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JuliaApproximation / MultivariateOrthogonalPolynomials.jl

Supports approximating functions and solving differential equations on various higher dimensional domains such as disks and triangles
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Weighted ∂ₓ on triangles errs #115

Open MikaelSlevinsky opened 2 years ago

MikaelSlevinsky commented 2 years ago 
julia> using MultivariateOrthogonalPolynomials
[ Info: Precompiling MultivariateOrthogonalPolynomials [4f6956fd-4f93-5457-9149-7bfc4b2ce06d]

julia> MultivariateOrthogonalPolynomials.Wx(1,1,1)
ERROR: ArgumentError: Data matrix must have number of row blocks equal to number of block bands
Stacktrace:
 [1] check_data_sizes(data::LazyBandedMatrices.BlockVcat{Float64, 2, Tuple{LinearAlgebra.Adjoint{Float64, LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{LazyArrays.BroadcastVector{Int64, typeof(*), Tuple{LazyArrays.BroadcastVector{Int64, typeof(+), Tuple{BlockArrays.BlockVector{Int64, LazyArrays.BroadcastVector{Base.OneTo{Int64}, Type{Base.OneTo}, Tuple{InfiniteArrays.OneToInf{Int64}}}, Tuple{BlockArrays.BlockedUnitRange{ArrayLayouts.RangeCumsum{Int64, InfiniteArrays.OneToInf{Int64}}}}}, Int64}}, LazyArrays.BroadcastVector{Int64, typeof(-), Tuple{LazyArrays.BroadcastVector{Int64, typeof(-), Tuple{BlockArrays.BlockVector{Int64, LazyArrays.BroadcastVector{Base.OneTo{Int64}, Type{Base.OneTo}, Tuple{InfiniteArrays.OneToInf{Int64}}}, Tuple{BlockArrays.BlockedUnitRange{ArrayLayouts.RangeCumsum{Int64, InfiniteArrays.OneToInf{Int64}}}}}, BlockArrays.BlockVector{Int64, LazyArrays.BroadcastVector{FillArrays.Fill{Int64, 1, Tuple{Base.OneTo{Int64}}}, Type{FillArrays.Fill}, Tuple{InfiniteArrays.OneToInf{Int64}, InfiniteArrays.OneToInf{Int64}}}, Tuple{BlockArrays.BlockedUnitRange{ArrayLayouts.RangeCumsum{Int64, InfiniteArrays.OneToInf{Int64}}}}}}}, Int64}}}}, LazyArrays.BroadcastVector{Int64, typeof(+), Tuple{BlockArrays.BlockVector{Int64, LazyArrays.BroadcastVector{StepRangeLen{Int64, Int64, Int64, Int64}, typeof(*), Tuple{Int64, LazyArrays.BroadcastVector{Base.OneTo{Int64}, Type{Base.OneTo}, Tuple{InfiniteArrays.OneToInf{Int64}}}}}, Tuple{BlockArrays.BlockedUnitRange{ArrayLayouts.RangeCumsum{Int64, InfiniteArrays.OneToInf{Int64}}}}}, Int64}}}}}, LinearAlgebra.Adjoint{Float64, LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{LazyArrays.BroadcastVector{Int64, typeof(*), Tuple{BlockArrays.BlockVector{Int64, LazyArrays.BroadcastVector{Base.OneTo{Int64}, Type{Base.OneTo}, Tuple{InfiniteArrays.OneToInf{Int64}}}, Tuple{BlockArrays.BlockedUnitRange{ArrayLayouts.RangeCumsum{Int64, InfiniteArrays.OneToInf{Int64}}}}}, LazyArrays.BroadcastVector{Int64, typeof(-), Tuple{LazyArrays.BroadcastVector{Int64, typeof(-), Tuple{BlockArrays.BlockVector{Int64, LazyArrays.BroadcastVector{Base.OneTo{Int64}, Type{Base.OneTo}, Tuple{InfiniteArrays.OneToInf{Int64}}}, Tuple{BlockArrays.BlockedUnitRange{ArrayLayouts.RangeCumsum{Int64, InfiniteArrays.OneToInf{Int64}}}}}, BlockArrays.BlockVector{Int64, LazyArrays.BroadcastVector{FillArrays.Fill{Int64, 1, Tuple{Base.OneTo{Int64}}}, Type{FillArrays.Fill}, Tuple{InfiniteArrays.OneToInf{Int64}, InfiniteArrays.OneToInf{Int64}}}, Tuple{BlockArrays.BlockedUnitRange{ArrayLayouts.RangeCumsum{Int64, InfiniteArrays.OneToInf{Int64}}}}}}}, Int64}}}}, LazyArrays.BroadcastVector{Int64, typeof(+), Tuple{BlockArrays.BlockVector{Int64, LazyArrays.BroadcastVector{StepRangeLen{Int64, Int64, Int64, Int64}, typeof(*), Tuple{Int64, LazyArrays.BroadcastVector{Base.OneTo{Int64}, Type{Base.OneTo}, Tuple{InfiniteArrays.OneToInf{Int64}}}}}, Tuple{BlockArrays.BlockedUnitRange{ArrayLayouts.RangeCumsum{Int64, InfiniteArrays.OneToInf{Int64}}}}}, Int64}}}}}}}, raxis::BlockArrays.BlockedUnitRange{ArrayLayouts.RangeCumsum{Int64, InfiniteArrays.OneToInf{Int64}}}, ::Tuple{Int64, Int64}, ::Tuple{Int64, Int64})
   @ BlockBandedMatrices ~/.julia/packages/BlockBandedMatrices/sYxap/src/BandedBlockBandedMatrix.jl:3
 [2] _BandedBlockBandedMatrix
   @ ~/.julia/packages/BlockBandedMatrices/sYxap/src/BandedBlockBandedMatrix.jl:37 [inlined]
 [3] Wx(a::Int64, b::Int64, c::Int64)
   @ MultivariateOrthogonalPolynomials ~/.julia/dev/MultivariateOrthogonalPolynomials/src/triangle.jl:120
 [4] top-level scope
   @ REPL[2]:1