TimeAwarePC is a Python package that implements the Time-Aware PC Algorithm for finding the Causal Functional Connectivity from time series data, based on recent research in directed probabilistic graphical modeling with time series [1]. The package also includes implementations of Granger Causality and the PC algorithm.
You can get the latest version of TimeAwarePC as follows.
$ pip install timeawarepc
- Python >=3.6
- Python packages automatically checked and installed as part of the setup. To use Granger Causality, additional dependency of
nitime
which can be installed bypip install nitime
. - R >=4.0
- R package
kpcalg
and its dependencies. They can be installed in R or RStudio as follows:
> install.packages("BiocManager")
> BiocManager::install("graph")
> BiocManager::install("RBGL")
> install.packages("pcalg")
> install.packages("kpcalg")
Documentation is available at readthedocs.org
See the Quick Start Guide for a quick tutorial of the main functionalities of this library and check if it is installed properly.
Your help is absolutely welcome! Please do reach out or create a feature branch!
Biswas, R., & Shlizerman, E. (2022). Statistical Perspective on Functional and Causal Neural Connectomics: The Time-Aware PC Algorithm. https://arxiv.org/abs/2204.04845
Biswas, R., & Shlizerman, E. (2021). Statistical Perspective on Functional and Causal Neural Connectomics: A Comparative Study. Frontiers in Systems Neuroscience. https://doi.org/10.3389/fnsys.2022.817962
R Clay Reid. (2012) From functional architecture to functional connectomics. Neuron, 75(2):209–217.
Smith, S. M., Miller, K. L., Salimi-Khorshidi, G., Webster, M., Beckmann, C. F., Nichols, T. E., ... & Woolrich, M. W. (2011). Network modelling methods for FMRI. Neuroimage, 54(2), 875-891.
Judea Pearl. (2009) Causality. Cambridge University press.
Markus Kalisch and Peter Bhlmann. (2007) Estimating high-dimensional directed acyclic graphs with the pc-algorithm. In The Journal of Machine Learning Research, Vol. 8, pp. 613-636.
Peter Spirtes, Clark N Glymour, Richard Scheines, and David Heckerman. (2000) Causation, prediction, and search. MIT press.