Apply JuliaFormatter (#31)

* Apply JuliaFormatter

* Update Project.toml

.JuliaFormatter.toml

@@ -0,0 +1,8 @@
+# Configuration file for JuliaFormatter.jl
+# For more information, see: https://domluna.github.io/JuliaFormatter.jl/stable/config/
+
+always_for_in = true
+always_use_return = true
+margin = 80
+remove_extra_newlines = true
+short_to_long_function_def = true

.github/workflows/format_check.yml

@@ -0,0 +1,31 @@
+name: format-check
+on:
+  push:
+    branches:
+      - master
+      - release-*
+  pull_request:
+    types: [opened, synchronize, reopened]
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: julia-actions/setup-julia@latest
+        with:
+          version: '1'
+      - uses: actions/checkout@v1
+      - name: Format check
+        shell: julia --color=yes {0}
+        run: |
+          using Pkg
+          Pkg.add(PackageSpec(name="JuliaFormatter", version="0.13.9"))
+          using JuliaFormatter
+          format("src", verbose=true)
+          format("test", verbose=true)
+          out = String(read(Cmd(`git diff`)))
+          if isempty(out)
+              exit(0)
+          end
+          @error "Some files have not been formatted !!!"
+          write(stdout, out)
+          exit(1)

src/MINLPTests.jl

@@ -1,19 +1,20 @@
 module MINLPTests
 
-using JuMP, Test
+using JuMP
+using Test
 
 ###
 ### Default tolerances that are used in the tests.
 ###
 
 # Absolute tolerance when checking the objective value.
-const OPT_TOL    = 1e-6
+const OPT_TOL = 1e-6
 
 # Absolute tolerance when checking the primal solution value.
 const PRIMAL_TOL = 1e-6
 
 # Absolue tolerance when checking the dual solution value.
-const DUAL_TOL   = 1e-6
+const DUAL_TOL = 1e-6
 
 ###
 ### Default expected status codes for different types of problems and solvers.
@@ -46,9 +47,12 @@ const PRIMAL_TARGET_GLOBAL = Dict(
 ### Helper functions for the tests.
 ###
 
-function check_status(model, problem_type::ProblemTypeCode,
-                      termination_target=TERMINATION_TARGET_LOCAL,
-                      primal_target=PRIMAL_TARGET_LOCAL)
+function check_status(
+    model,
+    problem_type::ProblemTypeCode,
+    termination_target = TERMINATION_TARGET_LOCAL,
+    primal_target = PRIMAL_TARGET_LOCAL,
+)
     @test JuMP.termination_status(model) == termination_target[problem_type]
     @test JuMP.primal_status(model) == primal_target[problem_type]
 end
@@ -82,7 +86,8 @@ end
 ###
 
 for directory in ["nlp", "nlp-cvx", "nlp-mi"]
-    for file_name in filter(f -> endswith(f, ".jl"), readdir(joinpath(@__DIR__, directory)))
+    files = readdir(joinpath(@__DIR__, directory))
+    for file_name in filter(f -> endswith(f, ".jl"), files)
         include(joinpath(@__DIR__, directory, file_name))
     end
 end
@@ -99,22 +104,37 @@ end
     test_directory("nlp", optimizer; include = ["001_010"])
 """
 function test_directory(
-        directory, optimizer; exclude=String[], include=String[],
-        objective_tol = OPT_TOL, primal_tol = PRIMAL_TOL, dual_tol = DUAL_TOL,
-        termination_target = TERMINATION_TARGET_LOCAL,
-        primal_target = PRIMAL_TARGET_LOCAL)
-
+    directory,
+    optimizer;
+    exclude = String[],
+    include = String[],
+    objective_tol = OPT_TOL,
+    primal_tol = PRIMAL_TOL,
+    dual_tol = DUAL_TOL,
+    termination_target = TERMINATION_TARGET_LOCAL,
+    primal_target = PRIMAL_TARGET_LOCAL,
+)
     @testset "$(directory)" begin
-        @testset "$(model_name)" for model_name in list_of_models(directory, exclude, include)
-            function_name = string(replace(directory, "-" => "_"), "_", model_name)
-            model_function = getfield(MINLPTests, Symbol(function_name))
-            model_function(optimizer, objective_tol, primal_tol, dual_tol,
-                           termination_target, primal_target)
+        models = _list_of_models(directory, exclude, include)
+        dir = replace(directory, "-" => "_")
+        @testset "$(model_name)" for model_name in models
+            getfield(MINLPTests, Symbol("$(dir)_$(model_name)"))(
+                optimizer,
+                objective_tol,
+                primal_tol,
+                dual_tol,
+                termination_target,
+                primal_target,
+            )
         end
     end
 end
 
