"""Image data container.
This module and class primarily deals with images containing spatial
information.
"""
# isort: split
# Import required to remove circular dependencies from type checking.
from __future__ import annotations
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from lezargus.library import hint
# isort: split
import numpy as np
from lezargus.library import logging
from lezargus.library.container import LezargusContainerArithmetic
[docs]
class LezargusImage(LezargusContainerArithmetic):
"""Container to hold image and perform operations on it.
Attributes
----------
For all available attributes, see :py:class:`LezargusContainerArithmetic`.
"""
[docs]
def __init__(
self: LezargusImage,
data: hint.NDArray,
uncertainty: hint.NDArray | None = None,
wavelength: float | None = None,
wavelength_unit: str | hint.Unit | None = None,
data_unit: str | hint.Unit | None = None,
spectral_scale: float | None = None,
pixel_scale: float | None = None,
slice_scale: float | None = None,
mask: hint.NDArray | None = None,
flags: hint.NDArray | None = None,
header: hint.Header | None = None,
) -> None:
"""Instantiate the spectra class.
Parameters
----------
wavelength : ndarray
The wavelength axis of the spectral component of the data, if any.
The unit of wavelength is typically in meters; but, check the
:py:attr:`wavelength_unit` value.
data : ndarray
The data stored in this container. The unit of the flux is typically
in W m^-2 m^-1; but, check the :py:attr:`data_unit` value.
uncertainty : ndarray
The uncertainty in the data of the spectra. The unit of the
uncertainty is the same as the data value; per
:py:attr:`uncertainty_unit`.
wavelength_unit : Astropy Unit
The unit of the wavelength array. If None, we assume unit-less.
data_unit : Astropy Unit
The unit of the data array. If None, we assume unit-less.
spectral_scale : float, default = None
The spectral scale, or spectral resolution, of the spectral
component, if any. Must be in meters per pixel. Scale is None if
none is provided.
pixel_scale : float, default = None
The E-W, "x" dimension, pixel plate scale of the spatial component,
if any. Must be in radians per pixel. Scale is None if none
is provided.
slice_scale : float, default = None
The N-S, "y" dimension, pixel slice scale of the spatial component,
if any. Must be in radians per slice-pixel. Scale is None if none
is provided.
mask : ndarray, default = None
A mask of the data, used to remove problematic areas. Where True,
the values of the data is considered masked. If None, we assume
the mask is all clear.
flags : ndarray, default = None
Flags of the data. These flags store metadata about the data. If
None, we assume that there are no harmful flags.
header : Header, default = None
A set of header data describing the data. Note that when saving,
this header is written to disk with minimal processing. We highly
suggest writing of the metadata to conform to the FITS Header
specification as much as possible. If None, we just use an
empty header.
"""
# The data must be two dimensional.
container_dimensions = 2
if len(data.shape) != container_dimensions:
logging.error(
error_type=logging.InputError,
message=(
"The input data for a LezargusImage instantiation has a"
" shape {data.shape}, which is not the expected two"
" dimension."
),
)
# The wavelength parameter is more metadata describing the image. It is
# completely optional. If provided, we add it.
if wavelength is not None:
set_wavelength = np.array(float(wavelength))
else:
set_wavelength = np.array(None)
# Constructing the original class. We do not deal with WCS here because
# the base class does not support it. We do not involve units here as
# well for speed concerns. Both are handled during reading and writing.
super().__init__(
wavelength=set_wavelength,
data=data,
uncertainty=uncertainty,
wavelength_unit=wavelength_unit,
data_unit=data_unit,
spectral_scale=spectral_scale,
pixel_scale=pixel_scale,
slice_scale=slice_scale,
mask=mask,
flags=flags,
header=header,
)
[docs]
@classmethod
def read_fits_file(
cls: type[hint.Self],
filename: str,
) -> hint.Self:
"""Read a Lezargus image FITS file.
We load a Lezargus FITS file from disk. Note that this should only
be used for 2-D image files.
Parameters
----------
filename : str
The filename to load.
Returns
-------
cube : Self-like
The LezargusImage class instance.
"""
# Any pre-processing is done here.
# Loading the file.
spectra = cls._read_fits_file(filename=filename)
# Any post-processing is done here.
# All done.
return spectra
[docs]
def write_fits_file(
self: hint.Self,
filename: str,
overwrite: bool = False,
) -> None:
"""Write a Lezargus image FITS file.
We write a Lezargus FITS file to disk.
Parameters
----------
filename : str
The filename to write to.
overwrite : bool, default = False
If True, overwrite file conflicts.
Returns
-------
None
"""
# Any pre-processing is done here.
# Saving the file.
self._write_fits_file(filename=filename, overwrite=overwrite)
# Any post-processing is done here.
# All done.