🤖 Format .jl files

JuliaSmoothOptimizers · Jun 5, 2024 · 29b1d2d · 29b1d2d
1 parent ed9756e
commit 29b1d2d
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Showing 5 changed files with 24 additions and 11 deletions.
diff --git a/src/sparse_hessian.jl b/src/sparse_hessian.jl
@@ -25,7 +25,7 @@ function SparseADHessian(
   kwargs...,
 ) where {S}
   T = eltype(S)
-  H = compute_hessian_sparsity(f, nvar, c!, ncon, detector=detector)
+  H = compute_hessian_sparsity(f, nvar, c!, ncon, detector = detector)
 
   colors = sparse_matrix_colors(H, alg)
   ncolors = maximum(colors)
@@ -96,7 +96,7 @@ function SparseReverseADHessian(
   detector::AbstractSparsityDetector = TracerSparsityDetector(),
   kwargs...,
 ) where {T}
-  H = compute_hessian_sparsity(f, nvar, c!, ncon, detector=detector)
+  H = compute_hessian_sparsity(f, nvar, c!, ncon, detector = detector)
 
   colors = sparse_matrix_colors(H, alg)
   ncolors = maximum(colors)

diff --git a/src/sparse_jacobian.jl b/src/sparse_jacobian.jl
@@ -20,7 +20,7 @@ function SparseADJacobian(
   kwargs...,
 ) where {T}
   output = similar(x0, ncon)
-  J = compute_jacobian_sparsity(c!, output, x0, detector=detector)
+  J = compute_jacobian_sparsity(c!, output, x0, detector = detector)
 
   colors = sparse_matrix_colors(J, alg)
   ncolors = maximum(colors)

diff --git a/src/sparsity_pattern.jl b/src/sparsity_pattern.jl
@@ -6,12 +6,21 @@ Return a sparse boolean matrix that represents the adjacency matrix of the Jacob
 """
 function compute_jacobian_sparsity end
 
-function compute_jacobian_sparsity(c, x0; detector::AbstractSparsityDetector=TracerSparsityDetector())
+function compute_jacobian_sparsity(
+  c,
+  x0;
+  detector::AbstractSparsityDetector = TracerSparsityDetector(),
+)
   S = ADTypes.jacobian_sparsity(c, x0, detector)
   return S
 end
 
-function compute_jacobian_sparsity(c!, cx, x0; detector::AbstractSparsityDetector=TracerSparsityDetector())
+function compute_jacobian_sparsity(
+  c!,
+  cx,
+  x0;
+  detector::AbstractSparsityDetector = TracerSparsityDetector(),
+)
   S = ADTypes.jacobian_sparsity(c!, cx, x0, detector)
   return S
 end
@@ -21,7 +30,13 @@ end
 
 Return a sparse boolean matrix that represents the adjacency matrix of the Hessian of f(x) + λᵀc(x).
 """
-function compute_hessian_sparsity(f, nvar, c!, ncon; detector::AbstractSparsityDetector=TracerSparsityDetector())
+function compute_hessian_sparsity(
+  f,
+  nvar,
+  c!,
+  ncon;
+  detector::AbstractSparsityDetector = TracerSparsityDetector(),
+)
   function lagrangian(x)
     if ncon == 0
       return f(x)

diff --git a/test/runtests.jl b/test/runtests.jl
@@ -4,7 +4,7 @@ using ADNLPModels:
   gradient, gradient!, jacobian, hessian, Jprod!, Jtprod!, directional_second_derivative, Hvprod!
 
 @testset "Test sparsity pattern of Jacobian and Hessian" begin
-  f(x) = sum(x.^2)
+  f(x) = sum(x .^ 2)
   c(x) = x
   c!(cx, x) = copyto!(cx, x)
   nvar, ncon = 2, 2

diff --git a/test/sparse_hessian.jl b/test/sparse_hessian.jl
@@ -1,7 +1,5 @@
-list_sparse_hess_backend = (
-  (ADNLPModels.SparseADHessian, Dict()),
-  (ADNLPModels.ForwardDiffADHessian, Dict()),
-)
+list_sparse_hess_backend =
+  ((ADNLPModels.SparseADHessian, Dict()), (ADNLPModels.ForwardDiffADHessian, Dict()))
 
 dt = (Float32, Float64)