🚧 Minor fixes to basic output analyses functions.

docs/make.jl

@@ -45,4 +45,4 @@ makedocs(;
     ],
 )
 
-deploydocs(; repo = "github.com/BecksLab/EcologicalNetworksDynamics.jl", devbranch = "doc")
+deploydocs(; repo = "github.com/BecksLab/EcologicalNetworksDynamics.jl", devbranch = "dev")

src/EcologicalNetworksDynamics.jl

@@ -97,10 +97,6 @@ include("./nontrophic_layers.jl")
 #-------------------------------------------------------------------------------------------
 # Analysis tools working on the output of the simulation.
 include("output-analysis.jl")
-export richness
-export persistence
-export shannon_diversity
-export total_biomass
 
 # Avoid Revise interruptions when redefining methods and properties.
 Framework.REVISING = true

src/output-analysis.jl

@@ -1,5 +1,5 @@
 """
-richness(solution::Solution; threshold = 0)
+    richness(solution::Solution; threshold = 0)
 
 Return the number of alive species at each timestep of the simulation.
 `solution` is the output of [`simulate`](@ref).
@@ -14,7 +14,8 @@ Let's start with a simple example where the richness remains constant:
 julia> foodweb = Foodweb([0 0; 1 0])
        m = default_model(foodweb)
        B0 = [0.5, 0.5]
-       sol = simulate(m, B0)
+       tmax = 100
+       sol = simulate(m, B0, tmax)
        richness_trajectory = richness(sol)
        all(richness_trajectory .== 2) # At each timestep, there are 2 alive species.
 true
@@ -26,36 +27,33 @@ We expect to observe a decrease in richness from 1 to 0 over time.
 
 ```jldoctest
 julia> B0 = [0, 0.5] # The producer is extinct at the beginning.
-       sol = simulate(m, B0)
+       sol = simulate(m, B0, 1_000)
        richness_trajectory = richness(sol)
        richness_trajectory[1] == 1 && richness_trajectory[end] == 0
 true
 ```
 """
-richness(solution::AbstractODESolution; threshold = 0) = richness.(solution.u; threshold)
+richness(solution::Solution; threshold = 0) = richness.(solution.u; threshold)
+export richness
 
 """
-    richness(vec::AbstractVector; threshold = 0)
+    richness(biomasses::AbstractVector; threshold = 0)
 
-Return the number of alive species given a biomass vector `vec`.
+Return the number of alive species given a biomass vector.
 By default, species are considered extinct if their biomass is 0.
 But, this `threshold` can be changed using the corresponding keyword argument.
 
 # Examples
 
 ```jldoctest
-julia> foodweb = Foodweb([0 0; 1 0])
-       m = default_model(foodweb)
-       B0 = [0.5, 0.5]
-       sol = simulate(m, B0)
-       richness(sol[end]) # Richness at the end of the simulation.
-2.0
+julia> richness([0.2, 0, 0.3]) # Only two species are non-extinct in this biomass vector.
+2
 ```
 """
-richness(vec::AbstractVector; threshold = 0) = count(>(threshold), vec)
+richness(biomasses::AbstractVector; threshold = 0) = count(>(threshold), biomasses)
 
 """
-    persistence(solution::AbstractODESolution; threshold = 0)
+    persistence(solution::Solution; threshold = 0)
 
