🤖 Format .jl files

JuliaSmoothOptimizers · Jan 26, 2023 · 33566ec · 33566ec
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commit 33566ec
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Showing 10 changed files with 20 additions and 18 deletions.
diff --git a/src/partitionedNLPModels/PBFGSNLPModels.jl b/src/partitionedNLPModels/PBFGSNLPModels.jl
@@ -59,7 +59,7 @@ mutable struct PBFGSNLPModel{
   name::Symbol
 end
 
-function PBFGSNLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool=true)
+function PBFGSNLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool = true)
   n = nlp.meta.nvar
   ex = get_expression_tree(nlp)
 

diff --git a/src/partitionedNLPModels/PCSNLPModels.jl b/src/partitionedNLPModels/PCSNLPModels.jl
@@ -59,7 +59,7 @@ mutable struct PCSNLPModel{
   name::Symbol
 end
 
-function PCSNLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool=true)
+function PCSNLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool = true)
   n = nlp.meta.nvar
   ex = get_expression_tree(nlp)
 

diff --git a/src/partitionedNLPModels/PLBFGSNLPModels.jl b/src/partitionedNLPModels/PLBFGSNLPModels.jl
@@ -59,7 +59,7 @@ mutable struct PLBFGSNLPModel{
   name::Symbol
 end
 
-function PLBFGSNLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool=true)
+function PLBFGSNLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool = true)
   n = nlp.meta.nvar
   ex = get_expression_tree(nlp)
 

diff --git a/src/partitionedNLPModels/PLSENLPModels.jl b/src/partitionedNLPModels/PLSENLPModels.jl
@@ -59,7 +59,7 @@ mutable struct PLSENLPModel{
   name::Symbol
 end
 
-function PLSENLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool=true)
+function PLSENLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool = true)
   n = nlp.meta.nvar
   ex = get_expression_tree(nlp)
 

diff --git a/src/partitionedNLPModels/PLSR1NLPModels.jl b/src/partitionedNLPModels/PLSR1NLPModels.jl
@@ -59,7 +59,7 @@ mutable struct PLSR1NLPModel{
   name::Symbol
 end
 
-function PLSR1NLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool=true)
+function PLSR1NLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool = true)
   n = nlp.meta.nvar
   ex = get_expression_tree(nlp)
 

diff --git a/src/partitionedNLPModels/PSENLPModels.jl b/src/partitionedNLPModels/PSENLPModels.jl
@@ -59,7 +59,7 @@ mutable struct PSENLPModel{
   name::Symbol
 end
 
-function PSENLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool=true)
+function PSENLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool = true)
   n = nlp.meta.nvar
   ex = get_expression_tree(nlp)
 

diff --git a/src/partitionedNLPModels/PSNLPModels.jl b/src/partitionedNLPModels/PSNLPModels.jl
@@ -59,7 +59,7 @@ mutable struct PSNLPModel{
   name::Symbol
 end
 
-function PSNLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool=true)
+function PSNLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool = true)
   n = nlp.meta.nvar
   ex = get_expression_tree(nlp)
 

diff --git a/src/partitionedNLPModels/PSR1NLPModels.jl b/src/partitionedNLPModels/PSR1NLPModels.jl
@@ -59,7 +59,7 @@ mutable struct PSR1NLPModel{
   name::Symbol
 end
 
-function PSR1NLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool=true)
+function PSR1NLPModel(nlp::SupportedNLPModel; type::DataType = Float64, merging::Bool = true)
   n = nlp.meta.nvar
   ex = get_expression_tree(nlp)
 

diff --git a/src/partitionedNLPModels/utils.jl b/src/partitionedNLPModels/utils.jl
@@ -96,7 +96,7 @@ function partitioned_structure(
   n::Int;
   type::DataType = Float64,
   name = :plse,
-  merging::Bool=true,
+  merging::Bool = true,
   kwargs...,
 ) where {G}
 
@@ -116,14 +116,17 @@ function partitioned_structure(
   )::Vector{Vector{Int}}
 
   mem_dense_elements = sum((element_var -> length(element_var)^2).(element_variables))
-  mem_linear_operator_elements = sum((element_var -> length(element_var)*5*2).(element_variables))
-  max_authorised_mem = n^3/log(n) # mem limit
+  mem_linear_operator_elements =
+    sum((element_var -> length(element_var) * 5 * 2).(element_variables))
+  max_authorised_mem = n^3 / log(n) # mem limit
   if merging && (mem_dense_elements > max_authorised_mem) && (name ∈ [:pbfgs, :pse, :psr1, :pcs])
     @warn "mem usage to important, reduction to a unstructrued structure"
     N = 1
     vec_element_function = [expr_tree]
     element_variables = [[1:n;]]
-  elseif merging && (mem_linear_operator_elements > max_authorised_mem) && (name ∈ [:plbfgs, :plse, :plsr1])
+  elseif merging &&
+         (mem_linear_operator_elements > max_authorised_mem) &&
+         (name ∈ [:plbfgs, :plse, :plsr1])
     @warn "mem usage to important, reduction to a unstructrued structure"
     N = 1
     vec_element_function = [expr_tree]

diff --git a/test/pqnnlp.jl b/test/pqnnlp.jl
@@ -81,13 +81,12 @@ end
   @test ges_psnlp.status == :first_order
 end
 
-
 @testset "Merge, from a limit function" begin
-  function limit(x; n=length(x))
-    sum(sum( sum(x[j] for j in 1:n)^2 * x[i] * x[z] for i in 1:n) for z in 1:n)
+  function limit(x; n = length(x))
+    sum(sum(sum(x[j] for j = 1:n)^2 * x[i] * x[z] for i = 1:n) for z = 1:n)
   end
-  start_limit(n :: Int) = ones(n)
-  
+  start_limit(n::Int) = ones(n)
+
   n = 10
   adnlp = ADNLPModel(limit, start_limit(n))
 
@@ -99,4 +98,4 @@ end
   psr1nlp = PSR1NLPModel(adnlp)
   psenlp = PSENLPModel(adnlp)
   psnlp = PSNLPModel(adnlp)
-end
+end