/usr/lib/python2.7/dist-packages/specutils/extinction.py is in python-specutils 0.2.2-1build3.
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"""Extinction models.
Classes are callables representing the corresponding extinction
function with a fixed R_V. When calling an extinction function multiple
times with the same R_V, it will be faster to create a class instance with
fixed R_V and use that object to evaluate the extinction. See class
documentation for details.
"""
from __future__ import division
from os import path
import numpy as np
from astropy.io import ascii
from astropy.utils import data as apydata
from astropy import units as u
from specutils import cextinction
try:
import scipy
except ImportError:
HAS_SCIPY = False
else:
HAS_SCIPY = True
__all__ = ['extinction_ccm89', 'extinction_od94', 'extinction_gcc09',
'extinction_f99', 'extinction_fm07', 'extinction_wd01',
'extinction_d03', 'extinction', 'reddening',
'ExtinctionF99', 'ExtinctionD03', 'ExtinctionWD01']
def _process_wave(wave):
return wave.to(u.angstrom).flatten()
def _process_inputs(wave, ebv, a_v, r_v):
if (a_v is None) and (ebv is None):
raise ValueError('Must specify either a_v or ebv')
if (a_v is not None) and (ebv is not None):
raise ValueError('Cannot specify both a_v and ebv')
if a_v is None:
a_v = ebv * r_v
scalar = np.isscalar(wave)
wave = np.atleast_1d(wave)
if wave.ndim > 2:
raise ValueError("wave cannot be more than 1-d")
return wave, scalar, a_v
def _check_wave(wave, minwave, maxwave):
if np.any((wave < minwave) | (wave > maxwave)):
raise ValueError('Wavelengths must be between {0:.2f} and {1:.2f} '
'angstroms'.format(minwave, maxwave))
def extinction_ccm89(wave, a_v, r_v=3.1):
"""Cardelli, Clayton, & Mathis (1989) extinction model.
The parameters given in the original paper [1]_ are used.
The function works between 910 A and 3.3 microns, although note the
claimed validity is only for wavelength above 1250 A.
{0}
Notes
-----
In Cardelli, Clayton & Mathis (1989) the mean
R_V-dependent extinction law, is parameterized as
.. math::
<A(\lambda)/A_V> = a(x) + b(x) / R_V
where the coefficients a(x) and b(x) are functions of
wavelength. At a wavelength of approximately 5494.5 angstroms (a
characteristic wavelength for the V band), a(x) = 1 and b(x) = 0,
so that A(5494.5 angstroms) = A_V. This function returns
.. math::
A(\lambda) = A_V (a(x) + b(x) / R_V)
where A_V can either be specified directly or via E(B-V)
(by defintion, A_V = R_V * E(B-V)).
References
----------
.. [1] Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245
"""
_check_wave(wave, 909.091 * u.angstrom, 33333.333 * u.angstrom)
res = cextinction.ccm89(_process_wave(wave).value, a_v, r_v)
return res.reshape(wave.shape)
def extinction_od94(wave, a_v, r_v=3.1):
"""O'Donnell (1994) extinction model.
Like Cardelli, Clayton, & Mathis (1989) [1]_ but using the O'Donnell
(1994) [2]_ optical coefficients between 3030 A and 9091 A.
{0}
Notes
-----
This function matches the Goddard IDL astrolib routine CCM_UNRED.
From the documentation for that routine:
1. The CCM curve shows good agreement with the Savage & Mathis (1979)
[3]_ ultraviolet curve shortward of 1400 A, but is probably
preferable between 1200 and 1400 A.
2. Curve is extrapolated between 912 and 1000 A as suggested by
Longo et al. (1989) [4]_
3. Valencic et al. (2004) [5]_ revise the ultraviolet CCM
curve (3.3 -- 8.0 um^-1). But since their revised curve does
not connect smoothly with longer and shorter wavelengths, it is
not included here.
