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improve linearize docstring
rm kwargs...
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src/systems/abstractsystem.jl

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@@ -1285,12 +1285,12 @@ The `simplified_sys` has undergone [`structural_simplify`](@ref) and had any occ
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See also [`linearize`](@ref) which provides a higher-level interface.
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"""
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function linearization_function(sys::AbstractSystem, inputs,
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outputs; simplify = false,
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initialize = true,
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op = Dict(),
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p = DiffEqBase.NullParameters(),
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zero_dummy_der = false,
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kwargs...)
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outputs; simplify = false,
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initialize = true,
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op = Dict(),
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p = DiffEqBase.NullParameters(),
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zero_dummy_der = false,
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kwargs...)
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inputs isa AbstractVector || (inputs = [inputs])
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outputs isa AbstractVector || (outputs = [outputs])
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ssys, diff_idxs, alge_idxs, input_idxs = io_preprocessing(sys, inputs, outputs;
@@ -1488,7 +1488,7 @@ end
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(; A, B, C, D), simplified_sys = linearize(sys, inputs, outputs; t=0.0, op = Dict(), allow_input_derivatives = false, zero_dummy_der=false, kwargs...)
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(; A, B, C, D) = linearize(simplified_sys, lin_fun; t=0.0, op = Dict(), allow_input_derivatives = false, zero_dummy_der=false)
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Return a NamedTuple with the matrices of a linear statespace representation
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Linearize `sys` between `inputs` and `outputs`, both vectors of variables. Return a NamedTuple with the matrices of a linear statespace representation
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on the form
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```math
@@ -1586,7 +1586,7 @@ lsys_sym, _ = ModelingToolkit.linearize_symbolic(cl, [f.u], [p.x])
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```
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"""
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function linearize(sys, lin_fun; t = 0.0, op = Dict(), allow_input_derivatives = false,
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p = DiffEqBase.NullParameters(), kwargs...)
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p = DiffEqBase.NullParameters())
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x0 = merge(defaults(sys), op)
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u0, p2, _ = get_u0_p(sys, x0, p; use_union = false, tofloat = true)
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