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docs/src/basics/NonlinearFunctions.md

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@@ -8,33 +8,6 @@ of pre-computed functions to speed up the calculations. This is offered via the
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## Function Type Definitions
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### Function Choice Definitions
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The full interface available to the solvers is as follows:
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- `jac`: The Jacobian of the differential equation with respect to the state
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variable `u` at a time `t` with parameters `p`.
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- `tgrad`: The gradient of the differential equation with respect to `t` at state
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`u` with parameters `p`.
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- `paramjac`: The Jacobian of the differential equation with respect to `p` at
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state `u` at time `t`.
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- `analytic`: Defines an analytical solution using `u0` at time `t` with `p`
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which will cause the solvers to return errors. Used for testing.
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- `syms`: Allows you to name your variables for automatic names in plots and
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other output.
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### NonlinearFunction
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```julia
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function NonlinearFunction{iip,true}(f;
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analytic=nothing, # (u0,p)
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jac=nothing, # (J,u,p) or (u,p)
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jvp=nothing,
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vjp=nothing,
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jac_prototype=nothing, # Type for the Jacobian
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sparsity=jac_prototype,
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paramjac = nothing,
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syms = nothing,
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observed = DEFAULT_OBSERVED_NO_TIME,
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colorvec = nothing)
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```@docs
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SciMLBase.NonlinearFunction
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```

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