Use SuiteSparse and Arpack packages (#78)

JuliaStats · Jun 25, 2018 · 9fe6b3c · 9fe6b3c
1 parent 2f7ba0c
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Showing 4 changed files with 4 additions and 2 deletions.
diff --git a/REQUIRE b/REQUIRE
@@ -1,2 +1,3 @@
 julia 0.7.0-DEV.5190 # for cholesky function
 Compat 0.61.0
+Arpack
diff --git a/src/PDMats.jl b/src/PDMats.jl
@@ -3,7 +3,7 @@ __precompile__()
 module PDMats
 
     using Compat
-    using IterativeEigensolvers, LinearAlgebra, SparseArrays, SuiteSparse
+    using LinearAlgebra, SparseArrays, SuiteSparse
 
     import Base: +, *, \, /, ==, convert, inv, Matrix
 

diff --git a/src/pdsparsemat.jl b/src/pdsparsemat.jl
@@ -1,3 +1,4 @@
+using Arpack
 # Sparse positive definite matrix together with a Cholesky factorization object
 struct PDSparseMat{T<:Real,S<:AbstractSparseMatrix} <: AbstractPDMat{T}
   dim::Int

diff --git a/test/pdmtypes.jl b/test/pdmtypes.jl
@@ -1,5 +1,5 @@
 # test pd matrix types
-using LinearAlgebra, PDMats, SparseArrays
+using LinearAlgebra, PDMats, SparseArrays, SuiteSparse
 using Test
 
 call_test_pdmat(p::AbstractPDMat,m::Matrix) = test_pdmat(p,m,cmat_eq=true,verbose=1)