From 93037e5a7d291c32dd98dc57c1e526190155ed15 Mon Sep 17 00:00:00 2001
From: "Matthew J. Michalska-Smith" <mjsmith037@gmail.com>
Date: Wed, 9 Feb 2022 20:46:00 -0500
Subject: [PATCH 01/12] :bug: fixed omnivory to use true trophic level and
 iterate across prey rather than predators

---
 src/foodwebs/omnivory.jl | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/foodwebs/omnivory.jl b/src/foodwebs/omnivory.jl
index 9f6ee28e1..cfe24b5e4 100644
--- a/src/foodwebs/omnivory.jl
+++ b/src/foodwebs/omnivory.jl
@@ -1,8 +1,8 @@
 function omnivory(N::T) where {T <: UnipartiteNetwork}
     OI = Dict([s => 0.0 for s in species(N)])
 
-    TL = fractional_trophic_level(N)
-    k = degree(N; dims=1)
+    TL = trophic_level(N)
+    k = degree_in(N)
 
     for sp_i in species(N)
 
@@ -11,10 +11,10 @@ function omnivory(N::T) where {T <: UnipartiteNetwork}
 
         # For every species, we set its initial omnivory to 0
         oi = 0.0
-        for (j, sp_j) in enumerate(species(N))
+        for sp_j in species(N)
             # Then for every species it consumes, we ha
             tl_diff = (TL[sp_j] - (TL[sp_i]-1.0)).^2.0
-            corr = N[sp_i,sp_j]/k[sp_i]
+            corr = N[sp_j,sp_i]/k[sp_i]
             oi += tl_diff * corr
         end
         OI[sp_i] = oi

From fe9f81feda011455a56d9e69c3cd4f34a84913e5 Mon Sep 17 00:00:00 2001
From: "Matthew J. Michalska-Smith" <mjsmith037@gmail.com>
Date: Wed, 9 Feb 2022 20:49:28 -0500
Subject: [PATCH 02/12] :books: adding docstring for omnivory function
 including reference

---
 src/foodwebs/omnivory.jl | 13 +++++++++++++
 1 file changed, 13 insertions(+)

diff --git a/src/foodwebs/omnivory.jl b/src/foodwebs/omnivory.jl
index cfe24b5e4..43b291ba6 100644
--- a/src/foodwebs/omnivory.jl
+++ b/src/foodwebs/omnivory.jl
@@ -1,3 +1,16 @@
+"""
+    omnivory(N::T) where {T <: UnipartiteNetwork}
+
+Returns a vector of length |species(N)| with an index of consumption across
+trophic levels. Note we explicitly assume that diet contribution is spread
+evenly across prey species.
+
+#### References
+- Christensen, Villy, and Daniel Pauly. "ECOPATH II—a software for balancing
+  steady-state ecosystem models and calculating network characteristics."
+  Ecological modelling 61, no. 3-4 (1992): 169-185.
+
+"""
 function omnivory(N::T) where {T <: UnipartiteNetwork}
     OI = Dict([s => 0.0 for s in species(N)])
 

From 88d87628155d397e3540b8f2b906fdc289e2c912 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Timoth=C3=A9e=20Poisot?= <timothee.poisot@umontreal.ca>
Date: Thu, 10 Feb 2022 21:42:37 -0500
Subject: [PATCH 03/12] update the documentation

---
 src/foodwebs/trophiclevels.jl | 75 ++++++++++++++++++++++++++---------
 1 file changed, 56 insertions(+), 19 deletions(-)

