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//! This module contains definitions for the network models and their constructing algorithms.

use crate::algorithms;
use super::Network;
use crate::CNErr;
use rand::prelude::*;
use serde::{Serialize, Deserialize};

/// `Model` decides the algorithm used to connect the nodes during `Network`'s
/// initialization.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum Model {
    /// The Erdos–Renyi random network model.
    ER {
        /// The probability of connecting any given pair of nodes.
        p: f64,
        /// Should the network be in one piece
        whole: bool,
    },
    /// The Barabasi–Albert preferential attachment model.
    BA {
        /// The initial number of clustered nodes.
        m0: usize,
        /// The number of nodes added in each step during network creation.
        /// Keep in mind that this should be strictly less or equal m0 and the Barabasi-Albert
        /// initialization fuction **will panic** if this is not the case.
        m: usize,
    },
    /// Placeholder for a network with no connections.
    None,
}

impl Model {
    /// Initialize (or reinitialize) the network's links according to the Erdos-Renyi model.
    /// See the [Model](enum.Model.html) for more detailed model explanation.
    ///
    /// If `whole` is `true` then the network is artificially stitched together after
    /// initialization, otherwise there is no guarantee that there are no 'outsiders' or even
    /// separate networks.
    ///
    /// Beware that the network is **not** cleared before linking.
    pub fn init_er(net: &mut Network, p: f64, whole: bool) {
        let net_len = net.size();
        if p <= 0. || p > 1. {
            CNErr::BadProbability(p).panic();
        }
        for i in 0..net_len {
            for j in i + 1..net_len {
                if net.rng().unwrap().gen::<f64>() <= p {
                    net.link(i, j).unwrap();
                }
            }
        }
        if whole {
            algorithms::stitch_together(net);
        }
        net.model = Model::ER { p, whole };
    }

    /// Initialize (or reinitialize) the network's links according to the Barabasi-Albert model.
    /// See the [Model](enum.Model.html) for more detailed model explanation.
    ///
    /// The links *are* cleared before re-linking because of the nature of initialization algorithm
    pub fn init_ba(net: &mut Network, m0: usize, m: usize) {
        if m0 < 1 || m == 0 || m > m0 || m0 > net.size() {
            panic!("Incorrect model parameters: m0 = {}, m = {}", m0, m);
        }
        net.disconnect_all();
        // Initial cluster - connect everything to everything
        for i in 0..m0 {
            if m0 == 1 {
                break;
            }
            for j in i + 1..m0 {
                net.link(i, j).unwrap();
            }
        }
        // Attach the other nodes one by one
        for current_idx in m0..net.size() {
            for other in net
                .nodes()
                .filter(|&node| *node.index() < current_idx)
                .map(|node| (*node.index(), *node.deg() as i32))
                .collect::<Vec<_>>() // This is sadly needed
                .choose_multiple_weighted(net.rng.get_mut(), m, |(_index, deg)| *deg)
                .unwrap()
                .map(|&(idx, _deg)| idx)
            {
                net.link(current_idx, other).unwrap();
            }
        }
    }
}