surrogate_based_local
- pydantic model dakota.spec.method.surrogate_based_local.SurrogateBasedLocalSelection
Generated model for SurrogateBasedLocalSelection
Show JSON schema
{ "title": "SurrogateBasedLocalSelection", "description": "Generated model for SurrogateBasedLocalSelection", "type": "object", "properties": { "surrogate_based_local": { "$ref": "#/$defs/SurrogateBasedLocalConfig", "x-materialization": [ { "ir_key": "method.algorithm", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SURROGATE_BASED_LOCAL" } ] } }, "$defs": { "AdaptivePenaltyMerit": { "additionalProperties": false, "description": "Use adaptive penalty merit function", "properties": { "adaptive_penalty_merit": { "const": true, "default": true, "description": "Use adaptive penalty merit function", "title": "Adaptive Penalty Merit", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.merit_function", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ADAPTIVE_PENALTY_MERIT" } ] } }, "title": "AdaptivePenaltyMerit", "type": "object" }, "ApproxSubproblem": { "additionalProperties": false, "description": "Identify functions to be included in surrogate merit function", "properties": { "objective_formulation": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/OriginalPrimary" }, { "$ref": "#/$defs/SingleObjective" }, { "$ref": "#/$defs/AugmentedLagrangianObjective" }, { "$ref": "#/$defs/LagrangianObjective" } ], "description": "Objective Formulation", "title": "Objective Formulation", "x-union-pattern": 4 }, "constraint_formulation": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/OriginalConstraints" }, { "$ref": "#/$defs/LinearizedConstraints" }, { "$ref": "#/$defs/NoConstraints" } ], "description": "Constraint Formulation", "title": "Constraint Formulation", "x-union-pattern": 4 } }, "required": [ "objective_formulation", "constraint_formulation" ], "title": "ApproxSubproblem", "type": "object" }, "AugmentedLagrangianMerit": { "additionalProperties": false, "description": "Use combined penalty and zeroth-order Lagrangian merit function", "properties": { "augmented_lagrangian_merit": { "const": true, "default": true, "description": "Use combined penalty and zeroth-order Lagrangian merit function", "title": "Augmented Lagrangian Merit", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.merit_function", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "AUGMENTED_LAGRANGIAN_MERIT" } ] } }, "title": "AugmentedLagrangianMerit", "type": "object" }, "AugmentedLagrangianObjective": { "additionalProperties": false, "description": "Augmented Lagrangian approximate subproblem formulation", "properties": { "augmented_lagrangian_objective": { "const": true, "default": true, "description": "Augmented Lagrangian approximate subproblem formulation", "title": "Augmented Lagrangian Objective", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "AUGMENTED_LAGRANGIAN_OBJECTIVE" } ] } }, "title": "AugmentedLagrangianObjective", "type": "object" }, "ConstraintRelax": { "additionalProperties": false, "description": "Enable constraint relaxation", "properties": { "homotopy": { "const": true, "description": "Surrogate-Based local constraint relaxation method for infeasible iterates", "title": "Homotopy", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.constraint_relax", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "HOMOTOPY" } ] } }, "required": [ "homotopy" ], "title": "ConstraintRelax", "type": "object" }, "Debug": { "additionalProperties": false, "description": "Level 5 of 5 - maximum", "properties": { "debug": { "const": true, "default": true, "description": "Level 5 of 5 - maximum", "title": "Debug", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "DEBUG_OUTPUT" } ] } }, "title": "Debug", "type": "object" }, "DefaultTrustRegionContext1TrustRegion": { "additionalProperties": false, "description": "Specification group for trust region model management", "properties": { "initial_size": { "anyOf": [ { "items": { "type": "number" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Trust region initial size (relative to bounds)", "title": "Initial Size", "x-materialization": [ { "ir_key": "method.trust_region.initial_size", "ir_value_type": "RealVector", "storage_type": "DIRECT_VALUE" } ] }, "minimum_size": { "default": 1e-06, "description": "Trust region minimum size", "title": "Minimum Size", "type": "number", "x-materialization": [ { "ir_key": "method.trust_region.minimum_size", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "contract_threshold": { "default": 0.25, "description": "Shrink trust region if trust region ratio is below this value", "title": "Contract Threshold", "type": "number", "x-materialization": [ { "ir_key": "method.trust_region.contract_threshold", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "expand_threshold": { "default": 