diff --git a/src/foodwebs/trophiclevels.jl b/src/foodwebs/trophiclevels.jl
index b3b23bbb1..b6d185fe0 100644
--- a/src/foodwebs/trophiclevels.jl
+++ b/src/foodwebs/trophiclevels.jl
@@ -1,24 +1,61 @@
-function fractional_trophic_level(N::T) where {T<:UnipartiteNetwork}
-  Y = nodiagonal(N)
-  producers = keys(filter(spedeg -> spedeg.second == 0, degree(Y; dims=1)))
-  sp = shortest_path(Y)
-  prod_id = findall(isequal(0), vec(sum(sp; dims=2)))
-  return Dict(zip(species(Y; dims=1), maximum(sp[:,prod_id]; dims=2).+1))
-end
+"""
+    trophic_level(N::UnipartiteNetwork; f=maximum)
+
+Returns the trophic level (from Christensen & Pauly 1992) of every species
+in the food web. Primary producers have a trophic level of 1, after that,
+it's complicated (see *e.g.* Williams & Martinez 2004, Thompson et al. 2007).
+
+Post (2002) notes that the trophic level can be obtained from the maximum,
+mean, or minimum distance to a producer. Given that consumers may be connected
+to more than one producer, one might argue that the *mode* of this distribution
+is also relevant.
+
+In favor of the minimum, one can argue that most energy transfer should happen
+along short chains; but imagining a consumer atop a chain of length 5, also
+connected directly to a producer, the minimum would give it a trophic level
+of 2, hiding its position at the top of the food web.
+
+In favor of the maximum, one can argue that the higher chains give a better
+idea of how far energy coming from the bottom of the food web can go. This
+is a strong indication of how *vertically* diverse it is.
 
+In this package, the keyword `f` defaults to `maximum`. Using any other
+function, as long as it accepts an array (of chain distances) and return a
+scalar, will work; `minimum` and `Statistics.mean` are natural alternatives,
+as is `StatsBase.mode` or `Statistics.median`.
+"""
 function trophic_level(N::T) where {T<:UnipartiteNetwork}
-  TL = fractional_trophic_level(N)
-  Y = nodiagonal(N)
-  D = zeros(Float64, size(Y))
-  ko = degree_out(Y)
-
-  # inner loop to avoid dealing with primary producers
-  for i in 1:richness(Y)
-    if ko[species(Y)[i]] > 0.0
-      D[i,:] = Y[i,:]./ko[species(Y)[i]]
+    Y = nodiagonal(N)
+    producers = keys(filter(spedeg -> spedeg.second == 0, degree(Y; dims=1)))
+    sp = shortest_path(Y)
+    prod_id = findall(isequal(0), vec(sum(sp; dims=2)))
+    return Dict(zip(species(Y; dims=1), maximum(sp[:, prod_id]; dims=2) .+ 1))
+end
+
+"""
+    fractional_trophic_level(N::UnipartiteNetwork)
+
+Returns the *fractional* trophic level (after Odum & Heald 1975)
+of species in a binary unipartite network. The trophic level is
+calculated after Pauly & Christensen (1995), specifically as TLᵢ = 1 +
+∑ⱼ(TLⱼ×DCᵢⱼ)/∑ⱼ(DCᵢⱼ), wherein TLᵢ is the trophic level
+of species i, and DCᵢⱼ is the proportion of species j in the diet of
+species i. Note that this function is calculated on a network where the
+diagonal (i.e. self loops) are removed.
+"""
+function fractional_trophic_level(N::T) where {T<:UnipartiteNetwork}
+    TL = trophic_level(N)
+    Y = nodiagonal(N)
+    D = zeros(Float64, size(Y))
+    ko = degree_out(Y)
+
+    # inner loop to avoid dealing with primary producers
+    for i in 1:richness(Y)
+        if ko[species(Y)[i]] > 0.0
+            D[i, :] = Y[i, :] ./ ko[species(Y)[i]]
+        end
     end
-  end
 
-  # return
-  return Dict(zip(species(N), 1 .+ D * [TL[s] for s in species(Y)]))
+    # return
+    return Dict(zip(species(N), 1 .+ D * [TL[s] for s in species(Y)]))
 end

From 8b63ac9356a63bf86825bd1ea0b8796b7a341825 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Timoth=C3=A9e=20Poisot?= <timothee.poisot@umontreal.ca>
Date: Thu, 10 Feb 2022 23:04:03 -0500
Subject: [PATCH 04/12] new code for trophic levels

