graph alternatives and similar packages
Based on the "Science and Data Analysis" category.
Alternatively, view graph alternatives based on common mentions on social networks and blogs.

gonum
Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more. 
gosl
Go scientific library for linear algebra, FFT, geometry, NURBS, numerical methods, probabilities, optimisation, differential equations, and more. 
gonum/mat64
The general purpose package for matrix computation. Package mat64 provides basic linear algebra operations for float64 matrices. 
TextRank
TextRank implementation in Golang with extendable features (summarization, weighting, phrase extraction) and multithreading (goroutine) support. 
sparse
Go Sparse matrix formats for linear algebra supporting scientific and machine learning applications, compatible with gonum matrix libraries. 
vectormath
Vectormath for Go, an adaptation of the scalar C functions from Sony's Vector Math library, as found in the Bullet2.79 source code. (currently inactive) 
triangolatte
2D triangulation library. Allows translating lines and polygons (both based on points) to the language of GPUs. 
ode
An ordinary differential equation (ODE) solver which supports extended states and channelbased iteration stop conditions. 
GoStats
GoStats is an Open Source GoLang library for math statistics mostly used in Machine Learning domains, it covers most of the Statistical measures functions. 
mudlarkgo
A collection of packages providing (hopefully) useful code for use in software using Google's Go programming language.
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README
Your basic graph
Golang library of basic graph algorithms
[Topological ordering](top.png)
Topological ordering, image by David Eppstein, CC0 1.0.
This library offers efficient and welltested algorithms for
 breadthfirst and depthfirst search,
 topological ordering,
 strongly and weakly connected components,
 bipartion,
 shortest paths,
 maximum flow,
 Euler walks,
 and minimum spanning trees.
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 n1, 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 selfloop, an edge connecting a vertex to itself, is both directed and undirected.
Graph data structures
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.
Virtual graphs
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:
 empty graphs,
 complete graphs and complete bipartite graphs,
 grid graphs and complete kary trees,
 cycle graphs and circulant graphs,
 and hypergraphs.
The following operations are supported:
 adding and deleting sets of edges,
 adding cost functions,
 filtering graphs by edge functions,
 complement, intersection and union,
 subgraphs,
 connecting graphs at a single vertex,
 joining two graphs by a set of edges,
 matching two graphs by a set of edges,
 cartesian product and tensor product.
Nonvirtual 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.
Installation
Once you have installed Go, run this command
to install the graph
package:
go get github.com/yourbasic/graph
Documentation
There is an online reference for the package at godoc.org/github.com/yourbasic/graph.
Roadmap
 The API of this library is frozen.
 Bug fixes and performance enhancement can be expected.
 New functionality might be included.
 Version numbers adhere to semantic versioning.
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