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Fix warning from DataStructures.jl #471

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Fix warning from DataStructures.jl #471

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2 changes: 1 addition & 1 deletion Project.toml
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Expand Up @@ -22,7 +22,7 @@ GraphsSharedArraysExt = "SharedArrays"
[compat]
ArnoldiMethod = "0.4"
Distributed = "1"
DataStructures = "0.18, 0.19"
DataStructures = "0.19"
Inflate = "0.1.3"
LinearAlgebra = "1"
Random = "1"
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2 changes: 1 addition & 1 deletion src/Graphs.jl
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Expand Up @@ -8,7 +8,7 @@ using Statistics: mean

using Inflate: InflateGzipStream
using DataStructures:
IntDisjointSets,
IntDisjointSet,
PriorityQueue,
dequeue!,
dequeue_pair!,
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2 changes: 1 addition & 1 deletion src/graphcut/karger_min_cut.jl
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Expand Up @@ -23,7 +23,7 @@ function karger_min_cut(g::AbstractGraph{T}) where {T<:Integer}
nvg < 2 && return zeros(Int, nvg)
nvg == 2 && return [1, 2]

connected_vs = IntDisjointSets(nvg)
connected_vs = IntDisjointSet(nvg)
num_components = nvg

for e in shuffle(collect(edges(g)))
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2 changes: 1 addition & 1 deletion src/spanningtrees/boruvka.jl
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Expand Up @@ -15,7 +15,7 @@ function boruvka_mst end
@traitfn function boruvka_mst(
g::AG::(!IsDirected), distmx::AbstractMatrix{T}=weights(g); minimize=true
) where {T<:Number,U,AG<:AbstractGraph{U}}
djset = IntDisjointSets(nv(g))
djset = IntDisjointSet(nv(g))
# maximizing Z is the same as minimizing -Z
# mode will indicate the need for the -1 multiplication
mode = minimize ? 1 : -1
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2 changes: 1 addition & 1 deletion src/spanningtrees/kruskal.jl
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Expand Up @@ -12,7 +12,7 @@ function kruskal_mst end
@traitfn function kruskal_mst(
g::AG::(!IsDirected), distmx::AbstractMatrix{T}=weights(g); minimize=true
) where {T<:Number,U,AG<:AbstractGraph{U}}
connected_vs = IntDisjointSets(nv(g))
connected_vs = IntDisjointSet(nv(g))

mst = Vector{edgetype(g)}()
nv(g) <= 1 && return mst
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2 changes: 1 addition & 1 deletion src/traversals/maxadjvisit.jl
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Expand Up @@ -30,7 +30,7 @@ assumed to be 1.
# still appearing in fadjlist. When iterating neighbors, is_merged makes sure we
# don't consider them
is_merged = falses(nvg)
merged_vertices = IntDisjointSets(U(nvg))
merged_vertices = IntDisjointSet(U(nvg))
graph_size = nvg
# We need to mutate the weight matrix,
# and we need it clean (0 for non edges)
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