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]