-function list_of_models(directory, exclude::Vector{String}, include::Vector{String})
+function _list_of_models(
+    directory,
+    exclude::Vector{String},
+    include::Vector{String},
+)
     if length(include) > 0
         return include
     else
@@ -134,39 +154,66 @@ end
 ###
 
 function test_nlp(
-        optimizer; exclude = String[], objective_tol = OPT_TOL,
-        primal_tol = PRIMAL_TOL, dual_tol = DUAL_TOL,
-        termination_target = TERMINATION_TARGET_LOCAL,
-        primal_target = PRIMAL_TARGET_LOCAL)
-    test_directory("nlp", optimizer;
-        exclude = exclude, objective_tol = objective_tol,
-        primal_tol = primal_tol, dual_tol = dual_tol,
+    optimizer;
+    exclude = String[],
+    objective_tol = OPT_TOL,
+    primal_tol = PRIMAL_TOL,
+    dual_tol = DUAL_TOL,
+    termination_target = TERMINATION_TARGET_LOCAL,
+    primal_target = PRIMAL_TARGET_LOCAL,
+)
+    return test_directory(
+        "nlp",
+        optimizer;
+        exclude = exclude,
+        objective_tol = objective_tol,
+        primal_tol = primal_tol,
+        dual_tol = dual_tol,
         termination_target = termination_target,
-        primal_target = primal_target)
+        primal_target = primal_target,
+    )
 end
 
 function test_nlp_cvx(
-        optimizer; exclude = String[], objective_tol = OPT_TOL,
-        primal_tol = PRIMAL_TOL, dual_tol = DUAL_TOL,
-        termination_target = TERMINATION_TARGET_LOCAL,
-        primal_target = PRIMAL_TARGET_LOCAL)
-    test_directory("nlp-cvx", optimizer;
-        exclude = exclude, objective_tol = objective_tol,
-        primal_tol = primal_tol, dual_tol = dual_tol,
+    optimizer;
+    exclude = String[],
+    objective_tol = OPT_TOL,
+    primal_tol = PRIMAL_TOL,
+    dual_tol = DUAL_TOL,
+    termination_target = TERMINATION_TARGET_LOCAL,
+    primal_target = PRIMAL_TARGET_LOCAL,
+)
+    return test_directory(
+        "nlp-cvx",
+        optimizer;
+        exclude = exclude,
+        objective_tol = objective_tol,
+        primal_tol = primal_tol,
+        dual_tol = dual_tol,
         termination_target = termination_target,
-        primal_target = primal_target)
+        primal_target = primal_target,
+    )
 end
 
 function test_nlp_mi(
-        optimizer; exclude = String[], objective_tol = OPT_TOL,
-        primal_tol = PRIMAL_TOL, dual_tol = DUAL_TOL,
-        termination_target = TERMINATION_TARGET_LOCAL,
-        primal_target = PRIMAL_TARGET_LOCAL)
-    test_directory("nlp-mi", optimizer;
-        exclude = exclude, objective_tol = objective_tol,
-        primal_tol = primal_tol, dual_tol = dual_tol,
+    optimizer;
+    exclude = String[],
+    objective_tol = OPT_TOL,
+    primal_tol = PRIMAL_TOL,
+    dual_tol = DUAL_TOL,
+    termination_target = TERMINATION_TARGET_LOCAL,
+    primal_target = PRIMAL_TARGET_LOCAL,
+)
+    return test_directory(
+        "nlp-mi",
+        optimizer;
+        exclude = exclude,
+        objective_tol = objective_tol,
+        primal_tol = primal_tol,
+        dual_tol = dual_tol,
         termination_target = termination_target,
-        primal_target = primal_target)
+        primal_target = primal_target,
+    )
 end
 
