CompatHelper: bump compat for ArnoldiMethod to 0.4, (keep existing compat) (#344)

* CompatHelper: bump compat for ArnoldiMethod to 0.4, (keep existing compat)

* Qualify ArnoldiMethod imports

* Clean up using in package source

* Remove ArnoldiMethod 0.3

---------

Co-authored-by: CompatHelper Julia <compathelper_noreply@julialang.org>
Co-authored-by: Guillaume Dalle <22795598+gdalle@users.noreply.github.com>

Author: 3 people

Project.toml

@@ -17,7 +17,7 @@ Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [compat]
 Aqua = "0.6"
-ArnoldiMethod = "0.3"
+ArnoldiMethod = "0.4"
 Compat = "3.40, 4"
 DataStructures = "0.17, 0.18"
 Documenter = "0.27"

src/Graphs.jl

@@ -3,7 +3,7 @@ module Graphs
 using SimpleTraits
 
 ### Remove the following line once #915 is closed
-using ArnoldiMethod
+using ArnoldiMethod: LM, SR, LR, partialschur, partialeigen
 using Statistics: mean
 
 # Currently used to support the ismutable function that is not available in Julia < v1.7

src/Parallel/Parallel.jl

@@ -5,7 +5,7 @@ using Graphs: sample, AbstractPathState, JohnsonState, BellmanFordState, FloydWa
 using Distributed: @distributed
 using Base.Threads: @threads, nthreads, Atomic, atomic_add!, atomic_cas!
 using SharedArrays: SharedMatrix, SharedVector, sdata
-using ArnoldiMethod
+using ArnoldiMethod: LM, SR, LR, partialschur, partialeigen
 using Random: AbstractRNG, shuffle
 import SparseArrays: sparse
 import Base: push!, popfirst!, isempty, getindex

src/graphcut/normalized_cut.jl

@@ -1,4 +1,3 @@
-using ArnoldiMethod
 # computes normalized cut cost for partition `cut`
 function _normalized_cut_cost(cut, W::AbstractMatrix, D)
     cut_cost = zero(eltype(W))

src/linalg/LinAlg.jl

@@ -1,10 +1,10 @@
 module LinAlg
 
-using ArnoldiMethod
+using ArnoldiMethod: LM, SR, LR, partialschur, partialeigen
 
 using SimpleTraits
 using SparseArrays: SparseMatrixCSC
-import SparseArrays: blockdiag, sparse
+import SparseArrays: blockdiag, sparse, spdiagm
 using LinearAlgebra: I, Symmetric, diagm, dot, eigen, eigvals, norm, rmul!, tril, triu
 import LinearAlgebra: Diagonal, diag, issymmetric, mul!
 

src/linalg/spectral.jl

@@ -1,8 +1,5 @@
 # This file provides reexported functions.
 
-using ArnoldiMethod
-using SparseArrays
-
 """
     adjacency_matrix(g[, T=Int; dir=:out])
 

src/shortestpaths/bellman-ford.jl

@@ -8,7 +8,6 @@
 #   The type that encapsulates the state of Bellman Ford algorithm
 #
 ###################################################################
-using Base.Threads
 
 struct NegativeCycleError <: Exception end
 

src/shortestpaths/spfa.jl

@@ -6,8 +6,6 @@
 #
 ###################################################################
 
-using Base.Threads
-
 """
     spfa_shortest_paths(g, s, distmx=weights(g))
 

test/linalg/graphmatrices.jl

@@ -1,5 +1,5 @@
 # export test_adjacency, test_laplacian, test_accessors, test_arithmetic, test_other
-using ArnoldiMethod
+using ArnoldiMethod: LM, SR, LR, partialschur, partialeigen
 
 @testset "Graph matrices" begin
 

test/linalg/spectral.jl

@@ -1,6 +1,6 @@
 import Base: Matrix
 import Base: size
-using ArnoldiMethod
+using ArnoldiMethod: LM, SR, LR, partialschur, partialeigen
 
 # using Graphs.LinAlg: eigs
 # just so that we can assert equality of matrices