import torch
from ...param import forward
from ...backend_obj import ArrayLike
from ...utils.decorators import ignore_numpy_warnings
from .._shared_methods import parametric_initialize, parametric_segment_initialize
from ...utils.parametric_profiles import sersic_np
from .. import func
def _x0_func(model, R, F):
return 2.0, R[4], 10 ** F[4]
[docs]
class SersicMixin:
"""Sersic radial light profile (Sersic 1963).
This is a classic profile used widely in galaxy modelling. It can be a good
starting point for many extended objects. The functional form of the Sersic
profile is defined as:
.. math::
I(R) = I_e \\exp(- b_n((R/R_e)^{1/n} - 1))
It is a generalization of a gaussian, exponential, and de-Vaucouleurs
profile. The Sersic index ``n`` controls the shape of the profile, with ``n=1``
being an exponential profile, ``n=4`` being a de-Vaucouleurs profile, and
``n=0.5`` being a Gaussian profile.
:param n: Sersic index which controls the shape of the brightness profile
:param Re: half light radius, also called effective radius [arcsec]
:param Ie: intensity at the half light radius [flux/arcsec^2]
"""
_model_type = "sersic"
_parameter_specs = {
"n": {
"units": "none",
"valid": (0.36, 8),
"shape": (),
"dynamic": True,
"description": "Sersic index which controls the shape of the brightness profile",
},
"Re": {
"units": "arcsec",
"valid": (0, None),
"shape": (),
"dynamic": True,
"description": "half light radius, also called effective radius [arcsec]",
},
"Ie": {
"units": "flux/arcsec^2",
"valid": (0, None),
"shape": (),
"dynamic": True,
"description": "intensity at the half light radius [flux/arcsec^2]",
},
}
[docs]
@torch.no_grad()
@ignore_numpy_warnings
def initialize(self):
super().initialize()
parametric_initialize(
self, self.target[self.window], sersic_np, ("n", "Re", "Ie"), _x0_func
)
[docs]
@forward
def radial_model(self, R: ArrayLike, n: ArrayLike, Re: ArrayLike, Ie: ArrayLike) -> ArrayLike:
return func.sersic(R, n, Re, Ie)
[docs]
class iSersicMixin:
"""Sersic radial light profile (Sersic 1963).
This is a classic profile used widely in galaxy modelling. It can be a good
starting point for many extended objects. The functional form of the Sersic
profile is defined as:
.. math::
I(R) = I_e \\exp(- b_n((R/R_e)^{1/n} - 1))
It is a generalization of a gaussian, exponential, and de-Vaucouleurs
profile. The Sersic index ``n`` controls the shape of the profile, with ``n=1``
being an exponential profile, ``n=4`` being a de-Vaucouleurs profile, and
``n=0.5`` being a Gaussian profile.
``n``, ``Re``, and ``Ie`` are batched by their first dimension, allowing for
multiple Sersic profiles to be defined at once.
:param n: Sersic index which controls the shape of the brightness profile
:param Re: half light radius, also called effective radius [arcsec]
:param Ie: intensity at the half light radius [flux/arcsec^2]
"""
_model_type = "sersic"
_parameter_specs = {
"n": {
"units": "none",
"valid": (0.36, 8),
"shape": (None,),
"dynamic": True,
"description": "Sersic index which controls the shape of the brightness profile",
},
"Re": {
"units": "arcsec",
"valid": (0, None),
"shape": (None,),
"dynamic": True,
"description": "half light radius, also called effective radius",
},
"Ie": {
"units": "flux/arcsec^2",
"valid": (0, None),
"shape": (None,),
"dynamic": True,
"description": "intensity at the half light radius, also called effective intensity",
},
}
[docs]
@torch.no_grad()
@ignore_numpy_warnings
def initialize(self):
super().initialize()
parametric_segment_initialize(
model=self,
target=self.target[self.window],
prof_func=sersic_np,
params=("n", "Re", "Ie"),
x0_func=_x0_func,
segments=self.segments,
)
[docs]
@forward
def iradial_model(
self, i: int, R: ArrayLike, n: ArrayLike, Re: ArrayLike, Ie: ArrayLike
) -> ArrayLike:
return func.sersic(R, n[i], Re[i], Ie[i])
[docs]
class SersicPSFMixin:
"""Sersic radial light profile (Sersic 1963).
This is a classic profile used widely in galaxy modelling, though it
is simply a generalization of a Gaussian. It can be a good starting
point for many objects. The functional form of the Sersic profile is
defined as:
.. math::
I(R) = I_e \\exp(- b_n((R/R_e)^{1/n} - 1))
It includes the gaussian, exponential, and de-Vaucouleurs
profiles. The Sersic index ``n`` controls the shape of the profile, with ``n=1``
being an exponential profile, ``n=4`` being a de-Vaucouleurs profile, and
``n=0.5`` being a Gaussian profile.
:param n: Sersic index which controls the shape of the brightness profile
:param Re: half light radius, also called effective radius [pix]
:param Ie: intensity at the half light radius, also called effective intensity [flux/pix^2]
"""
_model_type = "sersic"
_parameter_specs = {
"n": {
"units": "none",
"valid": (0.36, 8),
"shape": (),
"dynamic": True,
"description": "Sersic index which controls the shape of the brightness profile",
},
"Re": {
"units": "pix",
"valid": (0, None),
"shape": (),
"dynamic": True,
"description": "half light radius, also called effective radius",
},
"Ie": {
"units": "flux/pix^2",
"valid": (0, None),
"shape": (),
"dynamic": False,
"value": 1.0,
"description": "intensity at the half light radius, also called effective intensity",
},
}
[docs]
@torch.no_grad()
@ignore_numpy_warnings
def initialize(self):
super().initialize()
parametric_initialize(
self, self.target[self.window], sersic_np, ("n", "Re", "Ie"), _x0_func
)
[docs]
@forward
def radial_model(self, R: ArrayLike, n: ArrayLike, Re: ArrayLike, Ie: ArrayLike) -> ArrayLike:
return func.sersic(R, n, Re, Ie)