---
 src/foodwebs/trophiclevels.jl | 28 ++++++++++++++++++++--------
 1 file changed, 20 insertions(+), 8 deletions(-)

diff --git a/src/foodwebs/trophiclevels.jl b/src/foodwebs/trophiclevels.jl
index b6d185fe0..8c32a2972 100644
--- a/src/foodwebs/trophiclevels.jl
+++ b/src/foodwebs/trophiclevels.jl
@@ -23,17 +23,27 @@ In this package, the keyword `f` defaults to `maximum`. Using any other
 function, as long as it accepts an array (of chain distances) and return a
 scalar, will work; `minimum` and `Statistics.mean` are natural alternatives,
 as is `StatsBase.mode` or `Statistics.median`.
+
+The chain length from any species to any producer is taken as the shortest
+possible path between these two species, as identified by the Dijkstra
+algorithm.
 """
-function trophic_level(N::T) where {T<:UnipartiteNetwork}
+function trophic_level(N::T; f=maximum) where {T<:UnipartiteNetwork}
     Y = nodiagonal(N)
-    producers = keys(filter(spedeg -> spedeg.second == 0, degree(Y; dims=1)))
-    sp = shortest_path(Y)
-    prod_id = findall(isequal(0), vec(sum(sp; dims=2)))
-    return Dict(zip(species(Y; dims=1), maximum(sp[:, prod_id]; dims=2) .+ 1))
+    paths = dijkstra(Y)
+    consumers = collect(keys(filter(p -> iszero(p.second), degree(Y; dims=1))))
+    filter!(int -> int.to ∈ consumers, paths)
+    tl = Dict{eltype(species(Y)),Float64}()
+    for sp in species(Y)
+        sp_paths = filter(int -> isequal(sp)(int.from), paths)
+        chain_lengths = [int.weight for int in sp_paths]
+        tl[sp] = isempty(chain_lengths) ? 1.0 : f(chain_lengths)+1.0
+    end
+    return tl
 end
 
 """
-    fractional_trophic_level(N::UnipartiteNetwork)
+    fractional_trophic_level(N::UnipartiteNetwork; kwargs...)
 
 Returns the *fractional* trophic level (after Odum & Heald 1975)
 of species in a binary unipartite network. The trophic level is
@@ -42,9 +52,11 @@ calculated after Pauly & Christensen (1995), specifically as TLᵢ = 1 +
 of species i, and DCᵢⱼ is the proportion of species j in the diet of
 species i. Note that this function is calculated on a network where the
 diagonal (i.e. self loops) are removed.
+
+The keywords arguments are passed to `trophic_level`.
 """
-function fractional_trophic_level(N::T) where {T<:UnipartiteNetwork}
-    TL = trophic_level(N)
+function fractional_trophic_level(N::T; kwargs...) where {T<:UnipartiteNetwork}
+    TL = trophic_level(N; kwargs...)
     Y = nodiagonal(N)
     D = zeros(Float64, size(Y))
     ko = degree_out(Y)

From 4da975df002d33e20c92c53a9b581b884beeddbd Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Timoth=C3=A9e=20Poisot?= <timothee.poisot@umontreal.ca>
Date: Fri, 11 Feb 2022 09:39:51 -0500
Subject: [PATCH 05/12] patch release

---
 Project.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Project.toml b/Project.toml
index 194811487..d31fde164 100644
--- a/Project.toml
+++ b/Project.toml
@@ -2,7 +2,7 @@ name = "EcologicalNetworks"
 uuid = "f03a62fe-f8ab-5b77-a061-bb599b765229"
 authors = ["Timothée Poisot <timothee.poisot@umontreal.ca>"]
 repo = "https://github.com/EcoJulia/EcologicalNetworks.jl"
-version = "0.5.1"
+version = "0.5.2"
 
 [deps]
 Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"

