import torch
from ...param import forward
from ...backend_obj import ArrayLike
from ...utils.decorators import ignore_numpy_warnings
from ...utils.parametric_profiles import ferrer_np
from .._shared_methods import parametric_initialize, parametric_segment_initialize
from .. import func
[docs]
def x0_func(model_params, R, F):
return R[5], 1, 1, 10 ** F[0]
[docs]
class FerrerMixin:
"""Modified Ferrer radial light profile (Binney & Tremaine 1987).
This model has a relatively flat brightness core and then a truncation. It
is used in specialized circumstances such as fitting the bar of a galaxy.
The functional form of the Modified Ferrer profile is defined as:
$$I(R) = I_0 \\left(1 - \\left(\\frac{R}{r_{\\rm out}}\\right)^{2-\\beta}\\right)^{\\alpha}$$
where `rout` is the outer truncation radius, `alpha` controls the steepness
of the truncation, `beta` controls the shape, and `I0` is the intensity at
the center of the profile.
**Parameters:**
- `rout`: Outer truncation radius in arcseconds.
- `alpha`: Inner slope parameter.
- `beta`: Outer slope parameter.
- `I0`: Intensity at the center of the profile in flux/arcsec^2
"""
_model_type = "ferrer"
_parameter_specs = {
"rout": {"units": "arcsec", "valid": (0.0, None), "shape": (), "dynamic": True},
"alpha": {"units": "unitless", "valid": (0, 10), "shape": (), "dynamic": True},
"beta": {"units": "unitless", "valid": (0, 2), "shape": (), "dynamic": True},
"I0": {"units": "flux/arcsec^2", "valid": (0, None), "shape": (), "dynamic": True},
}
[docs]
@torch.no_grad()
@ignore_numpy_warnings
def initialize(self):
super().initialize()
parametric_initialize(
self,
self.target[self.window],
ferrer_np,
("rout", "alpha", "beta", "I0"),
x0_func,
)
[docs]
@forward
def radial_model(
self, R: ArrayLike, rout: ArrayLike, alpha: ArrayLike, beta: ArrayLike, I0: ArrayLike
) -> ArrayLike:
return func.ferrer(R, rout, alpha, beta, I0)
[docs]
class iFerrerMixin:
"""Modified Ferrer radial light profile (Binney & Tremaine 1987).
This model has a relatively flat brightness core and then a truncation. It
is used in specialized circumstances such as fitting the bar of a galaxy.
The functional form of the Modified Ferrer profile is defined as:
$$I(R) = I_0 \\left(1 - \\left(\\frac{R}{r_{\\rm out}}\\right)^{2-\\beta}\\right)^{\\alpha}$$
where `rout` is the outer truncation radius, `alpha` controls the steepness
of the truncation, `beta` controls the shape, and `I0` is the intensity at
the center of the profile.
`rout`, `alpha`, `beta`, and `I0` are batched by their first dimension,
allowing for multiple Ferrer profiles to be defined at once.
**Parameters:**
- `rout`: Outer truncation radius in arcseconds.
- `alpha`: Inner slope parameter.
- `beta`: Outer slope parameter.
- `I0`: Intensity at the center of the profile in flux/arcsec^2
"""
_model_type = "ferrer"
_parameter_specs = {
"rout": {"units": "arcsec", "valid": (0.0, None), "shape": (None,), "dynamic": True},
"alpha": {"units": "unitless", "valid": (0, 10), "shape": (None,), "dynamic": True},
"beta": {"units": "unitless", "valid": (0, 2), "shape": (None,), "dynamic": True},
"I0": {"units": "flux/arcsec^2", "valid": (0.0, None), "shape": (None,), "dynamic": True},
}
[docs]
@torch.no_grad()
@ignore_numpy_warnings
def initialize(self):
super().initialize()
parametric_segment_initialize(
model=self,
target=self.target[self.window],
prof_func=ferrer_np,
params=("rout", "alpha", "beta", "I0"),
x0_func=x0_func,
segments=self.segments,
)
[docs]
@forward
def iradial_model(
self,
i: int,
R: ArrayLike,
rout: ArrayLike,
alpha: ArrayLike,
beta: ArrayLike,
I0: ArrayLike,
) -> ArrayLike:
return func.ferrer(R, rout[i], alpha[i], beta[i], I0[i])
[docs]
class FerrerPSFMixin:
"""Modified Ferrer radial light profile (Binney & Tremaine 1987).
This model has a relatively flat brightness core and then a truncation. It
is used in specialized circumstances such as fitting the bar of a galaxy.
The functional form of the Modified Ferrer profile is defined as:
$$I(R) = I_0 \\left(1 - \\left(\\frac{R}{r_{\\rm out}}\\right)^{2-\\beta}\\right)^{\\alpha}$$
where `rout` is the outer truncation radius, `alpha` controls the steepness
of the truncation, `beta` controls the shape, and `I0` is the intensity at
the center of the profile.
**Parameters:**
- `rout`: Outer truncation radius in pixels.
- `alpha`: Inner slope parameter.
- `beta`: Outer slope parameter.
- `I0`: Intensity at the center of the profile in flux/pix^2
"""
_model_type = "ferrer"
_parameter_specs = {
"rout": {"units": "pix", "valid": (0.0, None), "shape": (), "dynamic": True},
"alpha": {"units": "unitless", "valid": (0, 10), "shape": (), "dynamic": True},
"beta": {"units": "unitless", "valid": (0, 2), "shape": (), "dynamic": True},
"I0": {
"units": "flux/pix^2",
"valid": (0, None),
"shape": (),
"dynamic": False,
"value": 1.0,
},
}
[docs]
@torch.no_grad()
@ignore_numpy_warnings
def initialize(self):
super().initialize()
parametric_initialize(
self,
self.target[self.window],
ferrer_np,
("rout", "alpha", "beta", "I0"),
x0_func,
)
[docs]
@forward
def radial_model(
self, R: ArrayLike, rout: ArrayLike, alpha: ArrayLike, beta: ArrayLike, I0: ArrayLike
) -> ArrayLike:
return func.ferrer(R, rout, alpha, beta, I0)
