interval*floating point falls back to generic algorithm in LinearAlgebra.jl

[lucaferranti]

Bug description

Multiplying an interval matrix with a floating point matrix uses the generic method in LinearAlgebra.jl instead of Rump multiplicaton in the package

Minimum (non-)working example

julia> A = [1..2 3..4;5..6 7..8]
2×2 Matrix{Interval{Float64}}:
 [1, 2]  [3, 4]
 [5, 6]  [7, 8]

julia> B = [1 2;3 4]
2×2 Matrix{Int64}:
 1  2
 3  4

julia> @which A*B
*(A::AbstractMatrix{T} where T, B::AbstractMatrix{T} where T) in LinearAlgebra at C:\Users\lucaa\AppData\Local\Programs\Julia-1.6.1\share\julia\stdlib\v1.6\LinearAlgebra\src\matmul.jl:151

Expected behavior

should dispatch to the method in IntervalLinearAlgebra.jl. It should be fixable by just adding

@eval *(A::AbstractMatrix{Interval{T}} where T, B::AbstractMatrix{T} where T) =
        *($type, A, B)

@eval *(A::AbstractMatrix{T} where T, B::AbstractMatrix{Interval{T}} where T) =
        *($type, A, B)

in the definition of set_multiplication_mode

Version info

• IntervalLinearAlgebra.jl version: main-branch
• System information:

Julia Version 1.6.1
Commit 6aaedecc44 (2021-04-23 05:59 UTC)
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: Intel(R) Core(TM) i7-8565U CPU @ 1.80GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-11.0.1 (ORCJIT, skylake)
Environment:
  JULIA_EDITOR = code.cmd -g
  JULIA_NUM_THREADS =

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