class LewisPatchDust(ExtinctionBase):
"""Mixin for a uniform dust distribution fitted from Lewis et al 15 Fig 17.
The maximum extinction is estimated from a Draine et al 2015 dust map.
Requires that the brick be known.
"""
def __init__(self, **kwargs):
# self.brick = kwargs.pop('brick', 23)
super(LewisPatchDust, self).__init__(**kwargs)
def build_extinction(self):
"""Young and old dust at equal here."""
lewis = LewisDustLaw()
max_av = lewis.estimate_mean_extinction(self.poly)
av = np.random.uniform(low=mw_Av(),
high=max_av,
size=1000)
self.young_av = ExtinctionDistribution()
self.young_av.set_samples(av)
self.old_av = ExtinctionDistribution()
self.old_av.set_samples(av)
self.rel_extinction = phat_rel_extinction()
class LewisBrickDust(ExtinctionBase):
"""Mixin for a uniform dust distribution fitted from Lewis et al 15 Fig 17.
The maximum extinction is estimated from a Draine et al 2015 dust map.
Requires that the brick be known.
"""
def __init__(self, **kwargs):
self.brick = kwargs.pop('brick', 23)
super(LewisBrickDust, self).__init__(**kwargs)
def build_extinction(self):
"""Young and old dust at equal here."""
# Get the coordinate of the brick
# brick_fits = phat_brick_path(self.brick, 'F814W')
# wcs = astropy.io.WCS(brick_fits[0].header)
# poly = wcs.calc_footprint()
data = PhatCatalog(self.brick) # FIXME pretty brick-specific
poly = data.polygon
lewis = LewisDustLaw()
max_av = lewis.estimate_mean_extinction(poly)
av = np.random.uniform(low=mw_Av(), high=max_av, size=1000)
self.young_av = ExtinctionDistribution()
self.young_av.set_samples(av)
self.old_av = ExtinctionDistribution()
self.old_av.set_samples(av)
self.rel_extinction = phat_rel_extinction()
def build_extinction(self):
# Add MW dust screen
self.young_av = ExtinctionDistribution()
self.young_av.set_uniform(mw_Av())
self.old_av = ExtinctionDistribution()
self.old_av.set_uniform(mw_Av())
self.rel_extinction = phat_rel_extinction()
def build_extinction(self):
"""Young and old dust at equal here."""
lewis = LewisDustLaw()
max_av = lewis.estimate_mean_extinction(self.poly)
av = np.random.uniform(low=mw_Av(), high=max_av, size=1000)
self.young_av = ExtinctionDistribution()
self.young_av.set_samples(av)
self.old_av = ExtinctionDistribution()
self.old_av.set_samples(av)
self.rel_extinction = phat_rel_extinction()
class NoDust(ExtinctionBase):
"""Mixin for no dust."""
def __init__(self, **kwargs):
super(NoDust, self).__init__(**kwargs)
def build_extinction(self):
# Add MW dust screen
self.young_av = ExtinctionDistribution()
self.young_av.set_uniform(mw_Av())
self.old_av = ExtinctionDistribution()
self.old_av.set_uniform(mw_Av())
self.rel_extinction = phat_rel_extinction()
class PhatGaussianDust(ExtinctionBase):
"""Mixin for Gaussian dust distributions for PHAT filters."""
def __init__(self, **kwargs):
self._young_av = kwargs.pop('young_av', 1.0)
self._old_av = kwargs.pop('old_av', 0.5)
self._av_sigma_ratio = kwargs.pop('av_sigma_ratio', 0.5)
super(PhatGaussianDust, self).__init__(**kwargs)
def build_extinction(self):
# NOTE includes the E(V
self.young_av = ExtinctionDistribution()
if self._young_av > 0.:
av = np.random.normal(loc=self._young_av,
scale=self._young_av * self._av_sigma_ratio,
size=1000)
av[av < 0.] = 0.
self.young_av.set_samples(av + mw_Av())
else:
self.young_av.set_samples(np.zeros(1000) + mw_Av())
self.old_av = ExtinctionDistribution()
if self._old_av > 0.:
av = np.random.normal(loc=self._old_av,
scale=self._old_av * self._av_sigma_ratio,
size=1000)
av[av < 0.] = 0.
