Fix method ambiguities in JuMP.Containers

[odow]

No description provided.

[codecov]

Codecov Report

Base: 97.72% // Head: 98.07% // Increases project coverage by +0.34% 🎉

Coverage data is based on head (49cb6fc) compared to base (9f61e95).
Patch coverage: 100.00% of modified lines in pull request are covered.

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #3173      +/-   ##
==========================================
+ Coverage   97.72%   98.07%   +0.34%     
==========================================
  Files          33       33              
  Lines        4522     4563      +41     
==========================================
+ Hits         4419     4475      +56     
+ Misses        103       88      -15     

Impacted Files	Coverage Δ
src/Containers/DenseAxisArray.jl	95.92% <100.00%> (+0.06%)	⬆️
src/Containers/SparseAxisArray.jl	98.43% <100.00%> (+0.05%)	⬆️
src/macros.jl	98.50% <0.00%> (+0.16%)	⬆️
src/JuMP.jl	96.09% <0.00%> (+0.26%)	⬆️
src/operators.jl	96.63% <0.00%> (+0.56%)	⬆️
src/Containers/Containers.jl	91.66% <0.00%> (+0.75%)	⬆️
src/precompile.jl	100.00% <0.00%> (+100.00%)	⬆️

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

☔ View full report at Codecov.
📢 Do you have feedback about the report comment? Let us know in this issue.

[blegat]

We also support axes that are not AbstractVector at the moment so that would be breaking

[odow]

The type allows it, but we convert everything to AbstractVector on creation: #2713.

JuMP.jl/src/Containers/DenseAxisArray.jl

Lines 158 to 206 in 9f61e95

	_abstract_vector(x::AbstractVector) = x
	function _abstract_vector(x::AbstractVector{<:CartesianIndex})
	return error(
	"Unsupported index type `CartesianIndex` in axis: $x. Cartesian " *
	"indices are restricted for indexing into and iterating over " *
	"multidimensional arrays.",
	)
	end
	_abstract_vector(x) = _abstract_vector([a for a in x])
	_abstract_vector(x::AbstractArray) = vec(x)
	function _abstract_vector(x::Number)
	@warn(
	"Axis contains one element: $x. If intended, you can safely " *
	"ignore this warning. To explicitly pass the axis with one " *
	"element, pass `[$x]` instead of `$x`.",
	)
	return _abstract_vector([x])
	end
	"""
	DenseAxisArray(data::Array{T, N}, axes...) where {T, N}
	Construct a JuMP array with the underlying data specified by the `data` array
	and the given axes. Exactly `N` axes must be provided, and their lengths must
	match `size(data)` in the corresponding dimensions.
	# Example
	```jldoctest; setup=:(using JuMP)
	julia> array = JuMP.Containers.DenseAxisArray([1 2; 3 4], [:a, :b], 2:3)
	2-dimensional DenseAxisArray{Int64,2,...} with index sets:
	Dimension 1, Symbol[:a, :b]
	Dimension 2, 2:3
	And data, a 2×2 Array{Int64,2}:
	1 2
	3 4
	julia> array[:b, 3]
	4
	```
	"""
	function DenseAxisArray(data::Array{T,N}, axs...) where {T,N}
	@assert length(axs) == N
	new_axes = _abstract_vector.(axs) # Force all axes to be AbstractVector!
	return DenseAxisArray(data, new_axes, build_lookup.(new_axes))
	end

[odow]

Urgh. #3152 just added new ambiguities. I think that shows we need to get these tests in ASAP to keep a lid on things.