title	emoji	colorFrom	colorTo	sdk	pinned	license	thumbnail	short_description
Stingray Explorer	🚀	gray	green	docker	false	mit	https://cdn-uploads.huggingface.co/production/uploads/668d17c6e6887d1f6afde2a6/4q5lnlS6-eJ_JBh8tW3_I.png	Stingray Explorer Dashboard Demo

StingrayExplorer

StingrayExplorer is a comprehensive data analysis and visualization dashboard designed for X-ray astronomy time series data. Built on top of the Stingray library, it provides an intuitive graphical interface for analyzing event lists, generating light curves, computing various types of spectra, and performing advanced timing analysis.

Overview

StingrayExplorer combines the powerful timing analysis capabilities of the Stingray library with a modern, interactive dashboard built using Panel and HoloViz. It enables astronomers to:

• Load and analyze event lists from various X-ray telescopes
• Generate and manipulate light curves
• Compute power spectra, cross spectra, and bispectra
• Analyze dynamical power spectra and power colors
• Visualize results through interactive plots
• Export analysis results in multiple formats

The dashboard is designed to be user-friendly while providing access to advanced features for experienced users.

Key Features

Data Loading and Management

• Support for multiple file formats (FITS, HDF5, ASCII, etc.)
• Batch loading of multiple event lists
• Automatic GTI (Good Time Interval) handling
• Energy calibration using RMF (Response Matrix File)
• File preview and metadata inspection

Event List Analysis

• Event list creation and simulation
• Deadtime correction
• Energy filtering and PI channel conversion
• Event list joining and sorting
• Color and intensity evolution analysis

Spectral Analysis

• Power spectrum computation
• Cross spectrum analysis
• Averaged power/cross spectra
• Bispectrum calculation
• Dynamical power spectrum visualization
• Power color analysis

Interactive Visualization

• Real-time plot updates
• Customizable plot layouts
• Floating plot panels
• Interactive plot manipulation
• Multiple visualization options

System Features

• Resource monitoring (CPU, RAM usage)
• Warning and error handling
• Comprehensive help documentation
• Responsive layout design

Architecture

The project follows a modular architecture with clear separation of concerns:

Core Components

1. explorer.py: Main entry point and dashboard initialization

   • Panel/HoloViz setup
   • Layout configuration
   • Component integration

2. modules/: Core functionality modules

   • DataLoading/: Data ingestion and management
   • Home/: Dashboard home page and navigation
   • QuickLook/: Analysis tools and visualizations
     • EventList handling
     • Light curve generation
     • Spectral analysis
     • Power color computation

3. utils/: Utility classes and functions

   • DashboardClasses.py: Reusable UI components
   • sidebar.py: Navigation and control
   • globals.py: Global state management
   • strings.py: Text content

4. assets/: Static resources

   • Images and icons
   • CSS stylesheets
   • Documentation assets

5. files/: Data storage

   • Sample data files
   • User-loaded data
   • Analysis outputs

Technology Stack

• Backend: Python 3.11+
• Frontend: Panel, HoloViz
• Data Analysis: Stingray, NumPy, Astropy
• Visualization: Bokeh, Matplotlib
• Deployment: Docker, Hugging Face Spaces

Installation Guide

Prerequisites

• Python 3.11 or above
• Conda package manager
• Git (for cloning the repository)

Dependencies

Core packages:

• Panel >= 1.3.0
• HoloViews >= 1.18.0
• Stingray >= 0.3
• NumPy >= 1.24.0
• Astropy >= 5.0
• Matplotlib >= 3.7.0
• Bokeh >= 3.3.0

Setup Instructions

1. Clone the repository:

   git clone https://github.com/kartikmandar-GSOC24/StingrayExplorer.git
   cd StingrayExplorer

2. Create and activate the conda environment:

   conda env create -f environment.yml
   conda activate stingray-env

3. Verify installation:

   python -c "import stingray; import panel; import holoviews"

Troubleshooting Dependencies

If you encounter dependency conflicts:

1. Check individual package versions:

   conda list stingray
   conda list panel
   conda list holoviews

2. Try installing missing dependencies:

   conda install -c conda-forge <package_name>
   # or
   pip install <package_name>

3. Common issues:

   • Stingray version compatibility
   • Panel/HoloViews version mismatch
   • Missing system libraries

4. Support channels:

   • Email: [email protected]
   • Stingray Slack: @kartikmandar
   • GitHub Issues

Deployment Options

Local Development Server

Run the application locally:

panel serve explorer.py --autoreload --static-dirs assets=./assets

This starts a development server with:

• Auto-reloading on file changes
• Static file serving
• Debug information
• Default port 5006

Docker Deployment

1. Build the image:

   docker build -t stingray-explorer .

