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Project.toml

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name = "ModelAnalyzer"
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name = "MathOptAnalyzer"
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uuid = "d1179b25-476b-425c-b826-c7787f0fff83"
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version = "0.1.0"
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JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
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[extensions]
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ModelAnalyzerJuMPExt = "JuMP"
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MathOptAnalyzerJuMPExt = "JuMP"
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[compat]
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Dualization = "0.6.0"

README.md

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# ModelAnalyzer.jl
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# MathOptAnalyzer.jl
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[![Build Status](https://github.com/jump-dev/ModelAnalyzer.jl/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/jump-dev/ModelAnalyzer.jl/actions?query=workflow%3ACI)
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[![codecov](https://codecov.io/gh/jump-dev/ModelAnalyzer.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/jump-dev/ModelAnalyzer.jl)
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[![Build Status](https://github.com/jump-dev/MathOptAnalyzer.jl/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/jump-dev/MathOptAnalyzer.jl/actions?query=workflow%3ACI)
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[![codecov](https://codecov.io/gh/jump-dev/MathOptAnalyzer.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/jump-dev/MathOptAnalyzer.jl)
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[ModelAnalyzer.jl](https://github.com/jump-dev/ModelAnalyzer.jl) is an
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[MathOptAnalyzer.jl](https://github.com/jump-dev/MathOptAnalyzer.jl) is an
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experimental package with analysis and debugging tools for JuMP and
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MathOptInterface.
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## License
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`ModelAnalyzer.jl` is licensed under the [MIT License](https://github.com/jump-dev/MultiObjectiveAlgorithms.jl/blob/main/LICENSE.md).
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`MathOptAnalyzer.jl` is licensed under the [MIT License](https://github.com/jump-dev/MultiObjectiveAlgorithms.jl/blob/main/LICENSE.md).
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## Getting help
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If you need help, please ask a question on the [JuMP community forum](https://jump.dev/forum).
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If you have a reproducible example of a bug, please [open a GitHub issue](https://github.com/jump-dev/ModelAnalyzer.jl/issues/new).
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If you have a reproducible example of a bug, please [open a GitHub issue](https://github.com/jump-dev/MathOptAnalyzer.jl/issues/new).
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## Installation
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Install `ModelAnalyzer` using `Pkg.add`:
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Install `MathOptAnalyzer` using `Pkg.add`:
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```julia
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import Pkg
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Pkg.add(; url = "https://github.com/jump-dev/ModelAnalyzer.jl")
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Pkg.add(; url = "https://github.com/jump-dev/MathOptAnalyzer.jl")
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```
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## Documentation
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The [documentation for ModelAnalyzer.jl](https://jump.dev/ModelAnalyzer.jl/dev/)
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The [documentation for MathOptAnalyzer.jl](https://jump.dev/MathOptAnalyzer.jl/dev/)
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describes how to use the package.

docs/Project.toml

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[deps]
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Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
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ModelAnalyzer = "d1179b25-476b-425c-b826-c7787f0fff83"
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MathOptAnalyzer = "d1179b25-476b-425c-b826-c7787f0fff83"
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JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
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[compat]

docs/make.jl

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using Documenter, ModelAnalyzer, JuMP
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using Documenter, MathOptAnalyzer, JuMP
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makedocs(; sitename = "ModelAnalyzer.jl documentation")
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makedocs(; sitename = "MathOptAnalyzer.jl documentation")
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deploydocs(;
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repo = "github.com/jump-dev/ModelAnalyzer.jl.git",
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repo = "github.com/jump-dev/MathOptAnalyzer.jl.git",
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push_preview = true,
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)

