AIRSplorer

Convenience tools for analysis and data manipulation related to ARIEL AIRS. The package provides utilities for working with images and cubes, basic flux calculations, coordinate conversions, mask handling, I/O helpers, and common plotting routines.

• Python ≥ 3.11
• License: MIT
• Repository: https://github.com/ccossou/airsplorer

Key features

• Image and cube manipulation (load, save, simple transforms)
• Basic photometry and flux/statistics utilities
• Sky/pixel coordinate conversions
• Mask creation, application, and operations
• Plotting helpers and tabulated outputs
• Test suite for core functionality

Indicative modules:

• coord: coordinate conversions and utilities
• flux: simple photometry and flux-related computations
• imager / imlib: image operations
• mask: mask creation and manipulation
• plot: common plotting helpers
• utils: assorted utility functions

Installation

From PyPI (when available):

python -m pip install airsplorer

Update to latest version of airsplorer

python -m pip install  --upgrade airsplorer

From source (development):

git clone https://github.com/ccossou/airsplorer.git
cd airsplorer
python -m pip install -e .

Main runtime dependencies are installed automatically.

On windows, one might have to install extra dependencies, namely, Visual C++ Redistributable. Go to Visual Studio, go at the bottom of the page, to the Downloads/Autre outils, infrastructures et redistribuables and take Microsoft Visual C++ v14 Redistributable x64 (or newer if any).

On Linux, I had to install:

sudo apt install libxcb-cursor-dev

On Mac, the dependencies should be installed automatically.

Quick start

# Example imports (see function docstrings for exact APIs)
from airsplorer import coord, flux, imager, mask, utils, read, write, plot

# Loading and saving (adjust paths and formats to your data)
# data = read.load_image("path/to/file.fits")
# write.save_image(data, "path/to/output.fits")

# Image operations
# img2 = imager.normalize(data)
# m = mask.create_threshold_mask(img2, threshold=5.0)
# img3 = imager.apply_mask(img2, m)

# Flux calculations
# f = flux.aperture_photometry(img3, center=(x0, y0), radius=5)

# Coordinate conversions
# px, py = coord.sky_to_pixel(ra, dec, wcs_header)
# ra2, dec2 = coord.pixel_to_sky(px, py, wcs_header)

# Plotting
# plot.imshow(img3, title="Processed image")

Notes:

• Check each function’s docstring for signatures, units, and options.
• Adjust examples to your data formats and WCS headers.

License and citation

• License: MIT
• If you use airsplorer in scientific work, please cite the repository and the software version you used. A DOI or BibTeX entry may be added in the future.