0.75, "description": "Expand trust region if trust region ratio is above this value", "title": "Expand Threshold", "type": "number", "x-materialization": [ { "ir_key": "method.trust_region.expand_threshold", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "contraction_factor": { "default": 0.25, "description": "Amount by which step length is rescaled", "title": "Contraction Factor", "type": "number", "x-materialization": [ { "ir_key": "method.trust_region.contraction_factor", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "expansion_factor": { "default": 2.0, "description": "Trust region expansion factor", "title": "Expansion Factor", "type": "number", "x-materialization": [ { "ir_key": "method.trust_region.expansion_factor", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] } }, "title": "DefaultTrustRegionContext1TrustRegion", "type": "object", "x-model-validations": [ { "validationContext": "trust_region", "validationErrorMessage": "For trust_region, trust region parameters are invalid.", "validationFields": [ "initial_size", "minimum_size", "contract_threshold", "expand_threshold", "contraction_factor", "expansion_factor" ], "validationLiterals": [], "validationRuleName": "trust_region_validate" } ] }, "Filter": { "additionalProperties": false, "description": "Surrogate-Based Local iterate acceptance logic", "properties": { "filter": { "const": true, "default": true, "description": "Surrogate-Based Local iterate acceptance logic", "title": "Filter", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.acceptance_logic", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "FILTER" } ] } }, "title": "Filter", "type": "object" }, "LagrangianMerit": { "additionalProperties": false, "description": "Use first-order Lagrangian merit function", "properties": { "lagrangian_merit": { "const": true, "default": true, "description": "Use first-order Lagrangian merit function", "title": "Lagrangian Merit", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.merit_function", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "LAGRANGIAN_MERIT" } ] } }, "title": "LagrangianMerit", "type": "object" }, "LagrangianObjective": { "additionalProperties": false, "description": "Lagrangian approximate subproblem formulation", "properties": { "lagrangian_objective": { "const": true, "default": true, "description": "Lagrangian approximate subproblem formulation", "title": "Lagrangian Objective", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "LAGRANGIAN_OBJECTIVE" } ] } }, "title": "LagrangianObjective", "type": "object" }, "LinearizedConstraints": { "additionalProperties": false, "description": "Use linearized approximations to the constraints", "properties": { "linearized_constraints": { "const": true, "default": true, "description": "Use linearized approximations to the constraints", "title": "Linearized Constraints", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_constraints", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "LINEARIZED_CONSTRAINTS" } ] } }, "title": "LinearizedConstraints", "type": "object" }, "NoConstraints": { "additionalProperties": false, "description": "Don't use constraints", "properties": { "no_constraints": { "const": true, "default": true, "description": "Don't use constraints", "title": "No Constraints", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_constraints", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "NO_CONSTRAINTS" } ] } }, "title": "NoConstraints", "type": "object" }, "Normal": { "additionalProperties": false, "description": "Level 3 of 5 - default", "properties": { "normal": { "const": true, "default": true, "description": "Level 3 of 5 - default", "title": "Normal", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "NORMAL_OUTPUT" } ] } }, "title": "Normal", "type": "object" }, "OriginalConstraints": { "additionalProperties": false, "description": "Use the constraints directly", "properties": { "original_constraints": { "const": true, "default": true, "description": "Use the constraints directly", "title": "Original Constraints", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_constraints", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ORIGINAL_CONSTRAINTS" } ] } }, "title": "OriginalConstraints", "type": "object" }, "OriginalPrimary": { "additionalProperties": false, "description": "Construct approximations of all primary functions", "properties": { "original_primary": { "const": true, "default": true, "description": "Construct approximations of all primary functions", "title": "Original Primary", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ORIGINAL_PRIMARY" } ] } }, "title": "OriginalPrimary", "type": "object" }, "PenaltyMerit": { "additionalProperties": false, "description": "Use penalty