Merge pull request #105 from sisl/moss/GraphPlot

TeX-free rendering, fallback to GraphPlot if LuaLaTeX fails #53

Author: mossr

Project.toml

@@ -8,6 +8,7 @@ DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
 Discretizers = "6e83dbb3-75ca-525b-8ae2-3751f0dd50b4"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
+GraphPlot = "a2cc645c-3eea-5389-862e-a155d0052231"
 IterTools = "c8e1da08-722c-5040-9ed9-7db0dc04731e"
 LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d"
 LightXML = "9c8b4983-aa76-5018-a973-4c85ecc9e179"
@@ -16,27 +17,28 @@ Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
+Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
-TikzGraphs = "b4f28e30-c73f-5eaf-a395-8a9db949a742"
 
 [compat]
 DataFrames = "0.21"
 DataStructures = "0.11,0.12,0.13,0.14,0.15,0.16,0.17"
 Discretizers = "3.0"
 Distributions = "0.17,0.18,0.19,0.20,0.21,0.22,0.23"
+GraphPlot = "0.4,0.4.1"
 IterTools = "1.3"
 LightGraphs = "1.0"
 LightXML = "0.8,0.9"
 NBInclude = "2.0"
 Parameters = "0.10,0.11,0.12"
 RDatasets = "0.5,0.6"
 Reexport = "0.2"
-SpecialFunctions = "0.8,0.9,0.10"
+Requires = "1.0.1"
+SpecialFunctions = "0.8,0.10"
 StatsBase = "0.25,0.26,0.27,0.28,0.29,0.30,0.31,0.32,0.33"
-TikzGraphs = "1.1"
 julia = "1"
 
 [extras]
@@ -46,6 +48,7 @@ RDatasets = "ce6b1742-4840-55fa-b093-852dadbb1d8b"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+TikzGraphs = "b4f28e30-c73f-5eaf-a395-8a9db949a742"
 
 [targets]
-test = ["Statistics", "NBInclude", "LinearAlgebra", "Test", "RDatasets", "Random"]
+test = ["Statistics", "NBInclude", "LinearAlgebra", "Test", "RDatasets", "Random", "TikzGraphs"]

doc/BayesNets.ipynb

@@ -30,7 +30,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Visualization of network structure is provided by the TikzGraphs package. Installation requirements (e.g., PGF/Tikz and pdf2svg) are provided [here](http://nbviewer.ipython.org/github/sisl/TikzGraphs.jl/blob/master/doc/TikzGraphs.ipynb)."
+    "Default visualization of the network structure is provided by the GraphPlot package. However, we recommend using tex-formatted graphs provided by the TikzGraphs package. Installation requirements for TikzGraphs (e.g., PGF/Tikz and pdf2svg) are provided [here](http://nbviewer.ipython.org/github/sisl/TikzGraphs.jl/blob/master/doc/TikzGraphs.ipynb). Simply run `using TikzGraphs` in your Julia session to automatically switch to tex-formatted graphs (thanks to the Requires.jl package)."
    ]
   },
   {
@@ -48,7 +48,8 @@
    "source": [
     "using Random\n",
     "Random.seed!(0) # seed the random number generator to 0, for a reproducible demonstration\n",
-    "using BayesNets"
+    "using BayesNets\n",
+    "using TikzGraphs # required to plot tex-formatted graphs (recommended), otherwise GraphPlot.jl is used"
    ]
   },
   {

src/BayesNets.jl

@@ -9,6 +9,7 @@ using IterTools
 using Dates
 using SpecialFunctions
 using SparseArrays
+using Requires
 
 include(joinpath("CPDs", "cpds.jl"))
 @reexport using BayesNets.CPDs
@@ -18,7 +19,7 @@ import Base: *, /, +, -
 import DataStructures: PriorityQueue, peek
 import BayesNets.CPDs.ProbabilisticGraphicalModels: markov_blanket, is_independent, infer
 import StatsBase: sample, Weights
-import TikzGraphs: plot
+import GraphPlot: gplot
 import LightGraphs: DiGraph, add_edge!, rem_edge!,
        add_vertex!, rem_vertex!, has_edge,
        edges, topological_sort_by_dfs, inneighbors,

src/io.jl

@@ -1,16 +1,35 @@
 #
 # Bayes Net
 #
-Base.showable(::MIME"image/svg+xml", bn::BayesNet) = success(`lualatex -v`)
+lualatex_available() = try success(`lualatex -v`) catch; false end
+Base.showable(::MIME"image/svg+xml", bn::BayesNet) = true
+
+
+plot(dag::DAG, nodelabel) = gplot(dag, nodelabel=nodelabel) # GraphPlot (default)
+
+# called at runtime (replaces plot with TikzGraphs, if loaded)
+function __init__()
+	@require TikzGraphs="b4f28e30-c73f-5eaf-a395-8a9db949a742" begin
+		if lualatex_available()
+			plot(dag::DAG, nodelabel) = TikzGraphs.plot(dag, nodelabel)
+		end
+	end
+end
+
 
 function plot(bn::BayesNet)
 	if !isempty(names(bn))
-		plot(bn.dag, AbstractString[string(s) for s in names(bn)]) # NOTE: sometimes the same var shows up twice
+		dag = bn.dag
+		nodelabel = AbstractString[string(s) for s in names(bn)] # NOTE: sometimes the same var shows up twice
 	else
-		plot(DiGraph(1), ["Empty Graph"])
+		dag = DiGraph(1)
+		nodelabel = ["Empty Graph"]
 	end
+
+	plot(dag, nodelabel)
 end
 
+
 function Base.show(f::IO, a::MIME"image/svg+xml", bn::BayesNet)
  	show(f, a, plot(bn))
 end