arboretum-td 0.1.0

A library and CLI for obtaining exact and heuristc tree decompositions for arbitrary graphs
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150

use crate::datastructures::BitSet;
use crate::graph::base_graph::BaseGraph;
use fxhash::FxHashMap;
use std::borrow::Borrow;
use std::cmp::Ordering;

#[derive(Clone, Debug)]
pub struct BitGraph {
    graph: Vec<BitSet>,
}

impl From<Vec<BitSet>> for BitGraph {
    fn from(graph: Vec<BitSet>) -> Self {
        Self { graph }
    }
}

impl From<&[BitSet]> for BitGraph {
    fn from(slice: &[BitSet]) -> Self {
        Self {
            graph: Vec::from(slice),
        }
    }
}

impl BitGraph {
    pub fn from_graph<G: BaseGraph>(og_graph: &G, og_to_self: &FxHashMap<u32, u32>) -> Self {
        let mut graph = vec![BitSet::new(og_graph.order()); og_graph.order()];

        for v in og_graph.vertices() {
            for u in og_graph.neighborhood(v) {
                let a = (*og_to_self.get(&(v as u32)).unwrap()) as usize;
                let b = (*og_to_self.get(&(u as u32)).unwrap()) as usize;
                graph[a].set_bit(b);
            }
        }
        Self { graph }
    }

    pub fn neighborhood_as_bitset(&self, u: usize) -> &BitSet {
        self.graph[u].borrow()
    }

    pub fn exterior_border(&self, c: &BitSet) -> BitSet {
        let mut border = BitSet::new(c.len());

        for v in c.iter() {
            border.or(&self.graph[v])
        }
        border.and_not(c);
        border
    }
}

impl BaseGraph for BitGraph {
    fn degree(&self, u: usize) -> usize {
        self.graph[u].cardinality()
    }

    fn order(&self) -> usize {
        self.graph.len()
    }

    fn is_clique(&self, vertices: &[usize]) -> bool {
        for u in vertices {
            for v in vertices {
                if u < v && !self.graph[*u][*v] {
                    return false;
                }
            }
        }
        true
    }

    fn is_neighborhood_clique(&self, u: usize) -> bool {
        for u in self.graph[u].iter() {
            for v in self.graph[u].iter() {
                if u < v && !self.graph[u][v] {
                    return false;
                }
            }
        }
        true
    }

    fn has_edge(&self, u: usize, v: usize) -> bool {
        self.graph[u][v]
    }

    fn is_simplicial(&self, u: usize) -> bool {
        self.is_neighborhood_clique(u)
    }

    fn is_almost_simplicial(&self, u: usize) -> bool {
        for ignore in self.graph[u].iter() {
            for u in self.graph[u].iter() {
                for v in self.graph[u].iter() {
                    if u < v && u != ignore && !self.graph[u][v] {
                        return false;
                    }
                }
            }
        }
        true
    }

    fn vertices(&self) -> Box<dyn Iterator<Item = usize>> {
        Box::new(0..self.graph.len())
    }

    fn neighborhood(&self, u: usize) -> Box<dyn Iterator<Item = usize> + '_> {
        Box::new(self.graph[u].iter())
    }

    fn fill_in_count(&self, u: usize) -> usize {
        let mut cnt = 0;
        for u in self.graph[u].iter() {
            for v in self.graph[u].iter() {
                if u < v && !self.graph[u][v] {
                    cnt += 1;
                }
            }
        }
        cnt
    }

    fn min_vertex_by<F: FnMut(&usize, &usize) -> Ordering>(&self, cmp: F) -> Option<usize> {
        (0..self.graph.len()).min_by(cmp)
    }

    fn max_vertex_by<F: FnMut(&usize, &usize) -> Ordering>(&self, cmp: F) -> Option<usize> {
        (0..self.graph.len()).max_by(cmp)
    }

    fn min_neighbor_by<F: FnMut(&usize, &usize) -> Ordering>(
        &self,
        u: usize,
        cmp: F,
    ) -> Option<usize> {
        self.graph[u].iter().min_by(cmp)
    }

    fn max_neighbor_by<F: FnMut(&usize, &usize) -> Ordering>(
        &self,
        u: usize,
        cmp: F,
    ) -> Option<usize> {
        self.graph[u].iter().max_by(cmp)
    }
}