References
----------
.. [1] Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245
.. [2] O'Donnell, J. E. 1994, ApJ, 422, 158O
.. [3] Savage & Mathis 1979, ARA&A, 17, 73
.. [4] Longo et al. 1989, ApJ, 339,474
.. [5] Valencic et al. 2004, ApJ, 616, 912
"""
_check_wave(wave, 909.091 * u.angstrom, 33333.333 * u.angstrom)
res = cextinction.od94(_process_wave(wave).value, a_v, r_v)
return res.reshape(wave.shape)
def extinction_gcc09(wave, a_v, r_v=3.1):
"""Gordon, Cartledge, & Clayton (2009) extinction model.
Uses the UV coefficients of Gordon, Cartledge, & Clayton (2009)
[1]_ between 910 A and 3030 A, otherwise the same as the
`extinction_od94` function. Also note that the two do not connect
perfectly: there is a discontinuity at 3030 A. Note that
GCC09 equations 14 and 15 apply to all x>5.9 (the GCC09 paper
mistakenly states they do not apply at x>8; K. Gordon,
priv. comm.).
.. warning :: Note that the Gordon, Cartledge, & Clayton (2009) paper
has incorrect parameters for the 2175 angstrom bump that
have not been corrected here.
{0}
References
----------
.. [1] Gordon, K. D., Cartledge, S., & Clayton, G. C. 2009, ApJ, 705, 1320
"""
_check_wave(wave, 909.091 * u.angstrom, 33333.333 * u.angstrom)
res = cextinction.gcc09(_process_wave(wave).value, a_v, r_v)
return res.reshape(wave.shape)
_f99_xknots = 1.e4 / np.array([np.inf, 26500., 12200., 6000., 5470.,
4670., 4110., 2700., 2600.])
class ExtinctionF99(object):
"""Fitzpatrick (1999) extinction model with fixed R_V.
Parameters
----------
r_v : float
Relation between specific and total extinction, ``a_v = r_v * ebv``.
Examples
--------
Create a callable that gives the extinction law for a given ``r_v``
and use it:
>>> f = ExtinctionF99(3.1)
>>> f(3000., a_v=1.)
1.7993995521481463
"""
def __init__(self, a_v, r_v=3.1):
if not HAS_SCIPY:
raise ImportError('To use this function scipy needs to be installed')
from scipy.interpolate import splmake
self.a_v = a_v
self.r_v = r_v
kknots = cextinction.f99kknots(_f99_xknots, self.r_v)
self._spline = splmake(_f99_xknots, kknots, order=3)
def __call__(self, wave):
if not HAS_SCIPY:
raise ImportError('To use this function scipy needs to be installed')
from scipy.interpolate import spleval
wave_shape = wave.shape
wave = _process_wave(wave)
_check_wave(wave, 909.091* u.angstrom, 6. * u.micron)
res = np.empty_like(wave.__array__(), dtype=np.float64)
# Analytic function in the UV.
uvmask = wave < (2700. * u.angstrom)
if np.any(uvmask):
res[uvmask] = cextinction.f99uv(wave[uvmask].value, self.a_v, self.r_v)
# Spline in the Optical/IR
oirmask = ~uvmask
if np.any(oirmask):
k = spleval(self._spline, 1. / wave[oirmask].to('micron'))
res[oirmask] = self.a_v / self.r_v * (k + self.r_v)
return res.reshape(wave_shape)
def extinction_f99(wave, a_v, r_v=3.1):
"""Fitzpatrick (1999) extinction model.
Fitzpatrick (1999) [1]_ model which relies on the parametrization
of Fitzpatrick & Massa (1990) [2]_ in the UV (below 2700 A) and
spline fitting in the optical and IR. This function is defined
from 910 A to 6 microns, but note the claimed validity goes down
only to 1150 A. The optical spline points are not taken from F99
Table 4, but rather updated versions from E. Fitzpatrick (this
matches the Goddard IDL astrolib routine FM_UNRED).
