✏️ typo function + general s

docs/src/properties/resilience.md

@@ -31,7 +31,7 @@ with
 
 - $$\langle s \rangle$$ the average weighted degree (computed using `s_mean`),
 - $$\mathcal{S}$$ the symmetry(computed using `symmetry`),
-- $$\mathcal{H}$$ the heterogenity (computed using `heterogenity`).
+- $$\mathcal{H}$$ the heterogeneity (computed using `heterogeneity`).
 
 
 > Goa, J., Barzael, B. and Barabási 2016. Universal resilience patterns in complex networks.
@@ -46,7 +46,7 @@ s_mean
 σ_in
 σ_out
 symmetry
-heterogenity
+heterogeneity
 βeff
 resilience
 ```

src/EcologicalNetworks.jl

@@ -111,8 +111,8 @@ export AJS, EAJS
 # Overlap
 include(joinpath(".", "community/resilience.jl"))
 export βeff, resilience
-export symmetry, heterogenity
-export s_in, s_out, s_mean
+export symmetry, heterogeneity
+export s
 export σ_in, σ_out
 
 # Modularity

src/community/resilience.jl

@@ -3,10 +3,26 @@ Some functions from *Universal resilience patterns in complex networks*
 by Gao et al. (2016)
 =#
 
-using StatsBase: mean, std
+using Statistics: mean, std
 
 """
-    s_in(N::AbstractUnipartiteNetwork)
+    s(N::AbstractUnipartiteNetwork; dims::Union{Nothing,Integer}=nothing)
+
+Computes the average weighted degree. This is proportional to the (weighted)
+density of interactions.
+
+If dims is provided, the incoming (`dims=1`) or outgoing (`dims=2`) is computed.
+"""
+function s(N::AbstractUnipartiteNetwork; dims::Union{Nothing,Integer}=nothing)
+    dims == 1 && return sum(N, dims=2)
+    dims == 2 && return sum(N, dims=1)'
+    if dims == nothing
+        return sum(N) / size(N)[1]
+    end
+end
+#=
+"""
+    s(N::AbstractUnipartiteNetwork; dims)
 
 Computes the vector of incoming weighted degrees of an unipartite network.
 """
@@ -19,13 +35,7 @@ Computes the vector of outgoing weighted degrees of an unipartite network.
 """
 s_out(N::AbstractUnipartiteNetwork) = sum(N.A, dims=1)'
 
-"""
-    s_mean(N::AbstractUnipartiteNetwork)
-
-Computes the average weighted degree. This is proportional to the (weighted)
-density of interactions.
-"""
-s_mean(N::AbstractUnipartiteNetwork) = sum(N.A) / size(N.A, 1)
+=#
 
 """
     σ_in(N::AbstractUnipartiteNetwork)
@@ -61,9 +71,9 @@ to be prey would have a negative symmetry.
 symmetry(N::AbstractUnipartiteNetwork) = (mean(s_in(N) .* s_out(N)) - mean(s_in(N)) * mean(s_out(N))) / (σ_in(N) * σ_out(N))
 
 """
-    heterogenity(N::AbstractUnipartiteNetwork)
+    heterogeneity(N::AbstractUnipartiteNetwork)
 
-Computes the heterogenity for an unipartite network, a topological characteristic
+Computes the heterogeneity for an unipartite network, a topological characteristic
 which quantifies the difference in in- and outgoing degrees between species. It
 is computed as σ_in * σ_out / s_mean. A value of 0 indicates that all species
 have the same (weighted) in- and outdegrees.
@@ -72,7 +82,7 @@ have the same (weighted) in- and outdegrees.
 > Nature 530(7590), 307-312. doi:10.1038/nature16948
 
 """
-heterogenity(N::AbstractUnipartiteNetwork) = (σ_in(N) * σ_out(N)) / s_mean(N)
+heterogeneity(N::AbstractUnipartiteNetwork) = (σ_in(N) * σ_out(N)) / s_mean(N)
 
 """
     βeff(N::AbstractUnipartiteNetwork)

test/community/resilience.jl

@@ -8,15 +8,15 @@ module TestResilience
     @assert s_in(N) ≈ sum(A, dims=2)
     @assert s_out(N) ≈ sum(A, dims=1)'
 
-    @assert βeff(N) ≈ s_mean(N) + symmetry(N) * heterogenity(N)
+    @assert βeff(N) ≈ s_mean(N) + symmetry(N) * heterogeneity(N)
 
     # species only interact with themselves
     Nid = UnipartiteNetwork([true false false false;
                               false true false false;
                               false false true false;
                               false false false true])
 
-    @assert heterogenity(Nid) ≈ 0.0
+    @assert heterogeneity(Nid) ≈ 0.0
     # @assert symmetry(Nid)   NAN
 
     # symetric network
@@ -25,7 +25,7 @@ module TestResilience
                                true false false false;
                                true false false false])
     @assert symmetry(Nsym) ≈ 1.0  # in- and out degree is same
-    @assert heterogenity(Nsym) ≈ 0.5
+    @assert heterogeneity(Nsym) ≈ 0.5
 
 
     # asymetric network
@@ -34,9 +34,9 @@ module TestResilience
                                false false false false;
                                false false false false])
     @assert symmetry(Nasym) ≈ -1.0  # in- and out degree is same
-    @assert heterogenity(Nasym) ≈ 0.75
+    @assert heterogeneity(Nasym) ≈ 0.75
 
     v = ones(10) / 10
     Nhomo = UnipartiteProbabilisticNetwork(v * v')
-    @assert isapprox(heterogenity(Nhomo), 0.0, atol=1e-10)
+    @assert isapprox(heterogeneity(Nhomo), 0.0, atol=1e-10)
 end