🤖 Format .jl files (#316)

Co-authored-by: tmigot <[email protected]>
JuliaSmoothOptimizers · Oct 25, 2023 · c72caaf · c72caaf
1 parent e66bd7e
commit c72caaf
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Showing 59 changed files with 112 additions and 672 deletions.
diff --git a/src/ADNLPProblems/arglina.jl b/src/ADNLPProblems/arglina.jl
@@ -5,12 +5,7 @@ function arglina(; use_nls::Bool = false, kwargs...)
   return arglina(Val(model); kwargs...)
 end
 
-function arglina(
-  ::Val{:nlp};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function arglina(::Val{:nlp}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   function f(x; n = length(x))
     m = 2 * n
     sj = sum(x[j] for j = 1:n)
@@ -21,12 +16,7 @@ function arglina(
   return ADNLPModels.ADNLPModel(f, x0, name = "arglina"; kwargs...)
 end
 
-function arglina(
-  ::Val{:nls};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function arglina(::Val{:nls}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   function F!(r, x)
     m = 2 * n
     sj = sum(x[j] for j = 1:n)

diff --git a/src/ADNLPProblems/arglinb.jl b/src/ADNLPProblems/arglinb.jl
@@ -5,12 +5,7 @@ function arglinb(; use_nls::Bool = false, kwargs...)
   return arglinb(Val(model); kwargs...)
 end
 
-function arglinb(
-  ::Val{:nlp};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function arglinb(::Val{:nlp}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   function f(x; n = length(x))
     m = 2 * n
     sj = sum(j * x[j] for j = 1:n)
@@ -20,12 +15,7 @@ function arglinb(
   return ADNLPModels.ADNLPModel(f, x0, name = "arglinb"; kwargs...)
 end
 
-function arglinb(
-  ::Val{:nls};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function arglinb(::Val{:nls}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   function F!(r, x; n = length(x))
     m = 2 * n
     sj = sum(j * x[j] for j = 1:n)

diff --git a/src/ADNLPProblems/bdqrtic.jl b/src/ADNLPProblems/bdqrtic.jl
@@ -5,12 +5,7 @@ function bdqrtic(; use_nls::Bool = false, kwargs...)
   return bdqrtic(Val(model); kwargs...)
 end
 
-function bdqrtic(
-  ::Val{:nlp};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function bdqrtic(::Val{:nlp}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   n < 5 && @warn("bdqrtic: number of variables must be ≥ 5")
   n = max(5, n)
   function f(x; n = length(x))
@@ -23,12 +18,7 @@ function bdqrtic(
   return ADNLPModels.ADNLPModel(f, x0, name = "bdqrtic"; kwargs...)
 end
 
-function bdqrtic(
-  ::Val{:nls};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function bdqrtic(::Val{:nls}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   n < 5 && @warn("bdqrtic: number of variables must be ≥ 5")
   n = max(5, n)
   function F!(r, x; n = length(x))

diff --git a/src/ADNLPProblems/bennett5.jl b/src/ADNLPProblems/bennett5.jl
@@ -5,12 +5,7 @@ function bennett5(; use_nls::Bool = false, kwargs...)
   return bennett5(Val(model); kwargs...)
 end
 
-function bennett5(
-  ::Val{:nlp};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function bennett5(::Val{:nlp}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   y = Rational{Int}[
     -34.834702E0 7.447168E0
     -34.393200E0 8.102586E0
@@ -175,12 +170,7 @@ function bennett5(
   return ADNLPModels.ADNLPModel(f, x0, name = "bennett5"; kwargs...)
 end
 
-function bennett5(
-  ::Val{:nls};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function bennett5(::Val{:nls}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   y = Rational{Int}[
     -34.834702E0 7.447168E0
     -34.393200E0 8.102586E0

diff --git a/src/ADNLPProblems/biggs5.jl b/src/ADNLPProblems/biggs5.jl
@@ -1,11 +1,6 @@
 export biggs5
 
-function biggs5(;
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  m::Int = 13,
-  kwargs...,
-) where {T}
+function biggs5(; n::Int = default_nvar, type::Type{T} = Float64, m::Int = 13, kwargs...) where {T}
   m = max(6, m)
   z = [i // 10 for i = 1:m]
   y = T[exp(-zi) - 5 * exp(-10 * zi) + 3 * exp(-4 * zi) for zi in z]

diff --git a/src/ADNLPProblems/biggs6.jl b/src/ADNLPProblems/biggs6.jl
@@ -1,11 +1,6 @@
 export biggs6
 
