Update to 0.6.0 and add CirrusCI

.cirrus.yml

@@ -0,0 +1,32 @@
+task:
+  matrix:
+    - name: FreeBSD
+      freebsd_instance:
+        image_family: freebsd-13-2
+      env:
+        matrix:
+          - JULIA_VERSION: 1.6
+          - JULIA_VERSION: 1
+    - name: MacOS M1
+      macos_instance:
+        image: ghcr.io/cirruslabs/macos-monterey-base:latest
+      env:
+        - JULIA_VERSION: 1
+  install_script: |
+    URL="https://raw.githubusercontent.com/ararslan/CirrusCI.jl/master/bin/install.sh"
+    set -x
+    if [ "$(uname -s)" = "Linux" ] && command -v apt; then
+        apt update
+        apt install -y curl
+    fi
+    if command -v curl; then
+        sh -c "$(curl ${URL})"
+    elif command -v wget; then
+        sh -c "$(wget ${URL} -q -O-)"
+    elif command -v fetch; then
+        sh -c "$(fetch ${URL} -o -)"
+    fi
+  build_script:
+    - cirrusjl build
+  test_script:
+    - cirrusjl test

.copier-answers.yml

@@ -1,11 +1,22 @@
 # Changes here will be overwritten by Copier
-AnswerStrategy: recommended
+AddAllcontributors: true
+AddCodeOfConduct: true
+AddCopierCI: false
+AddGitHubTemplates: true
+AddMacToCI: true
+AddPrecommit: true
+AddWinToCI: true
+AnswerStrategy: ask
 AuthorEmail: [email protected]
 AuthorName: Tangi Migot
+Indentation: 2
 JuliaMinVersion: '1.6'
 License: MPL-2.0
 PackageName: JSOSuite
 PackageOwner: JuliaSmoothOptimizers
 PackageUUID: ed6ae0be-a024-11e9-2788-05dbf8cd15d9
-_commit: v0.5.3
+RunJuliaNightlyOnCI: false
+SimplifiedPRTest: true
+UseCirrusCI: true
+_commit: v0.6.0
 _src_path: https://github.com/abelsiqueira/COPIERTemplate.jl

README.md

@@ -20,6 +20,8 @@ If you use JSOSuite.jl in your work, please cite using the reference given in [C
 
 If you want to make contributions of any kind, please first that a look into our [contributing guide directly on GitHub](docs/src/90-contributing.md) or the [contributing page on the website](https://JuliaSmoothOptimizers.github.io/JSOSuite.jl/dev/contributing/).
 
+---
+
 ### Contributors
 
 <!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->
@@ -30,7 +32,3 @@ If you want to make contributions of any kind, please first that a look into our
 <!-- prettier-ignore-end -->
 
 <!-- ALL-CONTRIBUTORS-LIST:END -->
-
----
-
-This repo was created with the [COPIERTemplate.jl](https://github.com/abelsiqueira/COPIERTemplate.jl) package.

docs/make.jl

@@ -3,13 +3,7 @@ using Documenter
 
 DocMeta.setdocmeta!(JSOSuite, :DocTestSetup, :(using JSOSuite); recursive = true)
 
-const page_rename = Dict(
-  "developer.md" => "Developer docs",
-  "nls.md" => "Nonlinear Least Squares",
-  "qp.md" => "Quadratic models with linear constraints",
-  "resolve.md" => "Re-solve and in-place solve",
-  "speed-up.md" => "Speed up Solvers Tips",
-) # Without the numbers
+const page_rename = Dict("developer.md" => "Developer docs") # Without the numbers
 
 function nice_name(file)
   file = replace(file, r"^[0-9]*-" => "")

docs/src/90-contributing.md

@@ -21,5 +21,5 @@ Otherwise, say what your proposed solution is and wait for a discussion around i
 !!! tip
     Feel free to ping us after a few days if there are no responses.
 
-If your solution involves code (or something that requires running the package locally), check the [developer documentation](90-developer.md).
+If your solution involves code (or something that requires running the package locally), check the [developer documentation](91-developer.md).
 Otherwise, you can use the GitHub interface directly to create your pull request.

docs/src/90-reference.md → docs/src/95-reference.md

@@ -3,13 +3,13 @@
 ## Contents
 
 ```@contents
-Pages = ["90-reference.md"]
+Pages = ["95-reference.md"]
 ```
 
