Tools to explore dynamic causal graphs in the case of undersampled data helping to unfold the apparent structure into the underlying truth.
Gunfolds v2.0 features a complete reorganization for better maintainability and usability!
- Get Started → - Quick start guide
- Documentation Hub → - All guides and tutorials
- Quick Script Lookup → - Find where your script moved (2 min)
- Migration Guide → - Complete migration instructions (30-60 min)
- Visual Workflow → - Step-by-step visual guide
- Documentation Index → - Complete guide to all docs
Key improvements in v2.0:
- ✅ 118+ scripts consolidated to ~33 organized modules
- ✅ Eliminated 85+ duplicate files
- ✅ Clear folder structure (analysis/benchmarks/experiments/visualization)
- ✅ Unified interfaces with command-line parameters
- ✅ Comprehensive documentation
- ✅ Full backward compatibility (old scripts preserved in
scripts/legacy/)
Please refer to the Online Documentation for API reference and the documentation links above for v2.0 guides.
Install the gunfolds package
pip install gunfoldsAdditionally, install these packages to use gunfolds
1. Install graph-tool
To install graph-tool package with conda install run the following command
conda install -c conda-forge graph-toolTo install graph-tool package with brew install run the following command
brew install graph-tool2. Install PyGObject
This is only required if you need to use gtool module of the gunfolds package
To install PyGObject package with brew install run the following command
brew install pygobject3 gtk+3To install PyGObject package in Windows, Linux and any other platforms please refer to the link
https://pygobject.readthedocs.io/en/latest/getting_started.html
This work was initially supported by NSF IIS-1318759 grant and is currently supported by NIH 1R01MH129047.