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Oct 10, 2022
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Update README jacobian_sparsity #204

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13 changes: 6 additions & 7 deletions README.md
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Expand Up @@ -43,18 +43,17 @@ end

For this function, we know that the sparsity pattern of the Jacobian is a
`Tridiagonal` matrix. However, if we didn't know the sparsity pattern for
the Jacobian, we could use the `jacobian_sparsity` function to automatically
detect the sparsity pattern. This function is only available if you
load SparsityDetection.jl as well. We declare that the function `f` outputs a
vector of length 30 and takes in a vector of length 30, and `jacobian_sparsity` spits
out a `Sparsity` object which we can turn into a `SparseMatrixCSC`:
the Jacobian, we could use the `Symbolics.jacobian_sparsity` function to automatically
detect the sparsity pattern. We declare that the function `f` outputs a
vector of length 30 and takes in a vector of length 30, and `jacobian_sparsity` returns
a `SparseMatrixCSC`:

```julia
using Symbolics, SparseArrays
using Symbolics
input = rand(30)
output = similar(input)
sparsity_pattern = Symbolics.jacobian_sparsity(f,output,input)
jac = Float64.(sparse(sparsity_pattern))
jac = Float64.(sparsity_pattern)
```

Now we call `matrix_colors` to get the colorvec vector for that matrix:
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