Fapra-OSM-2/src/alt.rs

use crate::gridgraph::{EdgeCost, GraphNode, GridGraph, NodeId};
use serde::{Deserialize, Serialize};
use std::cmp::Ordering;
use std::collections::BinaryHeap;

#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct Landmark {
    pub node: GraphNode,
    pub distances: Vec<EdgeCost>,
}

#[derive(Debug, Clone, Default, Serialize, Deserialize)]
pub struct LandmarkSet {
    pub landmarks: Vec<Landmark>,
}

#[derive(Debug, Clone)]
pub struct LandmarkBestSet<'a> {
    pub landmark_set: &'a LandmarkSet,
    pub best_size: usize,
    best_landmarks: Vec<usize>,
}

impl Landmark {
    pub fn generate(node: GraphNode, graph: &GridGraph) -> Landmark {
        let mut landmark = Landmark {
            node,
            distances: vec![EdgeCost::MAX; graph.nodes.len()],
        };
        landmark.node = node;

        #[derive(Eq, PartialEq)]
        struct DijkstraElement {
            index: u32,
            cost: EdgeCost,
        }

        impl Ord for DijkstraElement {
            // inverted cmp function, such that the Max-Heap provided by Rust
            // can be used as a Min-Heap
            fn cmp(&self, other: &Self) -> Ordering {
                other.cost.cmp(&self.cost)
            }
        }

        impl PartialOrd for DijkstraElement {
            fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
                Some(self.cmp(other))
            }
        }

        let mut heap = BinaryHeap::new();
        heap.push(DijkstraElement {
            cost: 0,
            index: landmark.node.index,
        });

        while let Some(DijkstraElement { index, cost }) = heap.pop() {
            // the heap does not support "update" operations, so we
            // insert elements again and if they come out of the heap but have
            // been processed earlier we simply skip them.
            if cost > landmark.distances[index as usize] {
                continue;
            };

            landmark.distances[index as usize] = cost;

            for edge in graph.get_edges(index as NodeId) {
                let new_cost = cost + edge.cost;

                if new_cost < landmark.distances[edge.neighbor as usize] {
                    //println!("adding new element to heap");
                    heap.push(DijkstraElement {
                        index: edge.neighbor,
                        cost: new_cost,
                    });
                    landmark.distances[edge.neighbor as usize] = new_cost;
                }
            }
        }
        // now the costs to all reachable nodes is calculated.

        landmark
    }

    /// calculates the lower-bounding distance estimate between the 2 nodes
    /// via the landmark.
    /// If one or more of the nodes are not reachable from the landmark
    /// an estimate of `0` is returned.
    pub fn estimate(&self, from: NodeId, to: NodeId) -> EdgeCost {
        let l_to = self.distances[to];
        let l_from = self.distances[from];

        if l_to == EdgeCost::MAX || l_from == EdgeCost::MAX {
            EdgeCost::MAX
        } else {
            // since we are working on an undirected graph we can
            // use the distances once from and once to the landmark.
            // This leads to l_to - l_from and l_from - l_to (as signed subtractions)
            // which except for the sign are the same value.
            // We can simply take the bigger one, which is handled
            // nicely the abs() function
            let distance = (l_to as i64 - l_from as i64).abs() as EdgeCost;
            //println!(
            //    "distance from {} to {} via landmark {} is at least {}",
            //    from, to, self.node.index, distance
            //);
            distance
        }
    }
}

impl LandmarkSet {
    pub fn random_set(size: usize, graph: &GridGraph) -> Self {
        let mut set = LandmarkSet::default();

        let nodes = graph.get_random_nodes(size);

        for node in nodes.into_iter() {
            let landmark = Landmark::generate(*node, graph);
            set.landmarks.push(landmark)
        }

        set
    }
}

impl LandmarkBestSet<'_> {
    pub fn select_best(&mut self, from: NodeId, to: NodeId) {
        let mut results = vec![];

        for (index, landmark) in self.landmark_set.landmarks.iter().enumerate() {
            results.push((index, landmark.estimate(from, to)));
        }

        results.sort_by_key(|k| k.1);
        results.reverse();

        self.best_landmarks.clear();
        for result in results[..self.best_size].iter() {
            self.best_landmarks.push(result.0);
        }
    }

    pub fn estimate(&self, from: NodeId, to: NodeId) -> EdgeCost {
        let mut distance = 0;

        for index in &self.best_landmarks {
            let candidate = self.landmark_set.landmarks[*index].estimate(from, to);

            if candidate == EdgeCost::MAX {
                continue;
            }

            distance = distance.max(candidate)
        }

        //println!("calculated estimate {:?} for {} to {}", distance, from, to);

        distance
    }

    pub fn new<'a>(best_size: usize, landmark_set: &'a LandmarkSet) -> LandmarkBestSet<'a> {
        LandmarkBestSet {
            best_size,
            landmark_set,
            best_landmarks: Vec::new(),
        }
    }
}