Minor style nitpicks.

- Vertical whitespace.
- Multiline strings.
- `; arg = arg` elisions.
- ..

src/measures/functioning.jl

@@ -1,6 +1,5 @@
 #=
-Quantifying functions
-Adapted from BioenergeticFoodWeb.jl
+Quantifying functions.
 =#
 
 """
@@ -64,7 +63,7 @@ julia> richness([1, 1])
 richness(n::AbstractVector; threshold = 0) = sum(n .> threshold)
 
 """
-    species_persistence(solution; threshold, kwargs...)
+    species_persistence(solution; kwargs...)
 
 Returns the average proportion of species having a biomass superior or equal to threshold
 over the `last` timesteps.
@@ -151,7 +150,7 @@ biomass(vec::AbstractVector;) = (total = mean(vec), species = mean(vec))
 
 
 """
-    shannon_diversity(solution; threshold, kwargs...)
+    shannon_diversity(solution; threshold = 0, kwargs...)
 
 Computes the average Shannon entropy index, i.e. the first Hill number,
 over the `last` timesteps.
@@ -167,14 +166,12 @@ https://en.wikipedia.org/wiki/Diversity_index#Shannon_index
 """
 function shannon_diversity(solution; threshold = 0, kwargs...)
     measure_on = extract_last_timesteps(solution; kwargs...)
-
     shan = shannon_diversity.(eachcol(measure_on); threshold)
     mean(shan)
 end
 
 function shannon_diversity(n::AbstractVector; threshold = 0)
     x = filter(>(threshold), n)
-
     if length(x) >= 1
         p = x ./ sum(x)
         p_ln_p = p .* log.(p)
@@ -187,7 +184,7 @@ end
 
 
 """
-    simpson(solution; threshold, kwargs...)
+    simpson(solution; threshold = 0, kwargs...)
 
 Computes the average Simpson diversity index, i.e. the second Hill number,
 over the `last` timesteps.
@@ -203,14 +200,12 @@ https://en.wikipedia.org/wiki/Diversity_index#Simpson_index
 """
 function simpson(solution; threshold = 0, kwargs...)
     measure_on = extract_last_timesteps(solution; kwargs...)
-
     simp = simpson.(eachcol(measure_on); threshold)
     mean(simp)
 end
 
 function simpson(n::AbstractVector; threshold = 0)
     x = filter(>(threshold), n)
-
     if length(x) >= 1
         p = x ./ sum(x)
         p2 = 2 .^ p
@@ -222,7 +217,7 @@ function simpson(n::AbstractVector; threshold = 0)
 end
 
 """
-    evenness(solution; threshold, kwargs...)
+    evenness(solution; threshold = 0, kwargs...)
 
 Computes the average Pielou evenness, over the `last` timesteps.
 
@@ -237,7 +232,6 @@ https://en.wikipedia.org/wiki/Species_evenness
 """
 function evenness(solution; threshold = 0, kwargs...)
     measure_on = extract_last_timesteps(solution; kwargs...)
-
     piel = evenness.(eachcol(measure_on); threshold)
     mean(piel)
 end
@@ -335,7 +329,7 @@ See also [`simulate`](@ref), [`get_extinct_species`](@ref).
 get_parameters(sol) = sol.prob.p.params
 
 """
-    trophic_structure(solution; threshold, kwargs...)
+    trophic_structure(solution; threshold = 0, idxs = nothing, kwargs...)
 
 Returns the maximum, mean and weighted mean trophic level averaged over the `last`
 timesteps. It also returns the adjacency matrix containing only the living species and the
@@ -371,10 +365,10 @@ julia> foodweb = FoodWeb([0 0 0; 0 1 0; 1 1 0]; quiet = true);
 """
 function trophic_structure(solution; threshold = 0, idxs = nothing, kwargs...)
 
-    isnothing(idxs) || throw(ArgumentError("`trophic_structure()` operates at the whole \
-                                           network level, so it makes no sense to ask for \
-                                           particular species with anything other than \
-                                           `idxs = nothing`."))
+    isnothing(idxs) ||
+        throw(ArgumentError("`trophic_structure()` operates at the whole network level, \
+                             so it makes no sense to ask for particular species \
+                             with anything other than `idxs = nothing`."))
 