From a28aab03dc016c4d0ba32bab23bcadfe7fed0fe7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Timoth=C3=A9e=20Poisot?= <timothee.poisot@umontreal.ca>
Date: Fri, 11 Feb 2022 10:55:39 -0500
Subject: [PATCH 06/12] use a pseudo-inverse method for the fractional trophic
 level

---
 Project.toml                  |  1 +
 src/foodwebs/trophiclevels.jl | 33 ++++++++++++++++-----------------
 2 files changed, 17 insertions(+), 17 deletions(-)

diff --git a/Project.toml b/Project.toml
index d31fde164..094879a6d 100644
--- a/Project.toml
+++ b/Project.toml
@@ -12,6 +12,7 @@ Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
+Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
diff --git a/src/foodwebs/trophiclevels.jl b/src/foodwebs/trophiclevels.jl
index 8c32a2972..fb2602528 100644
--- a/src/foodwebs/trophiclevels.jl
+++ b/src/foodwebs/trophiclevels.jl
@@ -37,7 +37,7 @@ function trophic_level(N::T; f=maximum) where {T<:UnipartiteNetwork}
     for sp in species(Y)
         sp_paths = filter(int -> isequal(sp)(int.from), paths)
         chain_lengths = [int.weight for int in sp_paths]
-        tl[sp] = isempty(chain_lengths) ? 1.0 : f(chain_lengths)+1.0
+        tl[sp] = isempty(chain_lengths) ? 1.0 : f(chain_lengths) + 1.0
     end
     return tl
 end
@@ -53,21 +53,20 @@ of species i, and DCᵢⱼ is the proportion of species j in the diet of
 species i. Note that this function is calculated on a network where the
 diagonal (i.e. self loops) are removed.
 
-The keywords arguments are passed to `trophic_level`.
+This function uses a *pseudo*-inverse to solve the linear system described
+above.
 """
-function fractional_trophic_level(N::T; kwargs...) where {T<:UnipartiteNetwork}
-    TL = trophic_level(N; kwargs...)
-    Y = nodiagonal(N)
-    D = zeros(Float64, size(Y))
-    ko = degree_out(Y)
-
-    # inner loop to avoid dealing with primary producers
-    for i in 1:richness(Y)
-        if ko[species(Y)[i]] > 0.0
-            D[i, :] = Y[i, :] ./ ko[species(Y)[i]]
-        end
-    end
-
-    # return
-    return Dict(zip(species(N), 1 .+ D * [TL[s] for s in species(Y)]))
+function fractional_trophic_level(N::UnipartiteNetwork)
+    # Get the degree as a vector, ordered the same way as species
+    kout = EcologicalNetworks.degree_out(N)
+    𝐤 = [kout[s] for s in species(N)]
+    # Adjacency matrix to solve the TL
+    𝐀 = adjacency(N)
+    # Diet matrix
+    𝐃 = .-(𝐀 ./ 𝐤)
+    replace!(𝐃, NaN => -0.0)
+    𝐃[diagind(𝐃)] .= 1.0 .- 𝐃[diagind(𝐃)]
+    # Solve with the inverse matrix
+    𝐛 = ones(eltype(𝐃), richness(N))
+    return Dict(zip(species(N), pinv(𝐃) * 𝐛))
 end

From 178309ac214647e079108f203b1a3b16dfb06175 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Timoth=C3=A9e=20Poisot?= <timothee.poisot@umontreal.ca>
Date: Fri, 11 Feb 2022 12:06:49 -0500
Subject: [PATCH 07/12] fix omnivory and add doc

