Struct DeGrootModel 

pub struct DeGrootModel {
    pub trust: Vec<Vec<f64>>,
}

DeGroot consensus model: linear opinion pooling on a network.

Each agent i updates: o_i(t+1) = Σ_j T_{ij} o_j(t) where T is a row-stochastic trust matrix.

Fields

trust: Vec<Vec<f64>>

Row-stochastic trust matrix T (n×n stored row-major).

Implementations

impl DeGrootModel

pub fn new(trust: Vec<Vec<f64>>) -> Self

Creates a DeGroot model from a trust matrix.

Rows must sum to 1 (caller’s responsibility).

pub fn from_graph(graph: &NetworkGraph) -> Self

Builds a uniform averaging DeGroot model from a graph.

pub fn n(&self) -> usize

Returns the number of agents.

pub fn step(&self, opinions: &[f64]) -> Vec<f64>

Applies one update step to opinions.

pub fn run(&self, opinions: &[f64], steps: usize) -> Vec<f64>

Runs steps iterations, returns final opinions.

pub fn has_consensus(&self, opinions: &[f64], tol: f64) -> bool

Checks if opinions have converged to consensus (max spread < tol).