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This should be able to catch most mistakes regarding gradients. It would either require to add a dependency on rascaline in tests, or write a small calculator in pure Python to be used in tests. I thi…
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https://github.com/JuliaDiffEq/DiffEqDiffTools.jl
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This benchmark was contributed by @pbrady: [b.tar.gz](https://github.com/symengine/symengine/files/567339/b.tar.gz).
To test this, do:
```
$ maxima
Maxima 5.37.2 http://maxima.sourceforge.net
…
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Error in the sensitivity analysis (and/or forward analysis) of eigenvaluebeamclamped
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Does it have to do with the finite difference mode chosen by default?
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The zeroth order thing we want to check is whether the fact that ngmix relies on finite differences to measure the gradients can have a measurable impact on the response matrix, on a galaxy per galaxy…
EiffL updated
2 years ago
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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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As requested...
In the equation hosted at `svgs/9f0117ddac55126872d30e373e4fa435.svg`, there appears to be a case of a missing 1/Δt, in the step I've highlighted below.
The terms p with dots ove…
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There are two interesting articles in the Intel's Blog:
I like this one as it addresses most common optimizations for such algorithms:
https://software.intel.com/en-us/articles/eight-optimizations-fo…