-function biggs6(;
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  m::Int = 13,
-  kwargs...,
-) where {T}
+function biggs6(; n::Int = default_nvar, type::Type{T} = Float64, m::Int = 13, kwargs...) where {T}
   m = max(6, m)
   z = [i // 10 for i = 1:m]
   y = T[exp(-zi) - 5 * exp(-10 * zi) + 3 * exp(-4 * zi) for zi in z]

diff --git a/src/ADNLPProblems/boxbod.jl b/src/ADNLPProblems/boxbod.jl
@@ -5,12 +5,7 @@ function boxbod(; use_nls::Bool = false, kwargs...)
   return boxbod(Val(model); kwargs...)
 end
 
-function boxbod(
-  ::Val{:nlp};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function boxbod(::Val{:nlp}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   y = Rational{Int}[
     109 1
     149 2
@@ -27,12 +22,7 @@ function boxbod(
   return ADNLPModels.ADNLPModel(f, x0, name = "boxbod"; kwargs...)
 end
 
-function boxbod(
-  ::Val{:nls};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function boxbod(::Val{:nls}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   y = Rational{Int}[
     109 1
     149 2

diff --git a/src/ADNLPProblems/brownal.jl b/src/ADNLPProblems/brownal.jl
@@ -5,12 +5,7 @@ function brownal(; use_nls::Bool = false, kwargs...)
   return brownal(Val(model); kwargs...)
 end
 
-function brownal(
-  ::Val{:nlp};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function brownal(::Val{:nlp}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   function f(x; n = length(x))
     sj = sum(x[j] for j = 1:n)
     pj = prod(x[j] for j = 1:n)
@@ -20,12 +15,7 @@ function brownal(
   return ADNLPModels.ADNLPModel(f, x0, name = "brownal"; kwargs...)
 end
 
-function brownal(
-  ::Val{:nls};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function brownal(::Val{:nls}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   function F!(r, x; n = length(x))
     sj = sum(x[j] for j = 1:n)
     for i = 1:(n - 1)

diff --git a/src/ADNLPProblems/brownbs.jl b/src/ADNLPProblems/brownbs.jl
@@ -5,12 +5,7 @@ function brownbs(; use_nls::Bool = false, kwargs...)
   return brownbs(Val(model); kwargs...)
 end
 
-function brownbs(
-  ::Val{:nlp};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function brownbs(::Val{:nlp}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   function f(x)
     return 1 // 2 * (x[1] - 1000000)^2 +
            1 // 2 * (x[2] - 2 * 1 // 1000000)^2 +
@@ -20,12 +15,7 @@ function brownbs(
   return ADNLPModels.ADNLPModel(f, x0, name = "brownbs"; kwargs...)
 end
 
-function brownbs(
-  ::Val{:nls};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function brownbs(::Val{:nls}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   function F!(r, x)
     r[1] = x[1] - 1000000
     r[2] = x[2] - 2 * 1 // 1000000

diff --git a/src/ADNLPProblems/brownden.jl b/src/ADNLPProblems/brownden.jl
@@ -5,12 +5,7 @@ function brownden(; use_nls::Bool = false, kwargs...)
   return brownden(Val(model); kwargs...)
 end
 
-function brownden(
-  ::Val{:nlp};
-  m::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function brownden(::Val{:nlp}; m::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   m < 4 && @warn("brownden: must have m ≥ 4")
   m = max(m, 4)
   x0 = T[25.0; 5.0; -5.0; -1.0]
@@ -27,12 +22,7 @@ function brownden(
   return ADNLPModels.ADNLPModel(f, x0, name = "brownden"; kwargs...)
 end
 
-function brownden(
-  ::Val{:nls};
-  m::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function brownden(::Val{:nls}; m::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   m < 4 && @warn("brownden: must have m ≥ 4")
   m = max(m, 4)
   x0 = T[25.0; 5.0; -5.0; -1.0]

diff --git a/src/ADNLPProblems/broyden3d.jl b/src/ADNLPProblems/broyden3d.jl
@@ -5,12 +5,7 @@ function broyden3d(; use_nls::Bool = false, kwargs...)
   return broyden3d(Val(model); kwargs...)
 end
 
