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LICENSE

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Copyright (c) 2019 JuliaDiffEq
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Copyright (c) 2019 JuliaDiff
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal

README.md

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# SparseDiffTools.jl
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[![Join the chat at https://gitter.im/JuliaDiffEq/Lobby](https://badges.gitter.im/JuliaDiffEq/Lobby.svg)](https://gitter.im/JuliaDiffEq/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
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[![Build Status](https://travis-ci.org/JuliaDiffEq/SparseDiffTools.jl.svg?branch=master)](https://travis-ci.org/JuliaDiffEq/SparseDiffTools.jl)
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[![GitlabCI](https://gitlab.com/juliadiffeq/SparseDiffTools-jl/badges/master/pipeline.svg)](https://gitlab.com/juliadiffeq/SparseDiffTools-jl/pipelines)
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[![Join the chat at https://gitter.im/JuliaDiff/Lobby](https://badges.gitter.im/JuliaDiff/Lobby.svg)](https://gitter.im/JuliaDiff/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
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[![Build Status](https://travis-ci.org/JuliaDiff/SparseDiffTools.jl.svg?branch=master)](https://travis-ci.org/JuliaDiff/SparseDiffTools.jl)
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[![GitlabCI](https://gitlab.com/JuliaDiff/SparseDiffTools-jl/badges/master/pipeline.svg)](https://gitlab.com/JuliaDiff/SparseDiffTools-jl/pipelines)
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This package is for exploiting sparsity in Jacobians and Hessians to accelerate
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computations. Matrix-free Jacobian-vector product and Hessian-vector product
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ForwardDiff.jl.
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For DiffEqDiffTools.jl, one simply has to use the provided `colorvec` keyword
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argument. See
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[the DiffEqDiffTools Jacobian documentation](https://github.com/JuliaDiffEq/DiffEqDiffTools.jl#jacobians)
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argument. See
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[the DiffEqDiffTools Jacobian documentation](https://github.com/JuliaDiff/DiffEqDiffTools.jl#jacobians)
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for more details.
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For forward-mode automatic differentiation, use of a colorvec vector is provided
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Notice that if a sparsity pattern is not supplied then the built Jacobian will
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be the compressed Jacobian: `sparsity` must be a sparse matrix or a structured matrix
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(`Tridiagonal`, `Banded`, etc. conforming to the ArrayInterface.jl specs) with the
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(`Tridiagonal`, `Banded`, etc. conforming to the ArrayInterface.jl specs) with the
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appropriate sparsity pattern to allow for decompression.
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This call will allocate the cache variables each time. To avoid allocating the

test/test_ad.jl

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forwarddiff_color_jacobian!(_Jt, f, x, colorvec = repeat(1:3,10), sparsity = _Jt)
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@test _Jt J
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#https://github.com/JuliaDiffEq/DiffEqDiffTools.jl/issues/67#issuecomment-516871956
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#https://github.com/JuliaDiff/DiffEqDiffTools.jl/issues/67#issuecomment-516871956
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function f(out, x)
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x = reshape(x, 100, 100)
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out = reshape(out, 100, 100)

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