updates in graph_traversal

README.md

@@ -117,7 +117,7 @@ save("mygraph.jgz", g, "mygraph", compress=true)
 
 - **distance:** eccentricity, diameter, periphery, radius, center
 
-- **connectivity:** strongly- and weakly-connected components, bipartite checks, condensation, attracting components
+- **connectivity:** strongly- and weakly-connected components, bipartite checks, condensation, attracting components, neighborhood
 
 - **operators:** complement, reverse, reverse!, union, join, intersect, difference,
 symmetric difference, blkdiag, induced subgraphs, products (cartesian/scalar)

doc/basicmeasures.md

@@ -186,3 +186,17 @@ common_neighbors(g::Union{LightGraphs.DiGraph,LightGraphs.Graph}, u::Int64, v::I
 ```
 Returns the neighbors common to vertices `u` and `v` in `g`.
 
+### neighborhood
+```julia
+neighborhood(g, v::Int, d::Int; dir=:out)
+```
+
+Returns a vector of the vertices in `g` at distance less or equal to `d` from `v`. If `g` is a `DiGraph` the `dir` optional argument specifies the edge direction the edge direction with respect to `v` (i.e. `:in` or `:out`) to be considered.
+
+### egonet
+```julia
+egonet(g, v::Int, d::Int; dir=:out)
+```
+
+Returns the subgraph of `g` induced by the neighbors of `v` up to distance `d`. If `g` is a `DiGraph` the `dir` optional argument specifies the edge direction the edge direction with respect to `v` (i.e. `:in` or `:out`) to be considered. This is equivalent to `induced_subgraph(g, neighborhood(g, v, d, dir=dir)).`
+

doc/build.jl

@@ -133,7 +133,8 @@ types:
 
 ## Neighbors and Degree
 
-{{degree, indegree, outdegree, Δ, δ, Δout, δout, δin, Δin, degree_histogram, density, neighbors, in_neighbors, all_neighbors, common_neighbors}}
+{{degree, indegree, outdegree, Δ, δ, Δout, δout, δin, Δin, degree_histogram, density, neighbors,
+    in_neighbors, all_neighbors, common_neighbors, neighborhood, egonet}}
 """
 
 @file "centrality.md" """
@@ -354,7 +355,9 @@ Any graph traversal  will traverse an edge only if it is present in the graph. W
 ## Connectivity / Bipartiteness
 `Graph connectivity` functions are defined on both undirected and directed graphs:
 
-{{is_connected, is_strongly_connected, is_weakly_connected, connected_components, strongly_connected_components, weakly_connected_components, has_self_loop, attracting_components, is_bipartite, condensation, period}}
+{{is_connected, is_strongly_connected, is_weakly_connected, connected_components,
+ strongly_connected_components, weakly_connected_components, has_self_loop,
+ attracting_components, is_bipartite, condensation, period, neighborhood}}
 
 ## Cycle Detection
 In graph theory, a cycle is defined to be a path that starts from some vertex

doc/index.md

@@ -118,7 +118,7 @@ save("mygraph.jgz", g, "mygraph", compress=true)
 
 - **distance:** eccentricity, diameter, periphery, radius, center
 
-- **connectivity:** strongly- and weakly-connected components, bipartite checks, condensation, attracting components
+- **connectivity:** strongly- and weakly-connected components, bipartite checks, condensation, attracting components, neighborhood
 
 - **operators:** complement, reverse, reverse!, union, join, intersect, difference,
 symmetric difference, blkdiag, induced subgraphs, products (cartesian/scalar)

doc/pathing.md

@@ -33,8 +33,9 @@ This function is a high level wrapper around bfs_tree!, use that function for mo
 
 ### dfs_tree
 ```julia
-dfs_tree(g::Union{LightGraphs.DiGraph,LightGraphs.Graph}, s::Int64)
+dfs_tree(g, s::Int)
 ```
+
 Provides a depth-first traversal of the graph `g` starting with source vertex `s`, and returns a directed acyclic graph of vertices in the order they were discovered.
 
 ### maximum_adjacency_visit
@@ -62,9 +63,9 @@ Performs a [self-avoiding walk](https://en.wikipedia.org/wiki/Self-avoiding_walk
 `Graph connectivity` functions are defined on both undirected and directed graphs:
 ### is_connected
 ```julia
-is_connected(g::LightGraphs.Graph)
-is_connected(g::LightGraphs.DiGraph)
+is_connected(g)
 ```
+
 Returns `true` if `g` is connected. For DiGraphs, this is equivalent to a test of weak connectivity.
 
 ### is_strongly_connected
@@ -83,7 +84,8 @@ Returns `true` if the undirected graph of `g` is connected.
 ```julia
 connected_components(g)
 ```
-Returns the [connected components](https://en.wikipedia.org/wiki/Connectivity_(graph_theory)) of an undirected graph `g` as a vector of components, each represented by a vector of vectors of vertices belonging to the component.
+
+Returns the [connected components](https://en.wikipedia.org/wiki/Connectivity_(graph_theory)) of `g` as a vector of components, each represented by a vector of vertices belonging to the component.
 
 ### strongly_connected_components
 ```julia
@@ -111,10 +113,11 @@ Returns a vector of vectors of integers representing lists of attracting compone
 
