🤖 Format .jl files (#109)

Co-authored-by: tmigot <tmigot@users.noreply.github.com>
JuliaSmoothOptimizers · Jan 26, 2024 · 8e130b7 · 8e130b7
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Showing 5 changed files with 43 additions and 21 deletions.
diff --git a/src/SolveModel/SolveModelKARC.jl b/src/SolveModel/SolveModelKARC.jl
@@ -1,4 +1,12 @@
-function solve_model!(X::PDataKARC{S, T, Fatol, Frtol}, H, g, gNorm2, calls, max_calls, α::T) where {S, T, Fatol, Frtol}
+function solve_model!(
+  X::PDataKARC{S, T, Fatol, Frtol},
+  H,
+  g,
+  gNorm2,
+  calls,
+  max_calls,
+  α::T,
+) where {S, T, Fatol, Frtol}
   # target value should be close to satisfy αλ=||d||
   start = findfirst(X.positives)
   if isnothing(start)

diff --git a/src/SolveModel/SolveModelNLSST_TR.jl b/src/SolveModel/SolveModelNLSST_TR.jl
@@ -1,4 +1,12 @@
-function solve_model!(PData::PDataNLSST{S, T, Fatol, Frtol}, Jx, Fx, norm_∇f, calls, max_calls, δ::T) where {S, T, Fatol, Frtol}
+function solve_model!(
+  PData::PDataNLSST{S, T, Fatol, Frtol},
+  Jx,
+  Fx,
+  norm_∇f,
+  calls,
+  max_calls,
+  δ::T,
+) where {S, T, Fatol, Frtol}
   # cas particulier Steihaug-Toint
   # ϵ = sqrt(eps(T)) # * 100.0 # old
   # cgtol = max(ϵ, min(cgtol, 9 * cgtol / 10, 0.01 * norm(g)^(1.0 + PData.ζ))) # old

diff --git a/src/SolveModel/SolveModelST_TR.jl b/src/SolveModel/SolveModelST_TR.jl
@@ -1,4 +1,12 @@
-function solve_model!(PData::PDataST{S, T, Fatol, Frtol}, H, g, gNorm2, calls, max_calls, δ::T) where {S, T, Fatol, Frtol}
+function solve_model!(
+  PData::PDataST{S, T, Fatol, Frtol},
+  H,
+  g,
+  gNorm2,
+  calls,
+  max_calls,
+  δ::T,
+) where {S, T, Fatol, Frtol}
   # cas particulier Steihaug-Toint
   # ϵ = sqrt(eps(T)) # * 100.0 # old
   # cgtol = max(ϵ, min(cgtol, 9 * cgtol / 10, 0.01 * norm(g)^(1.0 + PData.ζ))) # old

diff --git a/src/SolveModel/SolveModelTRK.jl b/src/SolveModel/SolveModelTRK.jl
@@ -1,4 +1,12 @@
-function solve_model!(X::PDataTRK{S, T, Fatol, Frtol}, H, g, gNorm2, calls, max_calls, α::T) where {S, T, Fatol, Frtol}
+function solve_model!(
+  X::PDataTRK{S, T, Fatol, Frtol},
+  H,
+  g,
+  gNorm2,
+  calls,
+  max_calls,
+  α::T,
+) where {S, T, Fatol, Frtol}
   # target value should be close to satisfy α=||d||
   start = findfirst(X.positives)
   if isnothing(start)

diff --git a/src/solvers.jl b/src/solvers.jl
@@ -1,12 +1,8 @@
 const solvers_const = Dict(
-  :ARCqKdense =>
-    (HessDense, PDataKARC, [(:shifts => 10.0 .^ (collect(-20.0:1.0:20.0)))]),
-  :ARCqKOp =>
-    (HessOp, PDataKARC, [:shifts => 10.0 .^ (collect(-20.0:1.0:20.0))]),
-  :ARCqKsparse =>
-    (HessSparse, PDataKARC, [:shifts => 10.0 .^ (collect(-20.0:1.0:20.0))]),
-  :ARCqKCOO =>
-    (HessSparseCOO, PDataKARC, [:shifts => 10.0 .^ (collect(-20.0:1.0:20.0))]),
+  :ARCqKdense => (HessDense, PDataKARC, [(:shifts => 10.0 .^ (collect(-20.0:1.0:20.0)))]),
+  :ARCqKOp => (HessOp, PDataKARC, [:shifts => 10.0 .^ (collect(-20.0:1.0:20.0))]),
+  :ARCqKsparse => (HessSparse, PDataKARC, [:shifts => 10.0 .^ (collect(-20.0:1.0:20.0))]),
+  :ARCqKCOO => (HessSparseCOO, PDataKARC, [:shifts => 10.0 .^ (collect(-20.0:1.0:20.0))]),
   :ST_TRdense => (HessDense, PDataST, ()),
   :ST_TROp => (HessOp, PDataST, ()),
   :ST_TRsparse => (HessSparse, PDataST, ()),
@@ -16,15 +12,9 @@ const solvers_const = Dict(
 )
 
 const solvers_nls_const = Dict(
-  :ARCqKOpGN => (
-    HessGaussNewtonOp,
-    PDataKARC,
-    [:shifts => 10.0 .^ (collect(-10.0:0.5:20.0))],
-  ),
+  :ARCqKOpGN => (HessGaussNewtonOp, PDataKARC, [:shifts => 10.0 .^ (collect(-10.0:0.5:20.0))]),
   :ST_TROpGN => (HessGaussNewtonOp, PDataST, ()),
-  :ST_TROpGNLSCgls =>
-    (HessGaussNewtonOp, PDataNLSST, [:solver_method => :cgls]),
-  :ST_TROpGNLSLsqr =>
-    (HessGaussNewtonOp, PDataNLSST, [:solver_method => :lsqr]),
+  :ST_TROpGNLSCgls => (HessGaussNewtonOp, PDataNLSST, [:solver_method => :cgls]),
+  :ST_TROpGNLSLsqr => (HessGaussNewtonOp, PDataNLSST, [:solver_method => :lsqr]),
   :ST_TROpLS => (HessOp, PDataNLSST, ()),
 )