docs/src/analyzer.md

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# ModelAnalyzer main API
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# MathOptAnalyzer main API
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All the analysis modules in `ModelAnalyzer` follow the same main API.
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All the analysis modules in `MathOptAnalyzer` follow the same main API.
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The main function to perform an analysis is:
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```@docs
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ModelAnalyzer.analyze
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MathOptAnalyzer.analyze
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```
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Once the analysis is performed, the resulting data structure can be summarized
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using:
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```@docs
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ModelAnalyzer.summarize
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MathOptAnalyzer.summarize
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```
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Alternatively, you can also query the types of issues found in the analysis
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and summarize them individually. The following functions are useful for this:
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```@docs
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ModelAnalyzer.list_of_issue_types
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ModelAnalyzer.list_of_issues
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MathOptAnalyzer.list_of_issue_types
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MathOptAnalyzer.list_of_issues
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```
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It is possible to extract data from the issues with the methods:
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```@docs
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ModelAnalyzer.variables
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ModelAnalyzer.variable
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ModelAnalyzer.constraints
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ModelAnalyzer.constraint
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ModelAnalyzer.set
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ModelAnalyzer.values
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ModelAnalyzer.value
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MathOptAnalyzer.variables
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MathOptAnalyzer.variable
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MathOptAnalyzer.constraints
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MathOptAnalyzer.constraint
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MathOptAnalyzer.set
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MathOptAnalyzer.values
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MathOptAnalyzer.value
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```

docs/src/feasibility.md

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This module follows the main API and is activated by the struct:
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```@docs
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ModelAnalyzer.Feasibility.Analyzer
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MathOptAnalyzer.Feasibility.Analyzer
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```
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The analysis will return issues of the abstract type:
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```@docs
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ModelAnalyzer.Feasibility.AbstractFeasibilityIssue
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MathOptAnalyzer.Feasibility.AbstractFeasibilityIssue
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```
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Specifically, the possible issues are:
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```@docs
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ModelAnalyzer.Feasibility.PrimalViolation
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ModelAnalyzer.Feasibility.DualConstraintViolation
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ModelAnalyzer.Feasibility.DualConstrainedVariableViolation
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ModelAnalyzer.Feasibility.ComplemetarityViolation
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ModelAnalyzer.Feasibility.DualObjectiveMismatch
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ModelAnalyzer.Feasibility.PrimalObjectiveMismatch
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ModelAnalyzer.Feasibility.PrimalDualMismatch
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ModelAnalyzer.Feasibility.PrimalDualSolverMismatch
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MathOptAnalyzer.Feasibility.PrimalViolation
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MathOptAnalyzer.Feasibility.DualConstraintViolation
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MathOptAnalyzer.Feasibility.DualConstrainedVariableViolation
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MathOptAnalyzer.Feasibility.ComplemetarityViolation
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MathOptAnalyzer.Feasibility.DualObjectiveMismatch
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MathOptAnalyzer.Feasibility.PrimalObjectiveMismatch
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MathOptAnalyzer.Feasibility.PrimalDualMismatch
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MathOptAnalyzer.Feasibility.PrimalDualSolverMismatch
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```
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These issues are saved in the data structure that is returned from the
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`ModelAnalyzer.analyze` function:
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`MathOptAnalyzer.analyze` function:
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```@docs
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ModelAnalyzer.Feasibility.Data
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MathOptAnalyzer.Feasibility.Data
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```

