SpecialMatrices.jl
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JuliaLinearAlgebra
Julia package for working with special matrix types.
- .travis.yml is modernized - test/cauchy.jl permits full coverage: https://coveralls.io/github/fp4code/SpecialMatrices.jl?branch=fp-cauchy - src/cauchy.jl is cleaned JF updates: - not using travis anymore - handle general NTuple and AbstractArray without `collect` -...
The Cauchy type claims it is a subtype of `AbstractArray{T}` but the `T` is incorrect in general: ```julia julia> C = Cauchy([1,2,3]) 3×3 Cauchy{Int64}: 0.5 0.333333 0.25 0.333333 0.25 0.2...
Anywhere we've used AbstractVector, per discussions in #69
Lazy Kronecker product that exploits Linear Algebra properties
Minimal example: ``` julia> using LinearAlgebra julia> N = 5 5 julia> A = Tridiagonal(-1 .* ones(N - 1), 2 .* ones(N), -1 .* ones(N-1)) 5×5 Tridiagonal{Float64, Vector{Float64}}: 2.0 -1.0...
The previous version of `Strang` was not type stable because it returned (typically) `SymTridiagonal` but `Diagonal` in the case n=1. It is simpler just to always use `SymTridiagonal` and rely...
- .travis.yml is modernized - test/hankel.jl permits full coverage: https://coveralls.io/github/fp4code/SpecialMatrices.jl?branch=fp-hankel - src/hankel.jl is cleaned, with Hankel constructor and functions inspired by SparseMatrixCSC: https://github.com/JuliaLang/julia/blob/master/base/sparse/sparsematrix.jl
as defined [here](http://en.wikipedia.org/wiki/Lehmer_matrix)
I think it would make sense for some types, like `Vandermonde` and `Companion`, to overload `Base.map`. The goal is to make things like `map(Float32, Vandermonde([0.5, 3])) isa Vandermonde{Float32}` hold. Any...
Here I have a module with a short and simple implementation of a Vandermonde matrix inverse: https://gitlab.com/nsajko/PolynomialPassingThroughIntervals.jl/-/blob/main/src/VandermondeInverse.jl The module depends on the `SkipVectors` module, located in the same directory. As...
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Julia package for working with special matrix types.