---
 docs/make.jl                    |  1 +
 docs/src/properties/foodwebs.md |  7 +++++
 src/EcologicalNetworks.jl       |  5 +--
 src/foodwebs/omnivory.jl        | 37 ----------------------
 src/foodwebs/trophiclevels.jl   | 55 +++++++++++++++++++++++++++------
 test/community/foodwebs.jl      | 12 +++----
 6 files changed, 60 insertions(+), 57 deletions(-)
 create mode 100644 docs/src/properties/foodwebs.md
 delete mode 100644 src/foodwebs/omnivory.jl

diff --git a/docs/make.jl b/docs/make.jl
index 035dfe2c3..e920f048f 100644
--- a/docs/make.jl
+++ b/docs/make.jl
@@ -31,6 +31,7 @@ makedocs(
             "Motifs" => "properties/motifs.md",
             "Centrality and paths" => "properties/paths.md",
             "Overlap and similarity" => "properties/overlap.md"
+            "Food web measures" => "properties/foodwebs.md"
         ],
         "Advanced information" => [
             "Beta-diversity" => "properties/betadiversity.md",
diff --git a/docs/src/properties/foodwebs.md b/docs/src/properties/foodwebs.md
new file mode 100644
index 000000000..6bcf9b5d0
--- /dev/null
+++ b/docs/src/properties/foodwebs.md
@@ -0,0 +1,7 @@
+# Food web measures
+
+```@docs
+distance_to_producer
+trophic_level
+omnivory
+```
diff --git a/src/EcologicalNetworks.jl b/src/EcologicalNetworks.jl
index f90e928d4..a25ea4e97 100644
--- a/src/EcologicalNetworks.jl
+++ b/src/EcologicalNetworks.jl
@@ -162,10 +162,7 @@ export KGL01, KGL02, KGL03, KGL04, KGL05, KGL06, KGL07, KGL08, KGL09, KGL10,
 
 # Food webs
 include(joinpath(".", "foodwebs/trophiclevels.jl"))
-export fractional_trophic_level, trophic_level
-
-include(joinpath(".", "foodwebs/omnivory.jl"))
-export omnivory
+export distance_to_producer, trophic_level, omnivory
 
 include(joinpath(".", "information/entropy.jl"))
 export entropy, make_joint_distribution, mutual_information, conditional_entropy,
diff --git a/src/foodwebs/omnivory.jl b/src/foodwebs/omnivory.jl
deleted file mode 100644
index 43b291ba6..000000000
--- a/src/foodwebs/omnivory.jl
+++ /dev/null
@@ -1,37 +0,0 @@
-"""
-    omnivory(N::T) where {T <: UnipartiteNetwork}
-
-Returns a vector of length |species(N)| with an index of consumption across
-trophic levels. Note we explicitly assume that diet contribution is spread
-evenly across prey species.
-
-#### References
-- Christensen, Villy, and Daniel Pauly. "ECOPATH II—a software for balancing
-  steady-state ecosystem models and calculating network characteristics."
-  Ecological modelling 61, no. 3-4 (1992): 169-185.
-
-"""
-function omnivory(N::T) where {T <: UnipartiteNetwork}
-    OI = Dict([s => 0.0 for s in species(N)])
-
-    TL = trophic_level(N)
-    k = degree_in(N)
-
-    for sp_i in species(N)
-
-        # Species with no interaction have an omnivory index of 0
-        k[sp_i] > 0 || continue
-
-        # For every species, we set its initial omnivory to 0
-        oi = 0.0
-        for sp_j in species(N)
-            # Then for every species it consumes, we ha
-            tl_diff = (TL[sp_j] - (TL[sp_i]-1.0)).^2.0
-            corr = N[sp_j,sp_i]/k[sp_i]
-            oi += tl_diff * corr
-        end
-        OI[sp_i] = oi
-    end
-
-    return OI
-end
diff --git a/src/foodwebs/trophiclevels.jl b/src/foodwebs/trophiclevels.jl
index fb2602528..3a7ecb739 100644
--- a/src/foodwebs/trophiclevels.jl
+++ b/src/foodwebs/trophiclevels.jl
@@ -1,9 +1,9 @@
 """
-    trophic_level(N::UnipartiteNetwork; f=maximum)
+    distance_to_producer(N::UnipartiteNetwork; f=maximum)
 
-Returns the trophic level (from Christensen & Pauly 1992) of every species
-in the food web. Primary producers have a trophic level of 1, after that,
-it's complicated (see *e.g.* Williams & Martinez 2004, Thompson et al. 2007).
+Returns the distance from a primary producert of every species in the food
+web. Primary producers have a trophic level of 1, after that, it's complicated
+(see *e.g.* Williams & Martinez 2004, Thompson et al. 2007).
 
