directed_graph 0.3.8

Generic directed graph and weighted directed graph with algorithms enabling sorting and topological ordering of vertices.

Directed Graph

Introduction

An integral part of storing, manipulating, and retrieving numerical data are data structures or as they are called in Dart: collections. Arguably the most common data structure is the list. It enables efficient storage and retrieval of sequential data that can be associated with an index.

A more general (non-linear) data structure where an element may be connected to one, several, or none of the other elements is called a graph.

Graphs are useful when keeping track of elements that are linked to or are dependent on other elements. Examples include: network connections, links in a document pointing to other paragraphs or documents, foreign keys in a relational database, file dependencies in a build system, etc.

The package directed_graph contains an implementation of a Dart graph that follows the recommendations found in graphs-examples and is compatible with the algorithms provided by graphs. It is simple to use and includes methods that enable:

• adding/removing vertices and edges,
• the sorting of vertices.

The library provides access to algorithms for finding:

• the shortest path between vertices,
• the path with the lowest/highest weight (for weighted directed graphs),
• all paths connecting two vertices,
• cycles,
• a topological ordering of the graph vertices.

The class GraphCrawler can be used to retrieve paths or walks connecting two vertices.

Terminology

Elements of a graph are called vertices (or nodes) and neighbouring vertices are connected by edges. The figure below shows a directed graph with unidirectional edges depicted as arrows. Graph edges are emanating from a vertex and ending at a vertex. In a weighted directed graph each edge is assigned a weight.

• In-degree of a vertex: Number of edges ending at this vertex. For example, vertex H has in-degree 3.
• Out-degree of a vertex: Number of edges starting at this vertex. For example, vertex F has out-degree 1.
• Source: A vertex with in-degree zero is called (local) source. Vertices A and D in the graph above are local sources.
• Directed Edge: An ordered pair of connected vertices (v_i, v_j). For example, the edge (A, C) starts at vertex A and ends at vertex C.
• Path: A path [v_i, ..., v_n] is an ordered list of at least two connected vertices where each inner vertex is distinct. The path [A, E, G] starts at vertex A and ends at vertex G.
• Cycle: A cycle is an ordered list of connected vertices where each inner vertex is distinct and the first and last vertices are identical. The sequence [F, I, K, F] completes a cycle.
• Walk: A walk is an ordered list of at least two connected vertices. [D, F, I, K, F] is a walk but not a path since the vertex F is listed twice.
• DAG: An acronym for Directed Acyclic Graph, a directed graph without cycles.
• Topological ordering: An ordered set of all vertices in a graph such that v_i occurs before v_j if there is a directed edge (v_i, v_j). A topological ordering of the graph above is: {A, D, B, C, E, K, F, G, H, I, L}. Hereby, dashed edges were disregarded since a cyclic graph does not have a topological ordering.

Note: In the context of this package the definition of edge might be more lax compared to a rigorous mathematical definition. For example, self-loops, that is edges connecting a vertex to itself are explicitly allowed.

Usage

To use this library include directed_graph as a dependency in your pubspec.yaml file. The example below shows how to construct an object of type DirectedGraph. The constructor takes an optional comparator function as parameter. If a comparator is specified, vertices are sorted accordingly. For more information see comparator.

import 'package:directed_graph/directed_graph.dart';
// To run this program navigate to
// the folder 'directed_graph/example'
// in your terminal and type:
//
// # dart bin/directed_graph_example.dart
//
// followed by enter.
void main() {
  int comparator(String s1, String s2) => s1.compareTo(s2);
  int inverseComparator(String s1, String s2) => -comparator(s1, s2);

  // Constructing a graph from vertices.
  final graph = DirectedGraph<String>(
    {
      'a': {'b', 'h', 'c', 'e'},
      'b': {'h'},
      'c': {'h', 'g'},
      'd': {'e', 'f'},
      'e': {'g'},
      'f': {'i'},
      'i': {'l'},
      'k': {'g', 'f'}
    },
    comparator: comparator,
  );

  print('Example Directed Graph...');
  print('graph.toString():');
  print(graph);

  print('\nIs Acylic:');
  print(graph.isAcyclic);

  print('\nStrongly connected components:');
  print(graph.stronglyConnectedComponents);

  print('\nShortestPath(d, l):');
  //print(graph.shortestPath('d', 'l');

  print('\nInDegree(C):');
  print(graph.inDegree('c'));

  print('\nOutDegree(C)');
  print(graph.outDegree('c'));

  print('\nVertices sorted in lexicographical order:');
  print(graph.sortedVertices);

  print('\nVertices sorted in inverse lexicographical order:');
  graph.comparator = inverseComparator;
  print(graph.sortedVertices);
  graph.comparator = comparator;

  print('\nInDegreeMap:');
  print(graph.inDegreeMap);

  print('\nSorted Topological Ordering:');
  print(graph.sortedTopologicalOrdering);

  print('\nTopological Ordering:');
  print(graph.topologicalOrdering);

  print('\nLocal Sources:');
  print(graph.localSources);

  // Add edge to render the graph cyclic
  graph.addEdges('i', {'k'});
  graph.addEdges('l', {'l'});
  graph.addEdges('i', {'d'});

  print('\nCycle:');
  print(graph.cycle);

  print('\nShortest Paths:');
  print(graph.shortestPaths('a'));
}

Click to show the console output.

