User guide

• Make GEMSEO easy to use
  • API: high level functions to use GEMSEO
    • The basics of APIs
    • Logs
    • GEMSEO configuration
    • About discipline
    • About surrogate discipline
    • About design space
    • About MDO formulations
    • About scenario
    • About optimization and DOE algorithms
    • About MDA
    • About post processing
  • Interface a software
    • Excel wrapper
    • Automatic wrapper for executables with Graphical User Interface
    • Interfacing simulation software
  • Define an MDO problem
    • GEMSEO Study Analysis
  • Cheat sheets
  • Extend GEMSEO features
• Main concepts
  • Design space
    • How to deal with design spaces
  • Discipline
    • The discipline, a key concept
    • How to build an analytic discipline?
    • Build a discipline from a simple Python function
    • How to create a discipline from scratch?
    • Automatic wrapper for executables with Graphical User Interface
    • How to manually create a discipline interfacing an external executable?
    • Build discipline from a MATLAB function
    • Coupled derivatives computation
    • Namespaces
  • Scenario
    • How to deal with scenarios
    • Monitoring the execution of a scenario
  • Saving / Storing data
    • Cache
    • Dataset
• Optimization and DOE
  • The GEMSEO concepts
    • Design space
    • Optimization problem
    • Driver
  • Optimization and DOE framework
    • Setting up an OptimizationProblem
    • Solving the problem by optimization
    • Solving the problem by DOE
    • Results analysis
    • DOE algorithms
  • Optimization algorithms
    • DIFFERENTIAL_EVOLUTION
    • DUAL_ANNEALING
    • L-BFGS-B
    • LINEAR_INTERIOR_POINT
    • NLOPT_BFGS
    • NLOPT_BOBYQA
    • NLOPT_COBYLA
    • NLOPT_MMA
    • NLOPT_NEWUOA
    • NLOPT_SLSQP
    • PDFO_BOBYQA
    • PDFO_COBYLA
    • PDFO_NEWUOA
    • PSEVEN
    • PSEVEN_FD
    • PSEVEN_MOM
    • PSEVEN_NCG
    • PSEVEN_NLS
    • PSEVEN_POWELL
    • PSEVEN_QP
    • PSEVEN_SQ2P
    • PSEVEN_SQP
    • PYMOO_GA
    • PYMOO_NSGA2
    • PYMOO_NSGA3
    • PYMOO_RNSGA3
    • PYMOO_UNSGA3
    • REVISED_SIMPLEX
    • SHGO
    • SIMPLEX
    • SLSQP
    • SNOPTB
    • TNC
  • DOE algorithms
    • CustomDOE
    • DiagonalDOE
    • OT_AXIAL
    • OT_COMPOSITE
    • OT_FACTORIAL
    • OT_FAURE
    • OT_FULLFACT
    • OT_HALTON
    • OT_HASELGROVE
    • OT_LHS
    • OT_LHSC
    • OT_MONTE_CARLO
    • OT_OPT_LHS
    • OT_RANDOM
    • OT_REVERSE_HALTON
    • OT_SOBOL
    • OT_SOBOL_INDICES
    • bbdesign
    • ccdesign
    • ff2n
    • fullfact
    • lhs
    • pbdesign
• Design of experiments
  • API
  • Algorithms
  • Advanced use
• Multidisciplinary design optimization
  • Coupling visualization
    • Dependency graph
    • Coupling graph visualization
    • N2 chart visualization
  • MDO formulations
    • Available formulations in GEMSEO
    • MDF
    • IDF
    • Bi level
    • XDSM visualization
  • Multi Disciplinary Analyses
    • Creation of the MDAs
    • Execution and convergence analysis
    • Classes organization
    • MDAChain and the Coupling structure for smart MDAs
  • How to deal with post-processing
    • What data to post-process?
    • Illustration on the Sobieski use case
    • How to apply a post-process feature?
    • What are the post-processing features?
