Cleanup tests and doc generation..

- Code chunks in `docs/` no longer fail silently: `@repl` → `@example`.

- Code chunks in `docs/` expected to fail are now `jldoctest` blocs.
  - This introduces code setup duplication until some limitation is lifted?
    JuliaDocs/Documenter.jl#452

- Fix broken DOI url.

- Docstring for helper macros are now plain comments for they are not in doc.

docs/src/example/paradox_enrichment.md

@@ -19,7 +19,7 @@ and check that our simulations fit with analytical predictions.
 
 We consider a 2-species system with one resource (``R``) and one consumer (``C``).
 
-```@repl befwm2
+```@example befwm2
 foodweb = FoodWeb([0 0; 1 0]); # 2 eats 1
 ```
 
@@ -29,7 +29,7 @@ Here we choose the [`ClassicResponse`](@ref)
 with a handling time (`hₜ`), an attack rate (`aᵣ`), and a hill exponent (`h`) equal to one
 to simplify analytical derivations.
 
-```@repl befwm2
+```@example befwm2
 response = ClassicResponse(foodweb, aᵣ=1, hₜ=1, h=1);
 ```
 

docs/src/index.md

@@ -25,7 +25,7 @@ but can also be easily customized if wanted.
     Simulations of biomass dynamics in community food webs
 - [Miele et al., 2019, PLOS](https://doi.org/10.1371/journal.pcbi.1007269) -
     Effect of non-trophic interactions on diversity-productivity relationship
-- [Kefi et al. 2018, Ecology Letters]( https://doi.org/10.1111/j.1461-0248.2011.01732.x) -
+- [Kefi et al. 2018, Ecology Letters](https://doi.org/10.1111/j.1461-0248.2011.01732.x) -
     More than a meal... integrating non-feeding interactions into food webs
 
 !!! note "Todo"

docs/src/man/foodwebs.md

@@ -28,40 +28,40 @@ that will return you the corresponding `FoodWeb` object.
 using BEFWM2
 ```
 
-```@repl befwm2
+```@example befwm2
 A = [0 0 0; 1 0 0; 0 1 0] # 1 producer ⋅ 2 eats 1 ⋅ 3 eats 2
 foodweb = FoodWeb(A)
 ```
 
 We can check that adjacency matrix stored in `foodweb` corresponds to the one we provided.
 
-```@repl befwm2
+```@example befwm2
 foodweb.A
 ```
 
 As we did not use a method (e.g. the `nichemodel`) to create the foodweb,
 the method is said to be `unspecified`.
 
-```@repl befwm2
+```@example befwm2
 foodweb.method
 ```
 
 Moreover, by default:
 - the consumers are assumed to be inverterbrates
 
-```@repl befwm2
+```@example befwm2
 foodweb.metabolic_class
 ```
 
 - all body-mass are set to 1
 
-```@repl befwm2
+```@example befwm2
 foodweb.M
 ```
 
 - the `species` vector stores only species indexes as no identities were provided.
 
-```@repl befwm2
+```@example befwm2
 foodweb.species
 ```
 
@@ -76,7 +76,7 @@ it is more suited to create the foodweb using structural models.
 implements various structural models to build foodwebs.
 You can pass any of those models, with the adequate arguments, to generate foodwebs.
 
-```@repl befwm2
+```@example befwm2
 using EcologicalNetworks
 S = 20; # number of species
 C = 0.2; # connectance
@@ -100,7 +100,7 @@ so you can directly give a `UnipartiteNetwork` object to the [`FoodWeb`](@ref) m
     This function is not yet able to attribute metabolic classes or a mass to species,
     it just pass the adjacency matrix.
 
-```@repl befwm2
+```@example befwm2
 unipartite_network = EcologicalNetworks.nz_stream_foodweb()[1] # load network
 foodweb = FoodWeb(unipartite_network, method="NZ stream")
 ```
@@ -110,7 +110,7 @@ foodweb = FoodWeb(unipartite_network, method="NZ stream")
 By default all species mass are set to 1.
 However, you cange that either by giving your own body-mass vector (`M`).
 
-```@repl befwm2
+```@example befwm2
 A = [0 0 0; 1 0 0; 0 1 0]; # define adjacency matrix
 M = rand(3) # body-mass are drawn randomly in [0,1]
 foodweb = FoodWeb(A, M=M)
@@ -121,7 +121,7 @@ Or by using a consumer-resource mass ratio `Z`,
 then mass will be computed using species trophic levels (``t_l``)
 such that: ``M = Z^{t_l - 1}``.
 
