github.com/yourbasic/graph
Package graph contains generic implementations of basic graph algorithms. The algorithms in this library can be applied to any graph data structure implementing the two Iterator methods: Order, which returns the number of vertices, and Visit, which iterates over the neighbors of a vertex. All algorithms operate on directed graphs with a fixed number of vertices, labeled from 0 to n-1, and edges with integer cost. An undirected edge {v, w} of cost c is represented by the two directed edges (v, w) and (w, v), both of cost c. A self-loop, an edge connecting a vertex to itself, is both directed and undirected. The type Mutable represents a directed graph with a fixed number of vertices and weighted edges that can be added or removed. The implementation uses hash maps to associate each vertex in the graph with its adjacent vertices. This gives constant time performance for all basic operations. The type Immutable is a compact representation of an immutable graph. The implementation uses lists to associate each vertex in the graph with its adjacent vertices. This makes for fast and predictable iteration: the Visit method produces its elements by reading from a fixed sorted precomputed list. This type supports multigraphs. The subpackage graph/build offers a tool for building virtual graphs. In a virtual graph no vertices or edges are stored in memory, they are instead computed as needed. New virtual graphs are constructed by composing and filtering a set of standard graphs, or by writing functions that describe the edges of a graph. The Basics example shows how to build a plain graph and how to efficiently use the Visit iterator, the key abstraction of this package. The DFS example contains a full implementation of depth-first search. Build a plain graph and visit all of its edges. Show how to use this package by implementing a complete depth-first search.
Readme
Topological ordering, image by David Eppstein, CC0 1.0.
This library offers efficient and well-tested algorithms for
The algorithms can be applied to any graph data structure implementing
the two Iterator methods: Order, which returns the number of vertices,
and Visit, which iterates over the neighbors of a vertex.
All algorithms operate on directed graphs with a fixed number of vertices, labeled from 0 to n-1, and edges with integer cost. An undirected edge {v, w} of cost c is represented by the two directed edges (v, w) and (w, v), both of cost c. A self-loop, an edge connecting a vertex to itself, is both directed and undirected.
The type Mutable represents a directed graph with a fixed number
of vertices and weighted edges that can be added or removed.
The implementation uses hash maps to associate each vertex
in the graph with its adjacent vertices. This gives constant
time performance for all basic operations.
The type Immutable is a compact representation of an immutable graph.
The implementation uses lists to associate each vertex in the graph
with its adjacent vertices. This makes for fast and predictable
iteration: the Visit method produces its elements by reading
from a fixed sorted precomputed list.
The subpackage graph/build offers a tool for building graphs of type Virtual.
In a virtual graph no vertices or edges are stored in memory, they are instead computed as needed. New virtual graphs are constructed by composing and filtering a set of standard graphs, or by writing functions that describe the edges of a graph.
The following standard graphs are predefined:
The following operations are supported:
Non-virtual graphs can be imported, and used as building blocks,
by the Specific function. Virtual graphs don't need to be “exported”;
they implement the Iterator interface and hence can be used directly
by any algorithm in the graph package.
Once you have installed Go, run this command
to install the graph package:
go get github.com/yourbasic/graph
There is an online reference for the package at godoc.org/github.com/yourbasic/graph.
The only accepted reason to modify the API of this package is to handle issues that can't be resolved in any other reasonable way.
New features and performance enhancements are limited to basic algorithms and data structures, akin to the ones that you might find in a computer science textbook.
Stefan Nilsson – korthaj
FAQs
Package graph contains generic implementations of basic graph algorithms. The algorithms in this library can be applied to any graph data structure implementing the two Iterator methods: Order, which returns the number of vertices, and Visit, which iterates over the neighbors of a vertex. All algorithms operate on directed graphs with a fixed number of vertices, labeled from 0 to n-1, and edges with integer cost. An undirected edge {v, w} of cost c is represented by the two directed edges (v, w) and (w, v), both of cost c. A self-loop, an edge connecting a vertex to itself, is both directed and undirected. The type Mutable represents a directed graph with a fixed number of vertices and weighted edges that can be added or removed. The implementation uses hash maps to associate each vertex in the graph with its adjacent vertices. This gives constant time performance for all basic operations. The type Immutable is a compact representation of an immutable graph. The implementation uses lists to associate each vertex in the graph with its adjacent vertices. This makes for fast and predictable iteration: the Visit method produces its elements by reading from a fixed sorted precomputed list. This type supports multigraphs. The subpackage graph/build offers a tool for building virtual graphs. In a virtual graph no vertices or edges are stored in memory, they are instead computed as needed. New virtual graphs are constructed by composing and filtering a set of standard graphs, or by writing functions that describe the edges of a graph. The Basics example shows how to build a plain graph and how to efficiently use the Visit iterator, the key abstraction of this package. The DFS example contains a full implementation of depth-first search. Build a plain graph and visit all of its edges. Show how to use this package by implementing a complete depth-first search.
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