rename unweighted

Author: GiggleLiu

Project.toml

@@ -1,7 +1,7 @@
 name = "GraphTensorNetworks"
 uuid = "0978c8c2-34f6-49c7-9826-ea2cc20dabd2"
 authors = ["GiggleLiu <cacate0129@gmail.com> and contributors"]
-version = "0.2.4"
+version = "0.2.5"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"

src/GraphTensorNetworks.jl

@@ -31,7 +31,7 @@ export line_graph
 # Tensor Networks (Graph problems)
 export GraphProblem, IndependentSet, MaximalIS, Matching, 
     Coloring, optimize_code, set_packing, MaxCut, PaintShop,
-    paintshop_from_pairs, UnWeighted, Satisfiability
+    paintshop_from_pairs, NoWeight, Satisfiability
 export flavors, labels, terms, nflavor, get_weights
 export mis_compactify!, cut_size, num_paint_shop_color_switch, paint_shop_coloring_from_config
 export is_good_vertex_coloring

src/networks/IndependentSet.jl

@@ -1,21 +1,21 @@
 """
-    IndependentSet{CT<:AbstractEinsum,WT<:Union{UnWeighted, Vector}} <: GraphProblem
-    IndependentSet(graph; weights=UnWeighted(), openvertices=(),
+    IndependentSet{CT<:AbstractEinsum,WT<:Union{NoWeight, Vector}} <: GraphProblem
+    IndependentSet(graph; weights=NoWeight(), openvertices=(),
                  optimizer=GreedyMethod(), simplifier=nothing)
 
 The [independent set problem](https://psychic-meme-f4d866f8.pages.github.io/dev/tutorials/IndependentSet.html) in graph theory.
 In the constructor, `weights` are the weights of vertices.
 `openvertices` specifies labels for the output tensor.
 `optimizer` and `simplifier` are for tensor network optimization, check [`optimize_code`](@ref) for details.
 """
-struct IndependentSet{CT<:AbstractEinsum,WT<:Union{UnWeighted, Vector}} <: GraphProblem
+struct IndependentSet{CT<:AbstractEinsum,WT<:Union{NoWeight, Vector}} <: GraphProblem
     code::CT
     nv::Int
     weights::WT
 end
 
