JuliaApproximation / JuliaApproximation/MultivariateOrthogonalPolynomials.jl
Finite sections of JacobiTriangle Jacobi matrices are ApplyArrays instead of BandedBlockBandedMatrices
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- Avg merge
- 2d 17h
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- 1
Description
I don't think this used to be the case.
julia> jacobimatrix(Val(1), RectPolynomial(ChebyshevT(), ChebyshevT()))[Block.(1:5), Block.(1:5)]
5×5-blocked 15×15 BandedBlockBandedMatrix{Float64} with block-bandwidths (1, 1) and sub-block-bandwidths block-bandwidths (0, 0) with data 3×5-blocked 3×15 BlockedMatrix{Float64}:
0.0 │ 0.5 ⋅ │ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ ⋅
─────┼────────────┼─────────────────┼──────────────────────┼─────────────────────────
1.0 │ 0.0 ⋅ │ 0.5 ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ │ ⋅ 0.0 │ ⋅ 0.5 ⋅ │ ⋅ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ ⋅
─────┼────────────┼─────────────────┼──────────────────────┼─────────────────────────
⋅ │ 0.5 ⋅ │ 0.0 ⋅ ⋅ │ 0.5 ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ │ ⋅ 1.0 │ ⋅ 0.0 ⋅ │ ⋅ 0.5 ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ 0.0 │ ⋅ ⋅ 0.5 ⋅ │ ⋅ ⋅ ⋅ ⋅ ⋅
─────┼────────────┼─────────────────┼──────────────────────┼─────────────────────────
⋅ │ ⋅ ⋅ │ 0.5 ⋅ ⋅ │ 0.0 ⋅ ⋅ ⋅ │ 0.5 ⋅ ⋅ ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ 0.5 ⋅ │ ⋅ 0.0 ⋅ ⋅ │ ⋅ 0.5 ⋅ ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ 1.0 │ ⋅ ⋅ 0.0 ⋅ │ ⋅ ⋅ 0.5 ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ 0.0 │ ⋅ ⋅ ⋅ 0.5 ⋅
─────┼────────────┼─────────────────┼──────────────────────┼─────────────────────────
⋅ │ ⋅ ⋅ │ ⋅ ⋅ ⋅ │ 0.5 ⋅ ⋅ ⋅ │ 0.0 ⋅ ⋅ ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ ⋅ │ ⋅ 0.5 ⋅ ⋅ │ ⋅ 0.0 ⋅ ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ ⋅ │ ⋅ ⋅ 0.5 ⋅ │ ⋅ ⋅ 0.0 ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ 1.0 │ ⋅ ⋅ ⋅ 0.0 ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ 0.0
julia> typeof(ans)
BlockBandedMatrices.BandedBlockBandedMatrix{Float64, BlockedMatrix{Float64, Matrix{Float64}, Tuple{BlockedOneTo{Int64, StepRangeLen{Int64, Int64, Int64, Int64}}, BlockedOneTo{Int64, Vector{Int64}}}}, BlockedOneTo{Int64, Vector{Int64}}}
julia> jacobimatrix(Val(1), JacobiTriangle())[Block.(1:5), Block.(1:5)]
(5×5-blocked 15×15 BandedBlockBandedMatrix{Float64} with block-bandwidths (1, 0) and sub-block-bandwidths block-bandwidths (0, 0) with data 2×5-blocked 2×15 BlockVcat{Float64}) * (5×5-blocked 15×15 BandedBlockBandedMatrix{Float64} with block-bandwidths (0, 1) and sub-block-bandwidths block-bandwidths (0, 0) with data 2×5-blocked 2×15 BlockVcat{Float64}) with indices BlockedOneTo([1, 3, 6, 10, 15])×BlockedOneTo([1, 3, 6, 10, 15]):
0.333333 │ 0.166667 ⋅ │ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ ⋅
──────────┼─────────────────┼────────────────────────────────┼──────────────────────────────────────────┼────────────────────────────────────────────────────