$ dart example/bin/directed_graph_example.dart
Example Directed Graph...
graph.toString():
{
 'a': {'b', 'h', 'c', 'e'},
 'b': {'h'},
 'c': {'h', 'g'},
 'd': {'e', 'f'},
 'e': {'g'},
 'f': {'i'},
 'g': {},
 'h': {},
 'i': {'l'},
 'k': {'g', 'f'},
 'l': {},
}

Is Acylic:
true

Strongly connected components:
[[h], [b], [g], [c], [e], [a], [l], [i], [f], [d], [k]]

ShortestPath(d, l):

InDegree(C):
1

OutDegree(C)
2

Vertices sorted in lexicographical order:
[a, b, c, d, e, f, g, h, i, k, l]

Vertices sorted in inverse lexicographical order:
[l, k, i, h, g, f, e, d, c, b, a]

InDegreeMap:
{a: 0, b: 1, h: 3, c: 1, e: 2, g: 3, d: 0, f: 2, i: 1, l: 1, k: 0}

Sorted Topological Ordering:
{a, b, c, d, e, h, k, f, g, i, l}

Topological Ordering:
{a, b, c, d, e, h, k, f, i, g, l}

Local Sources:
[[a, d, k], [b, c, e, f], [g, h, i], [l]]

Cycle:
[l, l]

Shortest Paths:
{e: (e), c: (c), h: (h), a: (), g: (c, g), b: (b)}

Weighted Directed Graphs

The example below shows how to construct an object of type WeightedDirectedGraph. Initial graph edges are specified in the form of map of type Map<T, Map<T, W>>. The vertex type T extends Object and therefore must be a non-nullable. The type associated with the edge weight W extends Comparable to enable sorting of vertices by their edge weight.

The constructor takes an optional comparator function as parameter. If a comparator is specified, vertices are sorted accordingly. For more information see comparator.

import 'package:directed_graph/directed_graph.dart';

void main(List<String> args) {
  int comparator(
    String s1,
    String s2,
  ) {
    return s1.compareTo(s2);
  }

  final a = 'a';
  final b = 'b';
  final c = 'c';
  final d = 'd';
  final e = 'e';
  final f = 'f';
  final g = 'g';
  final h = 'h';
  final i = 'i';
  final k = 'k';
  final l = 'l';

  int sum(int left, int right) => left + right;

  var graph = WeightedDirectedGraph<String, int>(
    {
      a: {b: 1, h: 7, c: 2, e: 40, g:7},
      b: {h: 6},
      c: {h: 5, g: 4},
      d: {e: 1, f: 2},
      e: {g: 2},
      f: {i: 3},
      i: {l: 3, k: 2},
      k: {g: 4, f: 5},
      l: {l: 0}
    },
    summation: sum,
    zero: 0,
    comparator: comparator,
  );

  print('Weighted Graph:');
  print(graph);

  print('\nNeighbouring vertices sorted by weight:');
  print(graph..sortEdgesByWeight());

  final lightestPath = graph.lightestPath(a, g);
  print('\nLightest path a -> g');
  print('$lightestPath weight: ${graph.weightAlong(lightestPath)}');

  final heaviestPath = graph.heaviestPath(a, g);
  print('\nHeaviest path a -> g');
  print('$heaviestPath weigth: ${graph.weightAlong(heaviestPath)}');

  final shortestPath = graph.shortestPath(a, g);
  print('\nShortest path a -> g');
  print('$shortestPath weight: ${graph.weightAlong(shortestPath)}');
}

Click to show the console output.

$ dart example/bin/weighted_graph_example.dart
Weighted Graph:
{
 'a': {'b': 1, 'h': 7, 'c': 2, 'e': 40, 'g': 7},
 'b': {'h': 6},
 'c': {'h': 5, 'g': 4},
 'd': {'e': 1, 'f': 2},
 'e': {'g': 2},
 'f': {'i': 3},
 'g': {},
 'h': {},
 'i': {'l': 3, 'k': 2},
 'k': {'g': 4, 'f': 5},
 'l': {'l': 0},
}

Neighbouring vertices sorted by weight
{
 'a': {'b': 1, 'c': 2, 'h': 7, 'g': 7, 'e': 40},
 'b': {'h': 6},
 'c': {'g': 4, 'h': 5},
 'd': {'e': 1, 'f': 2},
 'e': {'g': 2},
 'f': {'i': 3},
 'g': {},
 'h': {},
 'i': {'k': 2, 'l': 3},
 'k': {'g': 4, 'f': 5},
 'l': {'l': 0},
}

Lightest path a -> g
[a, c, g] weight: 6

Heaviest path a -> g
[a, e, g] weigth: 42

Shortest path a -> g
[a, g] weight: 7

Examples

For further information on how to generate a topological sorting of vertices see example.

Features and bugs

Please file feature requests and bugs at the issue tracker.