PyTOUGH
A Python library for automating TOUGH2 simulations of subsurface fluid and heat flow
Install / Use
/learn @acroucher/PyTOUGHREADME
What is PyTOUGH?
PyTOUGH (Python TOUGH) is a Python library for simplifying, extending and automating the use of the TOUGH2 subsurface fluid and heat flow simulator. Using PyTOUGH, it is possible to automate the creation and editing of TOUGH2 model grids and data files, and the analysis and display of model simulation results, using Python scripts.
Installing PyTOUGH:
From version 1.6.0, PyTOUGH can be installed via the pip Python package installer:
pip install PyTOUGH
You can also install a particular version of PyTOUGH, e.g. to install version 1.6.0:
pip install PyTOUGH==1.6.0
To uninstall PyTOUGH:
pip uninstall PyTOUGH
To install the testing branch, to get the most recent changes being tested for the next stable release:
pip install git+https://github.com/acroucher/PyTOUGH.git@testing
More information:
For more detailed information on PyTOUGH, consult the user guide (html, or you can download PDF or Epub versions) and the PyTOUGH wiki, which has links to published articles on PyTOUGH.
What's new in PyTOUGH?
The latest stable version is 1.6.6, which has:
- ability to convert EOS3 models to Waiwera JSON input
Related Skills
node-connect
349.2kDiagnose OpenClaw node connection and pairing failures for Android, iOS, and macOS companion apps
claude-opus-4-5-migration
109.5kMigrate prompts and code from Claude Sonnet 4.0, Sonnet 4.5, or Opus 4.1 to Opus 4.5
frontend-design
109.5kCreate distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
model-usage
349.2kUse CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.