 ### is_bipartite
 ```julia
-is_bipartite(g::Union{LightGraphs.DiGraph,LightGraphs.Graph})
-is_bipartite(g::Union{LightGraphs.DiGraph,LightGraphs.Graph}, s::Int64)
+is_bipartite(g)
+is_bipartite(g, v)
 ```
-Will return `true` if graph `g` is [bipartite](https://en.wikipedia.org/wiki/Bipartite_graph).
+
+Will return `true` if graph `g` is [bipartite](https://en.wikipedia.org/wiki/Bipartite_graph). If a node `v` is specified, only the connected component to which it belongs is considered.
 
 ### condensation
 ```julia
@@ -131,13 +134,21 @@ period(g::LightGraphs.DiGraph)
 ```
 Computes the (common) period for all nodes in a strongly connected graph.
 
+### neighborhood
+```julia
+neighborhood(g, v::Int, d::Int; dir=:out)
+```
+
+Returns a vector of the vertices in `g` at distance less or equal to `d` from `v`. If `g` is a `DiGraph` the `dir` optional argument specifies the edge direction the edge direction with respect to `v` (i.e. `:in` or `:out`) to be considered.
+
 ## Cycle Detection
 In graph theory, a cycle is defined to be a path that starts from some vertex
 `v` and ends up at `v`.
 ### is_cyclic
 ```julia
-is_cyclic(graph::Union{LightGraphs.DiGraph,LightGraphs.Graph})
+is_cyclic(g)
 ```
+
 Tests whether a graph contains a cycle through depth-first search. It returns `true` when it finds a cycle, otherwise `false`.
 
 ## Shortest-Path Algorithms
@@ -184,16 +195,17 @@ Note that this algorithm may return a large amount of data (it will allocate on
 ## Path discovery / enumeration
 ### gdistances
 ```julia
-gdistances(graph::Union{LightGraphs.DiGraph,LightGraphs.Graph}, sources)
+gdistances(g, source) -> dists
 ```
-Returns the geodesic distances of graph `g` from source vertex `s` or a set of source vertices `ss`.
+
+Returns a vector filled with the geodesic distances of vertices in  `g` from vertex/vertices `source`. For vertices in disconnected components the default distance is -1.
 
 ### gdistances!
 ```julia
-gdistances!{DMap}(graph::Union{LightGraphs.DiGraph,LightGraphs.Graph}, s::Int64, dists::DMap)
-gdistances!{DMap}(graph::Union{LightGraphs.DiGraph,LightGraphs.Graph}, sources::AbstractArray{Int64,1}, dists::DMap)
+gdistances!(g, source, dists) -> dists
 ```
-Returns the geodesic distances of graph `g` from source vertex `s` or a set of source vertices `ss`.
+
+Fills `dists` with the geodesic distances of vertices in  `g` from vertex/vertices `source`. `dists` can be either a vector or a dictionary.
 