merit function", "properties": { "penalty_merit": { "const": true, "default": true, "description": "Use penalty merit function", "title": "Penalty Merit", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.merit_function", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "PENALTY_MERIT" } ] } }, "title": "PenaltyMerit", "type": "object" }, "Quiet": { "additionalProperties": false, "description": "Level 2 of 5 - less than normal", "properties": { "quiet": { "const": true, "default": true, "description": "Level 2 of 5 - less than normal", "title": "Quiet", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "QUIET_OUTPUT" } ] } }, "title": "Quiet", "type": "object" }, "Silent": { "additionalProperties": false, "description": "Level 1 of 5 - minimum", "properties": { "silent": { "const": true, "default": true, "description": "Level 1 of 5 - minimum", "title": "Silent", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SILENT_OUTPUT" } ] } }, "title": "Silent", "type": "object" }, "SingleObjective": { "additionalProperties": false, "description": "Construct approximation a single objective functions only", "properties": { "single_objective": { "const": true, "default": true, "description": "Construct approximation a single objective functions only", "title": "Single Objective", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SINGLE_OBJECTIVE" } ] } }, "title": "SingleObjective", "type": "object" }, "SurrogateBasedLocalConfig": { "additionalProperties": false, "description": "Local Surrogate Based Optimization", "properties": { "constraint_tolerance": { "default": 0.0, "description": "Maximum allowable constraint violation still considered feasible", "title": "Constraint Tolerance", "type": "number", "x-materialization": [ { "ir_key": "method.constraint_tolerance", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "convergence_tolerance": { "default": -1.7976931348623157e+308, "description": "Stopping criterion based on objective function or statistics convergence", "title": "Convergence Tolerance", "type": "number", "x-materialization": [ { "ir_key": "method.convergence_tolerance", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" }, { "ir_key": "method.jega.percent_change", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "max_iterations": { "default": 9223372036854775807, "description": "Number of iterations allowed for optimizers and adaptive UQ methods", "minimum": 0, "title": "Max Iterations", "type": "integer", "x-materialization": [ { "ir_key": "method.max_iterations", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] }, "trust_region": { "anyOf": [ { "$ref": "#/$defs/DefaultTrustRegionContext1TrustRegion" }, { "type": "null" } ], "default": null, "description": "Specification group for trust region model management" }, "id_method": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Name the method block; helpful when there are multiple", "title": "Id Method", "x-materialization": [ { "ir_key": "method.id", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "output": { "anyOf": [ { "$ref": "#/$defs/Debug" }, { "$ref": "#/$defs/Verbose" }, { "$ref": "#/$defs/Normal" }, { "$ref": "#/$defs/Quiet" }, { "$ref": "#/$defs/Silent" } ], "description": "Control how much method information is written to the screen and output file", "title": "Output", "x-model-default": "Normal", "x-union-pattern": 1 }, "final_solutions": { "default": 0, "description": "Number of designs returned as the best solutions", "minimum": 0, "title": "Final Solutions", "type": "integer", "x-materialization": [ { "ir_key": "method.final_solutions", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] }, "sub_method": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/SurrogateBasedLocalMethodPointer" }, { "$ref": "#/$defs/SurrogateBasedLocalMethodName" } ], "description": "Subproblem Optimizer Selection", "title": "Sub Method", "x-union-pattern": 4 }, "model_pointer": { "description": "Identifier for model block to be used by a method", "title": "Model Pointer", "type": "string", "x-aliases": [ "approx_model_pointer" ], "x-block-pointer": "model", "x-materialization": [ { "ir_key": "method.model_pointer", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "soft_convergence_limit": { "default": 0, "description": "Limit number of iterations w/ little improvement", "title": "Soft Convergence Limit", "type": "integer", "x-materialization": [ { "ir_key": "method.soft_convergence_limit", "ir_value_type": "unsigned short", "storage_type": "DIRECT_VALUE" } ] }, "truth_surrogate_bypass": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Bypass lower level surrogates when performing truth verifications on a top level surrogate", "title": "Truth Surrogate Bypass", "x-materialization": [ { "ir_key": "method.sbl.truth_surrogate_bypass", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "approx_subproblem": { "anyOf": [ { "$ref": "#/$defs/ApproxSubproblem" }, { "type": "null" } ], "default": null, "description": "Identify functions to be included in surrogate merit function" }, "merit_function": { "anyOf": [ { "$ref": "#/$defs/PenaltyMerit" }, { "$ref": "#/$defs/AdaptivePenaltyMerit" }, { "$ref": "#/$defs/LagrangianMerit" }, { "$ref": "#/$defs/AugmentedLagrangianMerit" } ], "description": "Select type of penalty or merit function", "title": "Merit Function", "x-model-default": "AugmentedLagrangianMerit", "x-union-pattern": 1 }, "acceptance_logic": { "anyOf": [ { "$ref": "#/$defs/TrRatio" }, { "$ref": "#/$defs/Filter" } ], "description": "Set criteria for trusted surrogate", "title": "Acceptance Logic", "x-model-default": "Filter", "x-union-pattern": 1 }, "constraint_relax": { "anyOf": [ { "$ref": "#/$defs/ConstraintRelax" }, { "type": "null" } ], "default": null, "description": "Enable constraint relaxation" } }, "required": [ "sub_method", "model_pointer" ], "title": "SurrogateBasedLocalConfig", "type": "object" }, "SurrogateBasedLocalMethodName": { "additionalProperties": false, "description": "Specify sub-method by name", "properties": { "method_name": { "description": "Specify sub-method by name", "title": "Method Name", "type": "string", "x-aliases": [ "approx_method_name" ], "x-materialization": [ { "ir_key": "method.sub_method_name", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "method_name" ], "title": "SurrogateBasedLocalMethodName", "type": "object" }, "SurrogateBasedLocalMethodPointer": { "additionalProperties": false, "description": "Pointer to sub-method to apply to a surrogate or branch-and-bound sub-problem", "properties": { "method_pointer": { "description": "Pointer to sub-method to apply to a surrogate or branch-and-bound sub-problem", "title": "Method Pointer", "type": "string", "x-aliases": [ "approx_method_pointer" ], "x-block-pointer": "method", "x-materialization": [ { "ir_key": "method.sub_method_pointer", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "method_pointer" ], "title": "SurrogateBasedLocalMethodPointer", "type": "object" }, "TrRatio": { "additionalProperties": false, "description": "Surrogate-Based Local iterate acceptance logic", "properties": { "tr_ratio": { "const": true, "default": true, "description": "Surrogate-Based Local iterate acceptance logic", "title": "Tr Ratio", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.acceptance_logic", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "TR_RATIO" } ] } }, "title": "TrRatio", "type": "object" }, "Verbose": { "additionalProperties": false, "description": "Level 4 of 5 - more than normal", "properties": { "verbose": { "const": true, "default": true, "description": "Level 4 of 5 - more than normal", "title": "Verbose", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "VERBOSE_OUTPUT" } ] } }, "title": "Verbose", "type": "object" } }, "additionalProperties": false, "required": [ "surrogate_based_local" ] }
- field surrogate_based_local: SurrogateBasedLocalConfig [Required]
- classmethod get_registry() dict[str, type[MethodSelection]]
Get registry, performing deferred registration on first call
- classmethod get_union()
Generate Union from all registered selections
- pydantic model dakota.spec.method.surrogate_based_local.SurrogateBasedLocalConfig
Local Surrogate Based Optimization
Show JSON schema
{ "title": "SurrogateBasedLocalConfig", "description": "Local Surrogate Based Optimization", "type": "object", "properties": { "constraint_tolerance": { "default": 0.0, "description": "Maximum allowable constraint violation still considered feasible", "title": "Constraint Tolerance", "type": "number", "x-materialization": [ { "ir_key": "method.constraint_tolerance", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "convergence_tolerance": { "default": -1.7976931348623157e+308, "description": "Stopping criterion based on objective function or statistics convergence", "title": "Convergence Tolerance", "type": "number", "x-materialization": [ { "ir_key": "method.convergence_tolerance", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" }, { "ir_key": "method.jega.percent_change", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "max_iterations": { "default": 9223372036854775807, "description": "Number of iterations allowed for optimizers and adaptive UQ methods", "minimum": 0, "title": "Max Iterations", "type": "integer", "x-materialization": [ { "ir_key": "method.max_iterations", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] }, "trust_region": { "anyOf": [ { "$ref": "#/$defs/DefaultTrustRegionContext1TrustRegion" }, { "type": "null" } ], "default": null, "description": "Specification group for trust