Upgrade LuxorGraphPlot

docs/src/ref.md

@@ -134,8 +134,11 @@ MergeGreedy
 #### Graph
 ```@docs
 show_graph
-show_gallery
+show_configs
 show_einsum
+GraphDisplayConfig
+Layout
+render_locs
 
 diagonal_coupled_graph
 square_lattice_graph

examples/Coloring.jl

@@ -55,14 +55,14 @@ is_vertex_coloring(graph, single_solution.c.data)
 
 vertex_color_map = Dict(0=>"red", 1=>"green", 2=>"blue")
 
-show_graph(graph; locs=locations, format=:svg, vertex_colors=[vertex_color_map[Int(c)]
+show_graph(graph, locations; format=:svg, vertex_colors=[vertex_color_map[Int(c)]
      for c in single_solution.c.data])
 
 # Let us try to solve the same issue on its line graph, a graph that generated by mapping an edge to a vertex and two edges sharing a common vertex will be connected.
 linegraph = line_graph(graph)
 
-show_graph(linegraph; locs=[0.5 .* (locations[e.src] .+ locations[e.dst])
-     for e in edges(graph)], format=:svg)
+show_graph(linegraph, [0.5 .* (locations[e.src] .+ locations[e.dst])
+     for e in edges(graph)]; format=:svg)
 
 # Let us construct the tensor network and see if there are solutions.
 lineproblem = Coloring{3}(linegraph);

examples/DominatingSet.jl

@@ -74,7 +74,7 @@ all(c->is_dominating_set(graph, c), min_configs)
 
 #
 
-show_gallery(graph, (2, 5); locs=locations, vertex_configs=min_configs, format=:svg)
+show_configs(graph, locations, reshape(collect(min_configs), 2, 5); padding_left=20)
 
 # Similarly, if one is only interested in computing one of the minimum dominating sets,
 # one can use the graph property [`SingleConfigMin`](@ref).

examples/IndependentSet.jl

@@ -132,8 +132,8 @@ all_max_configs = solve(problem, ConfigsMax(; bounded=true))[]
 
 all_max_configs.c.data
 
-# These solutions can be visualized with the [`show_gallery`](@ref) function.
-show_gallery(graph, (1, length(all_max_configs.c)); locs=locations, vertex_configs=all_max_configs.c, format=:svg)
+# These solutions can be visualized with the [`show_configs`](@ref) function.
+show_configs(graph, locations, reshape(collect(all_max_configs.c), 1, length(all_max_configs.c)); padding_left=20)
 
 # We can use [`ConfigsAll`](@ref) to enumerate all sets satisfying the independence constraint.
 all_independent_sets = solve(problem, ConfigsAll())[]

examples/Matching.jl

@@ -66,7 +66,7 @@ matching_poly = solve(problem, GraphPolynomial())[]
 match_config = solve(problem, SingleConfigMax())[]
 
 # Let us show the result by coloring the matched edges to red
-show_graph(graph; locs=locations, format=:svg, edge_colors=
+show_graph(graph, locations; format=:svg, edge_colors=
     [isone(match_config.c.data[i]) ? "red" : "black" for i=1:ne(graph)])
 
 # where we use edges with red color to related pairs of matched vertices.

examples/MaxCut.jl

@@ -76,7 +76,7 @@ max_cut_size_verify = cut_size(graph, max_vertex_config)
 
 # You should see a consistent result as above `max_cut_size`.
 
-show_graph(graph; locs=locations, vertex_colors=[
+show_graph(graph, locations; vertex_colors=[
         iszero(max_vertex_config[i]) ? "white" : "red" for i=1:nv(graph)], format=:svg)
 
 # where red vertices and white vertices are separated by the cut.

examples/MaximalIS.jl

@@ -72,7 +72,7 @@ all(c->is_maximal_independent_set(graph, c), maximal_configs)
 
 #
 
-show_gallery(graph, (3, 5); locs=locations, vertex_configs=maximal_configs, format=:svg)
+show_configs(graph, locations, reshape(collect(maximal_configs), 3, 5); padding_left=20)
 
 # This result should be consistent with that given by the [Bron Kerbosch algorithm](https://en.wikipedia.org/wiki/Bron%E2%80%93Kerbosch_algorithm) on the complement of Petersen graph.