-```@repl befwm2
+```@example befwm2
 A = [0 0 0; 1 0 0; 0 1 0]; # trophic levels are respectively 1, 2 and 3
 foodweb = FoodWeb(A, Z=10)
 foodweb.M

docs/src/man/functionalresponse.md

@@ -41,7 +41,7 @@ The linear response and its parameters
 can be accessed by calling the [`LinearResponse`](@ref) method
 with the [`FoodWeb`](@ref) as a mandatory argument.
 
-```@repl befwm2
+```@example befwm2
 foodweb = FoodWeb([0 0 0; 1 0 0; 0 1 0]); # 1 producer ⋅ 2 eats 1 ⋅ 3 eats 2
 f = LinearResponse(foodweb);
 f.ω # preferency
@@ -51,7 +51,7 @@ f.α # consumption rate
 Above parameters take default values, but you can specify custom values.
 For instance if you want to double the attack rate of predator 3, you can do:
 
-```@repl befwm2
+```@example befwm2
 f = LinearResponse(foodweb, α=[0.0,1.0,2.0]);
 f.α # custom attack rates
 ```
@@ -62,7 +62,7 @@ corresponding to the linear functional response.
 To do so, you just need to provide the species biomass vector (`B`),
 where `B[i]` is the biomass of species ``i``.
 
-```@repl befwm2
+```@example befwm2
 f = LinearResponse(foodweb);
 B = [1, 1, 1]; # defining species biomass
 f(B) # F matrix, F[i,j] = Fᵢⱼ
@@ -118,7 +118,7 @@ The bioenergetic response and its parameters
 can be accessed by calling the [`BioenergeticResponse`](@ref) method
 with the [`FoodWeb`](@ref) as a mandatory argument.
 
-```@repl befwm2
+```@example befwm2
 foodweb = FoodWeb([0 0 0; 1 0 0; 0 1 0]); # 1 producer ⋅ 2 eats 1 ⋅ 3 eats 2
 f = BioenergeticResponse(foodweb);
 f.ω # preferency
@@ -130,7 +130,7 @@ f.h # hill exponent
 Above parameters take default values, but you can specify custom values.
 For instance if you want to set the hill exponent (`h`) to 1 instead of 2, you can do:
 
-```@repl befwm2
+```@example befwm2
 f = BioenergeticResponse(foodweb, h=1);
 f.h # custom hill exponent
 ```
@@ -141,7 +141,7 @@ corresponding to the bioenergetic functional response.
 To do so, you just need to provide the species biomass vector (`B`),
 where `B[i]` is the biomass of species ``i``.
 
-```@repl befwm2
+```@example befwm2
 f = BioenergeticResponse(foodweb);
 B = [1, 1, 1]; # defining species biomass
 f(B) # F matrix, F[i,j] = Fᵢⱼ
@@ -192,7 +192,7 @@ The classic response and its parameters
 can be accessed by calling the [`ClassicResponse`](@ref) method
 with the [`FoodWeb`](@ref) as a mandatory argument.
 
-```@repl befwm2
+```@example befwm2
 foodweb = FoodWeb([0 0 0; 1 0 0; 0 1 0]); # 1 producer ⋅ 2 eats 1 ⋅ 3 eats 2
 f = ClassicResponse(foodweb);
 f.ω # preferency
@@ -205,7 +205,7 @@ f.hₜ # handling time
 Above parameters take default values, but you can specify custom values.
 For instance if you want to set the handling time (`h`) to 0.1 instead of 1, you can do:
 
-```@repl befwm2
+```@example befwm2
 f = ClassicResponse(foodweb, hₜ=0.1);
 f.hₜ # custom handling time
 ```
@@ -216,7 +216,7 @@ corresponding to the classic functional response.
 To do so, you just need to provide the species biomass vector (`B`),
 where `B[i]` is the biomass of species ``i``.
 
-```@repl befwm2
+```@example befwm2
 f = ClassicResponse(foodweb);
 B = [1, 1, 1]; # defining species biomass
 f(B) # F matrix, F[i,j] = Fᵢⱼ

docs/src/man/modelparameters.md

@@ -21,7 +21,7 @@ By default, the model parameters can be simply generated by providing only the f
 using BEFWM2
 ```
 
