Merge d8028aa into 940861e

docs/pages.jl

@@ -66,6 +66,6 @@ pages = Any[
     #     # Contributor's guide.
     #     # Repository structure.
     # ],
-    #"FAQs" => "faqs.md",
+    "FAQs" => "faqs.md",
     "API" => "api.md"
 ]

docs/src/faqs.md

@@ -5,19 +5,17 @@ One can directly use symbolic variables to index into SciML solution objects.
 Moreover, observables can also be evaluated in this way. For example,
 consider the system
 ```@example faq1
-using Catalyst, DifferentialEquations, Plots
+using Catalyst, OrdinaryDiffEq, Plots
 rn = @reaction_network ABtoC begin
   (k₊,k₋), A + B <--> C
 end
-
-# initial condition and parameter values
-setdefaults!(rn, [:A => 1.0, :B => 2.0, :C => 0.0, :k₊ => 1.0, :k₋ => 1.0])
 nothing    # hide
 ```
 Let's convert it to a system of ODEs, using the conservation laws of the system
 to eliminate two of the species:
 ```@example faq1
 osys = convert(ODESystem, rn; remove_conserved = true)
+osys = complete(osys)
 ```
 Notice the resulting ODE system has just one ODE, while algebraic observables
 have been added for the two removed species (in terms of the conservation law
@@ -28,7 +26,9 @@ observed(osys)
 Let's solve the system and see how to index the solution using our symbolic
 variables
 ```@example faq1
-oprob = ODEProblem(osys, [], (0.0, 10.0), [])
+u0 = [rn.A => 1.0, rn.B => 2.0, rn.C => 0.0]
+ps = [rn.k₊ => 1.0, rn.k₋ => 1.0]
+oprob = ODEProblem(osys, u0, (0.0, 10.0), ps)
 sol = solve(oprob, Tsit5())
 ```
 Suppose we want to plot just species `C`, without having to know its integer
@@ -65,7 +65,7 @@ constant, giving `k*X^2/2` instead of `k*X^2` for ODEs and `k*X*(X-1)/2` instead
 of `k*X*(X-1)` for jumps. This can be disabled when directly `convert`ing a
 [`ReactionSystem`](@ref). If `rn` is a generated [`ReactionSystem`](@ref), we can
 do
-```julia
+```@example faq1
 osys = convert(ODESystem, rn; combinatoric_ratelaws=false)
 ```
 Disabling these rescalings should work for all conversions of `ReactionSystem`s
@@ -88,6 +88,7 @@ rx2 = Reaction(2*k, [B], [D], [1], [2.5])
 rx3 = Reaction(2*k, [B], [D], [2.5], [2])
 @named mixedsys = ReactionSystem([rx1, rx2, rx3], t, [A, B, C, D], [k, b])
 osys = convert(ODESystem, mixedsys; combinatoric_ratelaws = false)
+osys = complete(osys)
 ```
 Note, when using `convert(ODESystem, mixedsys; combinatoric_ratelaws=false)` the
 `combinatoric_ratelaws=false` parameter must be passed. This is also true when
@@ -127,6 +128,7 @@ t = default_t()
 rx1 = Reaction(β, [S, I], [I], [1,1], [2])
 rx2 = Reaction(ν, [I], [R])
 @named sir = ReactionSystem([rx1, rx2], t)
+sir = complete(sir)
 oprob = ODEProblem(sir, [], (0.0, 250.0))
 sol = solve(oprob, Tsit5())
 plot(sol)
@@ -162,7 +164,7 @@ Julia `Symbol`s corresponding to each variable/parameter to their values, or
 from ModelingToolkit symbolic variables/parameters to their values. Using
 `Symbol`s we have
 ```@example faq4
-using Catalyst, DifferentialEquations
+using Catalyst, OrdinaryDiffEq
 rn = @reaction_network begin
     α, S + I --> 2I
     β, I --> R
@@ -199,6 +201,7 @@ the second example, or one can use the `symmap_to_varmap` function to convert th
 `Symbol` mapping to a symbolic mapping. I.e. this works
 ```@example faq4
 osys = convert(ODESystem, rn)
+osys = complete(osys)
 
 # this works
 u0 = symmap_to_varmap(rn, [:S => 999.0, :I => 1.0, :R => 0.0])
@@ -221,6 +224,7 @@ rx1 = @reaction k, A --> 0
 rx2 = @reaction $f, 0 --> A
 eq = f ~ (1 + sin(t))
 @named rs = ReactionSystem([rx1, rx2, eq], t)
+rs = complete(rs)
 osys = convert(ODESystem, rs)
 ```
 In the final ODE model, `f` can be eliminated by using