 Post (2002) notes that the trophic level can be obtained from the maximum,
 mean, or minimum distance to a producer. Given that consumers may be connected
@@ -28,7 +28,7 @@ The chain length from any species to any producer is taken as the shortest
 possible path between these two species, as identified by the Dijkstra
 algorithm.
 """
-function trophic_level(N::T; f=maximum) where {T<:UnipartiteNetwork}
+function distance_to_producer(N::T; f=maximum) where {T<:UnipartiteNetwork}
     Y = nodiagonal(N)
     paths = dijkstra(Y)
     consumers = collect(keys(filter(p -> iszero(p.second), degree(Y; dims=1))))
@@ -43,7 +43,7 @@ function trophic_level(N::T; f=maximum) where {T<:UnipartiteNetwork}
 end
 
 """
-    fractional_trophic_level(N::UnipartiteNetwork; kwargs...)
+    trophic_level(N::UnipartiteNetwork; kwargs...)
 
 Returns the *fractional* trophic level (after Odum & Heald 1975)
 of species in a binary unipartite network. The trophic level is
@@ -53,10 +53,11 @@ of species i, and DCᵢⱼ is the proportion of species j in the diet of
 species i. Note that this function is calculated on a network where the
 diagonal (i.e. self loops) are removed.
 
-This function uses a *pseudo*-inverse to solve the linear system described
-above.
+This function uses a *pseudo*-inverse to solve the linear system
+described above *iff* the determinant of the diet matrix is 0 (it is
+non-invertible). Otherwise, it will use an exact inverse.
 """
-function fractional_trophic_level(N::UnipartiteNetwork)
+function trophic_level(N::UnipartiteNetwork)
     # Get the degree as a vector, ordered the same way as species
     kout = EcologicalNetworks.degree_out(N)
     𝐤 = [kout[s] for s in species(N)]
@@ -68,5 +69,39 @@ function fractional_trophic_level(N::UnipartiteNetwork)
     𝐃[diagind(𝐃)] .= 1.0 .- 𝐃[diagind(𝐃)]
     # Solve with the inverse matrix
     𝐛 = ones(eltype(𝐃), richness(N))
-    return Dict(zip(species(N), pinv(𝐃) * 𝐛))
+    invfunc = iszero(det(𝐃)) ? pinv : inv
+    return Dict(zip(species(N), invfunc(𝐃) * 𝐛))
+end
+
+"""
+    omnivory(N::T) where {T <: UnipartiteNetwork}
+
+Returns a vector of length richness(N) with an index of consumption across
+trophic levels. Note we explicitly assume that diet contribution is spread
+evenly across prey species, in proportion to their degree. Omnivory is
+measured based on the output of `trophic_level`.
+
+#### References
+- Christensen, Villy, and Daniel Pauly. "ECOPATH II—a software for balancing
+  steady-state ecosystem models and calculating network characteristics."
+  Ecological modelling 61, no. 3-4 (1992): 169-185.
+
+"""
+function omnivory(N::T) where {T<:UnipartiteNetwork}
+    # Get the trophic level as an array
+    TL = trophic_level(N)
+
+    # Prepare the omnivory index dictionary
+    OI = Dict(zip(species(N), fill(0.0, richness(N))))
+
+    # Loop
+    for sp in species(N)
+        if !isempty(N[sp,:])
+            TLj = [TL[prey] for prey in N[sp,:]]
+            # Note that we don't need the normalisation here, because ∑Dᵢⱼ=1
+            OI[sp] = sum((TLj .- mean(TLj)).^2.0)
+        end
+    end
+
+    return OI
 end
diff --git a/test/community/foodwebs.jl b/test/community/foodwebs.jl
index f1f57f310..3b0d9b0ba 100644
--- a/test/community/foodwebs.jl
+++ b/test/community/foodwebs.jl
@@ -6,14 +6,14 @@ module TestFoodWebs
   s1 = unipartitemotifs()[:S1]
   s1_ftl = fractional_trophic_level(s1)
   s1_tl = trophic_level(s1)
-  @test maximum(values(s1_ftl)) == 3
-  @test maximum(values(s1_tl)) == 3.0
-  @test s1_ftl[:a] == 3
-  @test s1_ftl[:b] == 2
-  @test s1_ftl[:c] == 1
+  @test maximum(values(s1_ftl)) ≈ 3
+  @test maximum(values(s1_tl)) ≈ 3.0
+  @test s1_ftl[:a] ≈ 3
+  @test s1_ftl[:b] ≈ 2
+  @test s1_ftl[:c] ≈ 1
 