• Machine learning
  • Introduction
    • Introduction
    • Development
  • API
  • Unsupervised learning for unlabeled data
    • Unsupervised learning
    • Clustering
  • Supervised learning for input-output data
    • Supervised learning
    • Classification
    • Regression
  • Measure the quality of a machine learning algorithm
    • Introduction
    • Measures for supervised models
    • Measures for clustering models
    • Examples
  • Calibrate or select a machine learning algorithm
    • Calibration
    • Selection
    • Examples
  • Transform data to improve the ML algorithm quality
    • Introduction
    • Scaling
    • Dimension reduction
    • Examples
• Surrogate models
  • Create a surrogate discipline
    • Import
    • Create the discipline to learn
    • Create the input sampling space
    • Create the learning set
    • Create the surrogate discipline
    • Predict output
• Uncertainty quantification
  • Introduction
    • Operate in an uncertain world
    • The package uncertainty
  • Probability distribution
    • The package distributions
    • The base class Distribution
    • Examples
  • Parameter space
    • The class ParameterSpace
    • Examples
  • Statistics
    • The base class Statistics
    • Examples
  • Sensitivity analysis
    • The package sensitivity
    • The base class SensitivityAnalysis
    • Examples
• Scalable models
  • Scalable models
    • Scalability study - API
    • Scalable MDO problem
    • Scalable discipline
    • Scalable model factory
    • Scalable model
    • Scalable diagonal model
  • The scalable problem
    • Introduction
    • Methodology
    • Properties
• Algorithm options
  • DOE algorithms
    • CustomDOE
    • DiagonalDOE
    • OT_AXIAL
    • OT_COMPOSITE
    • OT_FACTORIAL
    • OT_FAURE
    • OT_FULLFACT
    • OT_HALTON
    • OT_HASELGROVE
    • OT_LHS
    • OT_LHSC
    • OT_MONTE_CARLO
    • OT_OPT_LHS
    • OT_RANDOM
    • OT_REVERSE_HALTON
    • OT_SOBOL
    • OT_SOBOL_INDICES
    • bbdesign
    • ccdesign
    • ff2n
    • fullfact
    • lhs
    • pbdesign
  • MDO Formulation algorithms
    • BiLevel
    • DisciplinaryOpt
    • IDF
    • MDF
  • Linear solver algorithms
    • BICG
    • BICGSTAB
    • DEFAULT
    • GMRES
    • LGMRES
    • PETSC_KSP
    • QMR
  • MDA algorithms
    • GSNewtonMDA
    • MDAChain
    • MDAGaussSeidel
    • MDAJacobi
    • MDANewtonRaphson
    • MDAQuasiNewton
    • MDARoot
    • MDASequential
  • Machine learning models options
    • Classification algorithms
    • Clustering algorithms
    • Regression algorithms
    • Quality measure algorithms
  • Optimization algorithms
    • DIFFERENTIAL_EVOLUTION
    • DUAL_ANNEALING
    • L-BFGS-B
    • LINEAR_INTERIOR_POINT
    • NLOPT_BFGS
    • NLOPT_BOBYQA
    • NLOPT_COBYLA
    • NLOPT_MMA
    • NLOPT_NEWUOA
    • NLOPT_SLSQP
    • PDFO_BOBYQA
    • PDFO_COBYLA
    • PDFO_NEWUOA
    • PSEVEN
    • PSEVEN_FD
    • PSEVEN_MOM
    • PSEVEN_NCG
    • PSEVEN_NLS
    • PSEVEN_POWELL
    • PSEVEN_QP
    • PSEVEN_SQ2P
    • PSEVEN_SQP
    • PYMOO_GA
    • PYMOO_NSGA2
    • PYMOO_NSGA3
    • PYMOO_RNSGA3
    • PYMOO_UNSGA3
    • REVISED_SIMPLEX
    • SHGO
    • SIMPLEX
    • SLSQP
    • SNOPTB
    • TNC
  • Post-processing algorithms
    • BasicHistory
    • Compromise
    • ConstraintsHistory
    • Correlations
    • GradientSensitivity
    • HighTradeOff
    • KMeans
    • MultiObjectiveDiagram
    • ObjConstrHist
    • OptHistoryView
    • ParallelCoordinates
    • ParetoFront
    • Petal
    • QuadApprox
    • Radar
    • RadarChart
    • Robustness
    • SOM
    • ScatterPareto
    • ScatterPlotMatrix
    • VariableInfluence
  • Surrogate disciplines
    • GaussianProcessRegressor
    • LinearRegressor
    • MOERegressor
    • PCERegressor
    • PolynomialRegressor
    • RBFRegressor
    • RandomForestRegressor
  • Uncertainty algorithms
    • Probability distribution algorithms
    • Sensitivity analysis algorithms