 cliques = maximal_cliques(complement(graph))
@@ -83,7 +83,7 @@ cliques = maximal_cliques(complement(graph))
 # It is the [`ConfigsMin`](@ref) property in the program.
 minimum_maximal_configs = solve(problem, ConfigsMin())[].c
 
-show_gallery(graph, (2, 5); locs=locations, vertex_configs=minimum_maximal_configs, format=:svg)
+show_configs(graph, locations, reshape(collect(minimum_maximal_configs), 2, 5); padding_left=20)
 
 # Similarly, if one is only interested in computing one of the minimum sets,
 # one can use the graph property [`SingleConfigMin`](@ref).

examples/PaintShop.jl

@@ -90,9 +90,9 @@ best_configs = solve(problem, ConfigsMin())[]
 
 painting1 = paint_shop_coloring_from_config(pshop, best_configs.c.data[1])
 
-show_graph(graph; locs=locations, format=:svg, texts=string.(sequence),
+show_graph(graph, locations; format=:svg, texts=string.(sequence),
     edge_colors=[sequence[e.src] == sequence[e.dst] ? "blue" : "black" for e in edges(graph)],
-    vertex_colors=[isone(c) ? "red" : "black" for c in painting1], vertex_text_color="white")
+    vertex_colors=[isone(c) ? "red" : "black" for c in painting1], config=GraphDisplayConfig(;vertex_text_color="white"))
 
 # Since we have different choices of initial color, the number of best solution is 2.
 

examples/weighted.jl

@@ -41,5 +41,4 @@ max5_configs = solve(problem, SingleConfigMax(5))[]
 max5_configs.orders
 
 # Let us visually check these configurations
-show_gallery(graph, (1, 5); locs=locations, format=:svg, vertex_configs=[max5_configs.orders[k].c.data for k=1:5])
-
+show_configs(graph, locations, [max5_configs.orders[j].c.data for i=1:1, j=1:5]; padding_left=20)

src/GenericTensorNetworks.jl

@@ -7,6 +7,7 @@ using OMEinsum: contraction_complexity, timespace_complexity, timespacereadwrite
 using Graphs, Random
 using DelimitedFiles, Serialization, Printf
 using LuxorGraphPlot
+using LuxorGraphPlot.Luxor.Colors: @colorant_str
 import Polynomials
 using Polynomials: Polynomial, LaurentPolynomial, printpoly, fit
 using FFTW
@@ -59,7 +60,7 @@ export solve, SizeMax, SizeMin, PartitionFunction, CountingAll, CountingMax, Cou
 export save_configs, load_configs, hamming_distribution, save_sumproduct, load_sumproduct
 
 # Visualization
-export show_graph, spring_layout!, show_gallery, show_einsum
+export show_graph, spring_layout!, show_configs, show_einsum, GraphDisplayConfig, Layout, render_locs
 
 project_relative_path(xs...) = normpath(joinpath(dirname(dirname(pathof(@__MODULE__))), xs...))
 

src/visualize.jl

@@ -3,16 +3,16 @@
         tensor_locs=nothing,
         label_locs=nothing,  # dict
         spring::Bool=true,
-        optimal_distance=1.0,
+        optimal_distance=25.0,
 
-        tensor_size=0.3,
+        tensor_size=15,
         tensor_color="black",
         tensor_text_color="white",
         annotate_tensors=false,
 
-        label_size=0.15,
+        label_size=7,
         label_color="black",
-        open_label_color="red",
+        open_label_color="black",
         annotate_labels=true,
         kwargs...
