import numpy as np
from scipy.stats import iqr
import torch
from .sky_model_object import Sky_Model
from ._shared_methods import select_target
from ..utils.decorators import ignore_numpy_warnings, default_internal
from ..param import Param_Unlock, Param_SoftLimits
__all__ = ["Plane_Sky"]
[docs]
class Plane_Sky(Sky_Model):
"""Sky background model using a tilted plane for the sky flux. The brightness for each pixel is defined as:
I(X, Y) = S + X*dx + Y*dy
where I(X,Y) is the brightness as a funcion of image position X Y,
S is the central sky brightness value, and dx dy are the slopes of
the sky brightness plane.
Parameters:
sky: central sky brightness value
delta: Tensor for slope of the sky brightness in each image dimension
"""
model_type = f"plane {Sky_Model.model_type}"
parameter_specs = {
"F": {"units": "flux/arcsec^2"},
"delta": {"units": "flux/arcsec"},
}
_parameter_order = Sky_Model._parameter_order + ("F", "delta")
useable = True
[docs]
@torch.no_grad()
@ignore_numpy_warnings
@select_target
@default_internal
def initialize(self, target=None, parameters=None, **kwargs):
super().initialize(target=target, parameters=parameters)
with Param_Unlock(parameters["F"]), Param_SoftLimits(parameters["F"]):
if parameters["F"].value is None:
parameters["F"].value = np.median(target[self.window].data.detach().cpu().numpy()) / target.pixel_area.item()
if parameters["F"].uncertainty is None:
parameters["F"].uncertainty = (
iqr(
target[self.window].data.detach().cpu().numpy(),
rng=(31.731 / 2, 100 - 31.731 / 2),
)
/ (2.0)
) / np.sqrt(np.prod(self.window.shape.detach().cpu().numpy()))
with Param_Unlock(parameters["delta"]), Param_SoftLimits(parameters["delta"]):
if parameters["delta"].value is None:
parameters["delta"].value = [0.0, 0.0]
parameters["delta"].uncertainty = [self.default_uncertainty, self.default_uncertainty]
[docs]
@default_internal
def evaluate_model(self, X=None, Y=None, image=None, parameters=None, **kwargs):
if X is None:
Coords = image.get_coordinate_meshgrid()
X, Y = Coords - parameters["center"].value[..., None, None]
return (
image.pixel_area * parameters["F"].value
+ X * parameters["delta"].value[0]
+ Y * parameters["delta"].value[1]
)