   s2 = unipartitemotifs()[:S2]
-  @test minimum(values(fractional_trophic_level(s1))) == 1.0
+  @test minimum(values(fractional_trophic_level(s1))) ≈ 1.0
   @test minimum(values(trophic_level(s1))) == 1.0
 
   # test on a quantitative bipartite network

From 86ad20a5e7b6c105feb71c064be4aa6217ba645b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Timoth=C3=A9e=20Poisot?= <timothee.poisot@umontreal.ca>
Date: Fri, 11 Feb 2022 12:21:23 -0500
Subject: [PATCH 08/12] test fix

---
 test/community/foodwebs.jl | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/test/community/foodwebs.jl b/test/community/foodwebs.jl
index 3b0d9b0ba..6e789ec27 100644
--- a/test/community/foodwebs.jl
+++ b/test/community/foodwebs.jl
@@ -4,8 +4,8 @@ module TestFoodWebs
 
   # test trophic levels on motifs
   s1 = unipartitemotifs()[:S1]
-  s1_ftl = fractional_trophic_level(s1)
-  s1_tl = trophic_level(s1)
+  s1_ftl = trophic_level(s1)
+  s1_tl = distance_to_producer(s1)
   @test maximum(values(s1_ftl)) ≈ 3
   @test maximum(values(s1_tl)) ≈ 3.0
   @test s1_ftl[:a] ≈ 3
@@ -13,8 +13,8 @@ module TestFoodWebs
   @test s1_ftl[:c] ≈ 1
 
   s2 = unipartitemotifs()[:S2]
-  @test minimum(values(fractional_trophic_level(s1))) ≈ 1.0
-  @test minimum(values(trophic_level(s1))) == 1.0
+  @test minimum(values(trophic_level(s1))) ≈ 1.0
+  @test minimum(values(distance_to_producer(s1))) == 1.0
 
   # test on a quantitative bipartite network
   @test web_of_life("A_HP_002") |>

From 6a48cc8ae1d30ef0283a570af11871dc9a159066 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Timoth=C3=A9e=20Poisot?= <timothee.poisot@umontreal.ca>
Date: Fri, 11 Feb 2022 12:21:30 -0500
Subject: [PATCH 09/12] drop Revise

---
 Project.toml | 1 -
 1 file changed, 1 deletion(-)

diff --git a/Project.toml b/Project.toml
index 094879a6d..d31fde164 100644
--- a/Project.toml
+++ b/Project.toml
@@ -12,7 +12,6 @@ Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
-Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"

From 6cab51ac8e92565654ce2902e5cc039e9626b6d7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Timoth=C3=A9e=20Poisot?= <timothee.poisot@umontreal.ca>
Date: Fri, 11 Feb 2022 12:50:53 -0500
Subject: [PATCH 10/12] remove un-required test

---
 test/community/foodwebs.jl | 8 --------
 1 file changed, 8 deletions(-)

diff --git a/test/community/foodwebs.jl b/test/community/foodwebs.jl
index 6e789ec27..dd511510c 100644
--- a/test/community/foodwebs.jl
+++ b/test/community/foodwebs.jl
@@ -16,12 +16,4 @@ module TestFoodWebs
   @test minimum(values(trophic_level(s1))) ≈ 1.0
   @test minimum(values(distance_to_producer(s1))) == 1.0
 
