use new syntax in tests

Author: rokke

test/basic_indexing.jl

@@ -6,6 +6,9 @@ testa = cat(recs..., dims = 2)
 testva = VectorOfArray(recs)
 @test maximum(testva) == maximum(maximum.(recs))
 
+testva = VA[[1, 2, 3], [4, 5, 6], [7, 8, 9]]
+@test maximum(testva) == maximum(maximum.(recs))
+
 # broadcast with array
 X = rand(3, 3)
 mulX = sqrt.(abs.(testva .* X))
@@ -161,15 +164,15 @@ diffeq = DiffEqArray(recs, t)
 @test diffeq[:, (end - 1):end].t == t[(length(t) - 1):length(t)]
 
 # Test views of heterogeneous arrays (issue #453)
-f = VectorOfArray([[1.0], [2.0, 3.0]])
+f = VA[[1.0], [2.0, 3.0]]
 @test length(view(f, :, 1)) == 1
 @test length(view(f, :, 2)) == 2
 @test view(f, :, 1) == [1.0]
 @test view(f, :, 2) == [2.0, 3.0]
 @test collect(view(f, :, 1)) == f[:, 1]
 @test collect(view(f, :, 2)) == f[:, 2]
 
-f2 = VectorOfArray([[1.0, 2.0], [3.0]])
+f2 = VA[[1.0, 2.0], [3.0]]
 @test length(view(f2, :, 1)) == 2
 @test length(view(f2, :, 2)) == 1
 @test view(f2, :, 1) == [1.0, 2.0]
@@ -178,7 +181,7 @@ f2 = VectorOfArray([[1.0, 2.0], [3.0]])
 @test collect(view(f2, :, 2)) == f2[:, 2]
 
 # Test `end` with ragged arrays
-ragged = VectorOfArray([[1.0, 2.0], [3.0, 4.0, 5.0], [6.0, 7.0, 8.0, 9.0]])
+ragged = VA[[1.0, 2.0], [3.0, 4.0, 5.0], [6.0, 7.0, 8.0, 9.0]]
 @test ragged[end, 1] == 2.0
 @test ragged[end, 2] == 5.0
 @test ragged[end, 3] == 9.0
@@ -192,7 +195,7 @@ ragged = VectorOfArray([[1.0, 2.0], [3.0, 4.0, 5.0], [6.0, 7.0, 8.0, 9.0]])
 @test ragged[:, 2:end] == VectorOfArray(ragged.u[2:end])
 @test ragged[:, (end - 1):end] == VectorOfArray(ragged.u[(end - 1):end])
 
-ragged2 = VectorOfArray([[1.0, 2.0, 3.0, 4.0], [5.0, 6.0], [7.0, 8.0, 9.0]])
+ragged2 = VA[[1.0, 2.0, 3.0, 4.0], [5.0, 6.0], [7.0, 8.0, 9.0]]
 @test ragged2[end, 1] == 4.0
 @test ragged2[end, 2] == 6.0
 @test ragged2[end, 3] == 9.0
@@ -228,7 +231,7 @@ ragged_range_idx = 1:lastindex(ragged, 1)
 @test identity.(ragged_range_idx) === ragged_range_idx
 
 # Broadcasting of heterogeneous arrays (issue #454)
-u = VectorOfArray([[1.0], [2.0, 3.0]])
+u = VA[[1.0], [2.0, 3.0]]
 @test length(view(u, :, 1)) == 1
 @test length(view(u, :, 2)) == 2
 # broadcast assignment into selected column (last index Int)
@@ -293,7 +296,7 @@ u[1:2, 1, [1, 3], 2] .= [1.0 3.0; 2.0 4.0]
 @test u[end, 1, end] == u.u[end][end, 1, end]
 
 # Test that views can be modified
-f3 = VectorOfArray([[1.0, 2.0], [3.0, 4.0, 5.0]])
+f3 = VA[[1.0, 2.0], [3.0, 4.0, 5.0]]
 v = view(f3, :, 2)
 @test length(v) == 3
 v[1] = 10.0
@@ -384,7 +387,7 @@ mulX .= sqrt.(abs.(testva .* testvb))
 @test mulX == ref
 
