Merge pull request #12 from psrenergy/rs/format

Add format

.JuliaFormatter.toml

@@ -0,0 +1,24 @@
+# Configuration file for JuliaFormatter.jl
+# For more information, see: https://domluna.github.io/JuliaFormatter.jl/stable/config/
+
+indent = 4
+margin = 146
+always_for_in = true
+whitespace_typedefs = true
+whitespace_ops_in_indices = false
+remove_extra_newlines = true
+import_to_using = false
+pipe_to_function_call = false
+short_to_long_function_def = false
+long_to_short_function_def = false
+whitespace_in_kwargs = true
+annotate_untyped_fields_with_any = true
+format_docstrings = true
+conditional_to_if = false
+normalize_line_endings = "auto"
+trailing_comma = true
+join_lines_based_on_source = true
+indent_submodule = false
+separate_kwargs_with_semicolon = false
+surround_whereop_typeparameters = true
+always_use_return = true

format/Project.toml

@@ -0,0 +1,5 @@
+[deps]
+JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
+
+[compat]
+JuliaFormatter = "1"

format/format.bat

@@ -0,0 +1,5 @@
+@echo off
+
+SET BASEPATH=%~dp0
+
+CALL "%JULIA_194%" --project=%BASEPATH% %BASEPATH%\format.jl

format/format.jl

@@ -0,0 +1,6 @@
+import Pkg
+Pkg.instantiate()
+
+using JuliaFormatter
+
+format(dirname(@__DIR__))

revise.bat

@@ -3,4 +3,4 @@
 SET BASEPATH=%~dp0
 SET REVISE_PATH="%BASEPATH%\revise"
 
-%JULIA_194% --project=%REVISE_PATH% --load=%REVISE_PATH%\revise_load_script.jl
+CALL %JULIA_194% --project=%REVISE_PATH% --load=%REVISE_PATH%\revise_load_script.jl

src/cut_strategies/cuts_base.jl

@@ -15,7 +15,6 @@ Abstract type to hold various implementations of cut pools. A cut pool is a data
 """
 abstract type AbstractCutPool end
 
-
 """
     initialize_cut_pool(options)
 
@@ -29,6 +28,7 @@ function initialize_cut_pool(options)
         return [LightBenders.CutPoolMultiCut() for _ in 1:num_stages]
     end
     error("Not implemented.")
+    return nothing
 end
 
 """
@@ -64,9 +64,9 @@ end
 
 Add a cut to a Model and return the constraint reference.
 """
-function add_cut(model::JuMP.Model, epigraph_variable::JuMP.VariableRef, coefs::Vector{T}, rhs::T) where T <: Real
+function add_cut(model::JuMP.Model, epigraph_variable::JuMP.VariableRef, coefs::Vector{T}, rhs::T) where {T <: Real}
     alpha = epigraph_variable
     cache = model.ext[:state]::StateCache
     cref = @constraint(model, alpha >= rhs + dot(coefs, cache.variables))
     return cref
-end
+end

src/cut_strategies/local_cuts.jl

@@ -16,15 +16,15 @@ function number_of_cuts(pool::LocalCutPool)
 end
 
 function store_cut!(
-    pool::LocalCutPool, 
-    coefs::Vector{Float64}, 
-    state::Vector{Float64}, 
-    rhs::Float64, 
-    obj::Float64
+    pool::LocalCutPool,
+    coefs::Vector{Float64},
+    state::Vector{Float64},
+    rhs::Float64,
+    obj::Float64,
 )
     push!(pool.coefs, coefs)
     push!(pool.state, state)
     push!(pool.rhs, rhs)
     push!(pool.obj, obj)
     return nothing
-end
+end

src/cut_strategies/multi_cut.jl

@@ -14,21 +14,22 @@ function number_of_cuts(pool::CutPoolMultiCut)
 end
 
 function store_cut!(
-    pool_multicut::CutPoolMultiCut, 
-    local_pool::LocalCutPool
+    pool_multicut::CutPoolMultiCut,
+    local_pool::LocalCutPool,
 )
     push!(pool_multicut.cuts, local_pool)
     return nothing
 end
 
 function store_cut!(
-    pool::Vector{CutPoolMultiCut}, 
+    pool::Vector{CutPoolMultiCut},
     local_cuts::LocalCutPool,
     state::Vector{Float64},
     options,
-    t::Integer
+    t::Integer,
 )
     store_cut!(pool[t-1], local_cuts)
+    return nothing
 end
 