 ### Tests that haven't been updated.

src/nlp-cvx/001_010.jl

@@ -1,31 +1,38 @@
-function nlp_cvx_001_010(optimizer, objective_tol, primal_tol, dual_tol,
-        termination_target = TERMINATION_TARGET_LOCAL,
-        primal_target = PRIMAL_TARGET_LOCAL)
+function nlp_cvx_001_010(
+    optimizer,
+    objective_tol,
+    primal_tol,
+    dual_tol,
+    termination_target = TERMINATION_TARGET_LOCAL,
+    primal_target = PRIMAL_TARGET_LOCAL,
+)
     # Test Goals:
     # - linear objective
     # - quadratic objective
     # - linear constraints forming a closed set
     # Variants
     #   010 - binding constraints
-    #   011 - non-binding constraints 
-
-    m = Model(optimizer)
-
-    @variable(m, x)
-    @variable(m, y)
-
-    @objective(m, Min, x)
-    @constraint(m, x+y <= 5)
-    @constraint(m, 2*x-y <= 3)
-    @constraint(m, 3*x+9*y >= -10)
-    @constraint(m, 10*x-y >= -20)
-    @constraint(m, -x+2*y <= 8)
-
-    optimize!(m)
-
-    check_status(m, FEASIBLE_PROBLEM, termination_target, primal_target)
-    check_objective(m, -2.0430107680954848, tol = objective_tol)
-    check_solution([x,y], [-2.0430107680954848, -0.4301075068564087], tol = primal_tol)
-
-end
+    #   011 - non-binding constraints
+
+    model = Model(optimizer)
+
+    @variable(model, x)
+    @variable(model, y)
 
+    @objective(model, Min, x)
+    @constraint(model, x + y <= 5)
+    @constraint(model, 2 * x - y <= 3)
+    @constraint(model, 3 * x + 9 * y >= -10)
+    @constraint(model, 10 * x - y >= -20)
+    @constraint(model, -x + 2 * y <= 8)
+
+    optimize!(model)
+
+    check_status(model, FEASIBLE_PROBLEM, termination_target, primal_target)
+    check_objective(model, -2.0430107680954848, tol = objective_tol)
+    return check_solution(
+        [x, y],
+        [-2.0430107680954848, -0.4301075068564087],
+        tol = primal_tol,
+    )
+end

src/nlp-cvx/001_011.jl

@@ -1,23 +1,26 @@
-function nlp_cvx_001_011(optimizer, objective_tol, primal_tol, dual_tol,
-        termination_target = TERMINATION_TARGET_LOCAL,
-        primal_target = PRIMAL_TARGET_LOCAL)
-    m = Model(optimizer)
-
-    @variable(m, x)
-    @variable(m, y)
-
-    @objective(m, Min, (x-1)^2 + (y-2)^2)
-    @constraint(m, x+y <= 5)
-    @constraint(m, 2*x-y <= 3)
-    @constraint(m, 3*x+9*y >= -10)
-    @constraint(m, 10*x-y >= -20)
-    @constraint(m, -x+2*y <= 8)
-
-    optimize!(m)
-
-    check_status(m, FEASIBLE_PROBLEM, termination_target, primal_target)
-    check_objective(m, 0.0, tol = objective_tol)
-    check_solution([x,y], [1.0, 2.0], tol = primal_tol)
-
-end
+function nlp_cvx_001_011(
+    optimizer,
+    objective_tol,
+    primal_tol,
+    dual_tol,
+    termination_target = TERMINATION_TARGET_LOCAL,
+    primal_target = PRIMAL_TARGET_LOCAL,
+)
+    model = Model(optimizer)
+
+    @variable(model, x)
+    @variable(model, y)
+
+    @objective(model, Min, (x - 1)^2 + (y - 2)^2)
+    @constraint(model, x + y <= 5)
+    @constraint(model, 2 * x - y <= 3)
+    @constraint(model, 3 * x + 9 * y >= -10)
+    @constraint(model, 10 * x - y >= -20)
+    @constraint(model, -x + 2 * y <= 8)
 
+    optimize!(model)
+
+    check_status(model, FEASIBLE_PROBLEM, termination_target, primal_target)
+    check_objective(model, 0.0, tol = objective_tol)
+    return check_solution([x, y], [1.0, 2.0], tol = primal_tol)
+end