region model management" }, "id_method": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Name the method block; helpful when there are multiple", "title": "Id Method", "x-materialization": [ { "ir_key": "method.id", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "output": { "anyOf": [ { "$ref": "#/$defs/Debug" }, { "$ref": "#/$defs/Verbose" }, { "$ref": "#/$defs/Normal" }, { "$ref": "#/$defs/Quiet" }, { "$ref": "#/$defs/Silent" } ], "description": "Control how much method information is written to the screen and output file", "title": "Output", "x-model-default": "Normal", "x-union-pattern": 1 }, "final_solutions": { "default": 0, "description": "Number of designs returned as the best solutions", "minimum": 0, "title": "Final Solutions", "type": "integer", "x-materialization": [ { "ir_key": "method.final_solutions", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] }, "sub_method": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/SurrogateBasedLocalMethodPointer" }, { "$ref": "#/$defs/SurrogateBasedLocalMethodName" } ], "description": "Subproblem Optimizer Selection", "title": "Sub Method", "x-union-pattern": 4 }, "model_pointer": { "description": "Identifier for model block to be used by a method", "title": "Model Pointer", "type": "string", "x-aliases": [ "approx_model_pointer" ], "x-block-pointer": "model", "x-materialization": [ { "ir_key": "method.model_pointer", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "soft_convergence_limit": { "default": 0, "description": "Limit number of iterations w/ little improvement", "title": "Soft Convergence Limit", "type": "integer", "x-materialization": [ { "ir_key": "method.soft_convergence_limit", "ir_value_type": "unsigned short", "storage_type": "DIRECT_VALUE" } ] }, "truth_surrogate_bypass": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Bypass lower level surrogates when performing truth verifications on a top level surrogate", "title": "Truth Surrogate Bypass", "x-materialization": [ { "ir_key": "method.sbl.truth_surrogate_bypass", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "approx_subproblem": { "anyOf": [ { "$ref": "#/$defs/ApproxSubproblem" }, { "type": "null" } ], "default": null, "description": "Identify functions to be included in surrogate merit function" }, "merit_function": { "anyOf": [ { "$ref": "#/$defs/PenaltyMerit" }, { "$ref": "#/$defs/AdaptivePenaltyMerit" }, { "$ref": "#/$defs/LagrangianMerit" }, { "$ref": "#/$defs/AugmentedLagrangianMerit" } ], "description": "Select type of penalty or merit function", "title": "Merit Function", "x-model-default": "AugmentedLagrangianMerit", "x-union-pattern": 1 }, "acceptance_logic": { "anyOf": [ { "$ref": "#/$defs/TrRatio" }, { "$ref": "#/$defs/Filter" } ], "description": "Set criteria for trusted surrogate", "title": "Acceptance Logic", "x-model-default": "Filter", "x-union-pattern": 1 }, "constraint_relax": { "anyOf": [ { "$ref": "#/$defs/ConstraintRelax" }, { "type": "null" } ], "default": null, "description": "Enable constraint relaxation" } }, "$defs": { "AdaptivePenaltyMerit": { "additionalProperties": false, "description": "Use adaptive penalty merit function", "properties": { "adaptive_penalty_merit": { "const": true, "default": true, "description": "Use adaptive penalty merit function", "title": "Adaptive Penalty Merit", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.merit_function", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ADAPTIVE_PENALTY_MERIT" } ] } }, "title": "AdaptivePenaltyMerit", "type": "object" }, "ApproxSubproblem": { "additionalProperties": false, "description": "Identify functions to be included in surrogate merit function", "properties": { "objective_formulation": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/OriginalPrimary" }, { "$ref": "#/$defs/SingleObjective" }, { "$ref": "#/$defs/AugmentedLagrangianObjective" }, { "$ref": "#/$defs/LagrangianObjective" } ], "description": "Objective Formulation", "title": "Objective Formulation", "x-union-pattern": 4 }, "constraint_formulation": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/OriginalConstraints" }, { "$ref": "#/$defs/LinearizedConstraints" }, { "$ref": "#/$defs/NoConstraints" } ], "description": "Constraint Formulation", "title": "Constraint Formulation", "x-union-pattern": 4 } }, "required": [ "objective_formulation", "constraint_formulation" ], "title": "ApproxSubproblem", "type": "object" }, "AugmentedLagrangianMerit": { "additionalProperties": false, "description": "Use combined penalty and zeroth-order Lagrangian merit function", "properties": { "augmented_lagrangian_merit": { "const": true, "default": true, "description": "Use combined penalty and zeroth-order Lagrangian merit function", "title": "Augmented Lagrangian