Fix nesting structs in generators. (#176)

* nesting

* fixed nesting

* pretty print nodes

* add tests

* remove string / show

Author: hfytr

src/graph.jl

@@ -117,6 +117,10 @@ end
 @inline Base.getindex(n::ParSource, i) = ParIndexed(n, i)
 @inline Base.indexed_iterate(n::P, idx, start = 1) where P <: Union{ParSource, ParIndexed} = (ParIndexed(n, idx), idx + 1)
 
+@inline Base.getproperty(v::ParIndexed{I, n}, s::Symbol) where {I, n} = ParIndexed(v, s)
+@inline Base.getindex(v::ParIndexed{I, n}, i) where {I, n} = ParIndexed(v, i)
+@inline Base.indexed_iterate(v::ParIndexed{I, n}, idx, start = 1) where {I, n} = (ParIndexed(v, idx), idx + 1)
+
 
 @inline Base.getindex(n::VarSource, i) = Var(i)
 @inline Base.getindex(::ParameterSource, i) = ParameterNode(i)
@@ -140,7 +144,7 @@ struct Identity end
 @inline (v::ParameterNode{I})(::Identity, x, ::Nothing) where {I<:AbstractNode} = NaN
 
 @inline (v::ParSource)(i, x, θ) = i
-@inline (v::ParIndexed{I,n})(i, x, θ) where {I,n} = @inbounds getfield(v.inner(i, x, θ), n)
+@inline (v::ParIndexed{I,n})(i, x, θ) where {I,n} = @inbounds getfield(getfield(v, :inner)(i, x, θ), n)
 
 (v::ParIndexed)(i::Identity, x, θ) = NaN # despecialized
 (v::ParSource)(i::Identity, x, θ) = NaN # despecialized

test/NLPTest/NLPTest.jl

@@ -8,12 +8,12 @@ using JuMP, PowerModels, MadNLP, Percival
 import ..BACKENDS
 
 const NLP_TEST_ARGUMENTS = [
+    ("luksan_struct", 3),
+    ("luksan_struct", 20),
     ("luksan_vlcek", 3),
     ("luksan_vlcek", 20),
     ("ac_power", "pglib_opf_case3_lmbd.m"),
     ("ac_power", "pglib_opf_case14_ieee.m"),
-    ("struct_ac_power", "pglib_opf_case3_lmbd.m"),
-    ("struct_ac_power", "pglib_opf_case14_ieee.m"),
 ]
 
 const SOLVERS = [
@@ -36,8 +36,8 @@ end
 
 include("luksan.jl")
 include("power.jl")
+include("luksan_struct.jl")
 include("parameter_test.jl")
-include("power_struct.jl")
 
 function test_nlp(m1, m2; full = false)
     @testset "NLP meta tests" begin

test/NLPTest/luksan_struct.jl

@@ -0,0 +1,21 @@
+struct I2
+    i::Tuple{Int, Int}
+end
+
+struct I1
+    i::I2
+end
+
+function _exa_luksan_struct_model(backend, N; M = 1)
+
+    c = ExaCore(backend = backend)
+    data = [I1(I2((i,j))) for i = 1:N, j = 1:M]
+    x = variable(c, N, M; start = [luksan_vlcek_x0(i.i.i[1]) for i in data])
+    s = constraint(c, luksan_vlcek_con1(x, i.i.i[1], i.i.i[2]) for i in data[1:end-2,:])
+    constraint!(c, s, (i.i.i[1], i.i.i[2]) => luksan_vlcek_con2(x, i.i.i[1], i.i.i[2]) for i in data[1:end-2,:])
+    objective(c, luksan_vlcek_obj(x, i, j) for i = 2:N, j = 1:M)
+
+    return ExaModel(c; prod = true), (x,), (s,)
+end
+
+_jump_luksan_struct_model(backend, N; M = 1) = _jump_luksan_vlcek_model(backend, N; M)

test/NLPTest/power_struct.jl

@@ -11,12 +11,12 @@ NLPModels = "a4795742-8479-5a88-8948-cc11e1c8c1a6"
 NLPModelsIpopt = "f4238b75-b362-5c4c-b852-0801c9a21d71"
 NLPModelsJuMP = "792afdf1-32c1-5681-94e0-d7bf7a5df49e"
 NLPModelsTest = "7998695d-6960-4d3a-85c4-e1bceb8cd856"
+OpenCL = "08131aa3-fb12-5dee-8b74-c09406e224a2"
 Percival = "01435c0c-c90d-11e9-3788-63660f8fbccc"
 PowerModels = "c36e90e8-916a-50a6-bd94-075b64ef4655"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 oneAPI = "8f75cd03-7ff8-4ecb-9b8f-daf728133b1b"
-OpenCL = "08131aa3-fb12-5dee-8b74-c09406e224a2"
-pocl_jll = "627d6b7a-bbe6-5189-83e7-98cc0a5aeadd"
+pocl_jll = "627d6b7a-bbe6-5189-83e7-98cc0a5aeadd"