StaticVectors.jl

Statically sized tuple vectors for Julia

Subtypes of TupleVector are provided as a light weight alternative to StaticArrays.jl. This package was created for use in AbstractTensors.jl, Grassmann.jl, FieldAlgebra.jl, Similitude.jl, Geophysics.jl, and various other related repositories developed by chakravala.

TupleVector provides a framework for implementing statically sized tuple vectors in Julia, using the abstract type TupleVector{N,T} <: AbstractVector{T}. Subtypes of TupleVector will provide fast implementations of common array and linear algebra operations. Note that here "statically sized" means that the size can be determined from the type, and "static" does not necessarily imply immutable.

The package also provides some concrete static vector types: Values which may be used as-is (or else embedded in your own type). Mutable versions Variables are also exported, as well as FixedVector for annotating standard Vectors with static size information.

If the environment variable STATICJL is set, then StaticArrays is loaded instead.

Quick start

Add StaticVectors from the Pkg REPL, i.e., pkg> add StaticVectors. Then:

using StaticVectors

# Create Values using various forms, using constructors, functions or macros
v1 = Values(1, 2, 3)
v1.v === (1, 2, 3) # Values uses a tuple for internal storage
v2 = Values{3,Float64}(1, 2, 3) # length 3, eltype Float64
v5 = zeros(Values{3}) # defaults to Float64
v7 = Values{3}([1, 2, 3]) # Array conversions must specify size

# Can get size() from instance or type
size(v1) == (3,)
size(typeof(v1)) == (3,)

# Supports all the common operations of AbstractVector
v7 = v1 + v2
v8 = sin.(v2)

# Indexing can also be done using static vectors of integers
v1[1] === 1
v1[:] === v1
typeof(v1[[1,2,3]]) <: Vector # Can't determine size from the type of [1,2,3]

Approach

The package provides a range of different useful built-in TupleVector types, which include mutable and immutable vectors based upon tuples, vectors based upon structs, and wrappers of Vector. There is a relatively simple interface for creating your own, custom TupleVector types, too.

This package also provides methods for a wide range of AbstractVector functions, specialized for (potentially immutable) TupleVectors. Many of Julia's built-in method definitions inherently assume mutability, and further performance optimizations may be made when the size of the vector is known to the compiler. One example of this is by loop unrolling, which has a substantial effect on small arrays and tends to automatically trigger LLVM's SIMD optimizations. In combination with intelligent fallbacks to the methods in Base, we seek to provide a comprehensive support for statically sized vectors, large or small, that hopefully "just works".

TupleVector is directly inspired from StaticArrays.jl.