Update

TODO:

- write tests for the constructors of layers that use vector of nodes as vertices and vectors of 2-tuples of MultilayerVertexs as edges

- Bring the changes to the Interlayer

Co-Authored-By: Pietro Monticone <38562595+pitmonticone@users.noreply.github.com>
Co-Authored-By: Claudio Moroni <43729990+ClaudMor@users.noreply.github.com>

Author: 3 people

src/MultilayerGraphs.jl

@@ -59,6 +59,7 @@ export
     mv_outneighbors,
     neighbors,
     mv_neighbors,
+    get_v,
     edgetype,
     has_edge,
     ne,

src/abstractmultilayerugraph.jl

@@ -272,13 +272,10 @@ function get_subgraph(
         v for (v, mv) in collect(mg.v_V_associations) if mv.layer == descriptor.name
     ])
 
-    _vertices = get_rich_mv.(Ref(mg), vs)#MultilayerVertex{descriptor.name}[]
+    _vertices = get_rich_mv.(Ref(mg), vs)
 
-    #=     for (v,mv) in zip(vs, getindex.(Ref(mg.v_V_associations),vs))
-            push!(_vertices, get_rich_mv(mg, v)) #MV(mv.node, mv.layer, mg.v_metadata_dict[v] )
-        end
-     =#
-    edge_list = MultilayerEdge{U}[]#MultilayerEdge{U}[MultilayerEdge(src, vertex(halfedge),  weight(halfedge), metadata(halfedge)) for (src,halfedge) in zip(_vertices,mg.fadjlist[vs]) if vertex(halfedge).layer == descriptor.name && get_v(mg, vertex(halfedge)) >= get_v(mg,src) ]
+
+    edge_list = MultilayerEdge{U}[]
 
     for (src_v, halfedges_from_src) in zip(vs, getindex.(Ref(mg.fadjlist), vs))
         src_bare_V = mg.v_V_associations[src_v]

src/subgraphs/abstractsubgraph.jl

@@ -135,7 +135,7 @@ end
 """
     get_v(subgraph::AbstractSubGraph, V::MultilayerVertex)
 
-Return `v` associated with `V`. 
+Return the integer label `v` associated to `MultilayerVertex` `V` within `subgraph`. Useful for indexing the weight matrix of `subgraph`. 
 """
 function get_v(subgraph::AbstractSubGraph, V::MultilayerVertex)
     # Convert V to a bare vertex

src/subgraphs/layer.jl

@@ -62,8 +62,8 @@ Constructor for `Layer`.
 """
 function Layer(
     descriptor::LayerDescriptor{T},
-    vertices::Union{Vector{MultilayerVertex{nothing}}, Vector{Node}},
-    edge_list::Union{Vector{<:MultilayerEdge}, Vector{NTuple{2, <:MultilayerVertex}}}
+    vertices::Union{<:Vector{<:MultilayerVertex}, Vector{Node}},
+    edge_list::Union{Vector{<:MultilayerEdge}, Vector{Tuple{ MultilayerVertex{nothing}, MultilayerVertex{nothing}}}}
 ) where {T<:Integer}
     # First check that the vertices are of the correct type
     if hasproperty(eltype(vertices), :parameters)
@@ -199,7 +199,7 @@ function Layer(
 
     @assert(ne <= maxe, "The number of required edges, $ne, is greater than the number of edges the provided graph supports i.e. $maxe" )
 
-    edge_list = NTuple{2, MultilayerVertex{nothing}}[]  #MultilayerEdge
+    edge_list = NTuple{2, MultilayerVertex}[]  #MultilayerEdge
     already_chosen = Dict{MultilayerVertex, Vector{MultilayerVertex}}()
 
     max_links_per_vertex = directed ? _nv : _nv-1
@@ -243,7 +243,7 @@ function Layer(
         default_edge_metadata   = default_edge_metadata,
     )
 
-    edge_list = [rand() < 0.5 ? me : reverse(me) for me in edge_list]
+    edge_list = [rand() < 0.5 ? tup : reverse(tup) for tup in edge_list]
     layer = Layer(descriptor, vertices, edge_list)
 
     return layer
@@ -494,7 +494,7 @@ Returns an directed `Layer` with given `indegree_sequence` and `outdegree_sequen
 
     equivalent_graph = kleitman_wang_graph_generator(indegree_sequence, outdegree_sequence)
 
-    edge_list = NTuple{2, MultilayerVertex}[]
+    edge_list = NTuple{2, MultilayerVertex{nothing}}[]
 
     if @isdefined(V)
         for edge in edges(equivalent_graph)

test/layer.jl

@@ -108,13 +108,7 @@ rem_edge!(layer, rand_mv_1, rand_mv_2)
 @test rem_edge!(layer, rand_mv_1, rand_mv_2)
 @test add_edge!(layer, rand_mv_1, rand_mv_2, 3.14)
 @test has_edge(layer, rand_mv_1, rand_mv_2)
-@test layer.graph.weights[
-        layer.v_V_associations(rand_mv_1), layer.v_V_associations(rand_mv_2)
-    ] ==
-    layer.graph.weights[
-        layer.v_V_associations(rand_mv_2), layer.v_V_associations(rand_mv_1)
-    ] ==
-    3.14
+@test Graphs.weights(layer)[get_v(layer, rand_mv_1), get_v(layer, rand_mv_2) ] == Graphs.weights(layer)[get_v(layer, rand_mv_2), get_v(layer, rand_mv_1) ] == 3.14
 # Test uniform add_vertex!
 @test rem_vertex!(layer, rand_mv_1)
 @test !has_vertex(layer, rand_mv_1)
@@ -136,9 +130,7 @@ rem_edge!(layer, rand_mv_1, rand_mv_2)
 @test add_edge!(layer, rand_mv_1, rand_mv_2, weight=3.14, metadata=())
 @test has_edge(layer, rand_mv_1, rand_mv_2)
 # Why do I have to switch the vertices? 
-@test layer.graph.weights[
-    layer.v_V_associations(rand_mv_2), layer.v_V_associations(rand_mv_1)
-] == 3.14
+@test Graphs.weights(layer)[get_v(layer, rand_mv_1), get_v(layer, rand_mv_2) ] == 3.14
 # test hybrid add_edge!
 rem_edge!(layer, rand_mv_1, rand_mv_2)
 @test add_edge!(layer, rand_mv_1, rand_mv_2, 3.14)