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 Vector
s with static size information.
If the environment variable STATICJL
is set, then StaticArrays
is loaded instead.
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]
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) TupleVector
s. 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.