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lightcurver

lightcurver: A Python Pipeline for Precise Photometry of Multiple-Epoch Wide-Field Images - Published in JOSS (2024)

https://github.com/duxfrederic/lightcurver

Science Score: 93.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 1 DOI reference(s) in JOSS metadata
  • ✓
    Academic publication links
    Links to: joss.theoj.org
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ✓
    JOSS paper metadata
    Published in Journal of Open Source Software

Keywords

astronomy observational-cosmology photometry photometry-pipeline

Scientific Fields

Artificial Intelligence and Machine Learning Computer Science - 40% confidence
Last synced: 4 months ago · JSON representation

Repository

A pipeline for precise extraction of light curves through forward modelling of a region from time-series wide-field astronomical images

Basic Info
Statistics
  • Stars: 10
  • Watchers: 3
  • Forks: 0
  • Open Issues: 5
  • Releases: 10
Topics
astronomy observational-cosmology photometry photometry-pipeline
Created almost 2 years ago · Last pushed 6 months ago
Metadata Files
Readme License

README.md

logo

JOSS tests Docs python pypi License: GPL v3

lightcurver

Welcome to lightcurver! This is a photometry library leveraging STARRED, best used with time series of wide-field images. You can read more about it in the documentation.

Essentially, lightcurver provides the infrastructure to - prepare a Point Spread Function (PSF) model for each wide-field image, - precisely calibrate the relative zero point between each image.

This enables STARRED to model the pixels of the region of interest (ROI), yielding of course high quality light curves of the point sources in the ROI, but also recovering the subpixel information to provide a high signal-to-noise ratio/resolution of the ROI itself. The example below shows a cutout of a wide-field image (one in a set of a hundred), the fitted high resolution model, and the Hubble Space Telescope image of the same region.

example_deconvolution

Features

  • Plate solving: uses Astrometry.net to establish the footprint of each frame.
  • Gaia reference stars: leverages Gaia information to select the right reference stars in the field of view of each frame.
  • Preserves sub-pixel information: never interpolates, essential to preserve the sub-pixel information that can be recovered by STARRED in a multi-epoch forward modelling.
  • Incremental: uses SQL queries to dynamically determine which process needs be executed on which frame.
  • Semi-automatic: create a yaml configuration file once for the first few frames, then run the pipeline whenever a new frame is added, providing auto-updating light curves.

Getting Started

  1. Installation: the short version, install via pip:

    pip install lightcurver The slightly longer version, in case you plan on using a GPU or the plate solving.

  2. Usage: Adapt the yaml config file template, then run the pipeline with bash lc_run /path/to/config.yaml The pipeline is incremental, but in a scenario of testing, you can run specific steps only, for example: bash lc_run /path/to/config.yaml --start stamp_extraction --stop psf_modeling (The names of the pipeline steps/tasks are listed upon running lc_run -h.)

  3. Tutorial: follow the tutorial of the documentation, which provides a dataset you can experiment with. You can also test your installation with a subset of the dataset provided in the tutorial: bash cd /clone/of/lightcurver pytest .

Contributing

If you're encountering problems, then I would like to hear about them and will try to fix them. Feel free to create an issue in this repository. If you're finding this package useful and want to contribute, please create a pull request after forking the repository. If you need general help, feel free to reach out!

License

lightcurver is licensed under the GPL v3.0 License. See the LICENSE file for more details.

The implemented processing steps

This is an overview of the steps taken by the pipeline. flowdiagram

Owner

  • Name: Frédéric Dux
  • Login: duxfrederic
  • Kind: user

JOSS Publication

lightcurver: A Python Pipeline for Precise Photometry of Multiple-Epoch Wide-Field Images
Published
October 15, 2024
DOI
Volume 9, Issue 102, Page 6775
Authors
Frédéric Dux ORCID
European Southern Observatory, Alonso de Córdova 3107, Vitacura, Santiago, Chile, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland
Editor
Ivelina Momcheva ORCID
Tags
astronomy pipeline PSF photometry
View PDF Review Thread Software Archive

GitHub Events

Total
  • Create event: 14
  • Release event: 2
  • Issues event: 12
  • Watch event: 8
  • Delete event: 10
  • Issue comment event: 6
  • Push event: 74
  • Pull request review comment event: 3
  • Pull request event: 17
Last Year
  • Create event: 14
  • Release event: 2
  • Issues event: 12
  • Watch event: 8
  • Delete event: 10
  • Issue comment event: 6
  • Push event: 74
  • Pull request review comment event: 3
  • Pull request event: 17

Committers

Last synced: 5 months ago

All Time
  • Total Commits: 274
  • Total Committers: 1
  • Avg Commits per committer: 274.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 63
  • Committers: 1
  • Avg Commits per committer: 63.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Frédéric Dux d****c@g****m 274

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 20
  • Total pull requests: 37
  • Average time to close issues: 15 days
  • Average time to close pull requests: 1 day
  • Total issue authors: 2
  • Total pull request authors: 3
  • Average comments per issue: 0.5
  • Average comments per pull request: 0.14
  • Merged pull requests: 32
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 7
  • Pull requests: 17
  • Average time to close issues: 6 days
  • Average time to close pull requests: 4 days
  • Issue authors: 1
  • Pull request authors: 3
  • Average comments per issue: 0.57
  • Average comments per pull request: 0.18
  • Merged pull requests: 13
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • duxfrederic (19)
  • Onoddil (1)
Pull Request Authors
  • duxfrederic (53)
  • warrickball (4)
  • martin-millon (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 33 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 16
  • Total maintainers: 1
pypi.org: lightcurver

A thorough structure for precise photometry and forward modelling of time series of wide field images.

  • Versions: 16
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 33 Last month
Rankings
Dependent packages count: 9.7%
Average: 36.7%
Dependent repos count: 63.8%
Maintainers (1)
lithiumw
Last synced: 4 months ago

Dependencies

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pyproject.toml pypi
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  • astropy *
  • astroquery *
  • astroscrappy *
  • dill *
  • emcee *
  • ephem *
  • h5py *
  • jax *
  • jaxlib *
  • jaxopt *
  • matplotlib *
  • numpy *
  • optax *
  • pandas *
  • photutils *
  • pytest *
  • pyyaml *
  • scipy *
  • sep *
  • shapely *
  • starred-astro *
  • tqdm *
  • widefield_plate_solver *