self.old_av.set_samples(av + mw_Av())
else:
self.old_av.set_samples(np.zeros(1000) + mw_Av())
self.rel_extinction = phat_rel_extinction()
def build_extinction(self):
# NOTE includes MW extinction from __init__
self.young_av = ExtinctionDistribution()
self.young_av.set_samples(
np.random.uniform(low=self._young_av,
high=self._young_av + self._young_dav,
size=1000))
self.old_av = ExtinctionDistribution()
self.old_av.set_samples(
np.random.uniform(low=self._old_av,
high=self._old_av + self._old_dav,
size=1000))
self.rel_extinction = phat_rel_extinction()
def build_extinction(self):
"""Young and old dust at equal here."""
lewis = LewisDustLaw()
max_av = lewis.estimate_mean_extinction(self.poly)
av = np.random.uniform(low=mw_Av(),
high=max_av,
size=1000)
self.young_av = ExtinctionDistribution()
self.young_av.set_samples(av)
self.old_av = ExtinctionDistribution()
self.old_av.set_samples(av)
self.rel_extinction = phat_rel_extinction()
def build_extinction(self):
"""Young and old dust at equal here."""
# Get the coordinate of the brick
# brick_fits = phat_brick_path(self.brick, 'F814W')
# wcs = astropy.io.WCS(brick_fits[0].header)
# poly = wcs.calc_footprint()
data = PhatCatalog(self.brick) # FIXME pretty brick-specific
poly = data.polygon
lewis = LewisDustLaw()
max_av = lewis.estimate_mean_extinction(poly)
av = np.random.uniform(low=mw_Av(), high=max_av, size=1000)
self.young_av = ExtinctionDistribution()
self.young_av.set_samples(av)
self.old_av = ExtinctionDistribution()
self.old_av.set_samples(av)
self.rel_extinction = phat_rel_extinction()
class LewisPatchDust(ExtinctionBase):
"""Mixin for a uniform dust distribution fitted from Lewis et al 15 Fig 17.
The maximum extinction is estimated from a Draine et al 2015 dust map.
Requires that the brick be known.
"""
def __init__(self, **kwargs):
# self.brick = kwargs.pop('brick', 23)
super(LewisPatchDust, self).__init__(**kwargs)
def build_extinction(self):
"""Young and old dust at equal here."""
lewis = LewisDustLaw()
max_av = lewis.estimate_mean_extinction(self.poly)
av = np.random.uniform(low=mw_Av(), high=max_av, size=1000)
self.young_av = ExtinctionDistribution()
self.young_av.set_samples(av)
self.old_av = ExtinctionDistribution()
self.old_av.set_samples(av)
self.rel_extinction = phat_rel_extinction()
def build_extinction(self):
# NOTE includes the E(V
self.young_av = ExtinctionDistribution()
if self._young_av > 0.:
av = np.random.normal(loc=self._young_av,
scale=self._young_av * self._av_sigma_ratio,
size=1000)
av[av < 0.] = 0.
self.young_av.set_samples(av + mw_Av())
else:
self.young_av.set_samples(np.zeros(1000) + mw_Av())
self.old_av = ExtinctionDistribution()
if self._old_av > 0.:
av = np.random.normal(loc=self._old_av,
scale=self._old_av * self._av_sigma_ratio,
size=1000)
av[av < 0.] = 0.
self.old_av.set_samples(av + mw_Av())
else:
self.old_av.set_samples(np.zeros(1000) + mw_Av())
self.rel_extinction = phat_rel_extinction()
class PhatStepDust(ExtinctionBase):
"""Mixin for Uniform dust distributions for PHAT filters."""
def __init__(self, **kwargs):
self._young_av = kwargs.pop('young_av', 0.0) + mw_Av()
self._old_av = kwargs.pop('old_av', 0.0) + mw_Av()
self._young_dav = kwargs.pop('young_dav', 1.0)
self._old_dav = kwargs.pop('old_dav', 1.0)
super(PhatStepDust, self).__init__(**kwargs)
def build_extinction(self):
# NOTE includes MW extinction from __init__
self.young_av = ExtinctionDistribution()
self.young_av.set_samples(
np.random.uniform(low=self._young_av,
high=self._young_av + self._young_dav,
size=1000))
self.old_av = ExtinctionDistribution()
self.old_av.set_samples(
np.random.uniform(low=self._old_av,
high=self._old_av + self._old_dav,
size=1000))
self.rel_extinction = phat_rel_extinction()