Interactive Tutorial Notebook

This comprehensive tutorial demonstrates the complete pyKOSMOS++ spectroscopic reduction workflow through an interactive Jupyter notebook.

The tutorial covers:

  • Introduction & Setup - Installation verification and configuration loading

  • Data Exploration - Understanding KOSMOS FITS file structure

  • Calibration Creation - Master bias and flat frame generation with validation

  • Wavelength Calibration - Arc line detection, catalog matching, and polynomial fitting

  • Trace Detection & Extraction - Cross-correlation trace detection and optimal extraction

  • Quality Assessment - SNR computation and quality grading

  • Advanced Parameters - Customizing reduction parameters for specific observations

  • Batch Processing - Automated pipeline for multiple observations

Tutorial Notebook

Additional Resources

  • quickstart - Quick 5-minute reduction guide

  • user_guide_cli - Command-line interface reference

  • user_guide_python_api - Python API documentation

  • Troubleshooting - Common issues and solutions

Download

Download the tutorial notebook: tutorial.ipynb

To run the tutorial locally:

# Clone the repository
git clone https://github.com/gkhullar/pykosmospp.git
cd pykosmospp

# Install dependencies
pip install -e ".[dev]"

# Launch Jupyter
jupyter notebook examples/tutorial.ipynb

Requirements

  • Python ≥3.10

  • pyKOSMOS++ installed with all dependencies

  • KOSMOS FITS data (or use generated test data)

  • Jupyter notebook or JupyterLab

Estimated Time: 15-20 minutes for interactive execution