diff --git a/dev/.documenter-siteinfo.json b/dev/.documenter-siteinfo.json index 7767f83..a1ea7eb 100644 --- a/dev/.documenter-siteinfo.json +++ b/dev/.documenter-siteinfo.json @@ -1 +1 @@ -{"documenter":{"julia_version":"1.10.3","generation_timestamp":"2024-05-16T15:25:46","documenter_version":"1.4.1"}} \ No newline at end of file +{"documenter":{"julia_version":"1.10.3","generation_timestamp":"2024-05-16T15:26:45","documenter_version":"1.4.1"}} \ No newline at end of file diff --git a/dev/index.html b/dev/index.html index eb1c07f..0cc8e7f 100644 --- a/dev/index.html +++ b/dev/index.html @@ -1,2 +1,2 @@ -Home · NLPModelsKnitro.jl
GitHub

NLPModelsKnitro.jl documentation

This package provides a thin KNITRO wrapper for NLPModels, using jump-dev/KNITRO.jl internal structures directly.

Please refer to the NLPModels documentation for the API of NLPModels, if needed.

Install

Install NLPModelsKnitro.jl with the following commands.

pkg> add NLPModelsKnitro

Bug reports and discussions

If you think you found a bug, feel free to open an issue. Focused suggestions and requests can also be opened as issues. Before opening a pull request, start an issue or a discussion on the topic, please.

If you want to ask a question not suited for a bug report, feel free to start a discussion here. This forum is for general discussion about this repository and the JuliaSmoothOptimizers, so questions about any of our packages are welcome.

Contents

+Home · NLPModelsKnitro.jl
GitHub

NLPModelsKnitro.jl documentation

This package provides a thin KNITRO wrapper for NLPModels, using jump-dev/KNITRO.jl internal structures directly.

Please refer to the NLPModels documentation for the API of NLPModels, if needed.

Install

Install NLPModelsKnitro.jl with the following commands.

pkg> add NLPModelsKnitro

Bug reports and discussions

If you think you found a bug, feel free to open an issue. Focused suggestions and requests can also be opened as issues. Before opening a pull request, start an issue or a discussion on the topic, please.

If you want to ask a question not suited for a bug report, feel free to start a discussion here. This forum is for general discussion about this repository and the JuliaSmoothOptimizers, so questions about any of our packages are welcome.

Contents

diff --git a/dev/objects.inv b/dev/objects.inv index eff0cbc..220d2e4 100644 --- a/dev/objects.inv +++ b/dev/objects.inv @@ -1,6 +1,6 @@ # Sphinx inventory version 2 # Project: NLPModelsKnitro.jl -# Version: 0.9.0 +# Version: 0.9.1 # The remainder of this file is compressed using zlib. xuN0 y Kp59`Y 7g'Kz|۶D1kGgߒ$>Xӗ-SN54 diff --git a/dev/reference/index.html b/dev/reference/index.html index ab36408..7aee232 100644 --- a/dev/reference/index.html +++ b/dev/reference/index.html @@ -1,4 +1,4 @@ Reference · NLPModelsKnitro.jl
GitHub

Reference

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Contents

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​

Index

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NLPModelsKnitro.KnitroSolver — Type
KnitroSolver(::Val{Bool}, nlp; kwargs...,)

Returns a KnitroSolver structure to solve the problem nlp with knitro!.

Knitro does not accept least-squares problems with constraints other than bounds. If an NLSModel has constraints other than bounds, we convert it to a FeasibilityFormNLS. The first argument is Val(false) if the problem has been converted, and Val(true) otherwise.

For the possible kwargs, we refer to knitro.

source
NLPModelsKnitro.knitro — Function
output = knitro(nlp; kwargs...)

Solves the NLPModel problem nlp using KNITRO.

For advanced usage, first define a KnitroSolver to preallocate the memory used in the algorithm, and then call solve!:

solver = KnitroSolver(nlp)
 solve!(solver, nlp; kwargs...)
-solve!(solver, nlp, stats; kwargs...)

Optional keyword arguments

  • x0: a vector of size nlp.meta.nvar to specify an initial primal guess
  • y0: a vector of size nlp.meta.ncon to specify an initial dual guess for the general constraints
  • z0: a vector of size nlp.meta.nvar to specify initial multipliers for the bound constraints
  • callback: a user-defined Function called by KNITRO at each iteration.

For more information on callbacks, see https://www.artelys.com/docs/knitro/2userGuide/callbacks.html and the docstring of `KNITRO.KNsetnewptcallback`.

All other keyword arguments will be passed to KNITRO as an option. See https://www.artelys.com/docs/knitro/3_referenceManual/userOptions.html for the list of options accepted.

source
+solve!(solver, nlp, stats; kwargs...)

Optional keyword arguments

For more information on callbacks, see https://www.artelys.com/docs/knitro/2userGuide/callbacks.html and the docstring of `KNITRO.KNsetnewptcallback`.

All other keyword arguments will be passed to KNITRO as an option. See https://www.artelys.com/docs/knitro/3_referenceManual/userOptions.html for the list of options accepted.

source diff --git a/dev/tutorial/index.html b/dev/tutorial/index.html index 4724056..a1a3562 100644 --- a/dev/tutorial/index.html +++ b/dev/tutorial/index.html @@ -123,4 +123,4 @@ scatter(df.age[P], df.salary[P], c=:blue, m=:square) P = findall(df.buy .== false) scatter!(df.age[P], df.salary[P], c=:red, m=:xcross, ms=7) -contour!(range(18, 60, step=0.1), range(40_000, 180_000, step=1.0), f, levels=[0.5])

+contour!(range(18, 60, step=0.1), range(40_000, 180_000, step=1.0), f, levels=[0.5])