile = get_file(**kwargs)
template_wave = kwargs.pop('wave', None)
ff = pf.open(gridfile)
try:
#-- extenstion name as in fits files prepared by Steven
mod_name = "T%05d_logg%01.02f" % (teff, logg)
mod = ff[mod_name]
wave = mod.data.field('wavelength')
flux = mod.data.field('flux')
cont = mod.data.field('cont')
logger.debug('Model spectrum taken directly from file (%s)' %
(os.path.basename(gridfile)))
if template_wave is not None:
flux = np.interp(template_wave, wave, flux)
cont = np.interp(template_wave, wave, cont)
wave = template_wave
#-- if the teff/logg is not present, use the interpolation thing
except KeyError:
#-- it is possible we first have to set the interpolation function.
# This function is memoized, so if it will not be calculated
# twice.
meshkwargs = copy.copy(kwargs)
meshkwargs['wave'] = kwargs.get('wave', None)
meshkwargs['teffrange'] = kwargs.get('teffrange', None)
meshkwargs['loggrange'] = kwargs.get('loggrange', None)
wave, teffs, loggs, flux, flux_grid, cont_grid = get_grid_mesh(
wave=template_wave, **kwargs)
logger.debug('Model spectrum interpolated from grid %s (%s)' %
(os.path.basename(gridfile), meshkwargs))
wave = wave + 0.
try:
flux = flux_grid(np.log10(teff), logg) + 0.
cont = cont_grid(np.log10(teff), logg) + 0.
except ValueError:
teffs, loggs = get_grid_dimensions(**kwargs)
index = np.argmin(np.abs((teffs - teff)**2 + (loggs - logg)**2))
#logger.error('teff=%f-->%f, logg=%f-->%f'%(teff,teffs[index],logg,loggs[index]))
flux = flux_grid(np.log10(teffs[index]), loggs[index]) + 0.
cont = cont_grid(np.log10(teffs[index]), loggs[index]) + 0.
#-- convert to arrays
wave = np.array(wave, float)
flux = np.array(flux, float)
if vrot > 0:
#-- calculate rotational broadening but reinterpolate on original
# wavelength grid. First we need to check which arguments we can pass
# through
argspec = inspect.getargspec(tools.rotational_broadening)
mykwargs = dict(
list(zip(argspec.args[-len(argspec.defaults):], argspec.defaults)))
for key in kwargs:
if key in mykwargs:
mykwargs[key] = kwargs[key]
wave_, flux_ = tools.rotational_broadening(wave, flux, vrot,
**mykwargs)
flux = np.interp(wave, wave_, flux_)
if vrad != 0:
wave_ = tools.doppler_shift(wave, vrad)
flux = np.interp(wave, wave_, flux)
ff.close()
return wave, flux, cont
def get_table(teff=None,logg=None,vrad=0,vrot=0,**kwargs):
"""
Retrieve synthetic spectrum.
Wavelengths in angstrom, fluxes in eddington flux: erg/s/cm2/A.
It is possible to rotationally broaden the spectrum by supplying at least
'vrot' and optionally also other arguments for the rotation.rotin function.
Supply vrot in km/s
It is possibility to include a radial velocity shift in the spectrum. Supply
'vrad' in km/s. (+vrad means redshift). Uses spectra.tools.doppler_shift
"""
gridfile = get_file(**kwargs)
template_wave = kwargs.pop('wave',None)
ff = pyfits.open(gridfile)
try:
#-- extenstion name as in fits files prepared by Steven
mod_name = "T%05d_logg%01.02f" %(teff,logg)
mod = ff[mod_name]
wave = mod.data.field('wavelength')
flux = mod.data.field('flux')
cont = mod.data.field('cont')
logger.debug('Model spectrum taken directly from file (%s)'%(os.path.basename(gridfile)))
if template_wave is not None:
flux = np.interp(template_wave,wave,flux)
cont = np.interp(template_wave,wave,cont)
wave = template_wave
#-- if the teff/logg is not present, use the interpolation thing
except KeyError:
#-- it is possible we first have to set the interpolation function.
# This function is memoized, so if it will not be calculated
# twice.
meshkwargs = copy.copy(kwargs)
meshkwargs['wave'] = kwargs.get('wave',None)
meshkwargs['teffrange'] = kwargs.get('teffrange',None)
meshkwargs['loggrange'] = kwargs.get('loggrange',None)
wave,teffs,loggs,flux,flux_grid,cont_grid = get_grid_mesh(wave=template_wave,**kwargs)
logger.debug('Model spectrum interpolated from grid %s (%s)'%(os.path.basename(gridfile),meshkwargs))
wave = wave + 0.
try:
flux = flux_grid(np.log10(teff),logg) + 0.
cont = cont_grid(np.log10(teff),logg) + 0.
except ValueError:
teffs,loggs = get_grid_dimensions(**kwargs)
index = np.argmin(np.abs( (teffs-teff)**2 + (loggs-logg)**2 ))
#logger.error('teff=%f-->%f, logg=%f-->%f'%(teff,teffs[index],logg,loggs[index]))
flux = flux_grid(np.log10(teffs[index]),loggs[index]) + 0.
cont = cont_grid(np.log10(teffs[index]),loggs[index]) + 0.