 Fraction of alive species at each timestep of the simulation.
 See [`richness`](@ref) for details.
@@ -67,25 +65,25 @@ julia> S = 20 # Initial number of species.
        foodweb = Foodweb(:niche; S = 20, C = 0.1)
        m = default_model(foodweb)
        B0 = rand(S)
-       sol = simulate(m, B0)
+       sol = simulate(m, B0, 2000)
        all(persistence(sol) .== richness(sol) / S)
 true
 ```
 """
-function persistence(solution::AbstractODESolution; threshold = 0)
-    persistence.(solution.u; threshold)
-end
+persistence(solution::Solution; threshold = 0) = persistence.(solution.u; threshold)
+export persistence
 
 """
-    persistence(vec::AbstractVector; threshold = 0)
+    persistence(biomasses::AbstractVector; threshold = 0)
 
-Fraction of alive species given a biomass vector `vec`.
+Fraction of alive species given a biomass vector.
 See [`richness`](@ref) for details.
 """
-persistence(vec::AbstractVector; threshold = 0) = richness(vec; threshold) / length(vec)
+persistence(biomasses::AbstractVector; threshold = 0) =
+    richness(biomasses; threshold) / length(biomasses)
 
 """
-    total_biomass(solution::AbstractODESolution)
+    total_biomass(solution::Solution)
 
 Total biomass of a community at each timestep of the simulation.
 `solution` is the output of [`simulate`](@ref).
@@ -100,18 +98,19 @@ so we can observe the consumer's biomass decrease over time.
 julia> foodweb = Foodweb([0 0; 1 0])
        m = default_model(foodweb)
        B0 = [0, 0.5] # The producer is extinct at the beginning.
-       sol = simulate(m, B0)
+       sol = simulate(m, B0, 1_000)
        biomass_trajectory = total_biomass(sol)
        biomass_trajectory[1] == 0.5 && biomass_trajectory[end] == 0
 true
 ```
 """
-total_biomass(solution::AbstractODESolution) = total_biomass.(solution.u)
+total_biomass(solution::Solution) = total_biomass.(solution.u)
+export total_biomass
 
 """
-    total_biomass(vec::AbstractVector)
+    total_biomass(biomasses::AbstractVector)
 
-Total biomass of a community given a biomass vector `vec`.
+Total biomass of a community given a biomass vector.
 
 # Examples
 
@@ -120,10 +119,10 @@ julia> total_biomass([0.5, 1.5]) # 0.5 + 1.5 = 2.0
 2.0
 ```
 """
-total_biomass(vec::AbstractVector) = sum(vec)
+total_biomass(biomasses::AbstractVector) = sum(biomasses)
 
 """
-    shannon_diversity(solution::AbstractODESolution; threshold = 0)
+    shannon_diversity(solution::Solution; threshold = 0)
 
 Shannon diversity index at each timestep of the simulation.
 `solution` is the output of [`simulate`](@ref).
@@ -142,20 +141,21 @@ as the biomass of the species diverge from each other.
 julia> foodweb = Foodweb([0 0; 1 0])
        m = default_model(foodweb)
        B0 = [0.5, 0.5] # Even biomass, maximal shannon diversity.
-       sol = simulate(m, B0)
+       sol = simulate(m, B0, 1_000)
        shannon_trajectory = shannon_diversity(sol)
        biomass_trajectory[1] > biomass_trajectory[end]
 true
 ```
 """
-function shannon_diversity(solution::AbstractODESolution; threshold = 0)
+shannon_diversity(solution::Solution; threshold = 0) =
     shannon_diversity.(solution.u; threshold)
-end
+export shannon_diversity
 
 """
-    shannon_diversity(vec::AbstractVector; threshold = 0)
+    shannon_diversity(biomasses::AbstractVector; threshold = 0)
+
+Shannon diversity index given a biomass vector.
 
-Shannon diversitty index given a biomass vector `vec
 Shannon diversity is a measure of species diversity based on the entropy.
 According to the Shannon index, for a same number of species,
 the more evenly the biomass is distributed among them,
@@ -176,8 +176,8 @@ true
 We observe as we decrease the biomass of the third species,
 the shannon diversity tends to 2, as we tend towards an effective two-species community.
 """
-function shannon_diversity(vec::AbstractVector; threshold = 0)
-    x = filter(>(threshold), vec)
+function shannon_diversity(biomasses::AbstractVector; threshold = 0)
+    x = filter(>(threshold), biomasses)
     p = x ./ sum(x)
     exp(-sum(p .* log.(p)))
 end