updates. move petab doc page

Author: TorkelE

docs/src/inverse_problems/petab_ode_param_fitting.md renamed to docs/old_files/petab_ode_param_fitting.md

@@ -27,7 +27,7 @@ pages = Any[
         # Simulation introduction.
         # Simulation plotting.
         "model_simulation/simulation_structure_interfacing.md",
-        # Monte Carlo/Ensemble simulations.
+        "model_simulation/TOBEREMOVED_advanced_simulations.md",# Monte Carlo/Ensemble simulations.        
         # Stochastic simulation statistical analysis.
         # ODE Performance considerations/advice.
         # SDE Performance considerations/advice.

docs/pages.jl

@@ -0,0 +1,57 @@
+[deps]
+BifurcationKit = "0f109fa4-8a5d-4b75-95aa-f515264e7665"
+Catalyst = "479239e8-5488-4da2-87a7-35f2df7eef83"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+DiffEqParamEstim = "1130ab10-4a5a-5621-a13d-e4788d82bd4c"
+DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
+Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+HomotopyContinuation = "f213a82b-91d6-5c5d-acf7-10f1c761b327"
+Latexify = "23fbe1c1-3f47-55db-b15f-69d7ec21a316"
+Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
+ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
+NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
+Optim = "429524aa-4258-5aef-a3af-852621145aeb"
+Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
+OptimizationNLopt = "4e6fcdb7-1186-4e1f-a706-475e75c168bb"
+OptimizationOptimJL = "36348300-93cb-4f02-beb5-3c3902f8871e"
+OptimizationOptimisers = "42dfb2eb-d2b4-4451-abcd-913932933ac1"
+OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
+QuasiMonteCarlo = "8a4e6c94-4038-4cdc-81c3-7e6ffdb2a71b"
+SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
+SciMLSensitivity = "1ed8b502-d754-442c-8d5d-10ac956f44a1"
+Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
+SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
+SteadyStateDiffEq = "9672c7b4-1e72-59bd-8a11-6ac3964bc41f"
+StochasticDiffEq = "789caeaf-c7a9-5a7d-9973-96adeb23e2a0"
+StructuralIdentifiability = "220ca800-aa68-49bb-acd8-6037fa93a544"
+Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7"
+
+[compat]
+BifurcationKit = "0.3"
+Catalyst = "13"
+DataFrames = "1"
+DiffEqParamEstim = "2.1"
+DifferentialEquations = "7.7"
+Distributions = "0.25"
+Documenter = "0.27"
+HomotopyContinuation = "2.6"
+Latexify = "0.15, 0.16"
+ModelingToolkit = "9.5"
+NonlinearSolve = "3.4.0"
+Optim = "1"
+Optimization = "3.19"
+OptimizationNLopt = "0.1.8"
+OptimizationOptimJL = "0.1.14"
+OptimizationOptimisers = "0.1.1"
+OrdinaryDiffEq = "6"
+Plots = "1.36"
+SciMLBase = "2.13"
+SciMLSensitivity = "7.19"
+Setfield = "1.1"
+SpecialFunctions = "2.1"
+SteadyStateDiffEq = "2.0.1"
+StochasticDiffEq = "6"
+StructuralIdentifiability = "0.5.1"
+Symbolics = "5.14"

docs/src/assets/Project.toml

@@ -41,10 +41,11 @@ variables in Julia.
 The chemical reaction model is generated by the `@reaction_network` macro and
 stored in the `rn` variable (a normal Julia variable, which does not need to be
 called `rn`). It corresponds to a [`ReactionSystem`](@ref), a symbolic
-representation of the chemical network.  The generated `ReactionSystem` can be
+representation of the chemical network. The generated `ReactionSystem` can be
 converted to a symbolic differential equation model via
 ```@example tut2
-osys  = convert(ODESystem, rn)
+osys = convert(ODESystem, rn)
+osys = complete(osys)
 ```
 
 We can then convert the symbolic ODE model into a compiled, optimized

docs/src/model_creation/dsl_description.md

@@ -226,7 +226,7 @@ p = [:k => 1.0]
 oprob = ODEProblem(rn, u0, tspan, p)
 
 condition = [5.0]
-affect!(integrator) = integrator[:k] = 5.0
+affect!(integrator) = integrator.ps[:k] = 5.0
 ps_cb = PresetTimeCallback(condition, affect!)
 
 sol = solve(deepcopy(oprob); callback = ps_cb)
@@ -279,7 +279,7 @@ jprob = JumpProblem(rn, dprob, Direct())
 condition = [5.0]
 function affect!(integrator)
     integrator[:X1] += 5.0
-    integrator[:k] += 2.0
+    integrator.ps[:k] += 2.0
     reset_aggregated_jumps!(integrator)
     nothing
 end