Network Generators

The following network generators can be utilized in the configuration in the following format:

structure:
    random:
        type: 'conf-file-notation'
        parameter1: 100
        parameter2: 4
        ...

Name

Conf. File Notation

Parameters

Random Regular Graph (NetworkX)

random-regular

  • degree (int): The degree of each node.

  • count (int): The number of nodes in the graph.

Erdős-Rényi Graph (NetworkX)

erdos-renyi

  • p (float): Probability for edge creation.

  • count (int): The number of nodes in the graph.

Barabási-Albert Graph (NetworkX)

barabasi-albert

  • m (int): Number of edges to attach from a new node to existing nodes.

  • count (int): The number of nodes in the graph.

Watts-Strogatz Graph (NetworkX)

watts-strogatz

  • k (int): Number of nearest neighbors to be joined with for each node.

  • p (float): Rewiring probability.

  • count (int): The number of nodes in the graph.

Connected Watts-Strogatz Graph (NetworkX)

connected-watts-strogatz

  • k (int): Number of nearest neighbors to be joined with for each node.

  • p (float): Rewiring probability.

  • tries (int): Number of attempts to generate a connected graph.

  • count (int): The number of nodes in the graph.

Newman-Watts-Strogatz Graph (NetworkX)

newman-watts-strogatz

  • k (int): Number of nearest neighbors to be joined with for each node.

  • p (float): Rewiring probability.

  • count (int): The number of nodes in the graph.

Powerlaw Cluster Graph (NetworkX)

powerlaw-cluster-graph

  • m (int): Number of edges to add for each new node.

  • p (float): Probability of adding a triangle after adding a random edge.

  • count (int): The number of nodes in the graph.

Forest Fire Graph (iGraph)

forest-fire

  • fw-prob (float): Forward burning probability.

  • bw-factor (float): Backward burning ratio.

  • count (int): The number of nodes in the graph.

Stochastic Block Model (iGraph)

stochastic-block

  • p-matrix (list of lists): Preference matrix.

  • block-sizes (list of ints): Sizes of the blocks.

  • include-loops (bool): Whether loops are included (optional, defaults to False).

  • count (int): The number of nodes in the graph.

LFR Benchmark Graph (NetworkX)

LFR-benchmark

  • tau1 (float): Power-law exponent for degree distribution.

  • tau2 (float): Power-law exponent for community size distribution.

  • mu (float): Mixing parameter.

  • avg-degree (float): Average degree (optional).

  • min-degree (int): Minimum degree (optional).

  • max-degree (int): Maximum degree (optional).

  • min-community (int): Minimum community size (optional).

  • max-community (int): Maximum community size (optional).

  • tolerance (float): Tolerance for the community size (optional, defaults to 1e-07).

  • max-iterations (int): Maximum iterations (optional, defaults to 500).

  • count (int): The number of nodes in the graph.

Geometric Random Graph (iGraph)

geometric-random

  • radius (float): Distance threshold value.

  • count (int): The number of nodes in the graph.

Configuration Model (iGraph)

configuration

  • degrees-path (str): Path to file containing degree sequence.

  • method (str): Graph generation method (configuration or others, optional, defaults to configuration).

Static Fitness Model (iGraph)

static-fitness

  • m (int): Number of edges.

  • fitness-path (str): Path to file containing fitness values.

  • include-loops (bool): Whether loops are included (optional, defaults to False).

The following networks can be utilized in the configuration in the following format:

structure:
    from-library:
        type: 'conf-file-notation'
        if-parameter-exists: 100
        ...

Name

Conf. File Notation

Information

Complete Graph (NetworkX)

complete-graph

Parameter count (int): The number of nodes in the graph.

Zachary’s Karate Club Graph (NetworkX)

karate-club-graph

A social network of friendships between 34 members of a karate club.

Les Miserables Graph (NetworkX)

les-miserables

A coappearance network of characters in the novel Les Miserables.

Next: (Optional) Reading networks from file