GWeasy Directory Reference

Directory dependency graph for GWeasy:

Directories
	tests

Files
	GWeasy.py

Detailed Description

0# GWeasy

GWeasy: Multiplatform GUI Software for Gravitational Wave Data Analysis

Overview

GWeasy is a user-friendly, GUI-based software designed to streamline the process of fetching, analyzing, and visualizing gravitational wave (GW) data. This software aims to reduce the complexity of installing and running GW analysis tools by integrating all necessary software requirements into a single, easy-to-use platform.

Project Details

• Project Timeline: February - April 2025
• Lead Developer: Shantanusinh Parmar
• Supervisor: Prof. Chandrasinh Parmar
• Target Platforms: Windows , Linux
• Primary Software Components:
  • LIGO data fetching
  • OMICRON analysis pipeline
  • User-friendly GUI
  • Visualization tools
  • One-click installation and setup

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1. Introduction

The Laser Interferometer Gravitational-Wave Observatory (LIGO) operates four detectors and collects data across six runs, with over 300 channels, multiple sampling rates, and countless time segments. This raw time-series GW data is then analyzed using various pipelines such as:

• OMICRON
• Coherent WaveBurst (cWB)
• Matched filtering
• Fourier transforms

Currently, setting up the software environment for such analyses is a major challenge. The goal of this project is to simplify this process by creating a GUI-based tool that can handle everything—from **installation to execution**—without requiring extensive technical knowledge.

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2. Background & Motivation

While working with GW data, I encountered numerous challenges, spending over 10 weeks resolving library conflicts, configuring environment files, and understanding poorly documented installation processes. Through collaboration with scientists, developers, and LIGO repository maintainers, I finally managed to get the correct workflow established.

This experience highlighted the need for a user-friendly, platform-independent tool that can:

• Automate the installation of required dependencies.
• Manage multiple pipelines with ease.
• Provide an intuitive GUI for data selection, analysis, and visualization.
• Offer a one-click install and execution process.

Many astrophysicists spend more time setting up the software than analyzing the data. GWeasy aims to eliminate this technical barrier, allowing researchers to focus on their primary goal: gravitational wave science.

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3. Features & Functionalities

✔ Multi-Platform Support

• Windows
• Linux (Beta Version)
• MacOS (Planned)

✔ Minimal Setup & Installation

– Only WSL needs to be set up for Windows version, pre-loaded WSL Image also available – No installtion or setup for Linux app required

✔ User-Friendly GUI

• Data fetching from LIGO databases.
• Channel selection and configuration.
• Pipeline execution for OMICRON and other analyses.
• Graphical visualization of results.

- Format conversion tools.

4. Installation & Dependencies

For Windows

– If you want to use Omicron only, go to Windows/ and download the Omeasy.exe app and install.bat.

– Next, you can either set up Omicron library in wsl by yourself or if you don't want to get into the hassle of setup follow next instructions

– Donwload GWeasywsl.tar(https://drive.google.com/file/d/1TTU7GewMfHIUteGl6ND3cLCCKAQ677kt/view?usp=drive_link) and download the tar file.

– Put install.bat, GWeasywsl.tar in same directory, double click on install.bat.

– That's it, run the Omicron on Windows using the Omeasy.exe from here on.

For Linux

– Download GWeasy from /Linux – On terminal write chmod +x GWeasy – Run GWeasy via ./GWeasy command

1. Running a Test in the Gravfetch Tab

To perform a test run:

• Select test.csv as the time segment input.
• Select 4KCHANS.csv as the channels input.
• Optionally, specify an output directory. By default, GWEasy will create a folder named gwfout in the same directory.

Once execution starts, a completion message will appear in the terminal, indicating a successful run. Processing time varies (~5-7 minutes) depending on the number of time segments and channels selected. To speed up testing, start with a single time segment and channel.

2. Running Omicron Analysis

After generating gwf files, switch to the Omicron tab to proceed with analysis.

Configuring Omicron Settings

If you have worked with Omicron configuration files, this setup will feel familiar:

Steps:

1. Set Channel & Sampling Rate First (due to an existing UI issue, these must be configured before modifying other fields).
2. Channels are pre-populated based on the Gravfetch output, but you can also manually enter any channel name.

1. Select the .ffl files corresponding to each channel. These are located in the gwfout directory or your chosen output path. Each channel has an .ffl file listing all time segments.
2. Use the Custom Segments feature to manually specify time segments for analysis if needed.

1. Once all fields are filled, specify an output directory (default: Omicronout).
2. Click Save Config to generate a configuration file with the selected inputs.

1. Press Start Omicron to begin processing. Upon successful execution, a completion message will be displayed in the terminal.

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Additonal tabs

5. Development Timeline

| Task | Expected Completion | |----—|---------------—| | Project Start | February 2025 | Done | Workflow Documentation | March 2025 | Done | Prototype Development | Mid-March 2025 | Done | Windows Version Testing | April 2025 | Done | Linux Version Development | Future Update | Done

6. Future Enhancements

• Cross-platform compatibility (Linux & MacOS) Partially Done
• Expanded support for additional pipelines
• Real-time visualization improvements

7. Contributors

• Shantanusinh Parmar (Lead Developer)
• Dr. Kai Staats (Mentor, Software Development)
• Dr. Marco Cavaglia (Mentor, Linux Development)
• Dr. Florent Robinet (Mentor, Omicron)
• Dr. Jonah Kanner (Mentor, GWOSC support)

8. License

This project is open-source under the MIT License.

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9. Acknowledgments

Special thanks to the Dr. Marco Cavaglia, Dr. Kai Staats, Dr. Florent Robinet, Dr. Jonah Kranner, and thanks to the LIGO team, pipeline developers, and all researchers contributing to the field of gravitational wave astrophysics. Your work makes this project possible.

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10. How to Contribute

If you’d like to contribute:

1. Fork the repository
2. Clone your fork: git clone https://github.com/yourusername/GWeasy.git
3. Create a new branch: git checkout -b feature-branch
4. Make your changes and commit
5. Push to your fork and create a pull request

For any issues, feel free to open a GitHub issue!

Join the GWeasy Project – Making Gravitational Wave Analysis Accessible to All!