         )
@@ -46,7 +46,7 @@ $(LuxorGraphPlot.CONFIGHELP)
 function show_einsum(ein::AbstractEinsum;
         label_size=7,
         label_color="black",
-        open_label_color="red",
+        open_label_color="black",
         tensor_size=15,
         tensor_color="black",
         tensor_text_color="white",
@@ -56,7 +56,13 @@ function show_einsum(ein::AbstractEinsum;
         label_locs=nothing,  # dict
         layout::Symbol=:auto,
         optimal_distance=25.0,
-        kwargs...
+        filename=nothing,
+        format=:svg,
+        padding_left=10.0,
+        padding_right=10.0,
+        padding_top=10.0,
+        padding_bottom=10.0,
+        config=LuxorGraphPlot.GraphDisplayConfig(; vertex_line_width=0.0),
         )
     ixs = getixsv(ein)
     iy = getiyv(ein)
@@ -75,7 +81,7 @@ function show_einsum(ein::AbstractEinsum;
         end
     end
     if label_locs === nothing && tensor_locs === nothing
-        locs = LuxorGraphPlot.render_locs(graph, Layout(layout; optimal_distance, spring_mask = trues(nv(graph))))
+        locs = LuxorGraphPlot.render_locs(graph, LuxorGraphPlot.Layout(layout; optimal_distance, spring_mask = trues(nv(graph))))
     elseif label_locs === nothing
         # infer label locs from tensor locs
         label_locs = [(lst = [iloc for (iloc,ix) in zip(tensor_locs, ixs) if l ∈ ix]; reduce((x,y)->x .+ y, lst) ./ length(lst)) for l in labels]
@@ -89,5 +95,29 @@ function show_einsum(ein::AbstractEinsum;
     end
     show_graph(GraphViz(; locs, edges=[(e.src, e.dst) for e in edges(graph)], texts, vertex_colors=colors,
         vertex_text_colors,
-        vertex_sizes=sizes); config=LuxorGraphPlot.GraphDisplayConfig(vertex_line_width=0, kwargs...))
-end
+        vertex_sizes=sizes);
+        filename, format,
+        padding_left, padding_right, padding_top, padding_bottom, config
+        )
+end
+
+"""
+    show_configs(gp::GraphProblem, locs, configs::AbstractMatrix; kwargs...)
+    show_configs(graph::SimpleGraph, locs, configs::AbstractMatrix; nflavor=2, kwargs...)
+
+Show a gallery of configurations on a graph.
+"""
+function show_configs(gp::GraphProblem, locs, configs::AbstractMatrix; kwargs...)
+    show_configs(gp.graph, locs, configs; nflavor=nflavor(gp), kwargs...)
+end
+function show_configs(graph::SimpleGraph, locs, configs::AbstractMatrix;
+        nflavor::Int=2,
+        kwargs...)
+    cmap = range(colorant"white", stop=colorant"red", length=nflavor)
+    locs = render_locs(graph, locs)
+    graphs = map(configs) do cfg
+        @assert all(0 .<= cfg .<= nflavor-1)
+        GraphViz(graph; locs, vertex_colors=cmap[cfg .+ 1])
+    end
+    show_gallery(graphs; kwargs...)
+end

test/Project.toml

@@ -3,6 +3,7 @@ CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+LuxorGraphPlot = "1f49bdf2-22a7-4bc4-978b-948dc219fbbc"
 OMEinsum = "ebe7aa44-baf0-506c-a96f-8464559b3922"
 Polynomials = "f27b6e38-b328-58d1-80ce-0feddd5e7a45"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"

test/visualize.jl

@@ -1,8 +1,11 @@
 using GenericTensorNetworks, Test, Graphs
+using LuxorGraphPlot: Layout
 
 @testset "visualize" begin
     graph = smallgraph(:petersen)
     @test show_graph(graph) isa Any
+    configs = [rand(Bool, 10) for i=1:5, j=1:3]
+    @test show_configs(graph, Layout(:stress), configs) isa Any
 end
 
 @testset "einsum" begin