Avoid calls to eye and speye

Due to the deprcation in Julia 0.7, they are replaces with
`Array{...}(I, ...)` or `SparseMatrixCSC{...}(I, ...)` (or just `I`
where possible). Requires Compat 0.36.

REQUIRE

@@ -1,5 +1,5 @@
 julia 0.5
-Compat 0.35.0
+Compat 0.36.0
 DataStructures 0.2.9
 IterTools 0.1.0
 ProgressMeter 0.2.1

src/ACME.jl

@@ -352,7 +352,7 @@ end
 model_matrices(circ::Circuit, t) = model_matrices(circ, Rational{BigInt}(t))
 
 function tryextract(fq, numcols)
-    a = eye(eltype(fq), size(fq,2))
+    a = Matrix{eltype(fq)}(I, size(fq, 2), size(fq, 2))
     if numcols ≥ size(fq,2)
         return Nullable(a)
     end
@@ -383,7 +383,7 @@ end
 
 function nldecompose!(mats, nns, nqs)
     fq = mats[:fq]
-    a = eye(eltype(fq), size(fq,2))
+    a = Matrix{eltype(fq)}(I, size(fq, 2), size(fq, 2))
     sub_ranges = consecranges(nqs)
     extracted_subs = Vector{Int}[]
     rem_cols = 1:size(fq, 2)
@@ -483,7 +483,7 @@ nn(model::DiscreteModel, subidx) = size(model.fqs[subidx], 2)
 nn(model::DiscreteModel) = sum([size(fq, 2) for fq in model.fqs])
 
 function steadystate(model::DiscreteModel, u=zeros(nu(model)))
-    IA_LU = lufact(eye(nx(model))-model.a)
+    IA_LU = lufact(I-model.a)
     steady_z = zeros(nn(model))
     zoff = 1
     for idx in 1:length(model.solvers)
@@ -762,12 +762,12 @@ function gensolve(a::SparseMatrixCSC, b, x, h, thresh=0.1)
 end
 
 gensolve(a, b, thresh=0.1) =
-    gensolve(a, b, spzeros(promote_type(eltype(a), eltype(b)), size(a)[2], size(b)[2]), speye(eltype(a), size(a)[2]), thresh)
+    gensolve(a, b, spzeros(promote_type(eltype(a), eltype(b)), size(a, 2), size(b, 2)), SparseMatrixCSC{eltype(a)}(I, size(a,2), size(a,2)), thresh)
 
 function rank_factorize(a::SparseMatrixCSC)
     f = a
     nullspace = gensolve(a', spzeros(size(a, 2), 0))[2]
-    c = eye(eltype(a), size(a, 1))
+    c = Matrix{eltype(a)}(I, size(a, 1), size(a, 1))
     while size(nullspace, 2) > 0
         i, j = _indmax(abs.(nullspace))
         c -= c[:, i] * nullspace[:, j]' / nullspace[i, j]

src/circuit.jl

@@ -285,7 +285,7 @@ end
     dl = ti[:, (!).(t)]
     tv = spzeros(T, size(dl, 2), size(incidence, 2))
     tv[:, t] = -dl.'
-    tv[:, (!).(t)] = speye(T, size(dl, 2))
+    tv[:, (!).(t)] = SparseMatrixCSC{T}(I, size(dl, 2), size(dl, 2))
 
     tv, ti
 end

src/elements.jl

@@ -15,11 +15,12 @@ Pins: `1`, `2`
 """
 resistor(r) = Element(mv=-1, mi=r)
 
-potentiometer(r, pos) = Element(mv=-eye(2), mi=[r*pos 0; 0 r*(1-pos)],
+potentiometer(r, pos) = Element(mv=Matrix{Int}(-I, 2, 2), mi=[r*pos 0; 0 r*(1-pos)],
                                 pins=[1, 2, 2, 3])
 potentiometer(r) =
-    Element(mv=[eye(2); zeros(3, 2)], mi=[zeros(2, 2); eye(2); zeros(1, 2)],
-            mq=-eye(5), mu=[zeros(4, 1); -1],
+    Element(mv=[Matrix{Int}(I, 2, 2); zeros(3, 2)],
+            mi=[zeros(2, 2); Matrix{Int}(I, 2, 2); zeros(1, 2)],
+            mq=Matrix{Int}(-I, 5, 5), mu=[zeros(4, 1); -1],
             nonlinear_eq = quote
                 let v1=q[1], v2=q[2], i1=q[3], i2=q[4], pos=q[5]
                     res[1] = v1 - $(r)*pos*i1
@@ -434,7 +435,7 @@ function bjt(typ; is=1e-12, η=1, isc=is, ise=is, ηc=η, ηe=η, βf=1000, βr=
         end
     return Element(mv=[1 0; 0 1; 0 0; 0 0],
                    mi = [-(re+rb) -rb; -rb -(rc+rb); 1 0; 0 1],
-                   mq = -polarity*speye(4), nonlinear_eq = nonlinear_eq,
+                   mq = Matrix{Int}(-polarity*I, 4, 4), nonlinear_eq = nonlinear_eq,
                    pins = [:base; :emitter; :base; :collector])
 end
 

src/kdtree.jl

@@ -95,7 +95,7 @@ isless(e1::AltEntry, e2::AltEntry) = isless(e1.delta_norm, e2.delta_norm)
 end
 
 @pfunction Alts(p::Vector{T}) [T] begin
-     Alts([AltEntry(1, zeros(p), zero(T))], typemax(T), 0, 1)
+     Alts([AltEntry(1, Vector{T}(length(p)), zero(T))], typemax(T), 0, 1)
  end
 
 @pfunction init!(alts::Alts{T}, best_dist, best_pidx) [T] begin

test/runtests.jl

@@ -12,9 +12,9 @@ using ProgressMeter
 
     # Pathological cases for topomat:
     # two nodes, one loop branch (short-circuited) -> voltage==0, current arbitrary
-    @test ACME.topomat(spzeros(Int, 2, 1)) == (speye(1), spzeros(0, 1))
+    @test ACME.topomat(spzeros(Int, 2, 1)) == (hcat([1]), spzeros(0, 1))
     # two nodes, one branch between them -> voltage arbitrary, current==0
-    @test ACME.topomat(sparse([1,2], [1,1], [1,-1])) == (spzeros(0, 1), speye(1))
+    @test ACME.topomat(sparse([1,2], [1,1], [1,-1])) == (spzeros(0, 1), hcat([1]))
 end
 
 @testset "LinearSolver" begin