{0}
References
----------
.. [1] Fitzpatrick, E. L. 1999, PASP, 111, 63
.. [2] Fitzpatrick, E. L. & Massa, D. 1990, ApJS, 72, 163
"""
f = ExtinctionF99(a_v, r_v)
return f(wave)
# fm07 knots for spline
_fm07_r_v = 3.1
_fm07_xknots = np.array([0., 0.25, 0.50, 0.75, 1., 1.e4/5530., 1.e4/4000.,
1.e4/3300., 1.e4/2700., 1.e4/2600.])
_fm07_kknots = cextinction.fm07kknots(_fm07_xknots)
try:
from scipy.interpolate import splmake
_fm07_spline = splmake(_fm07_xknots, _fm07_kknots, order=3)
except ImportError:
pass
def extinction_fm07(wave, a_v):
"""Fitzpatrick & Massa (2007) extinction model for R_V = 3.1.
The Fitzpatrick & Massa (2007) [1]_ model, which has a slightly
different functional form from that of Fitzpatrick (1999) [3]_
(`extinction_f99`). Fitzpatrick & Massa (2007) claim it is
preferable, although it is unclear if signficantly so (Gordon et
al. 2009 [2]_). Defined from 910 A to 6 microns.
.. note :: This model is not R_V dependent.
{0}
References
----------
.. [1] Fitzpatrick, E. L. & Massa, D. 2007, ApJ, 663, 320
.. [2] Gordon, K. D., Cartledge, S., & Clayton, G. C. 2009, ApJ, 705, 1320
.. [3] Fitzpatrick, E. L. 1999, PASP, 111, 63
"""
if not HAS_SCIPY:
raise ImportError('To use this function scipy needs to be installed')
from scipy.interpolate import spleval
wave_shape = wave.shape
wave = _process_wave(wave)
_check_wave(wave, 909.091 * u.angstrom, 6.0 * u.micron)
res = np.empty_like(wave.__array__(), dtype=np.float64)
# Simple analytic function in the UV
uvmask = wave < (2700. * u.angstrom)
if np.any(uvmask):
res[uvmask] = cextinction.fm07uv(wave[uvmask].value, a_v)
# Spline in the Optical/IR
oirmask = ~uvmask
if np.any(oirmask):
k = spleval(_fm07_spline, (1. / wave[oirmask].to('micron')).value)
res[oirmask] = a_v / _fm07_r_v * (k + _fm07_r_v)
return res.reshape(wave_shape)
prefix = path.join('data', 'extinction_models', 'kext_albedo_WD_MW')
_wd01_fnames = {'3.1': prefix + '_3.1B_60.txt',
'4.0': prefix + '_4.0B_40.txt',
'5.5': prefix + '_5.5B_30.txt'}
_d03_fnames = {'3.1': prefix + '_3.1A_60_D03_all.txt',
'4.0': prefix + '_4.0A_40_D03_all.txt',
'5.5': prefix + '_5.5A_30_D03_all.txt'}
del prefix
class ExtinctionWD01(object):
"""Weingartner and Draine (2001) extinction model with fixed R_V.
Parameters
----------
r_v : float
Relation between specific and total extinction, ``a_v = r_v * ebv``.
Examples
--------
Create a callable that gives the extinction law for a given ``r_v``
and use it:
>>> f = ExtinctionWD01(3.1)
>>> f(3000., a_v=1.)
