Comments (3)
It looks like the issue is:
julia> Base.BroadcastStyle(typeof(X))
LinearAlgebra.StructuredMatrixStyle{Tridiagonal{Float64, ApplyArray{Float64, 1, typeof(vcat), Tuple{Float64, BroadcastVector{Float64, typeof(/), Tuple{Float64, BroadcastVector{Float64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Float64, Float64}, InfiniteArrays.InfStepRange{Float64, Float64}}}}}}}}}()
This should be returning some sort of LazyArrayStyle
.
Unfortunately it's currently overloaded in LazyBandedMatrices.jl so will have to wait until LazyArrays v2.0 to avoid having to fix it twice.
from classicalorthogonalpolynomials.jl.
Might be an issue with broadcasting somehow, since e.g.
julia> 1 .+ X
also never completes.
from classicalorthogonalpolynomials.jl.
Yes I started debugging and looks like 1 .* X
is the MWE. It should return:
julia> BroadcastArray(*, 1, X)
(Int64) .* (ℵ₀×ℵ₀ LazyBandedMatrices.Tridiagonal{Float64, ApplyArray{Float64, 1, typeof(vcat), Tuple{Float64, BroadcastVector{Float64, typeof(/), Tuple{BroadcastVector{Float64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfStepRange{Float64, Float64}}}, BroadcastVector{Float64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Float64, Float64}, InfiniteArrays.InfStepRange{Float64, Float64}}}}}}}, ApplyArray{Float64, 1, typeof(vcat), Tuple{Float64, BroadcastVector{Float64, typeof(/), Tuple{Float64, BroadcastVector{Float64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Float64, Float64}, InfiniteArrays.InfStepRange{Float64, Float64}}}}}}}, BroadcastVector{Float64, typeof(/), Tuple{BroadcastVector{Float64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Float64, Float64}, InfiniteArrays.InfStepRange{Float64, Float64}}}, BroadcastVector{Float64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Float64, Float64}, InfiniteArrays.InfStepRange{Float64, Float64}}}}}} with indices OneToInf()×OneToInf()) with indices OneToInf()×OneToInf():
0.111111 0.36036 ⋅ …
0.740741 0.0165485 0.410601
⋅ 0.621047 0.00666878
⋅ ⋅ 0.581304
⋅ ⋅ ⋅
⋅ ⋅ ⋅ …
⋅ ⋅ ⋅
⋅ ⋅ ⋅
⋅ ⋅ ⋅
⋅ ⋅ ⋅
⋮ ⋱
from classicalorthogonalpolynomials.jl.
Related Issues (20)
- Quadratically shifted bases HOT 4
- Stackoverflow for P'P HOT 2
- Lanczos Jacobi matrices and `^` HOT 2
- long compilation time for Jacobi(m,n) \ Jacobi(0,0) HOT 3
- Chebyshev() \ exp.(im*x) errors
- Make P[0.1,10] allocation free
- Ambiguities in ClassicalOrthogonalPolynomials and its dependencies
- Fourier{BigFloat} HOT 6
- UndefVarError in docs HOT 2
- Cholesky Jacobi matrices are insanely slow HOT 9
- Infinite loop converting between ChebyshevU and Ultraspherical HOT 1
- Can't print slices of orthogonal polynomials
- A \ B never completes when B is a `Normalized` basis HOT 2
- no method matching combine_axes() when indexing a transposed \(A, B)
- copy(Ldiv(A, B)) for Normalized(A) and Weighted(Normalized(B)) ambiguity
- Clenshaw errs with degree-0 polynomial
- Identity mapping wT -> wU HOT 1
- How to cite the package? HOT 4
- How to get BigFloat accurate conversion operators? HOT 4
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from classicalorthogonalpolynomials.jl.