-```@repl befwm2
+```@example befwm2
 foodweb = FoodWeb([0 0 0; 1 0 0; 0 1 0]);
 params = ModelParameters(foodweb)
 ```
@@ -34,7 +34,7 @@ We explain how to do so for each of the 3 containers in the following sections.
 [`BioRates`](@ref) contains the species metabolic demand (`x`)
 and the species intrinsic growth rates (`r`).
 
-```@repl befwm2
+```@example befwm2
 foodweb = FoodWeb([0 0 0; 1 0 0; 0 1 0], Z=10);
 biorates = BioRates(foodweb)
 biorates.x # metabolic demand
@@ -43,7 +43,7 @@ biorates.r # intrinsic growth rate
 
 If you want to change the default rate values you can specify your own rate vector.
 
-```@repl befwm2
+```@example befwm2
 x_custom = [1,2,3];
 r_custom = [4,5,6];
 biorates = BioRates(foodweb, x=x_custom, r=r_custom);
@@ -55,7 +55,7 @@ In case you want to attribute the same rate value for every species,
 instead of giving a vector filled with a constant,
 you can directly pass the constant.
 
-```@repl befwm2
+```@example befwm2
 biorates = BioRates(foodweb, x=1, r=2);
 biorates.x
 biorates.r
@@ -75,14 +75,14 @@ are stored in [`AllometricParams`](@ref) objects.
 You can access allometric parameters values taken from literature
 for the intrinsic growth rate and the metabolic demand.
 
-```@repl befwm2
+```@example befwm2
 DefaultGrowthParams() # default a, b for intrinsic growth rate
 DefaultMetabolismParams() # default a, b for intrinsic metabolic demand
 ```
 
 But you can also define your own allometric parameters.
 
-```@repl befwm2
+```@example befwm2
 my_allometric_params = AllometricParams(1,2,3,4,5,6)
 ```
 
@@ -92,7 +92,7 @@ which will compute the vector of the species rates:
 !!! note
     The foodweb is provided to get the species trophic levels.
 
-```@repl befwm2
+```@example befwm2
 foodweb = FoodWeb([0 0 0; 1 0 0; 0 1 0], Z=10)
 rate = allometric_rate(foodweb, my_allometric_params) # 1 value per species
 ```
@@ -113,7 +113,7 @@ rate = allometric_rate(foodweb, my_allometric_params) # 1 value per species
 Then the `rate` vector computed with your custom allometric parameters
 can be given to [`BioRates`](@ref) as seen previously.
 
-```@repl befwm2
+```@example befwm2
 biorates = BioRates(foodweb, x=rate) # custom metabolic demand
 ```
 
@@ -125,7 +125,7 @@ As for the biological rates,
 environmental variables can be generated by only providing the foodweb,
 in which case the parameters take default values.
 
-```@repl befwm2
+```@example befwm2
 foodweb = FoodWeb([0 0 0; 0 0 0; 0 1 0], Z=10)
 environment = Environment(foodweb)
 ```
@@ -134,13 +134,13 @@ By default carrying capacities (K) are set to 1 for producers and 0 for consumer
 as their growth term is assumed to be null.
 
 
-```@repl befwm2
+```@example befwm2
 environment.K
 ```
 
 And the temperature is set to 293.15 K.
 
-```@repl befwm2
+```@example befwm2
 environment.K
 ```
 
@@ -149,7 +149,7 @@ by providing custom values to the [`Environment`](@ref) method.
 For the temperature
 you just have to provide the scalar corresponding the the wanted temperature.
 
-```@repl befwm2
+```@example befwm2
 environment = Environment(foodweb, T=273.15);
 environment.T
 ```
@@ -159,7 +159,7 @@ And to change the carrying capacities you can either provide:
 - a scalar if you want to set all the producer carrying capacities to the
 same value
 
-```@repl befwm2
+```@example befwm2
 environment = Environment(foodweb, K=[1,2,0]); # using a vector
 environment.K
 
@@ -173,22 +173,22 @@ You can choose between 3 functional responses:
 [Linear response](@ref), [Bioenergetic response](@ref) and [Classic response](@ref).
 By default the [Bioenergetic response](@ref) response is selected.
 
-```@repl befwm2
+```@example befwm2
 params = ModelParameters(foodweb);
 params.functional_response
 ```
 
 However, if you want you can choose another functional response by giving it as an argument.
 For the classic response, do:
 
-```@repl befwm2
+```@example befwm2
 classic_response = ClassicResponse(foodweb); # define your response
 params = ModelParameters(foodweb, functional_response = classic_response);
 params.functional_response
 ```
 
 And for the linear response, do:
-```@repl befwm2
+```@example befwm2
 linear_response = LinearResponse(foodweb); # define your response
 params = ModelParameters(foodweb, functional_response = linear_response);
 params.functional_response