Arrays are also accepted and ``ebv`` can be specified instead of ``a_v``:
>>> f([3000., 4000.], ebv=1./3.1)
"""
def __init__(self, a_v, r_v):
if not HAS_SCIPY:
raise ImportError('To use this function scipy needs to be installed')
from scipy.interpolate import interp1d
self.a_v = a_v
self.r_v = r_v
fname_key = [item for item in _wd01_fnames.keys() if np.isclose(
float(item), self.r_v)]
if len(fname_key) == 0:
raise ValueError("model only defined for r_v in [3.1, 4.0, 5.5]")
elif len(fname_key) == 1:
fname = _wd01_fnames[fname_key[0]]
else:
raise ValueError('The given float {0} matches multiple available'
' r_vs [3.1, 4.0, 5.5] - unexpected code error')
fname = apydata.get_pkg_data_filename(fname)
data = ascii.read(fname, Reader=ascii.FixedWidth, data_start=51,
names=['wave', 'albedo', 'avg_cos', 'C_ext',
'K_abs'],
col_starts=[0, 10, 18, 25, 35],
col_ends=[9, 17, 24, 34, 42], guess=False)
# Reverse entries so that they ascend in x (needed for the spline).
waveknots = np.asarray(data['wave'])[::-1]
cknots = np.asarray(data['C_ext'])[::-1]
xknots = 1. / waveknots # Values in inverse microns.
# Create a spline just to get normalization.
spline = interp1d(xknots, cknots)
cknots = cknots / spline(1.e4 / 5495.) # Normalize cknots.
self._spline = interp1d(xknots, cknots)
def __call__(self, wave):
wave_shape = wave.shape
wave = _process_wave(wave)
x = (1 / wave).to('1/micron')
res = self.a_v * self._spline(x.value)
return res.reshape(wave_shape)
def extinction_wd01(wave, a_v, r_v=3.1):
"""Weingartner and Draine (2001) extinction model.
The Weingartner & Draine (2001) [1]_ dust model. This model is a
calculation of the interstellar extinction using a dust model of
carbonaceous grains and amorphous silicate grains. The
carbonaceous grains are like PAHs when small and like graphite
when large. This model is evaluated at discrete wavelengths and
interpolated between these wavelengths. Grid goes from 1 A to 1000
microns. The model has been calculated for three different grain
size distributions which produce interstellar exinctions that look
like 'ccm89' at Rv = 3.1, Rv = 4.0 and Rv = 5.5. No interpolation
to other Rv values is performed, so this model can be evaluated
only for these values.
The dust model gives the extinction per H nucleon. For
consistency with other extinction laws we normalize this
extinction law so that it is equal to 1.0 at 5495 angstroms.
.. note :: Model is not an analytic function of R_V. Only ``r_v``
values of 3.1, 4.0 and 5.5 are accepted.
.. note :: This function reads a table from a file on disk on each call.
For repeated calls with the same ``r_v``, it will be far faster
to use the class-based interface `ExtinctionWD01`.
{0}
See Also
--------
ExtinctionWD01
References
----------
.. [1] Weingartner, J.C. & Draine, B.T. 2001, ApJ, 548, 296
"""
f = ExtinctionWD01(a_v, r_v)
return f(wave)
class ExtinctionD03(ExtinctionWD01):
"""Draine (2003) extinction model with fixed R_V.
Parameters
----------
r_v : float
Relation between specific and total extinction, ``a_v = r_v * ebv``.
Examples
--------
Create a callable that gives the extinction law for a given ``r_v``
and use it:
>>> f = ExtinctionWD01(3.1)
>>> f(3000., a_v=1.)
