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Update symbolic_analysis.md
fixes #130
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docs/src/showcase/symbolic_analysis.md

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@@ -314,7 +314,8 @@ x_1'(t) = -b x_1(t) + \frac{1 }{ c + x_4(t)},\\
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x_2'(t) = \alpha x_1(t) - \beta x_2(t),\\
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x_3'(t) = \gamma x_2(t) - \delta x_3(t),\\
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x_4'(t) = \sigma x_4(t) \frac{(\gamma x_2(t) - \delta x_3(t))}{ x_3(t)},\\
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y(t) = x_1(t)
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y_1(t) = x_1(t) + x_2(t)
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y_2(t) = x_2(t)
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\end{cases}$$
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We will run a global identifiability check on this enzyme dynamics[^3] model. We will use the default settings: the probability of correctness will be `p=0.99` and we are interested in identifiability of all possible parameters.
@@ -326,7 +327,7 @@ __Note__: as of writing this tutorial, UTF-symbols such as Greek characters are
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```julia
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using StructuralIdentifiability, ModelingToolkit
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@parameters b c a beta g delta sigma
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@variables t x1(t) x2(t) x3(t) x4(t) y(t) y2(t)
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@variables t x1(t) x2(t) x3(t) x4(t) y1(t) y2(t)
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D = Differential(t)
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eqs = [
@@ -336,7 +337,7 @@ eqs = [
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D(x4) ~ sigma * x4 * (g * x2 - delta * x3) / x3
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]
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measured_quantities = [y ~ x1 + x2, y2 ~ x2]
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measured_quantities = [y1 ~ x1 + x2, y2 ~ x2]
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ode = ODESystem(eqs, t, name = :GoodwinOsc)
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@@ -369,7 +370,7 @@ eqs = [
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D(x3) ~ g * x2 - delta * x3 + u2,
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D(x4) ~ sigma * x4 * (g * x2 - delta * x3) / x3
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]
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measured_quantities = [y ~ x1 + x2, y2 ~ x2]
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measured_quantities = [y1 ~ x1 + x2, y2 ~ x2]
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# check only 2 parameters
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to_check = [b, c]

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