show gallery

Author: GiggleLiu

docs/Project.toml

@@ -1,5 +1,4 @@
 [deps]
-Compose = "a81c6b42-2e10-5240-aca2-a61377ecd94b"
 DocThemeIndigo = "8bac0ac5-51bf-41f9-885e-2bf1ac2bec5f"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 GenericTensorNetworks = "3521c873-ad32-4bb4-b63d-f4f178f42b49"

examples/DominatingSet.jl

@@ -10,7 +10,7 @@
 # The decision version of finding the minimum dominating set is an NP-complete.
 # In the following, we are going to solve the dominating set problem on the Petersen graph.
 
-using GenericTensorNetworks, Graphs, Compose
+using GenericTensorNetworks, Graphs
 
 graph = Graphs.smallgraph(:petersen)
 
@@ -72,13 +72,7 @@ all(c->is_dominating_set(graph, c), min_configs)
 
 #
 
-imgs = ntuple(k->show_graph(graph;
-                locs=locations, scale=0.25,
-                vertex_colors=[iszero(min_configs[k][i]) ? "white" : "red"
-                for i=1:nv(graph)]), length(min_configs));
-
-Compose.set_default_graphic_size(18cm, 8cm); Compose.compose(context(),
-     ntuple(k->(context((mod1(k,5)-1)/5, ((k-1)÷5)/2, 1.2/5, 1.0/2), imgs[k]), 10)...)
+show_gallery(graph, (2, 5); locs=locations, vertex_configs=min_configs)
 
 # 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

@@ -130,7 +130,7 @@ all_max_configs = solve(problem, ConfigsMax(; bounded=true))[]
 
 all_max_configs.c.data
 
-# Let us visualize the solutions with the visualization package [`Compose`](https://github.com/GiovineItalia/Compose.jl).
+# 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);
 
 # We can use [`ConfigsAll`](@ref) to enumerate all sets satisfying the independence constraint.

examples/MaximalIS.jl

@@ -9,7 +9,7 @@
 # It is different from maximum independent set because it does not require the set to have the max size.
 # In the following, we are going to solve the maximal independent set problem on the Petersen graph.
 
-using GenericTensorNetworks, Graphs, Compose
+using GenericTensorNetworks, Graphs
 
 graph = Graphs.smallgraph(:petersen)
 
@@ -73,13 +73,7 @@ all(c->is_maximal_independent_set(graph, c), maximal_configs)
 
 #
 
-imgs = ntuple(k->show_graph(graph;
-                locs=locations, scale=0.25,
-                vertex_colors=[iszero(maximal_configs[k][i]) ? "white" : "red"
-                for i=1:nv(graph)]), length(maximal_configs));
-
-Compose.set_default_graphic_size(18cm, 12cm); Compose.compose(context(),
-     ntuple(k->(context((mod1(k,5)-1)/5, ((k-1)÷5)/3, 1.2/5, 1.0/3), imgs[k]), 15)...)
+show_gallery(graph, (3, 5); locs=locations, vertex_configs=maximal_configs)
 
 # 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))
@@ -90,13 +84,7 @@ cliques = maximal_cliques(complement(graph))
 # It is the [`ConfigsMin`](@ref) property in the program.
 minimum_maximal_configs = solve(problem, ConfigsMin())[].c
 
-imgs2 = ntuple(k->show_graph(graph;
-                locs=locations, scale=0.25,
-                vertex_colors=[iszero(minimum_maximal_configs[k][i]) ? "white" : "red"
-                for i=1:nv(graph)]), length(minimum_maximal_configs));
-
-Compose.set_default_graphic_size(15cm, 12cm); Compose.compose(context(),
-     ntuple(k->(context((mod1(k,4)-1)/4, ((k-1)÷5)/3, 1.2/4, 1.0/3), imgs2[k]), 10)...)
+show_gallery(graph, (2, 5); locs=locations, vertex_configs=minimum_maximal_configs)
 
 # Similarly, if one is only interested in computing one of the minimum sets,
 # one can use the graph property [`SingleConfigMin`](@ref).

examples/weighted.jl

@@ -33,17 +33,6 @@ max5_configs = solve(problem, SingleConfigMax(5))[]
 # The return value also has type [`ExtendedTropical`](@ref), but this time the element type of `orders` has been changed to [`CountingTropical`](@ref)`{Float64,`[`ConfigSampler`](@ref)`}`.
 max5_configs.orders
 
-# Let us visually check these graphs
-using Compose
-
-imgs_max5 = ntuple(k->show_graph(graph;
-                    locs=locations, scale=0.25,
-                    vertex_colors=[iszero(max5_configs.orders[k].c.data[i]) ? "white" : "red"
-                    for i=1:nv(graph)]), 5);
-
-Compose.set_default_graphic_size(18cm, 4cm)
-
-Compose.compose(context(),
-     ntuple(k->(context((k-1)/5, 0.0, 1.2/5, 1.0), imgs_max5[k]), 5)...)
-
+# Let us visually check these configurations
+show_gallery(graph, (1, 5); locs=locations, vertex_configs=[max5_configs.orders[k].c.data for k=1:5])