 function create_epigraph_multi_cut_variables!(model::JuMP.Model, policy_training_options)
@@ -42,16 +43,16 @@ function create_epigraph_multi_cut_variables!(model::JuMP.Model, policy_training
 end
 
 function add_multi_cut_risk_neutral_cuts!(
-    model::JuMP.Model, 
+    model::JuMP.Model,
     alphas::Vector{JuMP.VariableRef},
-    pool::CutPoolMultiCut, 
-    policy_training_options
+    pool::CutPoolMultiCut,
+    policy_training_options,
 )
     for scen in 1:policy_training_options.num_scenarios
         JuMP.set_objective_coefficient(
-            model, 
-            alphas[scen], 
-            (1.0 - policy_training_options.discount_rate) / policy_training_options.num_scenarios
+            model,
+            alphas[scen],
+            (1.0 - policy_training_options.discount_rate) / policy_training_options.num_scenarios,
         )
         for i in 1:length(pool.cuts)
             add_cut(model, alphas[scen], pool.cuts[i].coefs[scen], pool.cuts[i].rhs[scen])
@@ -61,33 +62,34 @@ function add_multi_cut_risk_neutral_cuts!(
 end
 
 function add_multi_cut_cvar_cuts!(
-    model::JuMP.Model, 
+    model::JuMP.Model,
     alphas::Vector{JuMP.VariableRef},
-    pool::CutPoolMultiCut, 
-    policy_training_options
+    pool::CutPoolMultiCut,
+    policy_training_options,
 )
     discount_rate_multiplier = (1.0 - policy_training_options.discount_rate)
     JuMP.@variable(model, z_explicit_cvar)
     # λ * z
     JuMP.set_objective_coefficient(
-        model, 
-        z_explicit_cvar, 
-        discount_rate_multiplier * (policy_training_options.risk_measure.lambda)
+        model,
+        z_explicit_cvar,
+        discount_rate_multiplier * (policy_training_options.risk_measure.lambda),
     )
     JuMP.@variable(model, delta_explicit_cvar[scen = 1:policy_training_options.num_scenarios] >= 0)
     for scen in 1:policy_training_options.num_scenarios
         # (1 - λ)/L * sum(alphas) 
         JuMP.set_objective_coefficient(
-            model, 
-            alphas[scen], 
-            discount_rate_multiplier * (1 - policy_training_options.risk_measure.lambda) / policy_training_options.num_scenarios
+            model,
+            alphas[scen],
+            discount_rate_multiplier * (1 - policy_training_options.risk_measure.lambda) / policy_training_options.num_scenarios,
         )
         # λ / ((1 - CVaR_\alpha) * L) * sum(deltas)
         JuMP.set_objective_coefficient(
-            model, 
-            delta_explicit_cvar[scen], 
-            discount_rate_multiplier * 
-            (policy_training_options.risk_measure.lambda) / ((1 - policy_training_options.risk_measure.alpha) * policy_training_options.num_scenarios)
+            model,
+            delta_explicit_cvar[scen],
+            discount_rate_multiplier *
+            (policy_training_options.risk_measure.lambda) /
+            ((1 - policy_training_options.risk_measure.alpha) * policy_training_options.num_scenarios),
         )
         # Add delta constraint
         JuMP.@constraint(model, delta_explicit_cvar[scen] >= alphas[scen] - z_explicit_cvar)
@@ -119,4 +121,4 @@ function get_multi_cut_future_cost(model::JuMP.Model)::Float64
     end
     alphas = model[:epi_multi_cut]::Vector{JuMP.VariableRef}
     return mean(JuMP.value.(alphas))
-end
+end

src/cut_strategies/single_cut.jl

@@ -19,11 +19,11 @@ function number_of_cuts(pool::CutPoolSingleCut)
 end
 
 function store_cut!(
-    pool::CutPoolSingleCut, 
-    coefs::Vector{Float64}, 
-    state::Vector{Float64}, 
-    rhs::Float64, 
-    obj::Float64
+    pool::CutPoolSingleCut,
+    coefs::Vector{Float64},
+    state::Vector{Float64},
+    rhs::Float64,
+    obj::Float64,
 )
     push!(pool.coefs, coefs)
     push!(pool.state, state)
@@ -33,11 +33,11 @@ function store_cut!(
 end
 
 function store_cut!(
-    pool::Vector{CutPoolSingleCut}, 
+    pool::Vector{CutPoolSingleCut},
     local_cuts::LocalCutPool,
     state::Vector{Float64},
     options,
-    t::Integer
+    t::Integer,
 )
     if isa(options.risk_measure, RiskNeutral)
         return risk_neutral_single_cut!(pool, local_cuts, state, options, t)
@@ -49,11 +49,11 @@ function store_cut!(
 end
 
