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docs/make.jl

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

docs/src/inverse_problems/behaviour_optimisation.md

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@@ -38,7 +38,7 @@ function pulse_amplitude(p, _)
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SciMLBase.successful_retcode(sol) || return Inf
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return -(maximum(sol[:Z]) - sol[:Z][1])
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end
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nothing # here
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nothing # hide
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```
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This cost function takes two arguments (a parameter value `p`, and an additional one which we will ignore here but discuss later). It first calculates the new initial steady state concentration for the given parameter set. Next, it creates an updated `ODEProblem` using the steady state as initial conditions and the, to the cost function provided, input parameter set. While we could create a new `ODEProblem` within the cost function, cost functions are often called a large number of times during the optimisation process (making performance important). Here, using [`remake` on a previously created `ODEProblem`](@ref simulation_structure_interfacing_problems_remake) is more performant than creating a new one. Just like [when using Optimization.jl to fit parameters to data](@ref optimization_parameter_fitting), we use the `verbose = false` option to prevent unnecessary simulation printouts, and a reduced `maxiters` value to reduce time spent simulating (for the model) unsuitable parameter sets. We also use `SciMLBase.successful_retcode(sol)` to check whether the simulation return code indicates a successful simulation (and if it did not, returns a large cost function value). Finally, Optimization.jl finds the function's *minimum value*, so to find the *maximum* relative pulse amplitude, we make our cost function return the negative pulse amplitude.
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docs/src/model_creation/dsl_advanced.md

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nothing # hide
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```
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!!! note
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If only a single observable is declared, the `begin .. end` block is not required and the observable can be declared directly after the `@observables` option.
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If only a single observable is declared, the `begin ... end` block is not required and the observable can be declared directly after the `@observables` option.
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[Metadata](@ref dsl_advanced_options_species_and_parameters_metadata) can be supplied to an observable directly after its declaration (but before its formula). If so, the metadata must be separated from the observable with a `,`, and the observable plus the metadata encapsulated by `()`. E.g. to add a [description metadata](@ref dsl_advanced_options_species_and_parameters_metadata) to our observable we can use
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```@example dsl_advanced_observables

docs/src/model_creation/dsl_basics.md

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Here, `P`'s production rate will be reduced as `A` decays. We can [print the ODE this model produces with `Latexify`](@ref visualisation_latex):
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```@example dsl_basics
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using Latexify
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latexify(rn_13; form=:ode)
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latexify(rn_13; form = :ode)
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```
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In this case, we can generate an equivalent model by instead adding `A` as both a substrate and a product to `P`'s production reaction:
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```
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We can confirm that this generates the same ODE:
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```@example dsl_basics
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latexify(rn_13_alt; form=:ode)
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latexify(rn_13_alt; form = :ode)
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```
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Here, while these models will generate identical ODE, SDE, and jump simulations, the chemical reaction network models themselves are not equivalent. Generally, as pointed out in the two notes below, using the second form is preferable.
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!!! warn

docs/src/model_creation/model_visualisation.md

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```@example visualisation_latex
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using Latexify
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latexify(brusselator)
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brusselator # hide
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```
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Here, we note that the output of `latexify(brusselator)` is identical to how a model is displayed by default. Indeed, the reason is that Catalyst internally uses Latexify's `latexify` function to display its models. It is also possible to display the ODE equations a model would generate by adding the `form = :ode` argument:
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```@example visualisation_latex

docs/src/model_simulation/simulation_structure_interfacing.md

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```
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Note that here, species-interfacing yields (or changes) a simulation's current value for a species, not its initial condition.
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If you are interfacing with jump simulation integrators, please read this, highly relevant, section
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If you are interfacing with jump simulation integrators, you must always call `reset_aggregated_jumps!(integrator)` afterwards.
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## [Interfacing solution objects](@id simulation_structure_interfacing_solutions)
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