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## Description
As discussed over in #2839, the ODE methods are not `fvar` compatible, and it would be a significant amount of work to do so. This means that any downstream methods depending on `fva…
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Time-like paths recorded as a set of finite differences can be converted into a list of displacements.
These will always have a monotonic t(tau) and thus efficient methods can be used to display pre-r…
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When I execute either Example 1 or 2 of the git repo i get an error while fitting the model. Not sure if i did something wrong on installation, but i tried several hours to get it running.
### Erro…
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```julia
julia> function f(x,p)
grad = FiniteDiff.finite_difference_gradient(y -> sum(y.^3), x)
return grad .* p
end
f (generic function with 1 method)
julia> x,p …
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Hi,Matthew!
I ran your code and found it amazing. Your 2D simulation is really cool!
I just want to learn some finite difference methods for C-H equation. I read your code but find it hard for me…
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A paper describing the spatial discretization used by ParFlow notes that they use the harmonic mean of cell quantities when computing face quantities (for a particular field of interest, the hydraulic…
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the method your propose NLST is Interesting.
I have some questions about the retrial normal.
In your paper, you said that We retrieve the surface normal from the SDF via finite differences and trans…
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I am currently using "layered_halfspace" (from the examples folder of build) to perform benchmarking of the application. Is there a recommendation on which one is a popular suite to work with-for per…
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### Expected behavior
The derivative is (approximately) independent of decomposition and diff method
### Actual behavior
The derivative between `StatePrep` and its decomposition differs.
### Addit…
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`ngradient` implements a version of Finite Differences Method like that provided by
[JuliaDiff/FiniteDifferences.jl](https://github.com/JuliaDiff/FiniteDifferences.jl). The numerical gradient checki…