-function broyden3d(
-  ::Val{:nlp};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function broyden3d(::Val{:nlp}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   function f(x; n = length(x))
     return 1 // 2 * sum(((3 - 2 * x[i]) * x[i] - x[i - 1] - 2 * x[i + 1] + 1)^2 for i = 2:(n - 1)) +
            1 // 2 * ((3 - 2 * x[1]) * x[1] - 2 * x[2] + 1)^2 +
@@ -20,12 +15,7 @@ function broyden3d(
   return ADNLPModels.ADNLPModel(f, x0, name = "broyden3d"; kwargs...)
 end
 
-function broyden3d(
-  ::Val{:nls};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function broyden3d(::Val{:nls}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   function F!(r, x; n = length(x))
     r[1] = (3 - 2 * x[1]) * x[1] - 2 * x[2] + 1
     r[n] = (3 - 2 * x[n]) * x[n] - x[n - 1] + 1

diff --git a/src/ADNLPProblems/brybnd.jl b/src/ADNLPProblems/brybnd.jl
@@ -5,12 +5,7 @@ function brybnd(; use_nls::Bool = false, kwargs...)
   return brybnd(Val(model); kwargs...)
 end
 
-function brybnd(
-  ::Val{:nlp};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function brybnd(::Val{:nlp}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   function f(x; n = length(x))
     ml = 5
     mu = 1
@@ -25,12 +20,7 @@ function brybnd(
   return ADNLPModels.ADNLPModel(f, x0, name = "brybnd"; kwargs...)
 end
 
-function brybnd(
-  ::Val{:nls};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function brybnd(::Val{:nls}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   function F!(r, x; n = length(x))
     ml = 5
     mu = 1

diff --git a/src/ADNLPProblems/chwirut1.jl b/src/ADNLPProblems/chwirut1.jl
@@ -5,12 +5,7 @@ function chwirut1(; use_nls::Bool = false, kwargs...)
   return chwirut1(Val(model); kwargs...)
 end
 
-function chwirut1(
-  ::Val{:nlp};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function chwirut1(::Val{:nlp}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   y = Rational{Int}[
     92.9000E0 0.5000E0
     78.7000E0 0.6250E0
@@ -235,12 +230,7 @@ function chwirut1(
   return ADNLPModels.ADNLPModel(f, x0, name = "chwirut1"; kwargs...)
 end
 
-function chwirut1(
-  ::Val{:nls};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function chwirut1(::Val{:nls}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   y = Rational{Int}[
     92.9000E0 0.5000E0
     78.7000E0 0.6250E0

diff --git a/src/ADNLPProblems/chwirut2.jl b/src/ADNLPProblems/chwirut2.jl
@@ -5,12 +5,7 @@ function chwirut2(; use_nls::Bool = false, kwargs...)
   return chwirut2(Val(model); kwargs...)
 end
 
-function chwirut2(
-  ::Val{:nlp};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function chwirut2(::Val{:nlp}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   y = Rational{Int}[
     92.9000E0 0.500E0
     57.1000E0 1.000E0
@@ -75,12 +70,7 @@ function chwirut2(
   return ADNLPModels.ADNLPModel(f, x0, name = "chwirut2"; kwargs...)
 end
 
-function chwirut2(
-  ::Val{:nls};
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  kwargs...,
-) where {T}
+function chwirut2(::Val{:nls}; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) where {T}
   y = Rational{Int}[
     92.9000E0 0.500E0
     57.1000E0 1.000E0

diff --git a/src/ADNLPProblems/curly.jl b/src/ADNLPProblems/curly.jl
@@ -1,11 +1,6 @@
 export curly
 
-function curly(;
-  n::Int = default_nvar,
-  type::Type{T} = Float64,
-  b::Int = 10,
-  kwargs...,
-) where {T}
+function curly(; n::Int = default_nvar, type::Type{T} = Float64, b::Int = 10, kwargs...) where {T}
   n < 2 && @warn("curly: number of variables must be ≥ 2")
   n = max(2, n)
   function f(x; n = n, b = b)