linting and compat updates (#148)

Author: jalving

Project.toml

@@ -1,6 +1,6 @@
 name = "Plasmo"
 uuid = "d3f7391f-f14a-50cc-bbe4-76a32d1bad3c"
-version = "0.7.0"
+version = "0.7.1"
 authors = ["Jordan Jalving <[email protected]>"]
 repo = "https://github.com/plasmo-dev/Plasmo.jl.git"
 
@@ -24,12 +24,12 @@ UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 DataStructures = "0.18, 0.19"
 DistributedArrays = "0.6"
 GraphOptInterface = "0.1"
-Graphs = "1"
+Graphs = "1.8"
 JuMP = "1.2"
 MathOptInterface = "1.6"
 Reexport = "1"
 Requires = "1"
-julia = "1"
+julia = "1.6"
 
 [extras]
 HiGHS = "87dc4568-4c63-4d18-b0c0-bb2238e4078b"

docs/make.jl

@@ -27,14 +27,14 @@ makedocs(;
         "API Documentation" => "documentation/api_docs.md",
         "Distributed Memory" => [
             "Introduction" => "documentation/distributed.md",
-            "Quickstart" => "documentation/distributed_quickstart.md"
+            "Quickstart" => "documentation/distributed_quickstart.md",
         ],
         "Tutorials" => [
             "Supply Chain Optimization" => "tutorials/supply_chain.md",
             "Multi-Horizon Model Predictive Control" => "tutorials/MHMPC.md",
             "Optimal Control of a Quadcopter" => "tutorials/quadcopter.md",
             "Hierarchical HVAC Optimization" => "tutorials/HVAC.md",
-            "Optimal Control of a Natural Gas Network" => "tutorials/gas_pipeline.md"
+            "Optimal Control of a Natural Gas Network" => "tutorials/gas_pipeline.md",
         ],
     ],
 )

examples/01_create_optigraph.jl

@@ -1,7 +1,7 @@
 using Plasmo
 using Ipopt
 
-graph = OptiGraph(;name=:graph)
+graph = OptiGraph(; name=:graph)
 
 # add nodes to a OptiGraph
 n1 = add_node(graph)
@@ -55,4 +55,4 @@ for constraint_type in list_of_constraint_types(graph)
     for con in cons
         println("($con) = $(dual(con))")
     end
-end
+end

examples/02_create_nested_optigraph.jl

@@ -2,7 +2,7 @@ using Plasmo
 using Ipopt
 
 function add_model(graph::OptiGraph)
-	node = add_node(graph)
+    node = add_node(graph)
     @variable(node, x >= 0)
     @variable(node, y >= 1)
     @constraint(node, x + y <= 5)
@@ -11,16 +11,16 @@ function add_model(graph::OptiGraph)
 end
 
 # the top-level graph
-graph = OptiGraph(;name=:my_graph)
+graph = OptiGraph(; name=:my_graph)
 
 # subgraph 1
-subgraph1 = OptiGraph(;name=:sg1)
+subgraph1 = OptiGraph(; name=:sg1)
 n1 = add_model(subgraph1)
 n2 = add_model(subgraph1)
 @linkconstraint(subgraph1, n1[:x] == n2[:x])
 
 # subgraph 2
-subgraph2 = OptiGraph(;name=:sg2)
+subgraph2 = OptiGraph(; name=:sg2)
 n3 = add_model(subgraph2)
 n4 = add_model(subgraph2)
 @linkconstraint(subgraph2, n3[:x] == n4[:x])
@@ -44,4 +44,4 @@ println("n2[:x]= ", value(graph, n2[:x]))
 println("n3[:x]= ", value(graph, n3[:x]))
 println("n4[:x]= ", value(graph, n4[:x]))
 
