fix some broken examples

Author: Fredrik Bagge Carlson

docs/Project.toml

@@ -1,6 +1,15 @@
 [deps]
+BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
+DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
+Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+GalacticOptim = "a75be94c-b780-496d-a8a9-0878b188d577"
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
+Optim = "429524aa-4258-5aef-a3af-852621145aeb"
+OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
+Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 
 [compat]
 Documenter = "0.27"

docs/src/basics/Composition.md

@@ -75,7 +75,7 @@ Every `AbstractSystem` has a `system` keyword argument for specifying
 subsystems. A model is the composition of itself and its subsystems.
 For example, if we have:
 
-```@example composition
+```julia
 @named sys = compose(ODESystem(eqs,indepvar,states,ps),subsys)
 ```
 
@@ -100,7 +100,7 @@ associated `SciMLProblem` type using the standard constructors. When
 this is done, the initial conditions and parameters must be specified
 in their namespaced form. For example:
 
-```@example composition
+```julia
 u0 = [
   x => 2.0
   subsys.x => 2.0
@@ -190,7 +190,7 @@ N = S + I + R
 @named ieqn = ODESystem([D(I) ~ β*S*I/N-γ*I])
 @named reqn = ODESystem([D(R) ~ γ*I])
 
-@named sir = compose(ODESystem([
+sir = compose(ODESystem([
                     S ~ ieqn.S,
                     I ~ seqn.I,
                     R ~ ieqn.R,
@@ -204,7 +204,7 @@ N = S + I + R
                         ieqn.β => β
                         ieqn.γ => γ
                         reqn.γ => γ
-                    ]), seqn, ieqn, reqn)
+                    ], name=:sir), seqn, ieqn, reqn)
 ```
 
 Note that the states are forwarded by an equality relationship, while

docs/src/mtkitize_tutorials/modelingtoolkitize.md

@@ -5,7 +5,7 @@ via the `modelingtoolkitize` function. Take, for example, the Robertson ODE
 defined as an `ODEProblem` for DifferentialEquations.jl:
 
 ```@example mtkize
-using DifferentialEquations
+using DifferentialEquations, ModelingToolkit
 function rober(du,u,p,t)
   y₁,y₂,y₃ = u
   k₁,k₂,k₃ = p

docs/src/mtkitize_tutorials/sparse_jacobians.md

@@ -50,7 +50,7 @@ prob = ODEProblem(brusselator_2d_loop,u0,(0.,11.5),p)
 Now let's use `modelingtoolkitize` to generate the symbolic version:
 
 ```@example sparsejac
-sys = modelingtoolkitize(prob_ode_brusselator_2d)
+sys = modelingtoolkitize(prob)
 ```
 
 Now we regenerate the problem using `jac=true` for the analytical Jacobian