-function IndependentSet(g::SimpleGraph; weights=UnWeighted(), openvertices=(), optimizer=GreedyMethod(), simplifier=nothing)
-    @assert weights isa UnWeighted || length(weights) == nv(g)
+function IndependentSet(g::SimpleGraph; weights=NoWeight(), openvertices=(), optimizer=GreedyMethod(), simplifier=nothing)
+    @assert weights isa NoWeight || length(weights) == nv(g)
     rawcode = EinCode([[[i] for i in Graphs.vertices(g)]..., # labels for vertex tensors
                        [[minmax(e.src,e.dst)...] for e in Graphs.edges(g)]...], collect(Int, openvertices))  # labels for edge tensors
     code = _optimize_code(rawcode, uniformsize(rawcode, 2), optimizer, simplifier)
@@ -70,7 +70,7 @@ julia> res = best_solutions(gp; all=true)[]
 (2, {10010, 00110, 01100})ₜ
 ```
 """
-function set_packing(sets; weights=UnWeighted(), openvertices=(), optimizer=GreedyMethod(), simplifier=nothing)
+function set_packing(sets; weights=NoWeight(), openvertices=(), optimizer=GreedyMethod(), simplifier=nothing)
     n = length(sets)
     code = EinCode(vcat([[i] for i=1:n], [[i,j] for i=1:n,j=1:n if j>i && !isempty(sets[i] ∩ sets[j])]), collect(Int,openvertices))
     IndependentSet(_optimize_code(code, uniformsize(code, 2), optimizer, simplifier), n, weights)

src/networks/MaxCut.jl

@@ -1,19 +1,19 @@
 """
-    MaxCut{CT<:AbstractEinsum,WT<:Union{UnWeighted, Vector}} <: GraphProblem
-    MaxCut(graph; weights=UnWeighted(), openvertices=(),
+    MaxCut{CT<:AbstractEinsum,WT<:Union{NoWieght, Vector}} <: GraphProblem
+    MaxCut(graph; weights=NoWeight(), openvertices=(),
                 optimizer=GreedyMethod(), simplifier=nothing)
 
 The [cutting](https://psychic-meme-f4d866f8.pages.github.io/dev/tutorials/MaxCut.html) problem (or spin glass problem).
 In the constructor, `weights` are the weights of edges.
 `optimizer` and `simplifier` are for tensor network optimization, check [`optimize_code`](@ref) for details.
 """
-struct MaxCut{CT<:AbstractEinsum,WT<:Union{UnWeighted, Vector}} <: GraphProblem
+struct MaxCut{CT<:AbstractEinsum,WT<:Union{NoWeight, Vector}} <: GraphProblem
     code::CT
     nv::Int
     weights::WT
 end
-function MaxCut(g::SimpleGraph; weights=UnWeighted(), openvertices=(), optimizer=GreedyMethod(), simplifier=nothing)
-    @assert weights isa UnWeighted || length(weights) == ne(g)
+function MaxCut(g::SimpleGraph; weights=NoWeight(), openvertices=(), optimizer=GreedyMethod(), simplifier=nothing)
+    @assert weights isa NoWeight || length(weights) == ne(g)
     rawcode = EinCode([[minmax(e.src,e.dst)...] for e in Graphs.edges(g)], collect(Int, openvertices))  # labels for edge tensors
     MaxCut(_optimize_code(rawcode, uniformsize(rawcode, 2), optimizer, simplifier), nv(g), weights)
 end
@@ -34,11 +34,11 @@ function maxcutb(a, b)
 end
 
 """
-    cut_size(g::SimpleGraph, config; weights=UnWeighted())
+    cut_size(g::SimpleGraph, config; weights=NoWeight())
 
 Compute the cut size from vertex `config` (an iterator).
 """
-function cut_size(g::SimpleGraph, config; weights=UnWeighted())
+function cut_size(g::SimpleGraph, config; weights=NoWeight())
     size = zero(eltype(weights)) * false
     for (i, e) in enumerate(edges(g))
         size += (config[e.src] != config[e.dst]) * weights[i]

src/networks/MaximalIS.jl

@@ -1,18 +1,18 @@
 """
-    MaximalIS{CT<:AbstractEinsum,WT<:Union{UnWeighted, Vector}} <: GraphProblem
-    MaximalIS(graph; weights=UnWeighted(), openvertices=(),
+    MaximalIS{CT<:AbstractEinsum,WT<:Union{NoWeight, Vector}} <: GraphProblem
+    MaximalIS(graph; weights=NoWeight(), openvertices=(),
                  optimizer=GreedyMethod(), simplifier=nothing)
 
 The [maximal independent set](https://psychic-meme-f4d866f8.pages.github.io/dev/tutorials/MaximalIS.html) problem. In the constructor, `weights` are the weights of vertices.
 `optimizer` and `simplifier` are for tensor network optimization, check [`optimize_code`](@ref) for details.
 """
-struct MaximalIS{CT<:AbstractEinsum,WT<:Union{UnWeighted, Vector}} <: GraphProblem
+struct MaximalIS{CT<:AbstractEinsum,WT<:Union{NoWeight, Vector}} <: GraphProblem
     code::CT
     weights::WT
 end
 
-function MaximalIS(g::SimpleGraph; weights=UnWeighted(), openvertices=(), optimizer=GreedyMethod(), simplifier=nothing)
-    @assert weights isa UnWeighted || length(weights) == nv(g)
+function MaximalIS(g::SimpleGraph; weights=NoWeight(), openvertices=(), optimizer=GreedyMethod(), simplifier=nothing)
+    @assert weights isa NoWeight || length(weights) == nv(g)
     rawcode = EinCode(([[Graphs.neighbors(g, v)..., v] for v in Graphs.vertices(g)]...,), collect(Int, openvertices))
     MaximalIS(_optimize_code(rawcode, uniformsize(rawcode, 2), optimizer, simplifier), weights)
 end

src/networks/Satisfiability.jl

@@ -104,7 +104,7 @@ macro bools(syms::Symbol...)
 end
 
 """
-    Satisfiability{CT<:AbstractEinsum,WT<:Union{UnWeighted, Vector}} <: GraphProblem
+    Satisfiability{CT<:AbstractEinsum,WT<:Union{NoWeight, Vector}} <: GraphProblem
     Satisfiability(cnf::CNF; openvertices=(),
                  optimizer=GreedyMethod(), simplifier=nothing)
 

src/networks/networks.jl

@@ -5,9 +5,9 @@ The abstract base type of graph problems.
 """
 abstract type GraphProblem end
 
-struct UnWeighted end
-Base.getindex(::UnWeighted, i) = 1
-Base.eltype(::UnWeighted) = Int
+struct NoWeight end
+Base.getindex(::NoWeight, i) = 1
+Base.eltype(::NoWeight) = Int
 
 ######## Interfaces for graph problems ##########
 """

test/configurations.jl

@@ -32,7 +32,7 @@ end
 
 @testset "enumerating" begin
     rawcode = IndependentSet(smallgraph(:petersen); optimizer=nothing)
-    optcode = IndependentSet(optimize_code(rawcode.code, uniformsize(rawcode.code, 2), GreedyMethod()), 10, UnWeighted())
+    optcode = IndependentSet(optimize_code(rawcode.code, uniformsize(rawcode.code, 2), GreedyMethod()), 10, NoWeight())
     for code in [rawcode, optcode]
         res0 = max_size(code)
         _, res1 = max_size_count(code)