-println("objective = ", objective_value(graph))
+println("objective = ", objective_value(graph))

examples/03_aggregate_optigraph.jl

@@ -37,4 +37,4 @@ optimize!(agg_graph)
 # use the reference map to look up values on the aggregate node
 println("n1[:x] = ", value(reference_map[n1[:x]]))
 println("n2[:x] = ", value(reference_map[n2[:x]]))
-println("n1[:z] = ", value(reference_map[n1[:z]]))
+println("n1[:z] = ", value(reference_map[n1[:z]]))

examples/04_graph_functions.jl

@@ -3,7 +3,7 @@ using Graphs
 using HiGHS
 
 function create_optigraph(name)
-    graph = OptiGraph(;name=name)
+    graph = OptiGraph(; name=name)
     @optinode(graph, nodes[1:3])
 
     # node 1
@@ -35,7 +35,7 @@ end
 
 ### create optigraph
 
-graph = OptiGraph(;name=:graph)
+graph = OptiGraph(; name=:graph)
 
 graph1 = create_optigraph(:sg1)
 graph2 = create_optigraph(:sg2)
@@ -69,7 +69,7 @@ all_neighbors(projection, n1)
 
 # query the neighbors to `n1` in `graph1`
 subproj1 = hyper_projection(graph1)
-all_neighbors(subproj1, n1)          
+all_neighbors(subproj1, n1)
 
 # create an induced subgraph from a given set of nodes
 induced_graph = induced_subgraph(projection, [n1, n2, n3])
@@ -85,4 +85,4 @@ optimize!(expanded_graph)
 
 # nodes store solution for each graph
 println("value(induced_graph, n1[:x]): ", value(induced_graph, n1[:x]))
-println("value(expanded_graph, n1[:x]) ", value(expanded_graph, n1[:x]))
+println("value(expanded_graph, n1[:x]) ", value(expanded_graph, n1[:x]))

examples/05_partitioning_optigraphs.jl

@@ -118,4 +118,3 @@ new_graph = assemble_optigraph(partition)
 @objective(new_graph, Min, sum(node[:x] for node in nodes))
 set_optimizer(new_graph, Ipopt.Optimizer)
 optimize!(new_graph)
-

examples/06_plotting_optigraphs.jl

@@ -1,5 +1,6 @@
 using Plasmo
-using Plots; pyplot()
+using Plots;
+pyplot()
 using PlasmoPlots
 
 graph = OptiGraph()

examples/07_remote_optigraphs.jl

@@ -14,7 +14,7 @@ end
 end
 
 # Instantiate optigraph
-rg = Plasmo.RemoteOptiGraph(worker=2)
+rg = Plasmo.RemoteOptiGraph(; worker=2)
 
 @optinode(rg, n1)
 @optinode(rg, n2)
@@ -47,7 +47,7 @@ optimize!(rg)
 remote_obj = JuMP.objective_function(rg)
 
 # Define another graph and add nodes
-rg2 = Plasmo.RemoteOptiGraph(worker = 2)
+rg2 = Plasmo.RemoteOptiGraph(; worker=2)
 
 @optinode(rg2, n3)
 @optinode(rg2, n4)
@@ -58,9 +58,9 @@ rg2 = Plasmo.RemoteOptiGraph(worker = 2)
 
 # Add subgraphs to `rg` using two different methods
 Plasmo.add_subgraph(rg, rg2)
-rg3 = Plasmo.add_subgraph(rg, worker = 2)
+rg3 = Plasmo.add_subgraph(rg; worker=2)
 
 @optinode(rg3, n5)
 @variable(n5, x5)
 
-@linkconstraint(rg, x + x3 + rg3[:n5][:x5] == 0);
+@linkconstraint(rg, x + x3 + rg3[:n5][:x5] == 0);

examples/08_distribute_optigraph.jl

@@ -59,7 +59,6 @@ add_subgraph(g, g3)
 @linkconstraint(g, lc2, g1[:n1][:y] + g3[:n2][:x] >= -2)
 @linkconstraint(g, lc3, g2[:n2][:y] - g3[:n1][:x] == 0)
 
-workers = [2,2,2]
+workers = [2, 2, 2]
 
 rg = Plasmo.distribute_graph(g, workers)
-