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Two-Chain PAA Data Analysis Repository

Summary: Public facing data analysis repository for MD simulations of two-chain PAA in water. Analysis tools are written in Python and documented using Sphinx. Parallelized analysis scripts extend the MDAnalysis library and are called by scripts in the analysis directory to calculate collective variables. Collective variables are then analyzed with Jupiter notebooks in the analysis directory.
Authors: Alec Glisman, Sriteja Mantha

CodeFactor WakaTime

Pytest Linting

Project structure

Directories

  • .github: GitHub workflows and issue templates
  • .vscode: Visual Studio Code settings and preferences
  • analysis: Python scripts for analyzing MD simulation data
  • docs: Sphinx documentation for Python modules
  • requirements: Conda environment files
  • src: Python modules for loading MD simulation data and calculating collective variables. Unit tests are performed using Pytest.

Documentation

Documentation is generated using Sphinx. The HTML index file is found here and is best viewed in a web browser.

Continuous Integration (CI) and Continuous Deployment (CD)

On each pull request, GitHub Actions will check the code for linting errors and run unit tests. The code coverage results are uploaded to CodeCov, and code quality is checked using CodeFactor.

Python

Install Conda virtual environment with conda env create -f requirements/environment.yml. Update currently activated Conda virtual environment (and remove unneeded dependencies) with conda env update -f requirements/environment.yml --prune.

Visual Studio Code

Recommended extensions are located in .vscode/extensions.json. Python path and other editor variables are located in .vscode/settings.json.