Add Interlace

[dlfivefifty]

No description provided.

[codecov]

Codecov Report

❌ Patch coverage is 19.35484% with 25 lines in your changes missing coverage. Please review.
✅ Project coverage is 76.00%. Comparing base (3c87082) to head (207bedf).
⚠️ Report is 239 commits behind head on master.

Files with missing lines	Patch %	Lines
src/interlace.jl	0.00%	23 Missing ⚠️
src/lazybroadcasting.jl	0.00%	1 Missing ⚠️
src/lazyconcat.jl	85.71%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master      #41      +/-   ##
==========================================
- Coverage   77.60%   76.00%   -1.60%     
==========================================
  Files          14       15       +1     
  Lines        1143     1167      +24     
==========================================
  Hits          887      887              
- Misses        256      280      +24     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

[DanielVandH]

Was there any particular reason this stalled if you remember @dlfivefifty? I can see a version of this for infinite arrays here

https://github.com/JuliaApproximation/AlgebraicCurveOrthogonalPolynomials.jl/blob/5bf062d232194069b4d41a35a35b86950c3ed533/src/twoband.jl#L83-L93

but a LazyInterlace could be more broadly useful here, right?

[dlfivefifty]

The whole interlace business is just in a state of mess because I wasn't entirely sure the design.

The first question is: is there a need for Interlace? Here are two synonyms:

julia> a = [1,2,3]; b = [4,5,6]; LazyBandedMatrices.BlockVec(Hcat(a,b)')
blockvec(vcat(1×3 adjoint(::Vector{Int64}) with eltype Int64, 1×3 adjoint(::Vector{Int64}) with eltype Int64)) with indices BlockedOneTo(2:2:6):
 1
 4
 ─
 2
 5
 ─
 3
 6

julia> BlockBroadcastArray(vcat, unitblocks(a), unitblocks(b))
3-blocked 6-element BlockBroadcastArray{Int64, 1, typeof(vcat), Tuple{BlockedVector{Int64, Vector{Int64}, Tuple{BlockedOneTo{Int64, Base.OneTo{Int64}}}}, BlockedVector{Int64, Vector{Int64}, Tuple{BlockedOneTo{Int64, Base.OneTo{Int64}}}}}}:
 1
 4
 ─
 2
 5
 ─
 3
 6

The second question: how to unify the different version of concatentation in ContinuumArrays.jl? See:

1. https://github.com/JuliaApproximation/ContinuumArrays.jl/blob/master/src/bases/basisconcat.jl
2. https://github.com/JuliaApproximation/ClassicalOrthogonalPolynomials.jl/blob/main/src/interlace.jl

The types defined in the latter are more thoroughly developed but I don't remember why its in ClassicalOrthogonalPolynomials.jl. It should probably be moved to ContinuumArrays.jl and unified with the types in basisconcat.jl.

We can probably discuss this in more detail at the next meeting.