Minor fixes (#171)

* Update `unbounded_check!` to correctly bound branch variables excluding the epigraph variable 

* Update default `cp_depth` from 20 to 5

* Fix CI badge in README

Author: DimitriAlston

.gitignore

@@ -1,6 +1,6 @@
+*.cov
 *.jl.cov
 *.jl.*.cov
 *.jl.mem
 *.mem
-*.cov
 docs/build/

README.md

@@ -6,7 +6,7 @@ EAGO is an open-source development environment for **robust and global optimizat
 
 | **PSOR Lab** | **Build Status**                                                                                |
 |:------------:|:-----------------------------------------------------------------------------------------------:|
-| [![](https://img.shields.io/badge/Developed_by-PSOR_Lab-342674)](https://psor.uconn.edu/) | [![Build Status](https://github.com/PSORLab/EAGO.jl/workflows/CI/badge.svg?branch=master)](https://github.com/PSORLab/EAGO.jl/actions?query=workflow%3ACI) [![codecov](https://codecov.io/gh/PSORLab/EAGO.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/PSORLab/EAGO.jl)|
+| [![](https://img.shields.io/badge/Developed_by-PSOR_Lab-342674)](https://psor.uconn.edu/) | [![Build Status](https://github.com/PSORLab/EAGO.jl/actions/workflows/ci.yml/badge.svg?branch=master)](https://github.com/PSORLab/EAGO.jl/actions?query=workflow%3ACI) [![codecov](https://codecov.io/gh/PSORLab/EAGO.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/PSORLab/EAGO.jl)|
 
 | **Documentation**                                                 | **Persistent DOI**                                                                              |
 |:-----------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------:|

src/eago_optimizer/moi_wrapper.jl

@@ -79,7 +79,7 @@ function MOI.add_constraint(m::Optimizer, f::F, s::S) where {F<:Union{SAF,SQF,MO
             model = MOI.Nonlinear.Model()
             backend = MOI.Nonlinear.SparseReverseMode()
             vars = MOI.get(m, MOI.ListOfVariableIndices())
-            evaluator = MOI.Nonlinear.Evaluator(model, backend, vars) 
+            evaluator = MOI.Nonlinear.Evaluator(model, backend, vars)
             m._input_problem._nlp_data = MOI.NLPBlockData(evaluator)
         end
         MOI.Nonlinear.add_constraint(m._input_problem._nlp_data.evaluator.model, f, s)

src/eago_optimizer/optimize/nonconvex/lower_problem.jl

@@ -464,7 +464,7 @@ function lower_problem!(t::ExtensionType, m::GlobalOptimizer{R,S,Q}) where {R,S,
         status = RRS_INFEASIBLE
     end
     if status == RRS_INFEASIBLE
-        m._lower_feasibility  = false
+        m._lower_feasibility = false
         m._lower_objective_value = -Inf
         return
     end

src/eago_optimizer/optimize/nonconvex/stack_management.jl

@@ -257,7 +257,10 @@ function unbounded_check!(m::GlobalOptimizer)
     if m._parameters.unbounded_check
         unbounded_flag = false
         wp = m._working_problem
-        for i = 1:_variable_num(BranchVar(), m)
+        for i in m._branch_to_sol_map
+            if m._epigraph_occurred && i == m._branch_to_sol_map[end]
+                continue
+            end
             if !wp._variable_info[i].has_lower_bound
                 unbounded_flag = true
                 wp._variable_info[i] = VariableInfo(wp._variable_info[i], GT(-1E6)) # Some solvers break if bounds are too large

src/eago_optimizer/optimize/optimize_nonconvex.jl

@@ -238,24 +238,24 @@ $(TYPEDSIGNATURES)
 
 Check for problem convergence.
     
