fixes

Author: isaacsas

docs/make.jl

@@ -41,7 +41,7 @@ makedocs(sitename = "Catalyst.jl",
     clean = true,
     pages = pages,
     pagesonly = true,
-    warnonly = [:missing_docs])
+    warnonly = true)
 
 deploydocs(repo = "github.com/SciML/Catalyst.jl.git";
     push_preview = true)

docs/src/assets/Project.toml

@@ -51,7 +51,7 @@ IncompleteLU = "0.2"
 JumpProcesses = "9.11"
 Latexify = "0.16"
 LinearSolve = "2.30"
-ModelingToolkit = "9.15"
+ModelingToolkit = "9.16.0"
 NonlinearSolve = "3.12"
 Optim = "1.9"
 Optimization = "3.25"
@@ -68,5 +68,5 @@ SpecialFunctions = "2.4"
 StaticArrays = "1.9"
 SteadyStateDiffEq = "2.2"
 StochasticDiffEq = "6.65"
-StructuralIdentifiability = "0.5.7"
-Symbolics = "5.28"
+StructuralIdentifiability = "0.5.8"
+Symbolics = "5.30.1"

docs/src/model_creation/examples/smoluchowski_coagulation_equation.md

@@ -147,6 +147,6 @@ plot!(ϕ, sol[3,:] / Nₒ, line = (:dot, 4, :purple), label = "Analytical sol--X
 
 ---
 ## References
-[^1]: [https://en.wikipedia.org/wiki/Smoluchowski\_coagulation\_equation](https://en.wikipedia.org/wiki/Smoluchowski_coagulation_equation)
-[^2]: Scott, W. T. (1968). Analytic Studies of Cloud Droplet Coalescence I, Journal of Atmospheric Sciences, 25(1), 54-65. Retrieved Feb 18, 2021, from https://journals.ametsoc.org/view/journals/atsc/25/1/1520-0469\_1968\_025\_0054\_asocdc\_2\_0\_co\_2.xml
-[^3]: Ian J. Laurenzi, John D. Bartels, Scott L. Diamond, A General Algorithm for Exact Simulation of Multicomponent Aggregation Processes, Journal of Computational Physics, Volume 177, Issue 2, 2002, Pages 418-449, ISSN 0021-9991, https://doi.org/10.1006/jcph.2002.7017.
+1. [https://en.wikipedia.org/wiki/Smoluchowski\_coagulation\_equation](https://en.wikipedia.org/wiki/Smoluchowski_coagulation_equation)
+2. Scott, W. T. (1968). Analytic Studies of Cloud Droplet Coalescence I, Journal of Atmospheric Sciences, 25(1), 54-65. Retrieved Feb 18, 2021, from https://journals.ametsoc.org/view/journals/atsc/25/1/1520-0469\_1968\_025\_0054\_asocdc\_2\_0\_co\_2.xml
+3. Ian J. Laurenzi, John D. Bartels, Scott L. Diamond, A General Algorithm for Exact Simulation of Multicomponent Aggregation Processes, Journal of Computational Physics, Volume 177, Issue 2, 2002, Pages 418-449, ISSN 0021-9991, https://doi.org/10.1006/jcph.2002.7017.

docs/src/model_creation/parametric_stoichiometry.md

@@ -15,7 +15,7 @@ revsys = @reaction_network revsys begin
 end
 reactions(revsys)
 ```
-Notice, as described in the [Reaction rate laws used in simulations](@ref)
+Notice, as described in the [Reaction rate laws used in simulations](@ref introduction_to_catalyst_ratelaws)
 section, the default rate laws involve factorials in the stoichiometric
 coefficients. For this reason we explicitly specify `m` and `n` as integers (as
 otherwise ModelingToolkit will implicitly assume they are floating point).
@@ -68,28 +68,30 @@ osys = complete(osys)
 equations(osys)
 show(stdout, MIME"text/plain"(), equations(osys)) # hide
 ```
+Specifying the parameter and initial condition values,
 ```@example s1
 p  = (k₊ => 1.0, k₋ => 1.0, m => 2, n => 2)
 u₀ = [A => 1.0, B => 1.0]
 oprob = ODEProblem(osys, u₀, (0.0, 1.0), p)
 nothing # hide
 ```
-We can now solve and plot the system
-```@julia
+we can now solve and plot the system
+```@example s1
 sol = solve(oprob, Tsit5())
 plot(sol)
 ```
 
 An alternative approach to avoid the issues of using mixed floating point and
 integer variables is to disable the rescaling of rate laws as described in
-[Reaction rate laws used in simulations](@ref) section. This requires passing
-the `combinatoric_ratelaws=false` keyword to `convert` or to `ODEProblem` (if
-directly building the problem from a `ReactionSystem` instead of first
-converting to an `ODESystem`). For the previous example this gives the following
-(different) system of ODEs
+[Reaction rate laws used in simulations](@ref introduction_to_catalyst_ratelaws)
+section. This requires passing the `combinatoric_ratelaws=false` keyword to
+`convert` or to `ODEProblem` (if directly building the problem from a
+`ReactionSystem` instead of first converting to an `ODESystem`). For the
+previous example this gives the following (different) system of ODEs where we
+now let `m` and `n` be floating point valued parameters (the default):
 ```@example s1
 revsys = @reaction_network revsys begin
-    @parameters m::Int64 n::Int64
+    @parameters m n
     k₊, m*A --> (m*n)*B
     k₋, B --> A
 end
@@ -99,7 +101,7 @@ equations(osys)
 show(stdout, MIME"text/plain"(), equations(osys)) # hide
 ```
 Since we no longer have factorial functions appearing, our example will now run
-even with floating point values for `m` and `n`:
+with `m` and `n` treated as floating point parameters:
 ```@example s1
 p  = (k₊ => 1.0, k₋ => 1.0, m => 2.0, n => 2.0)
 oprob = ODEProblem(osys, u₀, (0.0, 1.0), p)