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This repository has been archived by the owner on Jun 24, 2022. It is now read-only.
Hey, this package will soon be supersceded by ModelingToolkit's sparsity detection algorithms, which are documented here: https://mtk.sciml.ai/dev/highlevel/#Sparsity-Detection-1 . You might want to try those since it's more robust. See https://mtk.sciml.ai/dev/tutorials/auto_parallel/ as an example with automated sparse Jacobians, or you can replace the actual symbolic Jacobians with just jacobian_sparsity to get the sparsity pattern and it's effectively the same algorithm as what's done here, except using MTK for the abstract interpretation.
Hello! Awesome package.
I'm trying to extend the examples and have found a simple case that fails:
function f!(dx,x)
dx[1:5] = x[1:5] + x[1:5]
nothing
end
output = zeros(5)
input = ones(5)
sparsity!(f!,output,input)
The above function 'f' should return the same sparsity pattern as the function 'g' below:
function g!(dx,x)
dx[1:5] = x[1:5]
nothing
end
but when called on 'f' the sparsity pattern returned is empty.
Is my usage incorrect?
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