 # https://github.com/SciML/RecursiveArrayTools.jl/issues/49
-a = ArrayPartition(1:5, 1:6)
+a = AP[1:5, 1:6]
 a[1:8]
 a[[1, 3, 8]]
 

test/downstream/downstream_events.jl

@@ -1,9 +1,9 @@
 using OrdinaryDiffEq, StaticArrays, RecursiveArrayTools
-u0 = ArrayPartition(SVector{1}(50.0), SVector{1}(0.0))
+u0 = AP[SVector{1}(50.0), SVector{1}(0.0)]
 tspan = (0.0, 15.0)
 
 function f(u, p, t)
-    return ArrayPartition(SVector{1}(u[2]), SVector{1}(-9.81))
+    return AP[SVector{1}(u[2]), SVector{1}(-9.81)]
 end
 
 prob = ODEProblem(f, u0, tspan)
@@ -13,7 +13,7 @@ function condition(u, t, integrator) # Event when event_f(u,t,k) == 0
 end
 
 affect! = nothingf = affect_neg! = function (integrator)
-    return integrator.u = ArrayPartition(SVector{1}(integrator.u[1]), SVector{1}(-integrator.u[2]))
+    return integrator.u = AP[SVector{1}(integrator.u[1]), SVector{1}(-integrator.u[2])]
 end
 
 callback = ContinuousCallback(condition, affect!, affect_neg!, interp_points = 100)

test/downstream/odesolve.jl

@@ -4,7 +4,7 @@ function lorenz(du, u, p, t)
     du[2] = u[1] * (28.0 - u[3]) - u[2]
     return du[3] = u[1] * u[2] - (8 / 3) * u[3]
 end
-u0 = ArrayPartition([1.0, 0.0], [0.0])
+u0 = AP[[1.0, 0.0], [0.0]]
 @test ArrayInterface.zeromatrix(u0) isa Matrix
 tspan = (0.0, 100.0)
 prob = ODEProblem(lorenz, u0, tspan)
@@ -25,26 +25,26 @@ function mymodel(F, vars)
     return
 end
 # To show that the function works
-F = ArrayPartition([0.0 0.0; 0.0 0.0], [0.0 0.0; 0.0 0.0])
-u0 = ArrayPartition([0.1 1.2; 0.1 1.2], [0.1 1.2; 0.1 1.2])
+F = AP[[0.0 0.0; 0.0 0.0], [0.0 0.0; 0.0 0.0]]
+u0 = AP[[0.1 1.2; 0.1 1.2], [0.1 1.2; 0.1 1.2]]
 result = mymodel(F, u0)
 nlsolve(mymodel, u0)
 
 # Nested ArrayPartition solves
 
 function dyn(u, p, t)
     return ArrayPartition(
-        ArrayPartition(zeros(1), [0.0]),
-        ArrayPartition(zeros(1), [0.0])
+        AP[zeros(1), [0.0]],
+        AP[zeros(1), [0.0]]
     )
 end
 
 @test solve(
     ODEProblem(
         dyn,
         ArrayPartition(
-            ArrayPartition(zeros(1), [-1.0]),
-            ArrayPartition(zeros(1), [0.75])
+            AP[zeros(1), [-1.0]],
+            AP[zeros(1), [0.75]]
         ),
         (0.0, 1.0)
     ),
@@ -55,8 +55,8 @@ end
     ODEProblem(
         dyn,
         ArrayPartition(
-            ArrayPartition(zeros(1), [-1.0]),
-            ArrayPartition(zeros(1), [0.75])
+            AP[zeros(1), [-1.0]],
+            AP[zeros(1), [0.75]]
         ),
         (0.0, 1.0)
     ),

test/interface_tests.jl

@@ -3,7 +3,7 @@ using FastBroadcast
 using SymbolicIndexingInterface: SymbolCache
 
 t = 1:3
-testva = VectorOfArray([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
+testva = VA[[1, 2, 3], [4, 5, 6], [7, 8, 9]]
 testda = DiffEqArray([[1, 2, 3], [4, 5, 6], [7, 8, 9]], t)
 
 for (i, elem) in enumerate(testva)
@@ -64,7 +64,7 @@ push!(testda, [-1, -2, -3, -4])
 