Arrays are also accepted and ``ebv`` can be specified instead of ``a_v``:
>>> f([3000., 4000.], ebv=1./3.1)
"""
def __init__(self, a_v, r_v):
if not HAS_SCIPY:
raise ImportError('To use this function scipy needs to be installed')
from scipy.interpolate import interp1d
super(ExtinctionD03, self).__init__(a_v, r_v)
fname_key = [item for item in _wd01_fnames.keys() if np.isclose(
float(item), self.r_v)]
if len(fname_key) == 0:
raise ValueError("model only defined for r_v in [3.1, 4.0, 5.5]")
elif len(fname_key) == 1:
fname = _d03_fnames[fname_key[0]]
else:
raise ValueError('The given float {0} matches multiple available'
' r_vs [3.1, 4.0, 5.5] - unexpected code error')
fname = apydata.get_pkg_data_filename(fname)
data = ascii.read(fname, Reader=ascii.FixedWidth, data_start=67,
names=['wave', 'albedo', 'avg_cos', 'C_ext',
'K_abs', 'avg_cos_sq', 'comment'],
col_starts=[0, 12, 20, 27, 37, 47, 55],
col_ends=[11, 19, 26, 36, 46, 54, 80], guess=False)
xknots = 1. / np.asarray(data['wave'])
cknots = np.asarray(data['C_ext'])
# Create a spline just to get normalization.
spline = interp1d(xknots, cknots)
cknots = cknots / spline((1. / (5495. * u.angstrom)).to('1/micron').value) # Normalize cknots.
self._spline = interp1d(xknots, cknots)
def extinction_d03(wave, a_v, r_v=3.1):
"""Draine (2003) extinction model.
The Draine (2003) [2]_ update to WD01 [1]_ where the
carbon/PAH abundances relative to 'wd01' have been reduced by a
factor of 0.93.
The dust model gives the extinction per H nucleon. For
consistency with other extinction laws we normalize this
extinction law so that it is equal to 1.0 at 5495 angstroms.
.. note :: Model is not an analytic function of R_V. Only ``r_v``
values of 3.1, 4.0 and 5.5 are accepted.
{0}
References
----------
.. [1] Weingartner, J.C. & Draine, B.T. 2001, ApJ, 548, 296
.. [2] Draine, B.T. 2003, ARA&A, 41, 241
"""
f = ExtinctionD03(a_v, r_v)
return f(wave)
_extinction_models = {'ccm89': extinction_ccm89,
'od94': extinction_od94,
'gcc09': extinction_gcc09,
'f99': extinction_f99,
'fm07': extinction_fm07,
'wd01': extinction_wd01,
'd03': extinction_d03}
def extinction(wave, a_v, r_v=3.1, model='od94'):
"""Generic interface for all extinction model functions.
Parameters
----------
wave : float or list_like
Wavelength(s) in angstroms.
a_v : float
Total V band extinction A(V), in magnitudes. A(V) = R_V * E(B-V).
r_v : float, optional
R_V parameter. Default is the standard Milky Way average of 3.1.
model : {'ccm89', 'od94', 'gcc09', 'f99', 'fm07', 'wd01', d03'}, optional
Use function ``extinction_[model]``. E.g., for 'ccm89', the function
``extinction_ccm89`` is used.
Returns
-------
extinction : float or `~numpy.ndarray`
Extinction in magnitudes at given wavelengths.
See Also
--------
extinction_ccm89
extinction_od94
extinction_gcc09
extinction_f99
extinction_fm07
extinction_wd01
extinction_d03
reddening
Notes
-----
**Visual comparison of models**
The plot below shows a comparison of the models for
``r_v=3.1``. The shaded regions show the limits of claimed
validity for the f99 model (> 1150 A) and the ccm89/od94 models (>
1250 A). The vertical dotted lines indicate transition wavelengths in
the models (3030.3 A and 9090.9 A for ccm89, od94 and gcc09;
2700. A for f99, fm07).
.. plot::
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
from specutils.extinction import extinction
models = ['ccm89', 'od94', 'gcc09', 'f99', 'fm07','wd01','d03']
wave = np.logspace(np.log10(910.), np.log10(30000.), 2000)
a_lambda = {model: extinction(wave, a_v=1., model=model)
for model in models}
fig = plt.figure(figsize=(8.5, 6.))
