Wrappers

This page documents the API of the NLPModels and the MOI wrapper implemented in Argos.

NLPModels

Argos.OPFModel — Type
OPFModel <: NLPModels.AbstractNLPModel{Float64,Vector{Float64}}

Wrap a AbstractNLPEvaluator as a NLPModels.AbstractNLPModel.

Examples

julia> datafile = "case9.m"  # specify a path to a MATPOWER instance

julia> nlp = Argos.ReducedSpaceEvaluator(datafile);

julia> model = Argos.OPFModel(nlp)

Attributes

  • meta::NLPModels.NLPModelMeta: information about the model.
  • counter::NLPModels.Counters: count how many time each callback is being called.
  • timer::NLPTimers: decompose time spent in each callback.
  • nlp::AbstractNLPEvaluator: OPF model.
  • hash_x::UInt: hash of the last evaluated variable x
  • hrows::Vector{Int}: row indices of the Hessian.
  • hcols::Vector{Int}: column indices of the Hessian.
  • jrows::Vector{Int}: row indices of the Jacobian.
  • jcols::Vector{Int}: column indices of the Jacobian.
  • etc::Dict{Symbol,Any}: a dictionnary for running experiments.
source
Argos.backend — Function

Query the AbstractNLPEvaluator backend used inside the OPFModel m.

source

MOI evaluator

Argos.MOIEvaluator — Type
MOIEvaluator <: MOI.AbstractNLPEvaluator

Bridge from a AbstractNLPEvaluator to a MOI.AbstractNLPEvaluator.

Example

julia> datafile = "case9.m"  # specify a path to a MATPOWER instance

julia> nlp = Argos.ReducedSpaceEvaluator(datafile);

julia> ev = Argos.MOIEvaluator(nlp)

Attributes

  • nlp::AbstractNLPEvaluator: the underlying ExaPF problem.
  • hash_x::UInt: hash of the last evaluated variable x
  • has_hess::Bool (default: false): if true, pass a Hessian structure to MOI.
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