Add layout weights (#105)

docs/src/data_transformations/layouts.md

@@ -64,4 +64,7 @@ The layout algorithm arguments can be also passed in directly through `powerplot
 powerplot(case; layout_algorithm=Spring, iterations=50)
 ```
 
-When using `fixed=true`, a variation of the `SFDP` algorithm is sued that does not update corrdinates with prior coordinates set.  The same arguments arguments as the `SFDP` algorithm can be used to modify the layout.
+When using `fixed=true`, a variation of the `SFDP` algorithm is used that does not update corrdinates with prior coordinates set.  The same arguments arguments as the `SFDP` algorithm can be used to modify the layout.
+
+
+The default weights for edge-type components (branches, dc lines, etc.) are `1.0`.  The default weight for connectors (links from  e.g. generators to buses) is 0.5.  They can be modified by passing the argument `edge_weight` or `connector_weight` to the layout function.  If a component has a `weight` entry in its data dictionary, such as `data["branch"]["1"]["weight"]`, this weight will be used instead.

src/core/data.jl

@@ -31,7 +31,7 @@ function offset_parallel_edges!(data,offset)
 
         dx = xcoord_2 - xcoord_1
         dy = ycoord_2 - ycoord_1
-        normal_direction = (-dy, dx)
+        normal_direction = (-dy, dx)./(sqrt(dx^2+dy^2))
 
         offset_range = range(-offset, offset, length=n_edges)
 

src/layouts/common.jl

@@ -39,12 +39,40 @@ function layout_network(case::Dict{String,<:Any};
     layout_algorithm = kamada_kawai,
     node_types::Array{String,1}=["bus","gen","storage","load"],
     edge_types::Array{String,1}=["switch","branch","dcline","transformer"],
+    connector_weight=0.5,
+    edge_weight=1.0,
     kwargs...
     )
 
     data = deepcopy(case)
     PMG = PowerModelsGraph(data,node_types,edge_types)
 
+    # calculate weights
+    weights = zeros(size(PMG.graph))
+    for ((s,d),(comp_type,comp_id)) in PMG.edge_comp_map
+
+        if haskey(case[comp_type][comp_id],"weight")
+            w = compcase[comp_type][comp_id]["weight"]
+        else
+            w=edge_weight
+        end
+        if w>weights[s,d]
+            weights[s,d]= w
+            weights[d,s]= w
+        end
+    end
+    for ((s,d),(comp_type,comp_id)) in PMG.edge_connector_map
+        if haskey(case[comp_type][comp_id],"weight")
+            w = compcase[comp_type][comp_id]["weight"]
+        else
+            w=connector_weight
+        end
+        if w>weights[s,d]
+            weights[s,d]= w
+            weights[d,s]= w
+        end
+    end
+
     if fixed==true # use fixed-position SFDP layout
         rng = MersenneTwister(1)
 
@@ -60,17 +88,19 @@ function layout_network(case::Dict{String,<:Any};
 
         # Create SFDP layout with fixed nodes
         a = Graphs.adjacency_matrix(PMG.graph)
+        a = a.*weights
         pos = convert(Array,RecursiveArrayTools.VectorOfArray(SFDP_fixed(; fixed = fixed_pos, initialpos=initialpos, kwargs...)(a)))
         positions = [[pos[1,i],pos[2,i]] for i in 1:size(pos,2)]
 
     elseif layout_algorithm ∈ [Shell, SFDP, Buchheim, Spring, Stress, SquareGrid, Spectral]  # Create layout from NetworkLayouts algorithms
         a = Graphs.adjacency_matrix(PMG.graph)
+        a = a.*weights
         pos = convert(Array,RecursiveArrayTools.VectorOfArray(layout_algorithm(;kwargs...)(a)))
         positions = [[pos[1,i],pos[2,i]] for i in 1:size(pos,2)]
 
     elseif layout_algorithm==kamada_kawai
         # create layout using Kamada Kawai algorithm
-        positions = layout_algorithm(PMG; kwargs...)
+        positions = layout_algorithm(PMG; weights=weights, kwargs...)
     else
         Memento.error(_LOGGER, "layout_algorithm `$(layout_algorithm)` not supported.")
     end

src/layouts/kamada_kawaii_layout.jl

@@ -12,7 +12,7 @@
     `
     calculate node positions use Kamada Kawai layout algorithm
 """
-function kamada_kawai(G::PowerModelsGraph, dist::Union{Nothing,AbstractMatrix{<:Real}}=nothing, pos::Union{Nothing,AbstractMatrix{<:Real}}=nothing, weight="weight", scale=1, center=nothing, dim=2; kwargs...)
+function kamada_kawai(G::PowerModelsGraph; dist::Union{Nothing,AbstractMatrix{<:Real}}=nothing, pos::Union{Nothing,AbstractMatrix{<:Real}}=nothing, weights=nothing, scale=1, center=nothing, dim=2, kwargs...)
     graph = G.graph # convert to undirected graph
     nNodes = Graphs.nv(graph)
     if nNodes == 0
@@ -22,7 +22,7 @@ function kamada_kawai(G::PowerModelsGraph, dist::Union{Nothing,AbstractMatrix{<:
     if dist===nothing
         dist=Dict()
         for i in 1:nNodes
-            dist[i]=Graphs.dijkstra_shortest_paths(graph, i).dists
+            dist[i]=Graphs.dijkstra_shortest_paths(graph, i, weights).dists
         end
     end
     dist_mtx = 1e6 * ones(nNodes, nNodes)

test/runtests.jl

@@ -196,8 +196,10 @@ data = PowerModels.parse_file("$(joinpath(dirname(pathof(PowerModels)), ".."))/t
             @test data["dcline"]["1"]["xcoord_2"] == data["branch"]["1"]["xcoord_2"]
 
             offset_parallel_edges!(data,0.05) # offset, ensures coordinates values are different
-            @test isapprox(data["dcline"]["1"]["xcoord_1"] - data["branch"]["1"]["xcoord_1"], .03, atol=1e-1)
-            @test isapprox(data["dcline"]["1"]["xcoord_2"] - data["branch"]["1"]["xcoord_2"], .03, atol=1e-1)
+            dist = sqrt((data["dcline"]["1"]["xcoord_1"] - data["branch"]["1"]["xcoord_1"])^2+
+                (data["dcline"]["1"]["ycoord_1"] - data["branch"]["1"]["ycoord_1"])^2
+            )
+            @test isapprox(dist, 0.05*2; atol=1e-8)
         end
     end