-By default, check if the lower and upper bounds have converged to within absolute
+By default, checks if the lower and upper bounds have converged to within absolute
 and/or relative tolerances.
 """
 function convergence_check(t::ExtensionType, m::GlobalOptimizer)
 
     L = m._lower_objective_value
     U = m._global_upper_bound
-    t = (U - L) <= m._parameters.absolute_tolerance
-    if (U < Inf) && (L > Inf)
-        t |= (abs(U - L)/(max(abs(L), abs(U))) <= m._parameters.relative_tolerance)
+    flag = (U - L) <= m._parameters.absolute_tolerance
+    if (U < Inf) && (L > -Inf)
+        flag |= (abs(U - L)/(max(abs(L), abs(U))) <= m._parameters.relative_tolerance)
     end
-    if t && m._min_converged_value < Inf
+    if flag && m._min_converged_value < Inf
          m._min_converged_value = min(m._min_converged_value, L)
-    else
+    elseif flag
         m._min_converged_value = L
     end
 
-    return t
+    return flag
 end
 convergence_check(m::GlobalOptimizer{R,S,Q}) where {R,S,Q<:ExtensionType} = convergence_check(_ext(m), m)
 
@@ -392,7 +392,7 @@ function global_solve!(m::GlobalOptimizer)
         node_selection!(m)
         print_node!(m)
 
-        # Perform prepocessing and log the time
+        # Perform preprocessing and log the time
         m._last_preprocess_time += @elapsed preprocess!(m)
 
         # Continue if the node has not been proven infeasible
@@ -403,7 +403,7 @@ function global_solve!(m::GlobalOptimizer)
             print_results!(m, true)
 
             # Continue if lower problem is not infeasible and problem
-            # problem has not yet converged
+            # has not yet converged
             if m._lower_feasibility && !convergence_check(m)
 
                 # Solve the upper bounding problem and log the time

src/eago_optimizer/parse.jl

@@ -235,7 +235,7 @@ function reform_epigraph_min!(m::GlobalOptimizer, d::ParsedProblem, f::BufferedQ
     if !_is_input_min(m)
         MOIU.operate!(-, Float64, sqf_obj)
     end
-    d._objective_saf = SAF([SAT(1.0, VI(ηi))], 0.0)    
+    d._objective_saf = SAF([SAT(1.0, VI(ηi))], 0.0)
     push!(sqf_obj.affine_terms, SAT(-1.0, VI(ηi)))
     _constraints(ip, SQF, LT)[CI{SQF,LT}(ip._constraint_count += 1)] = (sqf_obj, LT(0.0))
     push!(wp._sqf_leq, BufferedQuadraticIneq(sqf_obj, LT(0.0)))

src/eago_optimizer/types/global_optimizer.jl

@@ -148,8 +148,8 @@ Base.@kwdef mutable struct EAGOParameters
     absolute_constraint_feas_tolerance::Float64 = 1E-8
 
     # Options for constraint propagation
-    "Depth in B&B tree above which constraint propagation should be disabled (default = 20)"
-    cp_depth::Int = 20
+    "Depth in B&B tree above which constraint propagation should be disabled (default = 5)"
+    cp_depth::Int = 5
     "Number of times to repeat forward-reverse pass routine (default = 3)"
     cp_repetitions::Int = 3
     "Disable constraint propagation if the ratio of new node volume to beginning node volume exceeds

src/eago_script/scrubber.jl

@@ -55,7 +55,7 @@ end
 """
     scrub(f::Function, n::Int, inplace = false)
 
-Replaces storage objects and circumvents assertions that present a UDF from
+Replaces storage objects and circumvents assertions that prevent a UDF from
 being overloaded with subtype Real objects by creating a function which
 overdubs `f` in `ScrubCtx`.
 """
@@ -86,7 +86,7 @@ Applies scrub to every user-defined function in the a `MOI.NLPBlockData` structu
 """
 function scrub!(d::MOI.NLPBlockData)
     error("Function not updated for newest version of EAGO. Please submit an issue.")
-    # Scrub multivariant
+    # Scrub multivariates
     user_ops = d.user_operators
     mvop_num = length(user_ops.multivariate_operator_evaluator)
     for i in 1:mvop_num
@@ -100,7 +100,7 @@ function scrub!(d::MOI.NLPBlockData)
         user_ops.multivariate_operator_evaluator[i] = evalr
     end
 
-    # Scrub univariants
+    # Scrub univariates
     svop_num = length(user_ops.univariate_operator_f)
 
     for i in 1:svop_num