yog - v3.1.0

yog/generators/random

Stochastic graph generators for random graph models.

Values

barabasi_albert

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pub fn barabasi_albert(n: Int, m: Int) -> model.Graph(Nil, Int)

Generates a scale-free network using the Barabási-Albert model.

Starts with m₀ nodes in a complete graph, then adds nodes using preferential attachment.

Time Complexity: O(nm)

Example

let graph = random.barabasi_albert(100, 3)

barabasi_albert_with_type

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pub fn barabasi_albert_with_type(
  n: Int,
  m: Int,
  graph_type: model.GraphType,
) -> model.Graph(Nil, Int)

Generates a Barabási-Albert graph with specified graph type.

erdos_renyi_gnm

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pub fn erdos_renyi_gnm(n: Int, m: Int) -> model.Graph(Nil, Int)

Generates a random graph using the Erdős-Rényi G(n, m) model.

Exactly m edges are added uniformly at random.

Time Complexity: O(m) expected

Example

let graph = random.erdos_renyi_gnm(50, 100)

erdos_renyi_gnm_with_type

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pub fn erdos_renyi_gnm_with_type(
  n: Int,
  m: Int,
  graph_type: model.GraphType,
) -> model.Graph(Nil, Int)

Generates an Erdős-Rényi G(n, m) graph with specified graph type.

erdos_renyi_gnp

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pub fn erdos_renyi_gnp(n: Int, p: Float) -> model.Graph(Nil, Int)

Generates a random graph using the Erdős-Rényi G(n, p) model.

Each possible edge is included independently with probability p.

Time Complexity: O(n²)

Example

let graph = random.erdos_renyi_gnp(50, 0.1)

erdos_renyi_gnp_with_type

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pub fn erdos_renyi_gnp_with_type(
  n: Int,
  p: Float,
  graph_type: model.GraphType,
) -> model.Graph(Nil, Int)

Generates an Erdős-Rényi G(n, p) graph with specified graph type.

random_tree

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pub fn random_tree(n: Int) -> model.Graph(Nil, Int)

Generates a uniformly random tree on n nodes.

Time Complexity: O(n²) expected

Example

let tree = random.random_tree(50)

random_tree_with_type

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pub fn random_tree_with_type(
  n: Int,
  graph_type: model.GraphType,
) -> model.Graph(Nil, Int)

Generates a random tree with specified graph type.

watts_strogatz

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pub fn watts_strogatz(
  n: Int,
  k: Int,
  p: Float,
) -> model.Graph(Nil, Int)

Generates a small-world network using the Watts-Strogatz model.

Creates a ring lattice where each node connects to k nearest neighbors, then rewires with probability p.

Time Complexity: O(nk)

Example

let graph = random.watts_strogatz(100, 4, 0.1)

watts_strogatz_with_type

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pub fn watts_strogatz_with_type(
  n: Int,
  k: Int,
  p: Float,
  graph_type: model.GraphType,
) -> model.Graph(Nil, Int)

Generates a Watts-Strogatz graph with specified graph type.

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