# Internal functions

These functions may or may not be exported. They are used internally.

NLPModels.@lencheckMacro
@lencheck n x y z …

Check that arrays x, y, z, etc. have a prescribed length n.

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NLPModels.@rangecheckMacro
@rangecheck ℓ u i j k …

Check that values i, j, k, etc. are in the range [ℓ,u].

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NLPModels.coo_prod!Function
coo_prod!(rows, cols, vals, v, Av)

Compute the product of a matrix A given by (rows, cols, vals) and the vector v. The result is stored in Av, which should have length equals to the number of rows of A.

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NLPModels.coo_sym_prod!Function
coo_sym_prod!(rows, cols, vals, v, Av)

Compute the product of a symmetric matrix A given by (rows, cols, vals) and the vector v. The result is stored in Av, which should have length equals to the number of rows of A. Only one triangle of A should be passed.

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NLPModels.DimensionErrorType
DimensionError <: Exception
DimensionError(name, dim_expected, dim_found)

Error for unexpected dimension. Output: "DimensionError: Input name should have length dim_expected not dim_found"

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NLPModels.histlineFunction
histline(s, v, maxv)

Return a string of the form

______NAME______: ████⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 5

where:

• ______NAME______ is s with padding to the left and length 16.
• And the symbols █ and ⋅ fill 20 characters in the proportion of v / maxv to █ and the rest to ⋅.
• The number 5 is v.
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NLPModels.lines_of_descriptionFunction
lines_of_description(meta)

Describe meta for the show function.

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lines_of_description(nls_meta)

Describe nls_meta for the show function.

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NLPModels.lines_of_histFunction
lines_of_hist(S, V)

Return a vector of histline(s, v, maxv)s using pairs of s in S and v in V. maxv is given by the maximum of V.

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NLPModels.show_headerFunction
show_header(io, nlp)

Show a header for the specific nlp type. Should be imported and defined for every model implementing the NLPModels API.

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NLPModels.sparsitylineFunction
sparsityline(s, v, maxv)

Return a string of the form

______NAME______: ( 80.00% sparsity)   5

where:

• ______NAME______ is s with padding to the left and length 16.
• The sparsity value is given by v / maxv.
• The number 5 is v.
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