docs/src/index.md

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```@meta
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CurrentModule = ModelAnalyzer
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CurrentModule = MathOptAnalyzer
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DocTestSetup = quote
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using ModelAnalyzer
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using MathOptAnalyzer
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end
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```
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# ModelAnalyzer.jl
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# MathOptAnalyzer.jl
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This package provides tools for analyzing (and debugging)
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[JuMP](https://github.com/jump-dev/JuMP.jl) models.
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```julia
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using Pkg
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Pkg.add(url = "https://github.com/jump-dev/ModelAnalyzer.jl")
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Pkg.add(url = "https://github.com/jump-dev/MathOptAnalyzer.jl")
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```
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## Usage
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```julia
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using JuMP
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using ModelAnalyzer
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using MathOptAnalyzer
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using HiGHS # or any other supported solver
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# Create a simple JuMP model
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model = Model(HiGHS.Optimizer)
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# either
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# Perform a numerical analysis of the model
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data = ModelAnalyzer.analyze(ModelAnalyzer.Numerical.Analyzer(), model)
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data = MathOptAnalyzer.analyze(MathOptAnalyzer.Numerical.Analyzer(), model)
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# print report
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ModelAnalyzer.summarize(data)
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MathOptAnalyzer.summarize(data)
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# or
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# Check for solution feasibility and optimality
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data = ModelAnalyzer.analyze(ModelAnalyzer.Feasibility.Analyzer(), model)
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data = MathOptAnalyzer.analyze(MathOptAnalyzer.Feasibility.Analyzer(), model)
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# print report
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ModelAnalyzer.summarize(data)
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MathOptAnalyzer.summarize(data)
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# or
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# Infeasibility analysis (if the model was infeasible)
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data = ModelAnalyzer.analyze(
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ModelAnalyzer.Infeasibility.Analyzer(),
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data = MathOptAnalyzer.analyze(
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MathOptAnalyzer.Infeasibility.Analyzer(),
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model,
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optimizer = HiGHS.Optimizer,
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)
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# print report to the screen
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ModelAnalyzer.summarize(data)
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MathOptAnalyzer.summarize(data)
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# or print the report to a file
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# open a file
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open("my_report.txt", "w") do io
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ModelAnalyzer.summarize(io, data)
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MathOptAnalyzer.summarize(io, data)
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end
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The `ModelAnalyzer.analyze(...)` function can always take the keyword arguments:
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The `MathOptAnalyzer.analyze(...)` function can always take the keyword arguments:
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* `verbose = false` to condense the print output.
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* `max_issues = n` to limit the maximum number of issues to report for each
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### Advanced usage
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After any `ModelAnalyzer.analyze(...)` call is performed, the resulting data
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structure can be summarized using `ModelAnalyzer.summarize(data)` as show above,
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After any `MathOptAnalyzer.analyze(...)` call is performed, the resulting data
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structure can be summarized using `MathOptAnalyzer.summarize(data)` as show above,
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or it can be further inspected programmatically.
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```julia
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# given a `data` object obtained from `ModelAnalyzer.analyze(...)`
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# given a `data` object obtained from `MathOptAnalyzer.analyze(...)`
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# query the types of issues found in the analysis
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list = ModelAnalyzer.list_of_issue_types(data)
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list = MathOptAnalyzer.list_of_issue_types(data)
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ModelAnalyzer.summarize(list[1])
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MathOptAnalyzer.summarize(list[1])
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# for each issue type, you can get the actual issues found in the analysis
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issues = ModelAnalyzer.list_of_issues(data, list[1])
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issues = MathOptAnalyzer.list_of_issues(data, list[1])
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ModelAnalyzer.summarize(issues)
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MathOptAnalyzer.summarize(issues)
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ModelAnalyzer.summarize(issues[1])
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MathOptAnalyzer.summarize(issues[1])
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### Non JuMP (or MOI) models

docs/src/infeasibility.md

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This module follows the main API and is activated by the struct:
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```@docs
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ModelAnalyzer.Infeasibility.Analyzer
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MathOptAnalyzer.Infeasibility.Analyzer
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```
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The analysis will return issues of the abstract type:
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```@docs
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ModelAnalyzer.Infeasibility.AbstractInfeasibilitylIssue
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MathOptAnalyzer.Infeasibility.AbstractInfeasibilitylIssue
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Specifically, the possible issues are:
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```@docs
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ModelAnalyzer.Infeasibility.InfeasibleBounds
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ModelAnalyzer.Infeasibility.InfeasibleIntegrality
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ModelAnalyzer.Infeasibility.InfeasibleConstraintRange
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ModelAnalyzer.Infeasibility.IrreducibleInfeasibleSubset
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MathOptAnalyzer.Infeasibility.InfeasibleBounds
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MathOptAnalyzer.Infeasibility.InfeasibleIntegrality
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MathOptAnalyzer.Infeasibility.InfeasibleConstraintRange
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MathOptAnalyzer.Infeasibility.IrreducibleInfeasibleSubset
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These issues are saved in the data structure that is returned from the
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`MathOptAnalyzer.analyze` function:
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```@docs
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ModelAnalyzer.Infeasibility.Data
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MathOptAnalyzer.Infeasibility.Data
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docs/src/numerical.md

