🤖 Format .jl files

Author: MaxenceGollier

src/compositeNormL2.jl

@@ -45,13 +45,20 @@ mutable struct CompositeNormL2{
     J!::Function,
     A::AbstractMatrix{T},
     b::AbstractVector{T};
-    store_previous_jacobian::Bool = false
+    store_previous_jacobian::Bool = false,
   ) where {T <: Real}
     λ > 0 || error("CompositeNormL2: λ should be positive")
     length(b) == size(A, 1) || error(
       "Composite Norm L2: Wrong input dimensions, the length of c(x) should be the same as the number of rows of J(x)",
     )
-    new{T, typeof(c!), typeof(J!), typeof(A), typeof(b)}(NormL2(λ), c!, J!, A, b, store_previous_jacobian)
+    new{T, typeof(c!), typeof(J!), typeof(A), typeof(b)}(
+      NormL2(λ),
+      c!,
+      J!,
+      A,
+      b,
+      store_previous_jacobian,
+    )
   end
 end
 

src/shiftedCompositeNormL2.jl

@@ -53,7 +53,7 @@ mutable struct ShiftedCompositeNormL2{
     J!::Function,
     A::AbstractMatrix{T},
     b::AbstractVector{T};
-    store_previous_jacobian::Bool = false
+    store_previous_jacobian::Bool = false,
   ) where {T <: Real}
     p = similar(b, A.n + A.m)
     dp = similar(b, A.n + A.m)
@@ -86,7 +86,7 @@ mutable struct ShiftedCompositeNormL2{
       dq,
       p,
       dp,
-      false
+      false,
     )
   end
 end
@@ -105,7 +105,14 @@ shifted(
   ψ.c!(b, xk)
   A = similar(ψ.A)
   ψ.J!(A, xk)
-  ShiftedCompositeNormL2(ψ.h.lambda, ψ.c!, ψ.J!, A, b, store_previous_jacobian = ψ.store_previous_jacobian)
+  ShiftedCompositeNormL2(
+    ψ.h.lambda,
+    ψ.c!,
+    ψ.J!,
+    A,
+    b,
+    store_previous_jacobian = ψ.store_previous_jacobian,
+  )
 end
 
 fun_name(ψ::ShiftedCompositeNormL2) = "shifted `ℓ₂` norm"
@@ -120,7 +127,14 @@ function prox!(
   max_iter = 10,
   atol = eps(T)^0.3,
   max_time = 180.0,
-) where {T <: Real, F0 <: Function, F1 <: Function, M <: AbstractMatrix{T}, N <: Union{Nothing, M}, V <: AbstractVector{T}}
+) where {
+  T <: Real,
+  F0 <: Function,
+  F1 <: Function,
+  M <: AbstractMatrix{T},
+  N <: Union{Nothing, M},
+  V <: AbstractVector{T},
+}
   @assert ν > zero(T)
   start_time = time()
   θ = T(0.8)

test/runtests.jl

@@ -49,7 +49,7 @@ for (op, composite_op, shifted_op) ∈
     ν = 0.1056
     prox!(y, ϕ, x, ν)
     @test ϕ.full_row_rank == true
-    
+
     if "$op" == "NormL2"
       y_true = [0.24545429, 0.75250248, -0.66619752, 1.19372286]
       norm = Op(1.0)
@@ -64,17 +64,18 @@ for (op, composite_op, shifted_op) ∈
     @test ϕ.A == SparseMatrixCOO(Float64[2 0 0 -1; 0 1 1 0])
     @test ϕ(ones(Float64, 4)) ==
           h([1.0, 2.0] + SparseMatrixCOO(Float64[2 0 0 -1; 0 1 1 0])*ones(Float64, 4))
-    
+
     # test store previous Jacobian option
 
     function c_store_prev!(z, x)
       z[1] = 2*x[1]^2 - x[4]
       z[2] = x[2] + x[3]
     end
     function J_store_prev!(z, x)
-      z.vals .= Float64[4.0*x[1], 1.0, 1.0, -1.0]
+      z.vals .= Float64[4.0 * x[1], 1.0, 1.0, -1.0]
     end
-    ψ_store_prev = CompositeOp(λ, c_store_prev!, J_store_prev!, A, b, store_previous_jacobian = true)
+    ψ_store_prev =
+      CompositeOp(λ, c_store_prev!, J_store_prev!, A, b, store_previous_jacobian = true)
     @test ψ_store_prev.store_previous_jacobian == true
 
     xk = [1.0, 0.0, 0.0, 0.0]
@@ -95,7 +96,6 @@ for (op, composite_op, shifted_op) ∈
     @test all(ϕ_store_prev.A_prev .== SparseMatrixCOO([8.0 0.0 0.0 -1.0; 0.0 1.0 1.0 0.0]))
     @test all(ϕ_store_prev.A .== SparseMatrixCOO([2.0 0.0 0.0 -1.0; 0.0 1.0 1.0 0.0]))
 
-
     # test different types
     h = Op(Float32(λ))
     function c2!(z, x)