 # Type inference
 @inferred sum(testva)
-@inferred sum(VectorOfArray([VectorOfArray([zeros(4, 4)])]))
+@inferred sum(VA[VA[zeros(4, 4)]])
 @inferred mapreduce(string, *, testva)
 # Type stability for `end` indexing (issue #525)
 testva_end = VectorOfArray(fill(fill(2.0, 2), 10))
@@ -79,7 +79,7 @@ last_row = lastindex(testva_end, 1)
 @test testva_end[last_row, 1] == 2.0
 
 # mapreduce
-testva = VectorOfArray([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
+testva = VA[[1, 2, 3], [4, 5, 6], [7, 8, 9]]
 @test mapreduce(x -> string(x) * "q", *, testva) == "1q2q3q4q5q6q7q8q9q"
 
 testvb = VectorOfArray([rand(1:10, 3, 3, 3) for _ in 1:4])
@@ -128,7 +128,7 @@ end
 @test stack(testva) == [1 4 7; 2 5 8; 3 6 9]
 @test stack(testva; dims = 1) == [1 2 3; 4 5 6; 7 8 9]
 
-testva = VectorOfArray([VectorOfArray([ones(2, 2), 2ones(2, 2)]), 3ones(2, 2, 2)])
+testva = VA[VA[ones(2, 2), 2ones(2, 2)], 3ones(2, 2, 2)]
 @test stack(testva) ==
     [1.0 1.0; 1.0 1.0;;; 2.0 2.0; 2.0 2.0;;;; 3.0 3.0; 3.0 3.0;;; 3.0 3.0; 3.0 3.0]
 
@@ -180,29 +180,22 @@ testva = VectorOfArray([i * ones(3, 2) for i in 1:4])
 arr = rand(3, 2, 4)
 copyto!(testva, arr)
 @test Array(testva) == arr
-testva = VectorOfArray(
-    [
-        ones(3, 2, 2),
-        VectorOfArray(
-            [
-                2ones(3, 2),
-                VectorOfArray([3ones(3), 4ones(3)]),
-            ]
-        ),
-        DiffEqArray(
-            [
-                5ones(3, 2),
-                VectorOfArray(
-                    [
-                        6ones(3),
-                        7ones(3),
-                    ]
-                ),
-            ], [0.1, 0.2],
-            [100.0, 200.0], SymbolCache([:x, :y], [:a, :b], :t)
-        ),
-    ]
-)
+testva = VA[
+    ones(3, 2, 2),
+    VA[
+        2ones(3, 2),
+        VA[3ones(3), 4ones(3)],
+    ],
+    DiffEqArray(
+        [
+            5ones(3, 2),
+            VA[6ones(3), 7ones(3)],
+        ],
+        [0.1, 0.2],
+        [100.0, 200.0],
+        SymbolCache([:x, :y], [:a, :b], :t)
+    ),
+]
 arr = rand(3, 2, 2, 3)
 copyto!(testva, arr)
 @test Array(testva) == arr
@@ -244,16 +237,16 @@ resize!(u, 3)
 @test pointer(u) === pointer(u.u)
 
 # Ensure broadcast (including assignment) works with StaticArrays
-x = VectorOfArray([fill(2, SVector{2, Float64}), ones(SVector{2, Float64})])
-y = VectorOfArray([fill(2, SVector{2, Float64}), ones(SVector{2, Float64})])
-z = VectorOfArray([zeros(SVector{2, Float64}), zeros(SVector{2, Float64})])
+x = VA[fill(2, SVector{2, Float64}), ones(SVector{2, Float64})]
+y = VA[fill(2, SVector{2, Float64}), ones(SVector{2, Float64})]
+z = VA[zeros(SVector{2, Float64}), zeros(SVector{2, Float64})]
 z .= x .+ y
 
-@test z == VectorOfArray([fill(4, SVector{2, Float64}), fill(2, SVector{2, Float64})])
+@test z == VA[fill(4, SVector{2, Float64}), fill(2, SVector{2, Float64})]
 