-  # test on a quantitative bipartite network
-  @test web_of_life("A_HP_002") |>
-    x -> convert(BinaryNetwork, x) |> x -> convert(UnipartiteNetwork, x) |>
-    trophic_level |> values |> minimum |> x -> x == 1.0
-  @test web_of_life("A_HP_002") |>
-    x -> convert(BinaryNetwork, x) |> x -> convert(UnipartiteNetwork, x) |>
-    trophic_level |> values |> maximum |> x -> x == 2.0
-
 end

From 7c8c615df8fd1ead15456fa28bbc801dbbf5d041 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Timoth=C3=A9e=20Poisot?= <timothee.poisot@umontreal.ca>
Date: Fri, 11 Feb 2022 12:51:48 -0500
Subject: [PATCH 11/12] doc index fix

---
 docs/make.jl | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/make.jl b/docs/make.jl
index e920f048f..0906e2b85 100644
--- a/docs/make.jl
+++ b/docs/make.jl
@@ -30,7 +30,7 @@ makedocs(
             "Nestedness" => "properties/nestedness.md",
             "Motifs" => "properties/motifs.md",
             "Centrality and paths" => "properties/paths.md",
-            "Overlap and similarity" => "properties/overlap.md"
+            "Overlap and similarity" => "properties/overlap.md",
             "Food web measures" => "properties/foodwebs.md"
         ],
         "Advanced information" => [

From 478cd2d698d8945b2438d755f0869608f7a531e4 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Timoth=C3=A9e=20Poisot?= <timothee.poisot@umontreal.ca>
Date: Fri, 11 Feb 2022 14:01:49 -0500
Subject: [PATCH 12/12] fix the omnivory test

---
 test/community/foodwebs.jl | 35 +++++++++++++++++++++--------------
 1 file changed, 21 insertions(+), 14 deletions(-)

diff --git a/test/community/foodwebs.jl b/test/community/foodwebs.jl
index dd511510c..836e0783d 100644
--- a/test/community/foodwebs.jl
+++ b/test/community/foodwebs.jl
@@ -1,19 +1,26 @@
 module TestFoodWebs
-  using Test
-  using EcologicalNetworks
+using Test
+using EcologicalNetworks
 
-  # test trophic levels on motifs
-  s1 = unipartitemotifs()[:S1]
-  s1_ftl = trophic_level(s1)
-  s1_tl = distance_to_producer(s1)
-  @test maximum(values(s1_ftl)) ≈ 3
-  @test maximum(values(s1_tl)) ≈ 3.0
-  @test s1_ftl[:a] ≈ 3
-  @test s1_ftl[:b] ≈ 2
-  @test s1_ftl[:c] ≈ 1
+# test trophic levels on motifs
+s1 = unipartitemotifs()[:S1]
+s1_ftl = trophic_level(s1)
+s1_tl = distance_to_producer(s1)
+@test maximum(values(s1_ftl)) ≈ 3
+@test maximum(values(s1_tl)) ≈ 3.0
+@test s1_ftl[:a] ≈ 3
+@test s1_ftl[:b] ≈ 2
+@test s1_ftl[:c] ≈ 1
 
-  s2 = unipartitemotifs()[:S2]
-  @test minimum(values(trophic_level(s1))) ≈ 1.0
-  @test minimum(values(distance_to_producer(s1))) == 1.0
+s2 = unipartitemotifs()[:S2]
+@test minimum(values(trophic_level(s1))) ≈ 1.0
+@test minimum(values(distance_to_producer(s1))) == 1.0
+
+# Test for omnivory
+for s in species(s1)
+    if iszero(EcologicalNetworks.degree_out(s1)[s])
+        @test iszero(omnivory(s1)[s])
+    end
+end
 
 end