A Python library for exploring publicly available JWST data from the MAST archive.
Project description
Parallax
Parallax is a Python library for exploring publicly available JWST data from the MAST archive. It finds astronomical sources that existing catalogs have not yet characterized, cross-references them against SIMBAD, NED, and Gaia, and presents the results in terms an educated non-specialist can act on.
Installation
Requires Python 3.12 or later.
git clone https://github.com/teaguejg/parallax-jwst
cd parallax-jwst
pip install -e .
This installs all dependencies. PyQt6 is included for the desktop GUI.
Quick start
import parallax as par
# run the full pipeline on M92
report = par.survey.reduce("M92", instrument="NIRCAM")
print(f"Detected: {report.n_sources_detected}")
print(f"Unverified: {report.n_unverified}")
# launch the GUI
from parallax.gui import launch
launch()
reduce() downloads JWST images from MAST, runs source detection, queries
three catalogs, and writes JSON and markdown reports to data/reports/.
Validated targets
These targets have been tested end-to-end:
- M92 (NGC 6341) - globular cluster. ~23,800 sources detected, ~18,700 unverified candidates. Runs in under two minutes.
- NGC 3132 - Southern Ring Nebula. Use "NGC 3132" as the target string; "Southern Ring Nebula" does not resolve on MAST.
- Orion Bar - star-forming region. MAST has no Level 3 mosaic products for this target, only detector-level i2d files.
Configuration
All settings live in config.yaml in the project root. Key knobs:
detection.snr_threshold(default 3.0) - minimum signal-to-noise for a detection. Lower finds fainter sources but more noise.detection.min_pixels(default 25) - minimum connected pixels per source. Filters hot pixels and cosmic rays.detection.background_box_size(default 50) - background estimation tile size. Smaller values (20-25) work better near bright extended emission.resolver.search_radius_arcsec(default 2.0) - catalog cross-match radius. Increase if WCS alignment is imprecise.resolver.catalogs(default [SIMBAD, NED, GAIA]) - which catalogs to query.
Environment variables override config values using the prefix PARALLAX_ with
underscores between segments (e.g. PARALLAX_DETECTION_SNR_THRESHOLD=5.0).
Requirements
- astropy >= 5.3
- astroquery >= 0.4.8
- photutils >= 1.9
- matplotlib >= 3.7
- numpy >= 1.24
- PyYAML >= 6.0
- scipy >= 1.11
- PyQt6 >= 6.4
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file parallax_jwst-1.1.0.tar.gz.
File metadata
- Download URL: parallax_jwst-1.1.0.tar.gz
- Upload date:
- Size: 75.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.14.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d7ca81bb1ff90be2e7d7cf8fd6002fb8a15605a8851b12580c6f9d0c6e9402fb
|
|
| MD5 |
7921d83e993fb79b2daae9d257ab5418
|
|
| BLAKE2b-256 |
eca1d33515f67f1e4287a3ee38fd7698637187570288e946cfad8fa8976e29b0
|
File details
Details for the file parallax_jwst-1.1.0-py3-none-any.whl.
File metadata
- Download URL: parallax_jwst-1.1.0-py3-none-any.whl
- Upload date:
- Size: 68.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.14.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c17825405f01597481c3a95463a7163dc8e93b46430ba3a512da7fb096589006
|
|
| MD5 |
1b7a6d407c79e1813fdc0e7b1a27681f
|
|
| BLAKE2b-256 |
c3d8e6e527e89fe8c8da76ca609a9d01a4765700ad8b2c13da695d3c0e5df699
|