 
     # Measure trophic structure over last timesteps
@@ -388,7 +382,6 @@ function trophic_structure(solution; threshold = 0, idxs = nothing, kwargs...)
         alive = alive_trophic_network(measure_on[:, i], net; threshold)
         tlvl = alive.trophic_level
         bm = alive.species_biomass
-
         push!(maxl, max_trophic_level(tlvl))
         push!(avgl, mean_trophic_level(tlvl))
         push!(wavg, weighted_average_trophic_level(bm, tlvl))
@@ -440,9 +433,9 @@ function alive_trophic_network(n::AbstractVector, A::AbstractMatrix; kwargs...)
 end
 
 docstring = """
-    max_trophic_level(solution; threshold, kwargs...)
-    mean_trophic_level(solution; threshold, kwargs...)
-    weighted_average_trophic_level(solution; threshold, kwargs...)
+    max_trophic_level(solution; threshold = 0, kwargs...)
+    mean_trophic_level(solution; threshold = 0, kwargs...)
+    weighted_average_trophic_level(solution; threshold = 0, kwargs...)
 
 Return the aggregated trophic level over the `last` timesteps,
 either with `max` or `mean` aggregation,
@@ -597,9 +590,7 @@ julia> B0 = [0, 0.5, 0.5];
 """
 function living_species(solution::Solution; threshold = 0, idxs = nothing, kwargs...)
     measure_on = extract_last_timesteps(solution; idxs, kwargs...)
-
     alive_sp = living_species(measure_on; threshold)
-
     sp = get_parameters(solution).network.species
 
     tmp_idxs = process_idxs(solution; idxs)
@@ -611,7 +602,6 @@ end
 
 living_species(mat::AbstractMatrix; threshold = 0) =
     findall(>(threshold), biomass(mat).species)
-
 living_species(n::AbstractVector; threshold = 0) = findall(>(threshold), n)
 
 """

src/measures/stability.jl

@@ -1,5 +1,5 @@
 #=
-Various measures of stability
+Various measures of stability.
 =#
 
 """
@@ -11,6 +11,7 @@ See [`coefficient_of_variation`](@ref) for the details.
 """
 function species_cv(solution::Solution; threshold = 0, last = "10%", kwargs...)
     measure_on = extract_last_timesteps(solution; last, kwargs...)
+
     # Fetch species that are alive, whose avg biomass is > threshold
     living_sp = living_species(measure_on; threshold)
 
@@ -21,7 +22,6 @@ function species_cv(solution::Solution; threshold = 0, last = "10%", kwargs...)
 end
 
 function species_cv(mat::AbstractMatrix; corrected = true)
-
     if any(size(mat) .== 0)
         average = NaN
         species = NaN
@@ -59,19 +59,18 @@ function synchrony(
     corrected = true,
     kwargs...,
 )
-
     measure_on = extract_last_timesteps(solution; last, kwargs...)
+
     # Fetch species that are alive, whose avg biomass is > threshold
     living_sp = living_species(measure_on; threshold)
 
     # Transpose to get the time x species matrix
     mat = transpose(measure_on[living_sp, :])
 
     synchrony(mat; corrected = corrected)
-
 end
-function synchrony(mat::AbstractMatrix; corrected = true)
 
+function synchrony(mat::AbstractMatrix; corrected = true)
     if any(size(mat) .== 0)
         phi = NaN
     else
@@ -82,9 +81,7 @@ function synchrony(mat::AbstractMatrix; corrected = true)
 
         phi = com_var / std_sp^2
     end
-
     phi
-
 end
 
 """
@@ -101,19 +98,18 @@ function community_cv(
     corrected = true,
     kwargs...,
 )
+    measure_on = extract_last_timesteps(solution; last, kwargs...)
 
-    measure_on = extract_last_timesteps(solution; last = last, kwargs...)
     # Fetch species that are alive, whose avg biomass is > threshold
-    living_sp = living_species(measure_on; threshold = threshold, kwargs...)
+    living_sp = living_species(measure_on; threshold, kwargs...)
 
     # Transpose to get the time x species matrix
     mat = transpose(measure_on[living_sp, :])
 
     community_cv(mat; corrected)
-
 end
-function community_cv(mat::AbstractMatrix; corrected = true)
 
+function community_cv(mat::AbstractMatrix; corrected = true)
     if any(size(mat) .== 0)
         cv_com = NaN
     else
@@ -175,7 +171,6 @@ function coefficient_of_variation(
     corrected = true,
     kwargs...,
 )
-
     measure_on = extract_last_timesteps(solution; last, kwargs...)
     # Fetch species that are alive, whose avg biomass is > threshold
     alive_sp = living_species(measure_on; threshold)