ax = plt.axes()
for model in models:
plt.plot(wave, a_lambda[model], label=model)
plt.axvline(x=2700., ls=':', c='k')
plt.axvline(x=3030.3030, ls=':', c='k')
plt.axvline(x=9090.9091, ls=':', c='k')
plt.axvspan(wave[0], 1150., fc='0.8', ec='none', zorder=-1000)
plt.axvspan(1150., 1250., fc='0.9', ec='none', zorder=-1000)
plt.text(0.67, 0.95, '$R_V = 3.1$', transform=ax.transAxes, va='top',
size='x-large')
plt.ylabel('Extinction ($A(\lambda)$ / $A_V$)')
plt.legend()
plt.setp(ax.get_xticklabels(), visible=False)
divider = make_axes_locatable(ax)
axresid = divider.append_axes("bottom", size=2.0, pad=0.2, sharex=ax)
for model in models:
plt.plot(wave, a_lambda[model] - a_lambda['f99'])
plt.axvline(x=2700., ls=':', c='k')
plt.axvline(x=3030.3030, ls=':', c='k')
plt.axvline(x=9090.9091, ls=':', c='k')
plt.axvspan(wave[0], 1150., fc='0.8', ec='none', zorder=-1000)
plt.axvspan(1150., 1250., fc='0.9', ec='none', zorder=-1000)
plt.xlim(wave[0], wave[-1])
plt.ylim(ymin=-0.4,ymax=0.4)
plt.ylabel('residual from f99')
plt.xlabel('Wavelength ($\AA$)')
ax.set_xscale('log')
axresid.set_xscale('log')
plt.tight_layout()
fig.show()
Examples
--------
>>> wave = [2000., 2500., 3000.]
>>> extinction(wave, a_v=1., r_v=3.1, model='f99')
array([ 2.76225609, 2.27590036, 1.79939955])
The extinction scales linearly with ``a_v``. This means
that when calculating extinction for multiple values of ``a_v``, one can compute extinction ahead of time for a given set of
wavelengths and then scale by ``a_v`` or ``ebv`` later. For example:
>>> a_lambda_over_a_v = extinction(wave, a_v=1.)
>>> a_v = 0.5
>>> a_lambda = a_v * a_lambda_over_a_v
"""
model = model.lower()
if model not in _extinction_models:
raise ValueError('unknown model: {0}'.format(model))
if model == 'fm07':
if not np.isclose(r_v, 3.1):
raise ValueError('r_v must be 3.1 for fm07 model')
return _extinction_models[model](wave, a_v=a_v)
else:
return _extinction_models[model](wave, a_v=a_v, r_v=r_v)
def reddening(wave, a_v, r_v=3.1, model='od94'):
"""Inverse of flux transmission fraction at given wavelength(s).
Parameters
----------
wave : float or list_like
Wavelength(s) in angstroms at which to evaluate the reddening.
a_v : float
Total V band extinction, in magnitudes. A(V) = R_V * E(B-V).
r_v : float, optional
R_V parameter. Default is the standard Milky Way average of 3.1.
model : {'ccm89', 'od94', 'gcc09', 'f99', 'fm07'}, optional
Returns
-------
reddening : float or `~numpy.ndarray`
Inverse of flux transmission fraction, equivalent to
``10**(0.4 * extinction(wave))``. To deredden spectra,
multiply flux values by these value(s). To redden spectra, divide
flux values by these value(s).
See Also
--------
extinction
"""
return 10**(0.4 * extinction(wave, a_v, r_v=r_v, model=model))
_func_doc = """
Parameters
----------
wave : float or list_like
Wavelength(s) in angstroms.
a_v : float
A(V) total V band extinction,
in magnitudes.
r_v : float, optional
R_V parameter. Default is the standard Milky Way average of 3.1.
Returns
-------
extinction : `~numpy.ndarray`
Extinction in magnitudes at given wavelengths.
"""
for func in [extinction_ccm89, extinction_od94, extinction_gcc09,
extinction_f99, extinction_fm07, extinction_wd01,
extinction_d03]:
func.__doc__ = func.__doc__.format(_func_doc)
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