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https://github.com/JuliaArrays/InfiniteArrays.jl
A Julia package for representing infinite-dimensional arrays
https://github.com/JuliaArrays/InfiniteArrays.jl
Last synced: 3 months ago
JSON representation
A Julia package for representing infinite-dimensional arrays
- Host: GitHub
- URL: https://github.com/JuliaArrays/InfiniteArrays.jl
- Owner: JuliaArrays
- License: mit
- Created: 2018-03-16T19:52:34.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2024-07-25T10:06:51.000Z (4 months ago)
- Last Synced: 2024-07-26T11:11:17.003Z (4 months ago)
- Language: Julia
- Homepage:
- Size: 327 KB
- Stars: 72
- Watchers: 12
- Forks: 10
- Open Issues: 16
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-sciml - JuliaArrays/InfiniteArrays.jl: A Julia package for representing infinite-dimensional arrays
README
# InfiniteArrays.jl
[pkgeval-img]: https://juliaci.github.io/NanosoldierReports/pkgeval_badges/I/InfiniteArrays.svg
[pkgeval-url]: https://juliaci.github.io/NanosoldierReports/pkgeval_badges/report.html
[](https://github.com/JuliaArrays/InfiniteArrays.jl/actions)
[](https://codecov.io/gh/JuliaArrays/InfiniteArrays.jl)
[![PkgEval][pkgeval-img]][pkgeval-url]
A Julia package for representing arrays with infinite dimension sizes, designed to work
with other array types. Infinite arrays are by necessity lazy, and so this
package is closely linked to [LazyArrays.jl](https://github.com/JuliaArrays/LazyArrays.jl).
The package currently supports construction, but future versions will include
support for linear algebra operations like matrix multiplication, LU decompositions,
and QR decompositions.
Here are some examples of current functionality:
```julia
julia> using InfiniteArrays, LinearAlgebra, FillArrays
julia> x = Ones(∞) # infinite vector of all ones
Ones{Float64,1,Tuple{InfiniteArrays.OneToInf{Int64}}} with indices OneToInf():
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
⋮
julia> cumsum(x) # infinite sum
1.0:1.0:+∞
julia> exp.(-(1:∞)) .+ 2 # broadcasting supported
BroadcastArray{Float64,1,Base.Broadcast.Broadcasted{LazyArrays.LazyArrayStyle{1},Tuple{InfiniteArrays.OneToInf{Int64}},typeof(+),Tuple{BroadcastArray{Float64,1,Base.Broadcast.Broadcasted{LazyArrays.LazyArrayStyle{1},Tuple{InfiniteArrays.OneToInf{Int64}},typeof(exp),Tuple{InfiniteArrays.InfStepRange{Int64,Int64}}}},Int64}}} with indices OneToInf():
2.3678794411714423
2.135335283236613
2.049787068367864
2.018315638888734
2.0067379469990856
2.0024787521766663
2.0009118819655547
2.0003354626279024
2.0001234098040865
2.0000453999297623
2.0000167017007904
2.000006144212353
2.000002260329407
2.000000831528719
2.0000003059023204
2.0000001125351745
2.0000000413993773
2.00000001522998
2.0000000056027964
2.0000000020611535
2.000000000758256
2.0000000002789466
2.000000000102619
2.000000000037751
2.000000000013888
2.0000000000051092
⋮
julia> Diagonal(1:∞) # combines well with Base arrays
Diagonal{Int64,InfiniteArrays.InfUnitRange{Int64}} with indices OneToInf()×OneToInf():
1 ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ …
⋅ 2 ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ 3 ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ 4 ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ 5 ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ 6 ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ …
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 7 ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 8 ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 9 ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 10 ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 11 ⋅ ⋅ ⋅ ⋅ …
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 12 ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 13 ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 14 ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 15
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ …
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ …
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ …
⋮ ⋮ ⋮ ⋱
julia> C = cache(Ones(∞)); C[1] = 3; C # Use cache to make mutable
LazyArrays.CachedArray{Float64,1,Array{Float64,1},Ones{Float64,1,Tuple{InfiniteArrays.InfiniteCardinal{0}}}} with indices OneToInf():
3.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
⋮
```