Add precompilation workload (#252)

* Add precompilation workload

* Simplest matrix

* Bool

Author: gdalle

Project.toml

@@ -1,12 +1,13 @@
 name = "SparseMatrixColorings"
 uuid = "0a514795-09f3-496d-8182-132a7b665d35"
 authors = ["Guillaume Dalle", "Alexis Montoison"]
-version = "0.4.19"
+version = "0.4.20"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+PrecompileTools = "aea7be01-6a6a-4083-8856-8a6e6704d82a"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 
@@ -24,6 +25,7 @@ CliqueTrees = "1"
 Colors = "0.12.11, 0.13"
 DocStringExtensions = "0.8,0.9"
 LinearAlgebra = "<0.0.1, 1"
+PrecompileTools = "1.2.1"
 Random = "<0.0.1, 1"
 SparseArrays = "<0.0.1, 1"
 julia = "1.10"

src/SparseMatrixColorings.jl

@@ -27,6 +27,7 @@ using LinearAlgebra:
     ldiv!,
     parent,
     transpose
+using PrecompileTools: @compile_workload
 using Random: Random, AbstractRNG, default_rng, randperm
 using SparseArrays:
     SparseArrays,
@@ -39,6 +40,7 @@ using SparseArrays:
     nzrange,
     rowvals,
     sparse,
+    sprand,
     spzeros
 
 include("graph.jl")
@@ -55,6 +57,8 @@ include("check.jl")
 include("examples.jl")
 include("show_colors.jl")
 
+include("precompile.jl")
+
 export NaturalOrder, RandomOrder, LargestFirst
 export DynamicDegreeBasedOrder, SmallestLast, IncidenceDegree, DynamicLargestFirst
 export PerfectEliminationOrder

src/precompile.jl

@@ -0,0 +1,20 @@
+for (structure, partition, decompression) in [
+    (:nonsymmetric, :column, :direct),
+    (:nonsymmetric, :row, :direct),
+    (:symmetric, :column, :direct),
+    (:symmetric, :column, :substitution),
+    (:nonsymmetric, :bidirectional, :direct),
+    (:nonsymmetric, :bidirectional, :substitution),
+]
+    A = sparse(Bool[1 0; 0 1])
+    problem = ColoringProblem(; structure, partition)
+    algo = GreedyColoringAlgorithm(; decompression, postprocessing=true)
+    result = coloring(A, problem, algo)
+    if partition == :bidirectional
+        Br, Bc = compress(A, result)
+        decompress(Br, Bc, result)
+    else
+        B = compress(A, result)
+        decompress(B, result)
+    end
+end