#-- convert to arrays
wave = np.array(wave,float)
flux = np.array(flux,float)
if vrot>0:
#-- calculate rotational broadening but reinterpolate on original
# wavelength grid. First we need to check which arguments we can pass
# through
argspec = inspect.getargspec(tools.rotational_broadening)
mykwargs = dict(zip(argspec.args[-len(argspec.defaults):],argspec.defaults))
for key in kwargs:
if key in mykwargs:
mykwargs[key] = kwargs[key]
wave_,flux_ = tools.rotational_broadening(wave,flux,vrot,**mykwargs)
flux = np.interp(wave,wave_,flux_)
if vrad!=0:
wave_ = tools.doppler_shift(wave,vrad)
flux = np.interp(wave,wave_,flux)
ff.close()
return wave,flux,cont
def get_table(
teff=None, logg=None, ebv=None, vrad=None, star=None, wave_units="AA", flux_units="erg/cm2/s/AA/sr", **kwargs
):
"""
Retrieve the specific intensity of a model atmosphere.
ebv is reddening
vrad is radial velocity: positive is redshift, negative is blueshift (km/s!)
extra kwargs are for reddening
You get limb angles, wavelength and a table. The shape of the table is
(N_wave,N_mu).
WARNING: wave and flux units cannot be specificed for the moment.
>>> mu,wave,table = get_table(10000,4.0)
>>> p = pl.figure()
>>> ax1 = pl.subplot(221)
>>> p = pl.title('E(B-V)=0, vrad=0')
>>> ax = pl.gca()
>>> ax.set_color_cycle([pl.cm.spectral(i) for i in np.linspace(0,1,len(mu))])
>>> p = pl.loglog(wave,table)
>>> p = pl.xlim(700,15000)
>>> p = pl.ylim(1e3,1e8)
>>> mu,wave,table = get_table(10000,4.0,ebv=0.5)
>>> p = pl.subplot(222,sharex=ax1,sharey=ax1)
>>> p = pl.title('E(B-V)=0.5, vrad=0')
>>> ax = pl.gca()
>>> ax.set_color_cycle([pl.cm.spectral(i) for i in np.linspace(0,1,len(mu))])
>>> p = pl.loglog(wave,table)
>>> p = pl.xlim(700,15000)
>>> p = pl.ylim(1e3,1e8)
>>> mu,wave,table = get_table(10000,4.0,vrad=-1000.)
>>> p = pl.subplot(223,sharex=ax1,sharey=ax1)
>>> p = pl.title('E(B-V)=0., vrad=-10000.')
>>> ax = pl.gca()
>>> ax.set_color_cycle([pl.cm.spectral(i) for i in np.linspace(0,1,len(mu))])
>>> p = pl.loglog(wave,table)
>>> p = pl.xlim(700,15000)
>>> p = pl.ylim(1e3,1e8)
>>> mu,wave,table = get_table(10000,4.0,vrad=-1000.,ebv=0.5)
>>> p = pl.subplot(224,sharex=ax1,sharey=ax1)
>>> p = pl.title('E(B-V)=0.5, vrad=-10000.')
>>> ax = pl.gca()
>>> ax.set_color_cycle([pl.cm.spectral(i) for i in np.linspace(0,1,len(mu))])
>>> p = pl.loglog(wave,table)
>>> p = pl.xlim(700,15000)
>>> p = pl.ylim(1e3,1e8)
>>> mu,wave,table = get_table(10050,4.12)
>>> p = pl.figure()
>>> pl.gca().set_color_cycle([pl.cm.spectral(i) for i in np.linspace(0,1,len(mu))])
>>> p = pl.loglog(wave,table)
@param teff: effective temperature (K)
@type teff: float
@param logg: log surface gravity (cgs, dex)
@type logg: float
@param ebv: reddening (mag)
@type ebv: float
@param vrad: radial velocity (for doppler shifting) (km/s)
@type vrad: float
@return: mu angles, wavelengths, table (Nwave x Nmu)
@rtype: array, array, array
"""
# -- get the FITS-file containing the tables
gridfile = get_file(**kwargs)
# -- read the file:
ff = pyfits.open(gridfile)
teff = float(teff)
logg = float(logg)
# -- if we have a grid model, no need for interpolation
try:
# -- extenstion name as in fits files prepared by Steven
mod_name = "T%05d_logg%01.02f" % (teff, logg)
mod = ff[mod_name]
mu = np.array(mod.columns.names[1:], float)
table = np.array(mod.data.tolist())[:, 1:]
wave = mod.data.field("wavelength")
logger.debug("Model LD taken directly from file (%s)" % (os.path.basename(gridfile)))
except KeyError:
mu, wave, teffs, loggs, flux, flux_grid = get_grid_mesh(**kwargs)
logger.debug("Model LD interpolated from grid %s (%s)" % (os.path.basename(gridfile), kwargs))
wave = wave + 0.0
table = flux_grid(np.log10(teff), logg) + 0.0
ff.close()
# -- velocity shift if necessary
if vrad is not None and vrad != 0:
cc = constants.cc / 1000.0 # speed of light in km/s
for i in range(len(mu)):
flux_shift = tools.doppler_shift(wave, vrad, flux=table[:, i])
table[:, i] = flux_shift - 5.0 * vrad / cc * table[:, i]
# -- redden if necessary
if ebv is not None and ebv > 0:
for i in range(len(mu)):
table[:, i] = reddening.redden(table[:, i], wave=wave, ebv=ebv, rtype="flux", **kwargs)
# -- that's it!
return mu, wave, table
