add Stopping + import

Author: tmigot

Project.toml

@@ -9,6 +9,7 @@ FastClosures = "9aa1b823-49e4-5ca5-8b0f-3971ec8bab6a"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 NLPModels = "a4795742-8479-5a88-8948-cc11e1c8c1a6"
+Stopping = "c4fe5a9e-e7fb-5c3d-89d5-7f405ab2214f"
 
 [compat]
 julia = "1"

src/VariationalInequalitySolver.jl

@@ -1,6 +1,9 @@
 module VariationalInequalitySolver
 
-using FastClosures, LinearAlgebra, Logging, NLPModels
+using FastClosures, LinearAlgebra, Logging, NLPModels, Stopping
+
+import NLPModels: residual!, jac_structure_residual!, jac_coord_residual!, jprod_residual!, jtprod_residual!, jac_op_residual!, hess_structure_residual!, hess_coord_residual!, hprod_residual!, hess_op_residual!
+
 
 abstract type AbstractVIModel{T, S} end
 

src/solvers/projectionVI.jl

@@ -3,31 +3,37 @@ export ProjectionVI
 function ProjectionVI(
   model::AbstractVIModel,
   x0::AbstractVector;
-  prec :: Float64 = 1e-6,
   rho0 :: Float64 = 0.5,
-  itmax :: Int64 = 10000,
+  kwargs...
 )
-  xk = copy(x0)
+  stp = GenericStopping(model, x0; kwargs...)
+  return ProjectionVI(stp, rho0 = rho0)
+end
+
+function abresidual!(model, xk, rho, Fx) # xk + rho * F(xk)
+  residual!(model, xk, Fx)
+  Fx .*= rho
+  Fx .+= xk
+  return Fx
+end
+
+function ProjectionVI(stp::AbstractStopping; rho0 :: Float64 = 0.5)
+  xk = stp.current_state.x
   xkp = similar(xk)
   rho = rho0
-  i=0
-  OK = false
   Fx = similar(xk)
-  residual!(model, xk, Fx)
-  Fx .*= rho
-  Fx .+= xk # xk + rho * F(xk)
+  abresidual!(stp.pb, xk, rho, Fx)
 
-  #main loop
+  OK = update_and_start!(stp)
   while !OK
-    residual!(model, xk, Fx)
-    Fx .*= rho
-    Fx .+= xk # xk + rho * F(xk)
-    proj!(model, Fx, xkp) # possible failure here
+    abresidual!(stp.pb, xk, rho, Fx)
+    project!(stp.pb, Fx, xkp) # possible failure here
 
-    i=i+1
-    OK=(i>=itmax) || (norm(xk-xkp,Inf)<prec*rho )
-    xk = copy(xkp)
-  end #end of main loop
+    if norm(xk - xkp, Inf) < stp.meta.atol * rho
+      stp.meta.optimal = true
+    end
+    OK = OK || update_and_stop!(stp, x = xk)
+  end
 
   return xk
-end
+end