Source code for astrophot.models.planesky
import numpy as np
import torch
from .sky_model_object import SkyModel
from ..utils.decorators import ignore_numpy_warnings, combine_docstrings
from ..param import forward
from ..backend_obj import backend, ArrayLike
__all__ = ["PlaneSky"]
[docs]
@combine_docstrings
class PlaneSky(SkyModel):
"""Sky background model using a tilted plane for the sky flux. The brightness for each pixel is defined as:
$$I(X, Y) = I_0 + X*\\delta_x + Y*\\delta_y$$
where $I(X,Y)$ is the brightness as a function of image position $X, Y$,
$I_0$ is the central sky brightness value, and $\\delta_x, \\delta_y$ are the slopes of
the sky brightness plane.
**Parameters:**
- `I0`: central sky brightness value
- `delta`: Tensor for slope of the sky brightness in each image dimension
"""
_model_type = "plane"
_parameter_specs = {
"I0": {"units": "flux/arcsec^2", "shape": (), "dynamic": True},
"delta": {"units": "flux/arcsec", "shape": (2,), "dynamic": True},
}
usable = True
[docs]
@torch.no_grad()
@ignore_numpy_warnings
def initialize(self):
super().initialize()
if not self.I0.initialized:
dat = backend.to_numpy(self.target[self.window]._data).copy()
mask = backend.to_numpy(self.target[self.window]._mask)
dat[mask] = np.median(dat[~mask])
self.I0.value = np.median(dat) / self.target.pixel_area.item()
if not self.delta.initialized:
self.delta.value = [0.0, 0.0]
[docs]
@forward
def brightness(self, x: ArrayLike, y: ArrayLike, I0: ArrayLike, delta: ArrayLike) -> ArrayLike:
return I0 + x * delta[0] + y * delta[1]