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```@docs
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ModelAnalyzer.Numerical.Analyzer
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MathOptAnalyzer.Numerical.Analyzer
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```
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The analysis will return issues of the abstract type:
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```@docs
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ModelAnalyzer.Numerical.AbstractNumericalIssue
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MathOptAnalyzer.Numerical.AbstractNumericalIssue
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Specifically the possible issues are:
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```@docs
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ModelAnalyzer.Numerical.VariableNotInConstraints
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ModelAnalyzer.Numerical.EmptyConstraint
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ModelAnalyzer.Numerical.VariableBoundAsConstraint
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ModelAnalyzer.Numerical.DenseConstraint
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ModelAnalyzer.Numerical.SmallMatrixCoefficient
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ModelAnalyzer.Numerical.LargeMatrixCoefficient
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ModelAnalyzer.Numerical.SmallBoundCoefficient
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ModelAnalyzer.Numerical.LargeBoundCoefficient
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ModelAnalyzer.Numerical.SmallRHSCoefficient
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ModelAnalyzer.Numerical.LargeRHSCoefficient
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ModelAnalyzer.Numerical.SmallObjectiveCoefficient
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ModelAnalyzer.Numerical.LargeObjectiveCoefficient
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ModelAnalyzer.Numerical.SmallObjectiveQuadraticCoefficient
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ModelAnalyzer.Numerical.LargeObjectiveQuadraticCoefficient
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ModelAnalyzer.Numerical.SmallMatrixQuadraticCoefficient
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ModelAnalyzer.Numerical.LargeMatrixQuadraticCoefficient
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ModelAnalyzer.Numerical.NonconvexQuadraticObjective
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ModelAnalyzer.Numerical.NonconvexQuadraticConstraint
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MathOptAnalyzer.Numerical.VariableNotInConstraints
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MathOptAnalyzer.Numerical.EmptyConstraint
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MathOptAnalyzer.Numerical.VariableBoundAsConstraint
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MathOptAnalyzer.Numerical.DenseConstraint
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MathOptAnalyzer.Numerical.SmallMatrixCoefficient
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MathOptAnalyzer.Numerical.LargeMatrixCoefficient
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MathOptAnalyzer.Numerical.SmallBoundCoefficient
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MathOptAnalyzer.Numerical.LargeBoundCoefficient
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MathOptAnalyzer.Numerical.SmallRHSCoefficient
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MathOptAnalyzer.Numerical.LargeRHSCoefficient
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MathOptAnalyzer.Numerical.SmallObjectiveCoefficient
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MathOptAnalyzer.Numerical.LargeObjectiveCoefficient
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MathOptAnalyzer.Numerical.SmallObjectiveQuadraticCoefficient
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MathOptAnalyzer.Numerical.LargeObjectiveQuadraticCoefficient
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MathOptAnalyzer.Numerical.SmallMatrixQuadraticCoefficient
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MathOptAnalyzer.Numerical.LargeMatrixQuadraticCoefficient
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MathOptAnalyzer.Numerical.NonconvexQuadraticObjective
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MathOptAnalyzer.Numerical.NonconvexQuadraticConstraint
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These issues are saved in the data structure that is returned from the `ModelAnalyzer.analyze` function:
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These issues are saved in the data structure that is returned from the `MathOptAnalyzer.analyze` function:
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```@docs
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ModelAnalyzer.Numerical.Data
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MathOptAnalyzer.Numerical.Data
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```

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