Use symmetric_coefficient from SMC

JuliaSmoothOptimizers · Jul 18, 2024 · e1921d6 · e1921d6
1 parent 570798e
commit e1921d6
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Showing 3 changed files with 5 additions and 19 deletions.
diff --git a/Project.toml b/Project.toml
@@ -20,5 +20,5 @@ NLPModels = "0.18, 0.19, 0.20, 0.21"
 Requires = "1"
 ReverseDiff = "1"
 SparseConnectivityTracer = "0.5"
-SparseMatrixColorings = "0.3.4"
+SparseMatrixColorings = "0.3.5"
 julia = "^1.6"
diff --git a/src/ADNLPModels.jl b/src/ADNLPModels.jl
@@ -6,7 +6,8 @@ using LinearAlgebra, SparseArrays
 # external
 using ADTypes: ADTypes, AbstractColoringAlgorithm, AbstractSparsityDetector
 using SparseConnectivityTracer: TracerSparsityDetector
-using SparseMatrixColorings: GreedyColoringAlgorithm, symmetric_coloring_detailed
+using SparseMatrixColorings:
+  GreedyColoringAlgorithm, symmetric_coloring_detailed, symmetric_coefficient
 using ForwardDiff, ReverseDiff
 
 # JSO

diff --git a/src/sparsity_pattern.jl b/src/sparsity_pattern.jl
@@ -73,28 +73,13 @@ function nnz_colors(trilH, star_set, colors, ncolors)
   # Because we exploit the symmetry, we also need to store the row index for a given coefficient
   # in the "compressed column".
   dcolors = Dict(i => Tuple{Int,Int}[] for i=1:ncolors)
-  star = star_set.star
-  hub = star_set.hub
 
   n = LinearAlgebra.checksquare(trilH)
   for j in 1:n
     for k in trilH.colptr[j]:trilH.colptr[j+1]-1
       i = trilH.rowval[k]
-
-      if i == j
-        h = i
-      else
-        star_id = star[(j, i)]
-        h = hub[star_id]
-      end
-
-      # pick arbitrary hub
-      (h == 0) && (h = i)
-      c = colors[h]
-      # i is the spoke
-      (h == j) && push!(dcolors[c], (i,k))
-      # j is the spoke
-      (h == i) && push!(dcolors[c], (j,k))
+      l, c = symmetric_coefficient(i, j, color, star_set)
+      push!(dcolors[c], (l, k))
     end
   end