SciML / SciML/DataDrivenDiffEq.jl

Bad `ISINDy` results from trivial linear function.

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#200 4 comments 0 reactions 1 assignee View on GitHub

@AlCap23 is already working on this.

Since Mar 19, 2021.

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Description

Hi,

I've had some trouble with ISINDy results that I don't think makes any sense so I created a very small example (y = a*x + b) that "should" work but it turns out that it does not.

using DataDrivenDiffEq, ModelingToolkit
@variables A
x = permutedims(collect(1.:10))
y = 2 .+ 3 .* x
Ψ = ISINDy(x, y, Basis([1, A, A^2], [A]), ADM(1.1e-1))
print_equations(Ψ)
##Basis#1576 : 1 dimensional basis in ["A"]
Parameters : Sym{ModelingToolkit.Parameter{Real},Nothing}[p₁, p₂, p₃, p₄, p₅]

Independent variable: t
Equations
φ₁ = ((-p₂) - (A*p₄) - (p₅*(A^2)))*((p₁ + (A*p₃))^-1)

Should this example not work?

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