 ## Index
 
 ```@index
-Pages = ["90-reference.md"]
+Pages = ["95-reference.md"]
 ```
 
 ```@autodocs

test/runtests.jl

@@ -33,7 +33,7 @@ using SolverBenchmark
 meta = OptimizationProblems.meta
 
 function test_in_place_solve(nlp, solver_name)
-  pkg_name = JSOSuite.optimizers[JSOSuite.optimizers.name_solver.==solver_name, :name_pkg][1]
+  pkg_name = JSOSuite.optimizers[JSOSuite.optimizers.name_solver .== solver_name, :name_pkg][1]
   pkg_name = replace(pkg_name, ".jl" => "")
   solver = eval(Meta.parse(pkg_name * ".$solver_name"))(nlp)
   stats = solve!(solver, nlp)
@@ -46,7 +46,7 @@ end
 
 function test_in_place_solve(model::JuMP.Model, solver_name)
   nlp = MathOptNLPModel(model)
-  pkg_name = JSOSuite.optimizers[JSOSuite.optimizers.name_solver.==solver_name, :name_pkg][1]
+  pkg_name = JSOSuite.optimizers[JSOSuite.optimizers.name_solver .== solver_name, :name_pkg][1]
   pkg_name = replace(pkg_name, ".jl" => "")
   solver = eval(Meta.parse(pkg_name * ".$solver_name"))(nlp)
   stats = solve!(solver, model)
@@ -64,16 +64,16 @@ end
     solver_name == :DCIWorkspace && continue
     solver_name == :RipQPSolver && continue
     is_available =
-      JSOSuite.optimizers[JSOSuite.optimizers.name_solver.==solver_name, :is_available]
+      JSOSuite.optimizers[JSOSuite.optimizers.name_solver .== solver_name, :is_available]
     can_solve_nlp =
-      JSOSuite.optimizers[JSOSuite.optimizers.name_solver.==solver_name, :can_solve_nlp]
+      JSOSuite.optimizers[JSOSuite.optimizers.name_solver .== solver_name, :can_solve_nlp]
     spec_nls =
-      JSOSuite.optimizers[JSOSuite.optimizers.name_solver.==solver_name, :specialized_nls]
+      JSOSuite.optimizers[JSOSuite.optimizers.name_solver .== solver_name, :specialized_nls]
     if is_available[1] && can_solve_nlp[1]
       test_in_place_solve(nlp, solver_name)
       test_in_place_solve(model, solver_name)
     elseif is_available[1] && spec_nls[1] # NLS
-      nls = OptimizationProblems.ADNLPProblems.arglina(; use_nls=true)
+      nls = OptimizationProblems.ADNLPProblems.arglina(; use_nls = true)
       test_in_place_solve(nls, solver_name)
     elseif is_available[1] # RipQP
       nlp_qm = QuadraticModel(nlp, nlp.meta.x0)
@@ -85,15 +85,15 @@ end
 include("qp_tests.jl")
 
 @testset "Test `Float32`" begin
-  nlp = OptimizationProblems.ADNLPProblems.genrose(; type=Float32)
+  nlp = OptimizationProblems.ADNLPProblems.genrose(; type = Float32)
   atol, rtol = √eps(Float32), √eps(Float32)
   for solver in eachrow(JSOSuite.select_optimizers(nlp))
     if solver.nonlinear_obj
-      minimize(solver.name, nlp; verbose=0, atol=atol, rtol=rtol)
+      minimize(solver.name, nlp; verbose = 0, atol = atol, rtol = rtol)
       @test true
     else
       nlp_qm = QuadraticModel(nlp, nlp.meta.x0)
-      minimize(solver.name, nlp_qm; verbose=0, atol=atol, rtol=rtol)
+      minimize(solver.name, nlp_qm; verbose = 0, atol = atol, rtol = rtol)
       @test true
     end
   end
@@ -104,47 +104,47 @@ end
   jum = MathOptNLPModel(model)
   @test JSOSuite.select_optimizers(model) == JSOSuite.select_optimizers(jum)
   for solver in eachrow(JSOSuite.select_optimizers(model))
-    minimize(solver.name, model; verbose=0)
+    minimize(solver.name, model; verbose = 0)
     @test true
   end
 end
 
 @testset "Benchmark on unconstrained problems" begin
   ad_problems = [
     OptimizationProblems.ADNLPProblems.eval(Meta.parse(problem))() for problem in
-    first(meta[(5 .<= meta.nvar .<= 10).&(meta.ncon.==0).&(.!meta.has_bounds), :name], 5)
+    first(meta[(5 .<= meta.nvar .<= 10) .& (meta.ncon .== 0) .& (.!meta.has_bounds), :name], 5)
   ]
   select = JSOSuite.optimizers[
-    JSOSuite.optimizers.can_solve_nlp.&JSOSuite.optimizers.is_available,
+    JSOSuite.optimizers.can_solve_nlp .& JSOSuite.optimizers.is_available,
     :name,
   ]
-  stats = bmark_solvers(ad_problems, select; atol=1e-3, max_time=10.0, verbose=0)
+  stats = bmark_solvers(ad_problems, select; atol = 1e-3, max_time = 10.0, verbose = 0)
   @test true # just test that it runs
 end
 
 @testset "Basic solve tests" begin
   f = x -> 100 * (x[2] - x[1]^2)^2 + (x[1] - 1)^2
