BLiSS: Blind Line Search System
Project description
BLiSS — Blind Line Search System
BLiSS (Blind Line Search System) is an open-source Python package for the automatic detection and identification of emission lines in astronomical spectra.
Rather than requiring users to manually inspect spectra or provide a list of candidate line energies, BLiSS performs a genuine blind line search directly on the data, ranking statistically significant emission-line candidates and optionally identifying them using atomic databases.
Originally developed for X-ray spectroscopy, BLiSS is designed around a general workflow that can be applied to any spectral dataset with associated uncertainties.
Features
-
Blind emission-line search
- Automatically searches spectra for statistically significant emission features.
- No prior knowledge of line positions is required.
-
Automatic Gaussian fitting
- Fits candidate features with Gaussian profiles.
- Provides statistical ranking of all detected lines.
-
Continuum-independent workflow
- Line searches can be performed without defining a global continuum model beforehand.
-
Atomic line identification
- Cross-matches detected features with XSTAR atomic transitions.
- Supports Doppler velocity constraints.
-
Flexible rebinning
- Rebin spectra by instrumental resolution or target signal-to-noise ratio.
-
ISIS integration
- Automatically generates Gaussian components for ISIS spectral fitting.
-
Reproducible analyses
- Applies identical search criteria across large spectral samples.
Installation
Install BLiSS directly from PyPI:
pip install bliss-lib
or install the development version from GitHub:
git clone https://github.com/xragua/bliss.git
cd bliss
pip install -e .
Quick start
import bliss
# Import your spectrum
# Run the blind line search
# Inspect the detected candidates
Example notebooks are available in the example/ directory:
https://github.com/xragua/bliss/tree/main/example
Documentation
GitHub repository:
https://github.com/xragua/bliss
Latest releases:
https://github.com/xragua/bliss/releases
Requirements
- Python 3.10 or newer
- NumPy
- SciPy
- Pandas
- Astropy
- Matplotlib
These dependencies are installed automatically with BLiSS.
Citation
If you use BLiSS in your research, please cite:
Abalo, L., Sanjurjo-Ferrín, G., et al. (2026), BLiSS: Blind Line Search System, Astronomy & Computing.
(The citation will be updated once the paper is published.)
Support
Bug reports, feature requests and suggestions are welcome through GitHub Issues:
https://github.com/xragua/bliss/issues
For scientific questions, you can also contact:
luisabalo.com
License
This project is distributed under the MIT License.
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 bliss_lib-0.1.0.tar.gz.
File metadata
- Download URL: bliss_lib-0.1.0.tar.gz
- Upload date:
- Size: 3.3 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1d5d88a1b87d07456cdf8251b14e484be63870a4d0369d915a7e59f0aa31a38e
|
|
| MD5 |
2ac626f25a6b0715fe6d9a7da421518b
|
|
| BLAKE2b-256 |
e4e9745883943182e437c57d7efd2d09d65fb988c21def18204cdc73774f2bbc
|
File details
Details for the file bliss_lib-0.1.0-py3-none-any.whl.
File metadata
- Download URL: bliss_lib-0.1.0-py3-none-any.whl
- Upload date:
- Size: 3.6 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
0384164a5513b8127c7f5b23021e1cf6d14aaf29201351b3fa27b37260280b69
|
|
| MD5 |
f1794fcfbd0f210e8f2f52ff37d9af31
|
|
| BLAKE2b-256 |
c99f7d60e2423c2fe61858b9613717dbbaeaf65ea6b8e9589369d92ed7e5ab02
|