eliotwrobson / CyNetDiff

A performance-focused library implementing algorithms for simulating network diffusion processes, written in Cython.

CyNetDiff

• Documentation: https://eliotwrobson.github.io/CyNetDiff/

A performance-focused library implementing algorithms for simulating network diffusion processes, written in Cython.

Quick Start

Installation

pip install cynetdiff

Note: The installation includes a build step that requires having a C++ complier installed.

Usage

We can run models over graphs we define, using pre-defined weighting schemes. Here is a simple example

import random
import networkx as nx
from cynetdiff.utils import networkx_to_ic_model

# Randomly generate the graph
n = 1_000
p = 0.05
graph = nx.fast_gnp_random_graph(n, p)

# Randomly choose seed nodes
k = 10
nodes = list(graph.nodes)
seeds = random.sample(nodes, k)

# Set the activation probability uniformly and set seeds
model = networkx_to_ic_model(graph, activation_prob=0.2)
model.set_seeds(seeds)

# Run the diffusion process
model.advance_until_completion()

# Get the number of nodes activated
model.get_num_activated_nodes()

Project Status

This project is still considered in an alpha stage of development. As such, the API is still relatively undocumented, not yet fully featured, and could still change.

All feedback is greatly appreciated!