 ### enumerate_paths
 ```julia

src/LightGraphs.jl

@@ -23,9 +23,9 @@ catch
 end
 
 import Base: write, ==, <, *, isless, issubset, complement, union, intersect,
-            reverse, reverse!, blkdiag, getindex, show, print, copy, in,
+            reverse, reverse!, blkdiag, getindex, setindex!, show, print, copy, in,
             sum, size, sparse, eltype, length, ndims, issym, transpose,
-            ctranspose, join, start, next, done, eltype
+            ctranspose, join, start, next, done, eltype, get
 
 
 # core
@@ -48,7 +48,7 @@ crosspath,
 # graph visit
 SimpleGraphVisitor, TrivialGraphVisitor, LogGraphVisitor,
 discover_vertex!, open_vertex!, close_vertex!,
-examine_neighbor!, visited_vertices, traverse_graph, traverse_graph_withlog,
+examine_neighbor!, visited_vertices, traverse_graph!, traverse_graph_withlog,
 
 # bfs
 BreadthFirst, gdistances, gdistances!, bfs_tree, is_bipartite, bipartite_map,
@@ -62,7 +62,7 @@ randomwalk, saw, non_backtracking_randomwalk,
 # connectivity
 connected_components, strongly_connected_components, weakly_connected_components,
 is_connected, is_strongly_connected, is_weakly_connected, period,
-condensation, attracting_components,
+condensation, attracting_components, neighborhood, egonet,
 
 # cliques
 maximal_cliques,
@@ -100,7 +100,7 @@ maximum_weight_maximal_matching, MatchingResult,
 # randgraphs
 erdos_renyi, watts_strogatz, random_regular_graph, random_regular_digraph, random_configuration_model,
 StochasticBlockModel, make_edgestream, nearbipartiteSBM, blockcounts, blockfractions,
-stochastic_block_model, 
+stochastic_block_model,
 
 #community
 modularity, community_detection_nback, core_periphery_deg,

src/connectivity.jl

@@ -2,7 +2,10 @@
 # licensing details.
 
 
-"""connected_components! produces a label array of components
+"""
+    connected_components!(label::Vector{Int}, g::SimpleGraph)
+
+Fills `label` with the `id` of the connected component to which it belongs.
 
 Arguments:
     label: a place to store the output
@@ -21,14 +24,14 @@ function connected_components!(label::Vector{Int}, g::SimpleGraph)
     # passed to components(a)
     nvg = nv(g)
     visitor = LightGraphs.ComponentVisitorVector(label, 0)
-    colormap = zeros(Int,nvg)
-    que = Vector{Int}()
-    sizehint!(que, nvg)
+    colormap = fill(0, nvg)
+    queue = Vector{Int}()
+    sizehint!(queue, nvg)
     for v in 1:nvg
         if label[v] == 0
             visitor.labels[v] = v
             visitor.seed = v
-            traverse_graph(g, BreadthFirst(), v, visitor; colormap=colormap, que=que)
+            traverse_graph!(g, BreadthFirst(), v, visitor; vertexcolormap=colormap, queue=queue)
         end
     end
     return label
@@ -51,25 +54,25 @@ function components_dict(labels::Vector{Int})
     return d
 end
 
-"""components(labels) converts an array of labels to a Vector{Vector{Int}} of components
+"""
+    components(labels::Vector{Int})
+
+Converts an array of labels to a Vector{Vector{Int}} of components
 
 Arguments:
     c = labels[i] => vertex i belongs to component c.
 Output:
     vs = c[i] => vertices in vs belong to component i.
-    a = d[i] => if label[v[j]]==i then j in c[a] end
+    a = d[i] => if labels[v]==i then v in c[a] end
 """
 function components(labels::Vector{Int})
     d = Dict{Int, Int}()
     c = Vector{Vector{Int}}()
     i = 1
     for (v,l) in enumerate(labels)
-        index = get(d, l, i)
-        d[l] = index
+        index = get!(d, l, i)
         if length(c) >= index
-            vec = c[index]
-            push!(vec, v)
-            c[index] = vec
+            push!(c[index], v)
         else
             push!(c, [v])
