gunfolds
Tools to explore dynamic causal graphs in the case of undersampled data helping to unfold the apparent structure into the underlying truth.
Documentation
Please refer to the Documentation for more information.
Installation
Install the gunfolds package
pip install gunfolds
Additionally, install these packages to use gunfolds
graph-tool installation
1. Install graph-tool
To install graph-tool package with conda install run the following command
conda install -c conda-forge graph-tool
To install graph-tool package with brew install run the following command
brew install graph-tool
PyGObject installation
2. 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+3
To install PyGObject package in Windows, Linux and any other platforms please refer to the link
https://pygobject.readthedocs.io/en/latest/getting_started.html
Acknowledgment
This work was initially supported by NSF IIS-1318759 grant and is currently supported by NIH 1R01MH129047.
1 maintainer
Release files for gunfolds 0.0.33
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| gunfolds-0.0.33.tar.gz | 6.3 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| gunfolds-0.0.33-py3-none-any.whl | Python 3 | none | any | Details |
Total release size:12.6 MB
Release files / gunfolds-0.0.33.tar.gz
| Download URL | gunfolds-0.0.33.tar.gz |
|---|---|
| Size | 6.3 MB |
| Tags | Source |
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Release files / gunfolds-0.0.33-py3-none-any.whl
| Download URL | gunfolds-0.0.33-py3-none-any.whl |
|---|---|
| Size | 6.3 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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twine/7.0.0 CPython/3.13.14
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