-u1 = VectorOfArray([fill(2, SVector{2, Float64}), ones(SVector{2, Float64})])
-u2 = VectorOfArray([fill(4, SVector{2, Float64}), 2 .* ones(SVector{2, Float64})])
-u3 = VectorOfArray([fill(4, SVector{2, Float64}), 2 .* ones(SVector{2, Float64})])
+u1 = VA[fill(2, SVector{2, Float64}), ones(SVector{2, Float64})]
+u2 = VA[fill(4, SVector{2, Float64}), 2 .* ones(SVector{2, Float64})]
+u3 = VA[fill(4, SVector{2, Float64}), 2 .* ones(SVector{2, Float64})]
 
 function f(u1, u2, u3)
     return u3 .= u1 .+ u2
@@ -265,9 +258,9 @@ yy = [2.0 1.0; 2.0 1.0]
 zz = x .+ yy
 @test zz == [4.0 2.0; 4.0 2.0]
 
-z = VectorOfArray([zeros(SVector{2, Float64}), zeros(SVector{2, Float64})])
+z = VA[zeros(SVector{2, Float64}), zeros(SVector{2, Float64})]
 z .= zz
-@test z == VectorOfArray([fill(4, SVector{2, Float64}), fill(2, SVector{2, Float64})])
+@test z == VA[fill(4, SVector{2, Float64}), fill(2, SVector{2, Float64})]
 
 function f!(z, zz)
     return z .= zz
@@ -276,7 +269,7 @@ f!(z, zz)
 @test (@allocated f!(z, zz)) == 0
 
 z .= 0.1
-@test z == VectorOfArray([fill(0.1, SVector{2, Float64}), fill(0.1, SVector{2, Float64})])
+@test z == VA[fill(0.1, SVector{2, Float64}), fill(0.1, SVector{2, Float64})]
 
 function f2!(z)
     return z .= 0.1
@@ -288,7 +281,7 @@ function f3!(z, zz)
     return @.. broadcast = false z = zz
 end
 f3!(z, zz)
-@test z == VectorOfArray([fill(4, SVector{2, Float64}), fill(2, SVector{2, Float64})])
+@test z == VA[fill(4, SVector{2, Float64}), fill(2, SVector{2, Float64})]
 @test (@allocated f3!(z, zz)) == 0
 
 struct ImmutableVectorOfArray{T, N, A} <: AbstractVectorOfArray{T, N, A}
@@ -329,7 +322,7 @@ end
     using SparseArrays
 
     # Test that issparse returns false for VectorOfArray
-    testva = VectorOfArray([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
+    testva = VA[[1, 2, 3], [4, 5, 6], [7, 8, 9]]
     @test issparse(testva) == false
 
     # Test that issparse returns false for DiffEqArray
@@ -342,6 +335,6 @@ end
     @test issparse(testview) == false
 
     # Test with nested VectorOfArray
-    nested_voa = VectorOfArray([testva, testva])
+    nested_voa = VA[testva, testva]
     @test issparse(nested_voa) == false
 end

test/linalg.jl

@@ -56,4 +56,4 @@ mat = Array(va)
 @test all(va'[i] == mat'[i] for i in eachindex(mat'))
 @test Array(va') == mat'
 
-@test !ArrayInterface.issingular(VectorOfArray([rand(2), rand(2)]))
+@test !ArrayInterface.issingular(VA[rand(2), rand(2)])

test/partitions_and_static_arrays.jl

@@ -1,11 +1,10 @@
 using Test, RecursiveArrayTools, StaticArrays
 
-p = ArrayPartition(
-    (
-        zeros(Float32, 2), zeros(SMatrix{2, 2, Int64}, 2),
-        zeros(SVector{3, Float64}, 2),
-    )
-)
+p = AP[
+    zeros(Float32, 2),
+    zeros(SMatrix{2, 2, Int64}, 2),
+    zeros(SVector{3, Float64}, 2),
+]
 @test eltype(p) == Float64
 @test recursive_bottom_eltype(p) == Float64
 @test recursive_unitless_eltype(p) == Float64
@@ -14,5 +13,5 @@ p = ArrayPartition(
 p2 = similar(p)
 @test typeof(p2) == typeof(p)
 
-p3 = ArrayPartition(SA[1.0, 2.0], MMatrix{2, 2}([3.0 4.0; 3.0 5.0]))
+p3 = AP[SA[1.0, 2.0], MMatrix{2, 2}([3.0 4.0; 3.0 5.0])]
 @test (@inferred length(typeof(p3))) == 6