0.333333 │ 0.466667 ⋅ │ 0.2 ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ │ ⋅ 0.2 │ ⋅ 0.133333 ⋅ │ ⋅ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ ⋅
──────────┼─────────────────┼────────────────────────────────┼──────────────────────────────────────────┼────────────────────────────────────────────────────
⋅ │ 0.3 ⋅ │ 0.485714 ⋅ ⋅ │ 0.214286 ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ │ ⋅ 0.2 │ ⋅ 0.371429 ⋅ │ ⋅ 0.178571 ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ 0.142857 │ ⋅ ⋅ 0.107143 ⋅ │ ⋅ ⋅ ⋅ ⋅ ⋅
──────────┼─────────────────┼────────────────────────────────┼──────────────────────────────────────────┼────────────────────────────────────────────────────
⋅ │ ⋅ ⋅ │ 0.285714 ⋅ ⋅ │ 0.492063 ⋅ ⋅ ⋅ │ 0.222222 ⋅ ⋅ ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ 0.238095 ⋅ │ ⋅ 0.428571 ⋅ ⋅ │ ⋅ 0.2 ⋅ ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ 0.142857 │ ⋅ ⋅ 0.301587 ⋅ │ ⋅ ⋅ 0.155556 ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ 0.111111 │ ⋅ ⋅ ⋅ 0.0888889 ⋅
──────────┼─────────────────┼────────────────────────────────┼──────────────────────────────────────────┼────────────────────────────────────────────────────
⋅ │ ⋅ ⋅ │ ⋅ ⋅ ⋅ │ 0.277778 ⋅ ⋅ ⋅ │ 0.494949 ⋅ ⋅ ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ ⋅ │ ⋅ 0.25 ⋅ ⋅ │ ⋅ 0.454545 ⋅ ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ ⋅ │ ⋅ ⋅ 0.194444 ⋅ │ ⋅ ⋅ 0.373737 ⋅ ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ 0.111111 │ ⋅ ⋅ ⋅ 0.252525 ⋅
⋅ │ ⋅ ⋅ │ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ │ ⋅ ⋅ ⋅ ⋅ 0.0909091
julia> typeof(ans)
LazyArrays.ApplyArray{Float64, 2, typeof(*), Tuple{BlockBandedMatrices.BandedBlockBandedMatrix{Float64, LazyBandedMatrices.BlockVcat{Float64, 2, Tuple{Adjoint{Float64, BlockVector{Float64, Vector{Vector{Float64}}, Tuple{BlockedOneTo{Int64, Vector{Int64}}}}}, Adjoint{Float64, BlockVector{Float64, Vector{Vector{Float64}}, Tuple{BlockedOneTo{Int64, Vector{Int64}}}}}}, Tuple{BlockedOneTo{Int64, StaticArraysCore.SVector{2, Int64}}, BlockedOneTo{Int64, Vector{Int64}}}}, BlockedOneTo{Int64, Vector{Int64}}}, BlockBandedMatrices.BandedBlockBandedMatrix{Float64, LazyBandedMatrices.BlockVcat{Float64, 2, Tuple{Adjoint{Float64, BlockVector{Float64, Vector{Vector{Float64}}, Tuple{BlockedOneTo{Int64, Vector{Int64}}}}}, Adjoint{Float64, BlockVector{Float64, Vector{Vector{Float64}}, Tuple{BlockedOneTo{Int64, Vector{Int64}}}}}}, Tuple{BlockedOneTo{Int64, StaticArraysCore.SVector{2, Int64}}, BlockedOneTo{Int64, Vector{Int64}}}}, BlockedOneTo{Int64, Vector{Int64}}}}}
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing the two jacobimatrix slicing examples for JacobiTriangle and RectPolynomial. Trace the JacobiTriangle path from the jacobimatrix entry point and compare its finite-section representation with the BandedBlockBandedMatrix result. Done means the JacobiTriangle finite section no longer has an ApplyArray type.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- backend
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100