This repository contains a python class that represent a directed graph
Type in your terminal the following commands to create and activate your Virtual Environment once you have clone the repo
cd directedGraph
python3 -m venv venv
source venv/bin/activate (unix)
.\venv\Scripts\activate (windows)
For more info about Virtual Environments https://docs.python.org/3/library/venv.html Now to install the necessary packages, run the following command
pip install -r requirements.txt
First of all you'll need to import the package
from digraph import DirectedGraph
- You can initialize the object passing a list of vertices and a list of edges
vertices = ['a', 'b', 'c', 'd']
edges = [('a', 'b'), ('a', 'd'), ('b', 'c'), ('c', 'd')]
dgraph = DirectedGraph(vertices, edges)
- Or you can do it from a hdf5 file that represents an adjacency matrix
hdf_dgraph = DirectedGraph.from_hdf('data.h5', 'df')
Once the object is initialize. You can:
- check the number of vertices and edges by using the method info
dgraph.info()
- Visualize its out-degree distribution by using the method plot_histogram
dgraph.plot_histogram('histogram')
- Visualize its the out-degree by node using the method plot_bar
dgraph.plot_bar('bar_plot')
- Export to hdf5 file that represents the graph adjacency matrix by using the method to_hdf
dgraph.to_hdf('data.h5', 'df')
If you are using testing this class in a Jupyter notebook please be aware that the export image might make trasparent the axis and title. https://stackoverflow.com/questions/19576317/matplotlib-savefig-does-not-save-axes