 function risk_neutral_single_cut!(
-    pool::Vector{CutPoolSingleCut}, 
-    local_cuts::LocalCutPool, 
+    pool::Vector{CutPoolSingleCut},
+    local_cuts::LocalCutPool,
     state::Vector{Float64},
     options,
-    t::Integer
+    t::Integer,
 )
     num_local_cuts = length(local_cuts.obj)
     obj = mean(local_cuts.obj)
@@ -67,11 +67,11 @@ function risk_neutral_single_cut!(
 end
 
 function cvar_single_cut!(
-    pool::Vector{CutPoolSingleCut}, 
-    local_cuts::LocalCutPool, 
+    pool::Vector{CutPoolSingleCut},
+    local_cuts::LocalCutPool,
     state::Vector{Float64},
     options,
-    t::Int
+    t::Int,
 )
     weights = build_cvar_weights(local_cuts.obj, options.risk_measure.alpha, options.risk_measure.lambda)
     obj = dot(weights, local_cuts.obj)

src/debugging_options.jl

@@ -1,4 +1,4 @@
 Base.@kwdef mutable struct DebuggingOptions
     logs_dir::String = ""
     write_lp::Bool = false
-end
+end

src/deterministic_equivalent/deterministic_equivalent.jl

@@ -8,7 +8,7 @@ function deterministic_equivalent(;
     first_stage_builder::Function,
     second_stage_builder::Function,
     second_stage_modifier::Function,
-    inputs=nothing,
+    inputs = nothing,
     options::DeterministicEquivalentOptions,
 )
     num_scenarios = options.num_scenarios
@@ -61,7 +61,7 @@ function copy_and_replace_variables(
 )
     return JuMP.GenericAffExpr(
         src.constant,
-        Pair{VariableRef,Float64}[
+        Pair{VariableRef, Float64}[
             src_to_dest_variable[key] => val for (key, val) in src.terms
         ],
     )
@@ -73,7 +73,7 @@ function copy_and_replace_variables(
 )
     return JuMP.GenericQuadExpr(
         copy_and_replace_variables(src.aff, src_to_dest_variable),
-        Pair{UnorderedPair{VariableRef},Float64}[
+        Pair{UnorderedPair{VariableRef}, Float64}[
             UnorderedPair{VariableRef}(
                 src_to_dest_variable[pair.a],
                 src_to_dest_variable[pair.b],
@@ -104,7 +104,7 @@ function push_model!(
     model::JuMP.Model,
     subproblem::JuMP.Model,
     scenario::Int,
-    num_scenarios::Int
+    num_scenarios::Int,
 )
     # push variables
     src_variables = all_variables_but_state(subproblem)

src/optimize_helpers.jl

@@ -14,7 +14,7 @@ function print_conflict_to_file(model::JuMP.Model, filename::String = "infeasibl
             write(io, "IIS found\n")
             for cref in all_constraints(model, include_variable_in_set_constraints = true)
                 if MOI.get(model, MOI.ConstraintConflictStatus(), cref) == MOI.IN_CONFLICT
-                    println(io,  cref)
+                    println(io, cref)
                 end
             end
         end

src/progress_logs/abstractions.jl

@@ -3,4 +3,4 @@
 
 Abstract type to hold progress logs for differnt algorithms.
 """
-abstract type AbstractProgressLog end
+abstract type AbstractProgressLog end

src/progress_logs/benders_training_iterations.jl

@@ -55,20 +55,23 @@ function start_iteration!(progress::BendersTrainingIterationsLog)
     push!(progress.LB, 0.0)
     push!(progress.UB, 0.0)
     progress.current_iteration += 1
+    return nothing
 end
 
 function report_current_bounds(progress::BendersTrainingIterationsLog)
-    next(progress.progress_table, 
+    next(progress.progress_table,
         [
             progress.current_iteration,
             current_lower_bound(progress),
             current_upper_bound(progress),
             current_gap(progress),
             time() - progress.start_time,
-        ]
+        ],
     )
+    return nothing
 end
 
 function finish_training!(progress::BendersTrainingIterationsLog)
     finalize(progress.progress_table)
-end
+    return nothing
+end

src/progress_logs/deterministic_equivalent.jl

@@ -4,4 +4,5 @@ function DeterministicEquivalentLog(num_scenarios::Int)
     println(" ")
     println("Number of stages: 2")
     println("Number of scenarios: ", num_scenarios)
+    return nothing
 end