2. Run the container:

   docker run -p 7860:7860 stingray-explorer

3. Access the application at http://localhost:7860

Hugging Face Spaces

The dashboard is deployed on Hugging Face Spaces:

• Live demo: https://kartikmandar-stingrayexplorer.hf.space/explorer
• Repository: https://huggingface.co/spaces/kartikmandar/StingrayExplorer
• Website demo: https://www.kartikmandar.com/gsoc-2024/stingray-explorer

Continuous Integration

GitHub Actions automatically sync changes to Hugging Face Spaces:

• Triggers on pushes to main branch
• Builds and deploys Docker image
• Updates Hugging Face Space

Usage Guide

Quick Start

1. Launch the application:

   panel serve explorer.py --autoreload --static-dirs assets=./assets

2. Navigate to http://localhost:5006 in your browser

3. Basic workflow:

   • Use the sidebar navigation
   • Load data files
   • Generate visualizations
   • Export results

Data Loading

1. Click "Read Data" in the sidebar
2. Choose from multiple options:
   • Load local files
   • Fetch from URL
   • Use sample data

Supported formats:

• FITS event files
• HDF5 files
• ASCII tables
• ECSV files

Analysis Tools

1. Event List Operations

   • Create/simulate event lists
   • Apply deadtime corrections
   • Filter by energy range
   • Convert PI to energy

2. Light Curve Analysis

   • Generate light curves
   • Apply GTI filters
   • Compute statistics
   • Plot time series

3. Spectral Analysis

   • Compute power spectra
   • Generate cross spectra
   • Calculate bispectra
   • Analyze power colors

4. Advanced Features

   • Dynamical power spectra
   • Color evolution
   • Intensity analysis
   • Custom plotting

Visualization Options

1. Plot Types

   • Time series
   • Spectral plots
   • Contour plots
   • Scatter plots

2. Interactive Features

   • Zoom/pan
   • Hover tooltips
   • Plot customization
   • Export options

3. Layout Options

   • Floating panels
   • Grid arrangements
   • Multiple views
   • Responsive design

Data Export

• Save plots as PNG/SVG
• Export data as CSV/FITS
• Save analysis results
• Generate reports

Development Guide

Setting Up Development Environment

1. Fork and clone the repository
2. Create development environment:

   conda env create -f environment.yml
   conda activate stingray-env

3. Install development dependencies:

   pip install -r docs/requirements.txt

Project Structure

stingray-explorer/
├── explorer.py          # Main application entry point
├── modules/            # Core functionality modules
│   ├── DataLoading/   # Data ingestion components
│   ├── Home/          # Dashboard home components
│   └── QuickLook/     # Analysis tools
├── utils/             # Utility functions and classes
├── assets/            # Static resources
├── files/            # Data files
└── tests/            # Test suite

Development Workflow

1. Create feature branch:

   git checkout -b feature/new-feature

2. Make changes and test:

   # Run tests
   pytest tests/
   
   # Start development server
   panel serve explorer.py --autoreload

3. Submit pull request:

   • Fork repository
   • Push changes
   • Create PR with description

Coding Standards

• Follow PEP 8 style guide
• Add docstrings (NumPy format)
• Write unit tests
• Update documentation

Testing

Run test suite:

pytest tests/

Test coverage:

pytest --cov=./ tests/

Troubleshooting Guide

Common Issues

1. Installation Problems

   • Dependency conflicts
   • Python version mismatch
   • Missing system libraries

   Solution: Check versions, use conda-forge channel

2. Import Errors

   • Missing packages
   • Version incompatibilities
   • Path issues

   Solution: Verify environment, check imports

3. Runtime Errors

   • Memory issues
   • Performance problems
   • Display errors

   Solution: Monitor resources, check logs

4. Data Loading Issues

   • File format problems
   • Permission errors
   • Corrupt files

   Solution: Verify file integrity, check formats

Performance Optimization

1. Memory Management

   • Use chunked loading
   • Clear unused data
   • Monitor memory usage

2. Speed Improvements

   • Enable caching
   • Optimize computations
   • Use efficient algorithms

3. Display Performance

   • Limit plot sizes
   • Use appropriate renderers
   • Optimize updates

Getting Help

1. Documentation

   • Read the docs
   • Check examples
   • Review tutorials

2. Support Channels

   • GitHub Issues
   • Email support
   • Slack channel

3. Debugging

   • Check logs
   • Use debugger
   • Print statements

License and Credits

License

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

Credits

• Stingray Library: Core timing analysis functionality
• Panel/HoloViz: Interactive visualization framework
• Contributors: See GitHub contributors page

Acknowledgments

• The Stingray development team
• HoloViz community
• X-ray astronomy community
• Google Summer of Code program