clean ups

CHANGELOG.md

@@ -5,6 +5,7 @@ LaplacianOpt.jl Change Log
 - Added CITATION.bib
 - Added support for Gurobi MIP solver in `examples/solver.jl` 
 - Updated `LO` to `LOpt`
+- `lopt_model.jl` function calls updated with `LOpt`
 - Minor docs cleanups
 
 ### v0.1.4 

docs/README.md

@@ -1,7 +1,7 @@
 # Documentation for LaplacianOpt.jl
 
 ## Installation
-LaplacianOpt.jl's documentation is generated using [Documenter.jl](https://github.com/JuliaDocs/Documenter.jl). To install it, run the following command in a Julia session:
+LaplacianOpt's documentation is generated using [Documenter.jl](https://github.com/JuliaDocs/Documenter.jl). To install it, run the following command in a Julia session:
 
 ```julia
 Pkg.add("Documenter")

src/constraints.jl

@@ -111,7 +111,6 @@ function constraint_eigen_cuts_on_full_matrix(W_val::Matrix{Float64}, cb_cuts, l
         else
 
             Memento.warn(_LOGGER, "Eigen cut corresponding to the negative eigenvalue could not be added")
-
         end
     end
 

src/lopt_model.jl

@@ -2,41 +2,41 @@ function build_LOModel(data::Dict{String, Any})
 
     lom = LaplacianOptModel(data)
 
-    variable_LOModel(lom)
+    LOpt.variable_LOModel(lom)
 
     if lom.data["solution_type"] == "exact"
-        constraint_LOModel(lom)
+        LOpt.constraint_LOModel(lom)
     end
 
-    objective_LOModel(lom)
+    LOpt.objective_LOModel(lom)
 
     return lom
 end
 
 function variable_LOModel(lom::LaplacianOptModel)
 
-    variable_lifted_W_matrix(lom)
-    variable_edge_onoff(lom)
-    variable_algebraic_connectivity(lom)
+    LOpt.variable_lifted_W_matrix(lom)
+    LOpt.variable_edge_onoff(lom)
+    LOpt.variable_algebraic_connectivity(lom)
 
     return
 end
 
 function constraint_LOModel(lom::LaplacianOptModel)
 
-    constraint_build_W_var_matrix(lom)
+    LOpt.constraint_build_W_var_matrix(lom)
 
-    constraint_topology_no_self_loops(lom)
-    constraint_topology_vertex_cutset(lom)
-    constraint_topology_total_edges(lom)
+    LOpt.constraint_topology_no_self_loops(lom)
+    LOpt.constraint_topology_vertex_cutset(lom)
+    LOpt.constraint_topology_total_edges(lom)
 
-    constraint_lazycallback_wrapper(lom)
+    LOpt.constraint_lazycallback_wrapper(lom)
 
     return
 end
 
 function objective_LOModel(lom::LaplacianOptModel)
-    objective_maximize_algebraic_connectivity(lom)
+    LOpt.objective_maximize_algebraic_connectivity(lom)
 
     return
 end
@@ -70,7 +70,7 @@ function optimize_LOModel!(lom::LaplacianOptModel; optimizer=nothing)
 
     Memento.debug(_LOGGER, "JuMP model optimize time: $(time() - start_time)")
 
-    lom.result = build_LOModel_result(lom, solve_time) 
+    lom.result = LOpt.build_LOModel_result(lom, solve_time) 
 
     return lom.result
 end
@@ -84,7 +84,7 @@ function run_LOpt_model(params::Dict{String, Any}, lom_optimizer::MOI.OptimizerW
     result_lopt = LOpt.optimize_LOModel!(model_lopt, optimizer = lom_optimizer)
 
     if visualize_solution
-        LaplacianOpt.visualize_solution(result_lopt, data, visualizing_tool = visualizing_tool)
+        LOpt.visualize_solution(result_lopt, data, visualizing_tool = visualizing_tool)
     end
 
     return result_lopt
@@ -98,7 +98,7 @@ function run_MaxSpanTree_model(params::Dict{String, Any}, lom_optimizer::MOI.Opt
     result_mst = LOpt.optimize_LOModel!(model_mst, optimizer = lom_optimizer)
 
     if visualize_solution
-        LaplacianOpt.visualize_solution(result_mst, data, visualizing_tool = visualizing_tool)
+        LOpt.visualize_solution(result_mst, data, visualizing_tool = visualizing_tool)
     end
 
     return result_mst
@@ -109,43 +109,43 @@ function build_MaxSpanTree_model(data::Dict{String, Any}, lazy_callback::Bool)
 
     m_mst = LaplacianOptModel(data)
 
-    variable_MaxSpanTree_model(m_mst, lazy_callback)
+    LOpt.variable_MaxSpanTree_model(m_mst, lazy_callback)
 
-    constraint_MaxSpanTree_model(m_mst, lazy_callback)
+    LOpt.constraint_MaxSpanTree_model(m_mst, lazy_callback)
 
-    objective_MaxSpanTree_model(m_mst)
+    LOpt.objective_MaxSpanTree_model(m_mst)
 
     return m_mst
 end
 
 function objective_MaxSpanTree_model(lom::LaplacianOptModel)
 
-    objective_maximize_spanning_tree_cost(lom)
+    LOpt.objective_maximize_spanning_tree_cost(lom)
 
     return
 end
 
 function variable_MaxSpanTree_model(lom::LaplacianOptModel, lazy_callback::Bool)
 
-    variable_edge_onoff(lom)
+    LOpt.variable_edge_onoff(lom)
 
     if !lazy_callback
-        variable_multi_commodity_flow(lom)
+        LOpt.variable_multi_commodity_flow(lom)
     end
 
     return
 end
 
 function constraint_MaxSpanTree_model(lom::LaplacianOptModel, lazy_callback::Bool)
 
-    constraint_topology_no_self_loops(lom)
-    constraint_topology_vertex_cutset(lom)
-    constraint_topology_total_edges(lom)
+    LOpt.constraint_topology_no_self_loops(lom)
+    LOpt.constraint_topology_vertex_cutset(lom)
+    LOpt.constraint_topology_total_edges(lom)
 
     if lazy_callback 
-        constraint_lazycallback_wrapper(lom)
+        LOpt.constraint_lazycallback_wrapper(lom)
     else
-        constraint_topology_multi_commodity_flow(lom)
+        LOpt.constraint_topology_multi_commodity_flow(lom)
     end
 
     return

src/relaxations.jl

@@ -31,8 +31,8 @@ z <= JuMP.upper_bound(x)*y + JuMP.lower_bound(y)*x - JuMP.upper_bound(x)*JuMP.lo
 ```
 """
 function relaxation_bilinear(m::JuMP.Model, xy::JuMP.VariableRef, x::JuMP.VariableRef, y::JuMP.VariableRef)
-    lb_x, ub_x = variable_domain(x)
-    lb_y, ub_y = variable_domain(y)
+    lb_x, ub_x = LOpt.variable_domain(x)
+    lb_y, ub_y = LOpt.variable_domain(y)
 
     if (lb_x == 0) && (ub_x == 1) && ((lb_y != 0) || (ub_y != 1))
 

src/solution.jl

@@ -10,7 +10,7 @@ function build_LOModel_result(lom::LaplacianOptModel, solve_time::Number)
     solution = Dict{String,Any}()
 
     if result_count > 0
-        solution = build_LOModel_solution(lom)
+        solution = LOpt.build_LOModel_solution(lom)
     else
         Memento.warn(_LOGGER, "LaplacianOpt model has no results - solution cannot be built")
     end