             i += 1
@@ -78,19 +81,26 @@ function components(labels::Vector{Int})
     return c, d
 end
 
-"""Returns the [connected components](https://en.wikipedia.org/wiki/Connectivity_(graph_theory))
-of an undirected graph `g` as a vector of components, each represented by a
-vector of vectors of vertices belonging to the component.
 """
-function connected_components(g)
+    connected_components(g)
+
+Returns the [connected components](https://en.wikipedia.org/wiki/Connectivity_(graph_theory))
+of `g` as a vector of components, each represented by a
+vector of vertices belonging to the component.
+"""
+function connected_components(g::SimpleGraph)
     label = zeros(Int, nv(g))
     connected_components!(label, g)
     c, d = components(label)
     return c
 end
 
-"""Returns `true` if `g` is connected.
-For DiGraphs, this is equivalent to a test of weak connectivity."""
+"""
+    is_connected(g)
+
+Returns `true` if `g` is connected.
+For DiGraphs, this is equivalent to a test of weak connectivity.
+"""
 is_connected(g::Graph) = length(connected_components(g)) == 1
 is_connected(g::DiGraph) = is_weakly_connected(g)
 
@@ -123,7 +133,7 @@ function discover_vertex!(vis::TarjanVisitor, v)
 end
 
 function examine_neighbor!(vis::TarjanVisitor, v, w, w_color::Int, e_color::Int)
-    if w_color > 0 # 1 means added seen, but not explored; 2 means closed
+    if w_color != 0 # != 0 means seen
         while vis.index[w] > 0 && vis.index[w] < vis.lowlink[end]
             pop!(vis.lowlink)
         end
@@ -150,7 +160,7 @@ function strongly_connected_components(g::DiGraph)
     for v in vertices(g)
         if cmap[v] == 0 # 0 means not visited yet
             visitor = TarjanVisitor(nvg)
-            traverse_graph(g, DepthFirst(), v, visitor, vertexcolormap=cmap)
+            traverse_graph!(g, DepthFirst(), v, visitor, vertexcolormap=cmap)
             for component in visitor.components
                 push!(components, component)
             end
@@ -227,3 +237,46 @@ function attracting_components(g::DiGraph)
     end
     return scc[attracting]
 end
+
+type NeighborhoodVisitor <: SimpleGraphVisitor
+    d::Int
+    neigs::Vector{Int}
+end
+
+NeighborhoodVisitor(d::Int) = NeighborhoodVisitor(d, Vector{Int}())
+
+function examine_neighbor!(visitor::NeighborhoodVisitor, u::Int, v::Int, ucolor::Int, vcolor::Int, ecolor::Int)
+    -ucolor > visitor.d && return false # color is negative for not-closed vertices
+    if vcolor == 0
+        push!(visitor.neigs, v)
+    end
+    return true
+end
+
+
+"""
+    neighborhood(g, v::Int, d::Int; dir=:out)
+
+Returns a vector of the vertices in `g` at distance less or equal to `d`
+from `v`. If `g` is a `DiGraph` the `dir` optional argument specifies the edge direction
+the edge direction with respect to `v` (i.e. `:in` or `:out`) to be considered.
+"""
+function neighborhood(g::SimpleGraph, v::Int, d::Int; dir=:out)
+    @assert d >= 0 "Distance has to be greater then zero."
+    visitor = NeighborhoodVisitor(d)
+    push!(visitor.neigs, v)
+    traverse_graph!(g, BreadthFirst(), v, visitor,
+        vertexcolormap=Dict{Int,Int}(), dir=dir)
+    return visitor.neigs
+end
+
+
+"""
+    egonet(g, v::Int, d::Int; dir=:out)
+
+Returns the subgraph of `g` induced by the neighbors of `v` up to distance
+`d`. If `g` is a `DiGraph` the `dir` optional argument specifies
+the edge direction the edge direction with respect to `v` (i.e. `:in` or `:out`)
+to be considered. This is equivalent to `induced_subgraph(g, neighborhood(g, v, d, dir=dir)).`
+"""
+egonet(g::SimpleGraph, v::Int, d::Int; dir=:out) = induced_subgraph(g, neighborhood(g, v, d, dir=dir))