Skip to main content

GWeasy: Gravitational Wave analysis made easy

Project description

GWeasy

GWeasy is a user-friendly, GUI-based software for fetching, analyzing, and visualizing gravitational wave (GW) data from LIGO and other observatories. It simplifies the setup and execution of GW analysis pipelines like OMICRON, making gravitational wave science accessible to researchers with minimal technical setup.

YouTube Demo

Overview

GWeasy integrates tools for:

  • Data Fetching: Retrieve GW data from LIGO databases (Gravfetch tab).
  • Analysis: Run OMICRON and other pipelines with configurable settings.
  • Visualization: Display results graphically.
  • Ease of Use: One-click installation and intuitive GUI for Windows and Linux.

For detailed documentation and usage instructions, visit: https://shantanu-parmar.github.io/GWeasy/

Features

  • Multi-Platform Support: Windows, Linux (Beta), MacOS (Planned).
  • Minimal Setup: Pre-built executables for Windows (via WSL) and Linux, or script-based setup.
  • User-Friendly GUI: Select channels, time segments, and configure pipelines easily.
  • Pipeline Integration: Supports OMICRON with plans for additional pipelines (e.g., cWB).
  • Visualization Tools: Built-in plotting for GW data analysis.

Installation

Option 1: Pre-Built Executables

  • Windows:

    1. Download Omeasy.exefrom the Gweasy website GWeasy. ->That's it..... If you want to run Omicron also, follow steps 2 onwards
    2. Download GWeasywsl.tar and 'install.bat' from Gweasy website GWeasy.
    3. Place install.bat and GWeasywsl.tar in a same directory.
    4. Double-click install.bat to set up WSL and OMICRON.
    5. Run Omeasy.exe for OMICRON analysis.
  • Linux:

    1. Download GWeasy from the Releases page.
    2. Make executable: chmod +x GWeasy
    3. Run: ./GWeasy

Option 2: Script-Based Setup

For running gweasy.py directly or building from source:

  1. Install Miniconda:

  2. Create Environment:

    • Place environment.yml and requirements.txt (below) in the same directory as gweasy.py from this repository (you dont need to get any other files).
    • Run:
      conda env create -f environment.yml
      conda activate GWeasy
      pip install -r requirements.txt
      
  3. Run GWeasy:

    python gweasy.py
    

environment.yml

For windows

name: GWeasy
channels:
  - conda-forge
  - defaults
dependencies:
  - python=3.10
  - python-nds2-client
  - python-framel

For Linux/Mac

name: GWeasy
channels:
  - conda-forge
  - defaults
dependencies:
  - python=3.10
  - python-nds2-client
  - lalframe

requirements.txt

pandas
gwpy
PyQt5
requests-pelican

Usage

  1. Gravfetch Tab:

    • Select test-times.csv for time segments and test-chans.csv for channels from this repository /tests.
    • Set output directory (default: gwfout).
    • Click "Download Data" to fetch .gwf files.
    • Expect 5-7 minutes per channel/segment.
  2. Omicron Tab:

    • Select a channel from gwfout or enter manually.
    • Click on Custom segs and choose all time segments you would like.
    • Configure parameters (e.g., sampling rate, frequency range).
    • Click "Save Config" to generate a config file.
    • Click "Start Omicron" to run analysis.

For detailed steps and screenshots, refer to: https://shantanu-parmar.github.io/GWeasy/

Contributing

  1. Fork the repository: git clone https://github.com/shantanu-parmar/GWeasy.git
  2. Create a branch: git checkout -b feature-branch
  3. Make changes and commit: git commit -m "Add feature"
  4. Push and create a pull request: git push origin feature-branch
  5. Report issues on the GitHub Issues page.

License

This project is licensed under the MIT License.

Acknowledgments

  • Lead Developer: Shantanusinh Parmar
  • Mentors: Dr. Marco Cavaglia, Dr. Florent Robinet, Dr. Jonah Kanner, Mr. Kai Staats,
  • Testing: Mr. Federico Romeo
  • Thanks: LIGO team and GW astrophysics community

Join the GWeasy Project – Simplifying Gravitational Wave Analysis for All!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gweasy-0.2.0.tar.gz (4.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

gweasy-0.2.0-py3-none-any.whl (5.0 kB view details)

Uploaded Python 3

File details

Details for the file gweasy-0.2.0.tar.gz.

File metadata

  • Download URL: gweasy-0.2.0.tar.gz
  • Upload date:
  • Size: 4.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for gweasy-0.2.0.tar.gz
Algorithm Hash digest
SHA256 b3e83a8f3a9e45c8b1bd0f7db879221e2a99dce2a5230de701e23958ad695867
MD5 31497902206ad026a3901bf21ce17022
BLAKE2b-256 ce35b81bec9554793d5c8cadf953699e0463e9dc6ea55d113d54ced32e86841a

See more details on using hashes here.

Provenance

The following attestation bundles were made for gweasy-0.2.0.tar.gz:

Publisher: python-publish.yml on Shantanu-Parmar/GWeasy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file gweasy-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: gweasy-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 5.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for gweasy-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 2644fd0ed902ef5337c1235b9d9c74e917338c7aa95e7a27fa57ee5f0d051869
MD5 dcdbbd7df90f7b25a127b7beec1e7622
BLAKE2b-256 7e7503f0fdc6f02e54fe04d45341f4fb63341686c628a4f1a916df9f55e567de

See more details on using hashes here.

Provenance

The following attestation bundles were made for gweasy-0.2.0-py3-none-any.whl:

Publisher: python-publish.yml on Shantanu-Parmar/GWeasy

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page