snid-sage 0.3.2

SNID SAGE - SuperNova IDentification with Spectrum Analysis and Guided Enhancement

SNID SAGE - Advanced Supernova Spectral Analysis

SNID SAGE (SuperNova IDentification – Spectral Analysis and Guided Exploration) is your go-to tool for analyzing supernova spectra. It combines an intuitive PySide6/Qt graphical interface with the original SNID (Blondin & Tonry 2007) cross-correlation techniques, enhanced with modern clustering for classification choice, high-performance plotting via pyqtgraph, and LLM-powered analysis summaries and interactive chat assistance.

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SNID SAGE main GUI: intuitive workflow, interactive plotting, and advanced analysis tools.

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Quick Installation (v0.3.0)

Option 1: Install from PyPI (Recommended)

The easiest way to install SNID SAGE is directly from PyPI:

pip install snid-sage

Option 2: Virtual Environment (Recommended for Development)

We recommend using a virtual environment to avoid conflicts with other Python packages. This ensures a clean, isolated installation.

Using venv (Python's built-in virtual environment)

# Create virtual environment
python -m venv snid_env

# Activate environment
# Windows:
snid_env\Scripts\activate
# macOS/Linux:
source snid_env/bin/activate

# Install SNID SAGE
pip install snid-sage
 

Using conda

# Create conda environment
conda create -n snid_sage python=3.10
conda activate snid_sage

# Install SNID SAGE
pip install snid-sage
 

Option 3: Development Installation

For development or testing the latest features:

# Install from Test PyPI (development versions)
pip install -i https://test.pypi.org/simple/ snid-sage

# Or install from source
git clone https://github.com/FiorenSt/SNID-SAGE.git
cd SNID-SAGE
pip install -e .

Note: If you choose global installation, we recommend using pip install --user to install in your user directory rather than system-wide.

Getting Started

Launch the GUI (Recommended)

# Using installed entry point
snid-gui
# or
snid-sage

Use the CLI (For automation)

# Single spectrum analysis (templates auto-discovered). By default saves summary (.output) and plots
snid data/sn2003jo.dat -o results/

# Single spectrum with explicit templates
snid identify data/sn2003jo.dat templates/ -o results/

# Batch processing (default saves per-object summary and plots)
snid batch "data/*.dat" templates/ -o results/

# Minimal outputs (summary only, no plots)
snid identify data/sn2003jo.dat -o results/ --minimal

# Complete outputs (summary, plots, and all additional data files)
snid identify data/sn2003jo.dat -o results/ --complete

# Disable plots explicitly (default is to generate plots)
snid identify data/sn2003jo.dat -o results/ --no-plots

Documentation & Support

• Complete Documentation - Comprehensive guides and tutorials
• Quick Start Guide - Your first analysis in 5 minutes
• GUI Manual - Complete interface guide
• CLI Reference - All commands and options
• AI Integration - Setting up AI analysis
• Troubleshooting - Common issues and solutions
• FAQ - Frequently asked questions

Supported Data Formats

• FITS files (.fits, .fit)
• ASCII tables (.dat, .txt, .ascii, .asci, .flm)
• Space-separated values with flexible column detection
• Custom formats with configurable parsers

Research & Citation

If you use SNID SAGE in your research, please cite:

@software{snid_sage_2025,
  title={SNID SAGE: A Modern Framework for Interactive Supernova
         Classification and Spectral Analysis},
  author={F. Stoppa},
  year={In Prep, 2025},
  url={https://github.com/FiorenSt/SNID-SAGE}
}

Community & Support

• Report Bug - Found a bug?
• Request Feature - Want a new feature?
• Discussions - Questions and community chat
• Email Support - Direct contact

License

This project is licensed under the MIT License - see the LICENSE file for details.

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Made with care for the astronomical community

Documentation • Report Bug • Request Feature • Discussions