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change measured quantities in Goodwin example
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docs/src/tutorials/parameter_identifiability.md

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@@ -109,7 +109,7 @@ __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)
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@variables t x1(t) x2(t) x3(t) x4(t) y(t) y2(t)
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D = Differential(t)
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eqs = [
@@ -119,21 +119,21 @@ 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]
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measured_quantities = [y~x1+x2, y2~x2]
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ode = ODESystem(eqs, t, name=:GoodwinOsc)
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@time global_id = assess_identifiability(ode, measured_quantities=measured_quantities)
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# 28.961573 seconds (88.92 M allocations: 5.541 GiB, 4.01% gc time)
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# Dict{Num, Symbol} with 7 entries:
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# c => :globally
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# a => :nonidentifiable
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# g => :nonidentifiable
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# delta => :locally
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# sigma => :globally
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# beta => :locally
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# b => :globally
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# 30.672594 seconds (100.97 M allocations: 6.219 GiB, 3.15% gc time, 0.01% compilation time)
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# Dict{Num, Symbol} with 7 entries:
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# a => :globally
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# b => :globally
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# beta => :globally
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# c => :globally
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# sigma => :globally
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# g => :nonidentifiable
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# delta => :globally
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```
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We can see that only parameters `a, g` are unidentifiable and everything else can be uniquely recovered.
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@@ -151,7 +151,7 @@ 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]
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measured_quantities = [y~x1+x2, y2~x2]
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# check only 2 parameters
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to_check = [b, c]

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