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Copy file name to clipboardExpand all lines: src/sparsity_pattern.jl
+12-15Lines changed: 12 additions & 15 deletions
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@@ -55,7 +55,7 @@ function compute_hessian_sparsity(
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end
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"""
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S = get_sparsity_pattern(model::ADModel, derivate::Symbol)
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S = get_sparsity_pattern(model::ADModel, derivative::Symbol)
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Retrieve the sparsity pattern of a Jacobian or Hessian from an `ADModel`.
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For the Hessian, only the lower triangular part of its sparsity pattern is returned.
@@ -67,27 +67,24 @@ Supported backends include `SparseADJacobian`, `SparseADHessian`, and `SparseRev
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#### Input arguments
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* `model`: An automatic differentiation model (either `AbstractADNLPModel` or `AbstractADNLSModel`).
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* `derivate`: The type of derivative for which the sparsity pattern is needed. The supported values are `:jacobian`, `:hessian`, `:jacobian_residual` and `:hessian_residual`.
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* `derivative`: The type of derivative for which the sparsity pattern is needed. The supported values are `:jacobian`, `:hessian`, `:jacobian_residual` and `:hessian_residual`.
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#### Output argument
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* `S`: A sparse matrix of type `SparseMatrixCSC{Bool,Int}` indicating the sparsity pattern of the requested derivative.
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