Contents

• 1. Welcome to pymetamodels documentation!
  • 1.1. Intro
  • 1.2. Installing pymetamodels
  • 1.3. Installing pre-requisite software
• 2. The pymetamodels description
  • 2.1. Metamodel configuration (spreadsheet)
  • 2.2. Available DOEX sampling generators and sensitivity analysis
  • 2.3. Optimal forecasting metamodels construction
  • 2.4. Optimization problem resolution
• 3. API pymetamodels (main class object)
  • 3.1. Class -> pymetamodels (functions)
    • load()
    • newconf()
  • 3.2. Class -> pymetamodels
    • metamodel
      • metamodel.logging_start()
      • metamodel.keys()
      • metamodel.objconf()
      • metamodel.obj_samplig_sensi()
      • metamodel.sensitivity_type()
      • metamodel.run_sampling_routine()
      • metamodel.run_sensitivity_analisis()
      • metamodel.run_sensitivity_normalization()
      • metamodel.run_metamodel_construction()
      • metamodel.obj_metamodel()
      • metamodel.save_metamodel()
      • metamodel.load_metamodel()
      • metamodel.obj_optimization()
      • metamodel.save_optimization()
      • metamodel.load_optimization()
      • metamodel.run_optimization_problem()
      • metamodel.print_structure()
      • metamodel.vars_parameter_matrix()
      • metamodel.vars_out_parameter_matrix()
      • metamodel.doeX()
      • metamodel.doeY()
      • metamodel.SiY()
      • metamodel.read_xls_case()
      • metamodel.output_xls()
      • metamodel.save_tofile_DOEX()
      • metamodel.read_fromfile_DOEX()
      • metamodel.save_tofile_DOEY()
      • metamodel.read_fromfile_DOEY()
      • metamodel.output_plts_sensitivity()
      • metamodel.output_plts_models_XY()
      • metamodel.output_plts_models_XYZ()
      • metamodel.output_plts_models_residuals_plot()
      • metamodel.print_dict()
  • 3.3. Class -> objconf
    • objconf
      • objconf.start()
      • objconf.add_case()
      • objconf.add_vars_sheet_variable()
      • objconf.add_output_sheet()
      • objconf.check_consistency()
      • objconf.save_conf()
      • objconf.read_xls_sheet_to_dict()
      • objconf.save_dict_to_xls_sheet()
  • 3.4. Class -> objsamplingsensitivity
    • objsamplingsensitivity
  • 3.5. Class -> objmetamodel
    • objmetamodel
      • objmetamodel.save_to_file()
      • objmetamodel.load_file()
      • objmetamodel.fit_model()
      • objmetamodel.predict()
      • objmetamodel.predict_1D()
      • objmetamodel.score_doeY_target()
      • objmetamodel.doeX_np_shape
      • objmetamodel.doeY_np_shape
      • objmetamodel.doeX_varX
      • objmetamodel.doeY_varY
      • objmetamodel.metamodel_score
  • 3.6. Class -> objoptimization
    • objoptimization
      • objoptimization.min_fun
      • objoptimization.DOEX_min_func
      • objoptimization.min_func_model
      • objoptimization.DOEY_min_func
      • objoptimization.doeX_varX
      • objoptimization.doeY_varY
      • objoptimization.save_to_file()
      • objoptimization.load_file()
      • objoptimization.run_optimization()
• 4. First steps and pymetamodels tutorials
  • 4.1. Tutorial case A01: “Sensitivity analysis of a coupled function”
  • 4.2. Tutorial case A02: “Sensitivity analysis of a coupled function, structure of data objects”
  • 4.3. Tutorial case A03: “Models and metamodels construction of a coupled function”
  • 4.4. Tutorial case A04: “Sensitivity analysis and metamodeling of Kursawe Functions”
  • 4.5. Tutorial case A05: “Sensitivity analysis and metamodeling of a damped oscillator”
  • 4.6. Tutorial case A06: “Minimization of the Kursawe Functions”
  • 4.7. Tutorial case A07: “Calibration of a damped oscillator”
  • 4.8. Tutorial case A08: “Building the configuration spreadsheet programatically”
  • 4.9. Tutorial case A09: “Loading DOEs from file, couple function case”

• Glossary
• Bibliography
• Changelog
• Authors
• License