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Add a default value for postprocessing #218

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Merged
gdalle merged 4 commits into from
Mar 31, 2025
Merged

Add a default value for postprocessing #218

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19a768a
Add a default value for postprocessing
amontoison Mar 31, 2025
24216a2
Update coloring.jl
amontoison Mar 31, 2025
76efa64
Find a better solution for Guillaume
amontoison Mar 31, 2025
97c602c
suitesparse.jl
amontoison Mar 31, 2025
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8 changes: 4 additions & 4 deletions src/coloring.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -54,7 +54,7 @@ function partial_distance2_coloring!(
end

"""
star_coloring(g::AdjacencyGraph, order::AbstractOrder; postprocessing::Bool)
star_coloring(g::AdjacencyGraph, order::AbstractOrder, postprocessing::Bool)

Compute a star coloring of all vertices in the adjacency graph `g` and return a tuple `(color, star_set)`, where

Expand All @@ -76,7 +76,7 @@ If `postprocessing=true`, some colors might be replaced with `0` (the "neutral"

> [_New Acyclic and Star Coloring Algorithms with Application to Computing Hessians_](https://epubs.siam.org/doi/abs/10.1137/050639879), Gebremedhin et al. (2007), Algorithm 4.1
"""
function star_coloring(g::AdjacencyGraph, order::AbstractOrder; postprocessing::Bool)
function star_coloring(g::AdjacencyGraph, order::AbstractOrder, postprocessing::Bool)
# Initialize data structures
nv = nb_vertices(g)
ne = nb_edges(g)
Expand Down Expand Up @@ -272,7 +272,7 @@ function symmetric_coefficient(
end

"""
acyclic_coloring(g::AdjacencyGraph, order::AbstractOrder; postprocessing::Bool)
acyclic_coloring(g::AdjacencyGraph, order::AbstractOrder, postprocessing::Bool)

Compute an acyclic coloring of all vertices in the adjacency graph `g` and return a tuple `(color, tree_set)`, where

Expand All @@ -294,7 +294,7 @@ If `postprocessing=true`, some colors might be replaced with `0` (the "neutral"

> [_New Acyclic and Star Coloring Algorithms with Application to Computing Hessians_](https://epubs.siam.org/doi/abs/10.1137/050639879), Gebremedhin et al. (2007), Algorithm 3.1
"""
function acyclic_coloring(g::AdjacencyGraph, order::AbstractOrder; postprocessing::Bool)
function acyclic_coloring(g::AdjacencyGraph, order::AbstractOrder, postprocessing::Bool)
# Initialize data structures
nv = nb_vertices(g)
ne = nb_edges(g)
Expand Down
8 changes: 4 additions & 4 deletions src/interface.jl
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Expand Up @@ -266,7 +266,7 @@ function _coloring(
symmetric_pattern::Bool,
)
ag = AdjacencyGraph(A)
color, star_set = star_coloring(ag, algo.order; postprocessing=algo.postprocessing)
color, star_set = star_coloring(ag, algo.order, algo.postprocessing)
if speed_setting isa WithResult
return StarSetColoringResult(A, ag, color, star_set)
else
Expand All @@ -283,7 +283,7 @@ function _coloring(
symmetric_pattern::Bool,
) where {R}
ag = AdjacencyGraph(A)
color, tree_set = acyclic_coloring(ag, algo.order; postprocessing=algo.postprocessing)
color, tree_set = acyclic_coloring(ag, algo.order, algo.postprocessing)
if speed_setting isa WithResult
return TreeSetColoringResult(A, ag, color, tree_set, R)
else
Expand All @@ -301,7 +301,7 @@ function _coloring(
) where {R}
A_and_Aᵀ = bidirectional_pattern(A; symmetric_pattern)
ag = AdjacencyGraph(A_and_Aᵀ; has_diagonal=false)
color, star_set = star_coloring(ag, algo.order; postprocessing=algo.postprocessing)
color, star_set = star_coloring(ag, algo.order, algo.postprocessing)
if speed_setting isa WithResult
symmetric_result = StarSetColoringResult(A_and_Aᵀ, ag, color, star_set)
return BicoloringResult(A, ag, symmetric_result, R)
Expand All @@ -321,7 +321,7 @@ function _coloring(
) where {R}
A_and_Aᵀ = bidirectional_pattern(A; symmetric_pattern)
ag = AdjacencyGraph(A_and_Aᵀ; has_diagonal=false)
color, tree_set = acyclic_coloring(ag, algo.order; postprocessing=algo.postprocessing)
color, tree_set = acyclic_coloring(ag, algo.order, algo.postprocessing)
if speed_setting isa WithResult
symmetric_result = TreeSetColoringResult(A_and_Aᵀ, ag, color, tree_set, R)
return BicoloringResult(A, ag, symmetric_result, R)
Expand Down
3 changes: 2 additions & 1 deletion test/suitesparse.jl
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Expand Up @@ -95,7 +95,8 @@ what_table_41_42 = CSV.read(
@test nb_edges(ag) == row[:E]
@test maximum_degree(ag) == row[:Δ]
@test minimum_degree(ag) == row[:δ]
color_N, _ = star_coloring(ag, NaturalOrder(); postprocessing=false)
postprocessing = false
color_N, _ = star_coloring(ag, NaturalOrder(), postprocessing)
@test_skip row[:KS1] <= length(unique(color_N)) <= row[:KS2] # TODO: find better
yield()
end
Expand Down