Vgraph

A graphical interface to visibility graph

Cite

Please cite this work as:

Rodriguez-Torres EE, Paredes-Hernandez U, Vazquez-Mendoza E, Tetlalmatzi-Montiel M, Morgado-Valle C, Beltran-Parrazal L and Villarroel-Flores R (2020) Characterization and Classification of Electrophysiological Signals Represented as Visibility Graphs Using the Maxclique Graph. Front. Bioeng. Biotechnol. 8:324. doi: 10.3389/fbioe.2020.00324

Install 🔧

1. Install python 3.7 (download link https://www.python.org/downloads/release/python-370/ ), mark "Add to path" option, add click next
   2.Open CMD or Terminal and install packages: numpy, pandas, networkx, sklearn, pyqtgraph and pyqt5, with pip install comand:

pip install numpy      # enter
pip install pandas     # enter
pip install pyqtgraph  # enter
pip install networkx   # enter
pip install sklearn    # enter

Run program ⚙️

1. Locate (with cd comand) interface folder and run python main.py in CMD:

Use Vgraph ⌨️

1. Load signal(s) in format 1 column .txt or .csv:

2. Select the parameters to create visibility graph and maxclique graph and click in "visibility graph" button:

3. At the end of the process, the files are automatically saved in the folder of the loaded signal:

K-means clustering 🛠️

1. This interface can perform k-means clustering with graphs parameters:

2. Load 2 files (parameters) to k-means clustering, set axis labels to graph and number of clusters and click "k-means" button:

3. The clasification image is automatically saved in the folder of the loaded parameters: