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GraphDS

What is GraphDS and why was it created?

GraphDS is an object-oriented, lightweight implementation of the graph data-structure in PHP.

In a project of mine, I needed a way to represent graphs in PHP. None of the existing solutions suited me, so I have decided to write my own graph library from scratch. The original implementation used in my project contains additional functions for graph traversal and refactoring of graphs, but these functions are specific to my project.

This version of GraphDS used to be a toned-down version of my original implementation, but has now grown into a separate project. It makes use of OOP practices to allow on-demand loading of algorithms, making GraphDS fast, extendable and lightweight at the same time.

GraphDS requires at least PHP version 5.3. Unit tests can be run from PHP 5.4 onwards. Although compatibility with older PHP versions tries to be maintained, unit tests are only run officially for the last 3 major PHP versions.

How to install

Simply require the Composer package. In the directory of your project, run:

composer require algb12/graph-ds

What is it even useful for?

Graphs are useful for many things, ranging from transportation to social networks. In this regard, GraphDS makes working with graphs in PHP a lot easier.

Please see the RoadPlanner sample app in the SampleApp_RoadPlanner directory to find a primitive application of GraphDS. The RoadPlanner app calculates the shortest road between two cities, using Dijkstra's, multi-path Dijkstra's and the Floyd-Warshall algorithm. Computed paths are represented visually on the source map. To test GraphDS out with your own map, take a look at the roads.json file in src/data, where you can add in your own map/"country".

Basic syntax

GraphDS has functions to create vertices and edges for both, undirected and directed graphs. The user does not need to worry about which type of edge/vertex is created, as this is all abstracted away under the relevant classes.

The following is a quick primer on the usage of GraphDS:

Directed and undirected graphs

In graph theory, there are two main types of graphs. On one hand, there are directed graphs. A directed graph has vertices connected with by one-way edges. Think of a edges of a directed graph as a one-way lanes – you can start at any vertex, but can then only follow along the directionality of the edge to the neighboring vertex.

On the other hand, there are undirected graphs. They allow you to get from any vertex to any neighbor, as in undirected graphs, there is no concept of ancestors and descendants. Think of edges of an undirected graph as normal roads, with traffic in both directions. Vertices are simply connected with each other by directionless edges.

The following shows how to initialize a directed graph:

Note that a graph is an object, and any vertices and edges are contained within this object.

In a similar manner, an undirected graph can be initialized, by creating an instance of the UndirectedGraph object in place of DirectedGraph.

Transpose graphs

The transpose graph of a directed graph is when all edges (u, v) become (v, u), where u and v are vertices connected by a directed edge.

To get the transpose of a directed graph $g as a DirectedGraph object, call:

$g->getTranspose()

This may be useful for algorithms which require graph transposition, and now, GraphDS provides a method to achieve it.

Vertices

In any graph, all vertices can be accessed through the $g->vertices array, where $g is an instance of a graph object. So, to access vertex A, the syntax would be $g->vertices['A'].

Adding and removing vertices

Adding and removing vertices can be accomplished using the $g->addVertex('v') and $g->removeVertex('v') methods, where v is the name of the vertex to be added/removed.

Getting and setting the value of a vertex

To get the value of a vertex, $g->vertices['v']->getValue() can be called. To set the value of a vertex, $g->vertices['v']->setValue(value) can be called, where value can be any storable data-type.

Getting neighbors of a vertex

Getting the neighbors of a vertex in an undirected graph can be accomplished by using $g->vertices['v']->getNeighbors().

In a directed graph, $g->vertices['v']->getInNeighbors() returns an array of all vertices connected by an incoming edge, whereas $g->vertices['v']->getOutNeighbors() returns an array of all vertices connected by an outgoing edge from the current vertex. $g->vertices['v']->getNeighbors() returns an array of two subarrays, in and out, for incoming and outgoing vertices, respectively.

Indegrees and outdegrees

The indegree and outdegree of a vertex is simply how many incoming and outgoing vertices are connected to a vertex, respectively.

Indegrees and outdegrees only apply to directed graphs, since undirected graphs cannot have incoming or outgoing edges.

The indegree and outdegree of a vertex can be easily determined using $g->vertices['v']->getIndegree() and $g->vertices['v']->getOutdegree().

Asserting vertex adjacency

In any graph, asserting that vertex B is adjacent to A can be done by calling $g->vertices['A']->adjacent('B'). If the vertex is adjacent, then true is returned, otherwise, false. Note that in a directed graph, a vertex will be considered as adjacent using the adjacent method, no matter whether it is incoming or outgoing.

In a directed graph, inward and outward adjacency can be asserted by using $g->vertices['A']->inAdjacent('B') and $g->vertices['A']->outAdjacent('B'), respectively.

Edges

Edges are the objects that connect vertices together. Note that in GraphDS, edges are stored as separate objects to the vertices, meaning that they exist independently. It is the GraphDS core that manages the relationship between edges and vertices within the graph.

Edges can be accessed easily via $g->edge('A', 'B'), where A and B are the vertices connected by the edge. Note that in an undirected graph, $g->edge('A', 'B') and $g->edge('B', 'A') are equivalent, whereas in directed graphs, they represent 2 distinct edges.

Real and virtual edges

In GraphDS, edges are stored as objects, and each object takes up memory space. To reduce the spatial footprint, the edge function was introduced in version 1.0.3, which returns both, real edges and "virtual" edges.

Real edges are actual DirectedEdge or UndirectedEdge objects, whereas virtual edges are not actually edge objects, but merely a result of the edge function returning edge ('A', 'B'), even when ('B', 'A') is requested. A virtual edge can be modified just like a real edge. Virtual edges are not part of directed graphs, since every directed edge is distinct.

This is desired behavior, as in undirected graphs, edge ('A', 'B') would be equivalent to ('B', 'A'). Virtual edges also eliminate the problem of edge duplication in undirected graphs, and therefore also reduce the memory GraphDS takes up.

Adding and removing edges

To add an edge, simply call $g->addEdge('A', 'B', 'value'), where A and B are the vertices in graph $g to be connected by this edge, and value is an optional value of the edge. The value could be used as the weight of the edge. The default value of edges is null.

Note that in undirected graphs, this will result in the "virtual" edge ('B', 'A') being returned, even if ('A', 'B') is requested.

Removing an edge can be accomplished via $g->removeEdge('A', 'B'). Due to the behavior of virtual edges, this will remove both, the real edge ('A', 'B') and the virtual edge ('B', 'A') in an undirected graph, but only the real edge in a directed graph. In undirected graphs, edge removal is order-agnostic, meaning that regardless whether a real or virtual edge is supplied, the correct edge will still be removed.

Getting and setting the value of an edge

To get the value of an edge, $g->edge('A', 'B')->getValue() can be called. To set the value of an edge, $g->edge('A', 'B')->setValue(value) can be called, where value can be any storable data-type.

Algorithms

Since version 1.0.1, GraphDS has support for algorithms. GraphDS\Algo is the namespace for algorithms in GraphDS.

In GraphDS, algorithms are treated as separate objects modifying the graph. They accept the graph and work on it, but do not impact the graph's core functionality.

This is what makes GraphDS lean and streamlined, as algorithms only have to be loaded into memory whenever they are needed, as they are not intrinsic to a graph object.

Running algorithms

1. Any algorithm first has to be "used" by PHP, e.g. use GraphDS\Algo\Algorithm
2. An new instance of the algorithm on the relevant graph ($g) has to be created, e.g. $a = new Algorithm($g)
3. The algorithm can now be run using $a->run(args), where args are arguments which differ from algorithm to algorithm
4. Getting the results of an algorithm is done using $a->get(args), where args are arguments which differ from algorithm to algorithm

The "run-and-get" pragma eases the use of algorithms, as these are the only two public exposed methods an algorithm should have. From now on, the documentation will only refer to the those two methods accept.

Writing GraphDS algorithms

In order to ease the writing of algorithms, PHP's Standard PHP Library (SPL) provides useful helper classes, such as:

• SplQueue: An implementation of a FIFO queue
• SplStack: An implementation of a LIFO stack

These classes greatly simplify the writing of algorithms, such as depth-first search (DFS) and breadth-first search (BFS), which can be found in the directory with the algorithms.

The following outlines the basic structure of GraphDS algorithms. For the sake of brevity, docblocks have been left out, although it is most recommended to properly document the algorithm:

The above, outlined in words again:

• Check if graph is actually a graph and use it, otherwise throw InvalidArgumentException
• run(args) executes the algorithm, where args are arguments
• get(args) gets the results of the algorithm, where args are arguments

Do note that the way the results variable is handled is left flexible, as different algorithms may require access to it form different parts of the code.

Breadth-first search (BFS)

BFS, a path traversal algorithm, is in the class GraphDS\Algo\BFS. It visits every vertex in the graph, and goes along the breadth of the graph. As such, level by level, it visits every vertex in the graph.

• $bfs->run(root) accepts root as a compulsory argument, this is the name of the starting vertex for the BFS
• $bfs->get() accepts no arguments. It returns an array, $arr, with 3 subarrays:
  • $arr['discovered'] (vertices discovered in BFS order)
  • $arr['dist'] (the distances of each vertex to the root vertex, in hops)
  • $arr['parent'] (each vertex's parent vertex when using BFS)

Depth-first search (DFS)

DFS, a path traversal algorithm, is in the class GraphDS\Algo\DFS. It visits every vertex in the graph, and goes along the depth of the graph. As such, it visits every vertex in the graph, and only moves from one vertex to another vertex once all the vertex's descendants have been visited to their full depth.

• $dfs->run(root) accepts root as a compulsory argument, this is the name of the starting vertex for the DFS
• $dfs->get() accepts no arguments. It returns an array, arr, with 3 subarrays:
  • $arr['discovered'] (vertices discovered in DFS order)
  • $arr['dist'] (the distances of each vertex to the root vertex, in hops)
  • $arr['parent'] (each vertex's parent vertex when using DFS)

Dijkstra's shortest path algorithm

Dijkstra's shortest path algorithm finds the shortest path between a vertex and all other vertices. It is in the class GraphDS\Algo\Dijkstra.

• $dijkstra->run(start) accepts start as a compulsory argument, this is the name of the vertex from which Dijkstra should start
• $dijkstra->get(dest) accepts dest as a compulsory argument, which is the name of the destination vertex to which the shortest path should be returned. It returns an array, arr, with 2 subarrays:
  • $arr['path'] (the shortest path to the vertex dest from start)
  • $arr['dist'] (the shortest distances of each vertex to the root vertex, in edge weights)

Multi-path Dijkstra's shortest path algorithm

Unlike the single-path version, the multi-path Dijkstra's shortest path algorithm finds all the shortest path between a vertex and all other vertices. It is in the class GraphDS\Algo\DijkstraMulti.

• $dijkstra_mult->run(start) accepts start as a compulsory argument, this is the name of the vertex from which the multi-path Dijkstra should start
• $dijkstra_mult->get(dest) accepts dest as a compulsory argument, which is the destination vertex to which all the shortest paths should be computed. It returns an array, $arr, with 2 subarrays:
  • $arr['paths'] (an array of all the shortest paths to the vertex $dest from $start)
  • $arr['dist'] (the shortest distances of each vertex to the root vertex, in edge weights)

Floyd-Warshall algorithm

The Floyd-Warshall algorithm calculates the shortest path between every single vertex in the graph. It is in the class GraphDS\Algo\FloydWarshall.

• $fw->run() accepts no arguments, and simply runs then algorithm on the graph
• $fw->get(startVertex, sestVertex) accepts startVertex and destVertex as a compulsory argument, which are the start vertex and the destination vertex, respectively, between which the shortest path should be worked out. It returns an array arr, with subarrays:
  • $arr['path'] (the shortest path to the vertex $dest from start)
  • $arr['dist'] (the shortest distance of the destination vertex to the start vertex, in edge weights)

Yen's algorithm

Yen's algorithm computes single-source K-shortest loopless paths in the graph. It is in the class GraphDS\Algo\Yen.

• $yen->run(start, dest, k) accepts start as a compulsory argument, this is the name of the vertex from which Yen should start. Accepts dest as a compulsory argument, which is the name of the destination vertex to which the shortest K paths should be returned. Accepts k as an optional argument with a default of 3, this is the maximum amount of paths to return.
• $yen->get() accepts no arguments. It returns a sorted array arr, with subarrays:
  • $arr[i]['path'] (the path to the vertex dest from start)
  • $arr[i]['dist'] (the distance of the destination vertex to the start vertex, in edge weights)

Persistence

GraphDS has the ability to export and import graphs using the popular GraphML format. Note that for graph persistence to function correctly, the correct read/write permissions should be set on the server, which is beyond the scope of this README.

Examples of GraphML files are graphUndirected.graphml and graphDirected.graphml, both found in this repository.

Exporting graphs

To export a graph to a GraphML file, use the GraphDS\Persistence\ExportGraph class, and run $e = new ExportGraph($g), where $e is the graph exporter object, and $g is a graph. $graphml = $e->getGraphML() sets $graphml to the GraphML markup of the graph, and $e->saveToFile($graphml, 'graph.graphml') writes this markup to the file graph.graphml.

Importing graphs

To import a graph from a GraphML file, use the GraphDS\Persistence\ImportGraph class, and run $i = new ImportGraph(), where $i is the graph importer object. $g = $i->fromGraphML('graph.graphml') sets $g to a GraphDS graph object represented by the GraphML markup in the file graph.graphml.

The object $g is now a conventional GraphDS, reconstructed from the GraphML markup in the file of graph.graphml.

Testing

This app can be tested locally on php 7.2 using docker

1. Build the docker container using the command below

2. Run php unit inside the docker container using the command below.

In case of bugs and/or suggestions

If, for any reason, there is a bug found in GraphDS, please message me on GitHub or send me an email to: [email protected]. The same goes for any suggestions.

Despite thorough unit testing, bugs will inevitably appear, so please open up any issues on GitHub if they arise! Currently, PHP 5.3 and onwards is supported, although at least PHP 5.6 is recommended.