scinet-JoshGoA 0.3.1

Network science abstract data types

SCINET

Graph theory abstract data type.

scinet.Graph is designed upon the graph (abstract data type) definition and functions as a bare bones skeletal graph data mapping, containing abstract vertices and edges.

Installation

1. Install Python >= 3.8
2. Install scinet

$ pip install scinet

Usage

Import scinet

import scinet as sn

Create graph

G = sn.Graph()

Manipulate data

• add_vertex

G.add_vertex(vertex := "foo")

• remove_vertex

G.remove_vertex(vertex := "foo")

• add_edge

G.add_edge(edge := "foobar", source_vertex="foo", target_vertex="bar")

• remove_edge

G.remove_edge(edge := "foobar", source_vertex="foo", target_vertex="bar")

• adjacent

(target_vertex := "bar") in G[(source_vertex := "foo")]

• neighbors

G[(vertex := "foo")].keys()

See docs for further details.

Contributors

• JoshGoA - Main contributor - GitHub

TODO

1. Undirected graph

Add "directed" mappable property to edge data

2. Network visualization

Create "matplotlib.pyplot" supported API