fix laurent polynomial switch (#63)

* fix laurent polynomial switch

* bump version

* remove debugger dep that commited by mistake

Author: GiggleLiu

Project.toml

@@ -1,7 +1,7 @@
 name = "GenericTensorNetworks"
 uuid = "3521c873-ad32-4bb4-b63d-f4f178f42b49"
 authors = ["GiggleLiu <cacate0129@gmail.com> and contributors"]
-version = "1.3.3"
+version = "1.3.4"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"

src/interfaces.jl

@@ -276,9 +276,15 @@ function solve(gp::GraphProblem, property::AbstractProperty; T=Float64, usecuda=
         return asarray(post_invert_exponent.(res), res)
     elseif property isa GraphPolynomial
         ws = get_weights(gp)
-        if ws isa NoWeight || ws isa ZeroWeight || all(>=(0), ws)
+        if !(eltype(ws) <: Integer)
+            @warn "Input weights are not Integer types, try casting to weights of `Int64` type..."
+            gp = chweights(gp, Int.(ws))
+            ws = get_weights(gp)
+        end
+        n = length(terms(gp))
+        if ws isa NoWeight || ws isa ZeroWeight || all(i->all(>=(0), get_weights(gp, i)), 1:n)
             return graph_polynomial(gp, Val(graph_polynomial_method(property)); usecuda=usecuda, T=T, property.kwargs...)
-        elseif all(<=(0), ws)
+        elseif all(i->all(<=(0), get_weights(gp, i)), 1:n)
             res = graph_polynomial(chweights(gp, -ws), Val(graph_polynomial_method(property)); usecuda=usecuda, T=T, property.kwargs...)
             return asarray(invert_polynomial.(res), res)
         else

src/networks/HyperSpinGlass.jl

@@ -29,6 +29,7 @@ $(TYPEDSIGNATURES)
 function HyperSpinGlass(n::Int, cliques::AbstractVector; weights=NoWeight(), openvertices=(), fixedvertices=Dict{Int,Int}(), optimizer=GreedyMethod(), simplifier=nothing)
     clqs = collect(collect.(cliques))
     @assert weights isa NoWeight || length(weights) == length(clqs)
+    @assert all(c->all(b->1<=b<=n, c), cliques) "vertex index out of bound 1-$n, got: $cliques"
     rawcode = EinCode([clqs..., [[i] for i=1:n]...], collect(Int, openvertices))  # labels for edge tensors
     HyperSpinGlass(_optimize_code(rawcode, uniformsize_fix(rawcode, 2, fixedvertices), optimizer, simplifier), n, clqs, weights, Dict{Int,Int}(fixedvertices))
 end
@@ -42,7 +43,7 @@ fixedvertices(gp::HyperSpinGlass) = gp.fixedvertices
 # weights interface
 get_weights(c::HyperSpinGlass) = c.weights
 get_weights(gp::HyperSpinGlass, i::Int) = [-gp.weights[i], gp.weights[i]]
-chweights(c::HyperSpinGlass, weights) = HyperSpinGlass(c.code, c.cliques, weights, c.fixedvertices)
+chweights(c::HyperSpinGlass, weights) = HyperSpinGlass(c.code, c.n, c.cliques, weights, c.fixedvertices)
 
 function generate_tensors(x::T, gp::HyperSpinGlass) where T
     ixs = getixsv(gp.code)

test/networks/HyperSpinGlass.jl

@@ -35,4 +35,20 @@ using GenericTensorNetworks, Test, Graphs
     poly = solve(gp, GraphPolynomial(; method=:laurent))[]
     @test poly.m[] == sorted_energies[1]
     @test poly.n[] == sorted_energies[end]
+end
+
+@testset "auto laurent" begin
+    hyperDim = 2
+    blockDim = 3
+    graph = [[2, 12], [3, 11], [1, 5], [2, 4], [4, 5], [4, 8], [5, 7], [1, 9], [3, 7], [5, 9], [6, 8], [4, 9], [6, 7], [7, 12], [9, 10], [10, 12], [4, 6], [5, 6], [10, 11], [1, 2, 12], [1, 3, 11], [1, 11, 12], [2, 3, 10], [2, 10, 12], [3, 10, 11], [4, 8, 12], [4, 9, 11], [5, 7, 12], [7, 8, 12], [6, 7, 11], [7, 9, 11], [7, 11, 12], [5, 9, 10], [6, 8, 10], [8, 9, 10], [8, 10, 12], [9, 10, 11], [1, 2, 9], [1, 3, 8], [1, 8, 9], [2, 3, 7], [2, 7, 9], [3, 7, 8], [1, 2, 3], [4, 5, 6], [7, 8, 9]]
+    num_vertices = blockDim* 2^hyperDim
+    weights = ones(Int, length(graph));
+    problem = HyperSpinGlass(num_vertices, graph; weights);
+    poly = solve(problem, GraphPolynomial())[]
+    @test poly isa LaurentPolynomial
+
+    weights = ones(length(graph));
+    problem = HyperSpinGlass(num_vertices, graph; weights);
+    poly = solve(problem, GraphPolynomial())[]
+    @test poly isa LaurentPolynomial
 end