feat: add kw version of linearfilter

src/random/linearfilter.jl

@@ -52,6 +52,22 @@ function linearfilter(N::SpeciesInteractionNetwork{<:Partiteness, <:Binary}; α:
     return SpeciesInteractionNetwork(copy(N.nodes), edges)
 end
 
+"""
+    linearfilter(N::SpeciesInteractionNetwork{<:Partiteness, <:Binary}; interaction::T=1.0, generality::T=1.0, vulnerability::T=1.0, connectance::T=1.0) where {T <: AbstractFloat}
+
+Keyword version of `linearfilter` where the parameters are all set to 1.0 by default.
+"""
+function linearfilter(
+    N::SpeciesInteractionNetwork{<:Partiteness, <:Binary};
+    interaction::T = 1.0,
+    generality::T = 1.0,
+    vulnerability::T = 1.0,
+    connectance::T = 1.0,
+) where {T <: AbstractFloat}
+    α = [interaction, generality, vulnerability, connectance]
+    return linearfilter(N; α = α)
+end
+
 @testitem "The linearfilter function returns the correct type" begin
     nodes = Unipartite([:A, :B, :C, :D, :E, :F])
     edges = Binary(rand(Bool, (richness(nodes, 1), richness(nodes, 2))))
@@ -84,6 +100,18 @@ end
     end
 end
 
+@testitem "We can use the keyword version of linearfilter" begin
+    import Statistics
+    nodes = Unipartite([:A, :B, :C, :D, :E, :F])
+    edges = Binary(rand(Bool, (richness(nodes, 1), richness(nodes, 2))))
+    N = SpeciesInteractionNetwork(nodes, edges)
+    R = linearfilter(N; α = [1.0, 0.0, 0.0, 0.0])
+    S = linearfilter(N; generality=0.0, vulnerability=0.0, connectance=0.0)
+    for interaction in interactions(N)
+        @test R[interaction[1], interaction[2]] == S[interaction[1], interaction[2]]
+    end
+end
+
 """
     nullmodel(::Type{Degree}, N::SpeciesInteractionNetwork{<:Partiteness, <:Binary})
 
@@ -203,4 +231,4 @@ end
     @test R[:B, :b] == 3 / 3
     @test R[:B, :c] == 1 / 3
     @test R[:C, :c] == 1 / 3
-end
+end