-  stats = minimize(f, [-1.2; 1.0]; verbose=0)
+  stats = minimize(f, [-1.2; 1.0]; verbose = 0)
   @test stats.status_reliable && (stats.status == :first_order)
 
-  stats = minimize("DCISolver", f, [-1.2; 1.0]; verbose=0)
+  stats = minimize("DCISolver", f, [-1.2; 1.0]; verbose = 0)
   @test stats.status_reliable && (stats.status == :first_order)
 
   F = x -> [10 * (x[2] - x[1]^2); x[1] - 1]
-  stats = minimize(F, [-1.2; 1.0], 2; verbose=0)
+  stats = minimize(F, [-1.2; 1.0], 2; verbose = 0)
   @test stats.status_reliable && (stats.status == :first_order)
 
-  stats = minimize("DCISolver", F, [-1.2; 1.0], 2; verbose=0)
+  stats = minimize("DCISolver", F, [-1.2; 1.0], 2; verbose = 0)
   @test stats.status_reliable && (stats.status == :first_order)
 end
 
-@testset "Test solve OptimizationProblems: $name" for name in first(meta[meta.nvar.<10, :name], 5)
+@testset "Test solve OptimizationProblems: $name" for name in first(meta[meta.nvar .< 10, :name], 5)
   name in ["bennett5", "channel", "hs253", "hs73", "misra1c"] && continue
   nlp = OptimizationProblems.ADNLPProblems.eval(Meta.parse(name))()
-  minimize(nlp; verbose=0)
+  minimize(nlp; verbose = 0)
   @test true
   model = OptimizationProblems.PureJuMP.eval(Meta.parse(name))()
-  minimize(model; verbose=0)
+  minimize(model; verbose = 0)
   @test true
 end
 
@@ -165,23 +165,23 @@ for solver in eachrow(JSOSuite.optimizers)
         minimize(
           solver.name,
           nlp;
-          atol=1e-5,
-          rtol=1e-5,
-          max_time=12.0,
-          max_eval=10,
-          verbose=0,
+          atol = 1e-5,
+          rtol = 1e-5,
+          max_time = 12.0,
+          max_eval = 10,
+          verbose = 0,
         )
         @test true
       else
         nlp_qm = QuadraticModel(nlp, nlp.meta.x0)
         minimize(
           solver.name,
           nlp_qm;
-          atol=1e-5,
-          rtol=1e-5,
-          max_time=12.0,
-          max_eval=10,
-          verbose=0,
+          atol = 1e-5,
+          rtol = 1e-5,
+          max_time = 12.0,
+          max_eval = 10,
+          verbose = 0,
         )
         @test true
       end
@@ -191,7 +191,7 @@ end
 
 @testset "Test kwargs in optimizers on $model" for model in (:arglina, :hs6)
   nlp = OptimizationProblems.ADNLPProblems.eval(model)()
-  nls = OptimizationProblems.ADNLPProblems.eval(model)(; use_nls=true)
+  nls = OptimizationProblems.ADNLPProblems.eval(model)(; use_nls = true)
   callback = (args...) -> nothing
   for solver in eachrow(JSOSuite.optimizers)
     @testset "Test options in $(solver.name)" begin
@@ -202,42 +202,42 @@ end
         minimize(
           solver.name,
           nlp;
-          atol=1e-5,
-          rtol=1e-5,
-          max_time=12.0,
-          max_iter=100,
-          max_eval=10,
-          callback=callback,
-          verbose=0,
+          atol = 1e-5,
+          rtol = 1e-5,
+          max_time = 12.0,
+          max_iter = 100,
+          max_eval = 10,
+          callback = callback,
+          verbose = 0,
         )
         @test true
       elseif solver.specialized_nls
         minimize(
           solver.name,
           nls;
-          atol=1e-5,
-          rtol=1e-5,
-          Fatol=1e-5,
-          Frtol=1e-5,
-          max_time=12.0,
-          max_iter=100,
-          max_eval=10,
-          callback=callback,
-          verbose=0,
+          atol = 1e-5,
+          rtol = 1e-5,
+          Fatol = 1e-5,
+          Frtol = 1e-5,
+          max_time = 12.0,
+          max_iter = 100,
+          max_eval = 10,
+          callback = callback,
+          verbose = 0,
         )
         @test true
       else # RipQP
         nlp_qm = QuadraticModel(nlp, nlp.meta.x0)
         minimize(
           solver.name,
           nlp_qm;
-          atol=1e-5,
-          rtol=1e-5,
-          max_time=12.0,
-          max_iter=100,
-          max_eval=10,
-          callback=callback,
-          verbose=0,
+          atol = 1e-5,
+          rtol = 1e-5,
+          max_time = 12.0,
+          max_iter = 100,
+          max_eval = 10,
+          callback = callback,
+          verbose = 0,
         )
         @test true
       end