Eliminate speye from miscellaneous tests.

test/arrayops.jl

@@ -1008,7 +1008,7 @@ end
     @test m[1,2] == ([2,4],)
 
     # issue #21123
-    @test mapslices(nnz, speye(3), 1) == [1 1 1]
+    @test mapslices(nnz, sparse(1.0I, 3), 1) == [1 1 1]
 end
 
 @testset "single multidimensional index" begin

test/hashing.jl

@@ -73,7 +73,7 @@ vals = Any[
     Dict(x => x for x in 1:10),
     Dict(7=>7,9=>9,4=>4,10=>10,2=>2,3=>3,8=>8,5=>5,6=>6,1=>1),
     [], [1], [2], [1, 1], [1, 2], [1, 3], [2, 2], [1, 2, 2], [1, 3, 3],
-    zeros(2, 2), spzeros(2, 2), eye(2, 2), speye(2, 2),
+    zeros(2, 2), spzeros(2, 2), eye(2, 2), sparse(1.0I, 2),
     sparse(ones(2, 2)), ones(2, 2), sparse([0 0; 1 0]), [0 0; 1 0],
     [-0. 0; -0. 0.], SparseMatrixCSC(2, 2, [1, 3, 3], [1, 2], [-0., -0.])
 ]

test/linalg/arnoldi.jl

@@ -163,7 +163,7 @@ let
     # Adjust the tolerance a bit since matrices with repeated eigenvalues
     # can be very stressful to ARPACK and this may therefore fail with
     # info = 3 if the tolerance is too small
-    @test eigs(speye(50), nev=10, tol = 5e-16)[1] ≈ ones(10) #Issue 4246
+    @test eigs(sparse(1.0I, 50), nev=10, tol = 5e-16)[1] ≈ ones(10) #Issue 4246
 end
 
 @testset "real svds" begin

test/linalg/special.jl

@@ -178,7 +178,7 @@ end
     annotations = testfull ? (triannotations..., symannotations...) : (LowerTriangular, Symmetric)
     # Concatenations involving these types, un/annotated, should yield sparse arrays
     spvec = spzeros(N)
-    spmat = speye(N)
+    spmat = sparse(1.0I, N)
     diagmat = Diagonal(ones(N))
     bidiagmat = Bidiagonal(ones(N), ones(N-1), :U)
     tridiagmat = Tridiagonal(ones(N-1), ones(N), ones(N-1))

test/linalg/uniformscaling.jl

@@ -81,7 +81,7 @@ let
         @test B + I == B + eye(B)
         @test I + B == B + eye(B)
         AA = randn(2, 2)
-        for SS in (sprandn(3,3, 0.5), speye(Int, 3))
+        for SS in (sprandn(3,3, 0.5), sparse(Int(1)I, 3))
             for (A, S) in ((AA, SS), (view(AA, 1:2, 1:2), view(SS, 1:3, 1:3)))
                 @test @inferred(A + I) == A + eye(A)
                 @test @inferred(I + A) == A + eye(A)

test/perf/kernel/getdivgrad.jl

@@ -5,9 +5,9 @@
 #----------------- Get the A matrix
 function getDivGrad(n1,n2,n3)
     # the Divergence
-    D1 = kron(speye(n3),kron(speye(n2),ddx(n1)))
-    D2 = kron(speye(n3),kron(ddx(n2),speye(n1)))
-    D3 = kron(ddx(n3),kron(speye(n2),speye(n1)))
+    D1 = kron(sparse(1.0I, n3), kron(sparse(1.0I, n2), ddx(n1)))
+    D2 = kron(sparse(1.0I, n3), kron(ddx(n2), sparse(1.0I, n1)))
+    D3 = kron(ddx(n3), kron(sparse(1.0I, n2), sparse(1.0I, n1)))
     # DIV from faces to cell-centers
     Div = [D1 D2 D3]
 

test/perf/sparse/fem.jl

@@ -7,7 +7,7 @@ function fdlaplacian(N)
     # create a 1D laplacian and a sparse identity
     fdl1 = spdiagm(-1 => ones(N-1), 0 => -2*ones(N), 1 => ones(N-1))
     # laplace operator on the full grid
-    return kron(speye(N), fdl1) + kron(fdl1, speye(N))
+    return kron(sparse(1.0I, N), fdl1) + kron(fdl1, sparse(1.0I, N))
 end
 
 # get the list of boundary dof-indices

test/show.jl

@@ -492,7 +492,7 @@ end
 # issue #12960
 mutable struct T12960 end
 let
-    A = speye(3)
+    A = sparse(1.0I, 3)
     B = similar(A, T12960)
     @test sprint(show, B)  == "\n  [1, 1]  =  #undef\n  [2, 2]  =  #undef\n  [3, 3]  =  #undef"
     @test sprint(print, B) == "\n  [1, 1]  =  #undef\n  [2, 2]  =  #undef\n  [3, 3]  =  #undef"