Time-varying Graphical Lasso

Time-varying Graphical Lasso(TVGL) is a python solver for time-varying network inferring.
Based on paper from Hallac et al. (2017) "Network inference via the Time-Varying Graphical Lasso"
https://arxiv.org/abs/1703.01958

Download

git clone https://github.com/ams129/TVGL.git

Usage

TVGL can be called through the following file:

tvgl.py

Parameters

• X : numpy array with the raw data
• alpha : the regularization parameter controlling the network sparsity
• beta : the beta parameter controlling the temporal consistency
• penalty_type : the penalty type("L1" or "L2")
• slice_size : Number of samples in each timestamps

Example

Running the following script provides an example of how the TVGL solver can be used:

example.py