Merit", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.merit_function", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "AUGMENTED_LAGRANGIAN_MERIT" } ] } }, "title": "AugmentedLagrangianMerit", "type": "object" }, "AugmentedLagrangianObjective": { "additionalProperties": false, "description": "Augmented Lagrangian approximate subproblem formulation", "properties": { "augmented_lagrangian_objective": { "const": true, "default": true, "description": "Augmented Lagrangian approximate subproblem formulation", "title": "Augmented Lagrangian Objective", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "AUGMENTED_LAGRANGIAN_OBJECTIVE" } ] } }, "title": "AugmentedLagrangianObjective", "type": "object" }, "ConstraintRelax": { "additionalProperties": false, "description": "Enable constraint relaxation", "properties": { "homotopy": { "const": true, "description": "Surrogate-Based local constraint relaxation method for infeasible iterates", "title": "Homotopy", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.constraint_relax", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "HOMOTOPY" } ] } }, "required": [ "homotopy" ], "title": "ConstraintRelax", "type": "object" }, "Debug": { "additionalProperties": false, "description": "Level 5 of 5 - maximum", "properties": { "debug": { "const": true, "default": true, "description": "Level 5 of 5 - maximum", "title": "Debug", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "DEBUG_OUTPUT" } ] } }, "title": "Debug", "type": "object" }, "DefaultTrustRegionContext1TrustRegion": { "additionalProperties": false, "description": "Specification group for trust region model management", "properties": { "initial_size": { "anyOf": [ { "items": { "type": "number" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Trust region initial size (relative to bounds)", "title": "Initial Size", "x-materialization": [ { "ir_key": "method.trust_region.initial_size", "ir_value_type": "RealVector", "storage_type": "DIRECT_VALUE" } ] }, "minimum_size": { "default": 1e-06, "description": "Trust region minimum size", "title": "Minimum Size", "type": "number", "x-materialization": [ { "ir_key": "method.trust_region.minimum_size", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "contract_threshold": { "default": 0.25, "description": "Shrink trust region if trust region ratio is below this value", "title": "Contract Threshold", "type": "number", "x-materialization": [ { "ir_key": "method.trust_region.contract_threshold", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "expand_threshold": { "default": 0.75, "description": "Expand trust region if trust region ratio is above this value", "title": "Expand Threshold", "type": "number", "x-materialization": [ { "ir_key": "method.trust_region.expand_threshold", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "contraction_factor": { "default": 0.25, "description": "Amount by which step length is rescaled", "title": "Contraction Factor", "type": "number", "x-materialization": [ { "ir_key": "method.trust_region.contraction_factor", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "expansion_factor": { "default": 2.0, "description": "Trust region expansion factor", "title": "Expansion Factor", "type": "number", "x-materialization": [ { "ir_key": "method.trust_region.expansion_factor", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] } }, "title": "DefaultTrustRegionContext1TrustRegion", "type": "object", "x-model-validations": [ { "validationContext": "trust_region", "validationErrorMessage": "For trust_region, trust region parameters are invalid.", "validationFields": [ "initial_size", "minimum_size", "contract_threshold", "expand_threshold", "contraction_factor", "expansion_factor" ], "validationLiterals": [], "validationRuleName": "trust_region_validate" } ] }, "Filter": { "additionalProperties": false, "description": "Surrogate-Based Local iterate acceptance logic", "properties": { "filter": { "const": true, "default": true, "description": "Surrogate-Based Local iterate acceptance logic", "title": "Filter", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.acceptance_logic", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "FILTER" } ] } }, "title": "Filter", "type": "object" }, "LagrangianMerit": { "additionalProperties": false, "description": "Use first-order Lagrangian merit function", "properties": { "lagrangian_merit": { "const": true, "default": true, "description": "Use first-order Lagrangian merit function", "title": "Lagrangian Merit", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.merit_function", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "LAGRANGIAN_MERIT" } ] } }, "title": "LagrangianMerit", "type": "object" }, "LagrangianObjective": { "additionalProperties": false, "description": "Lagrangian approximate subproblem formulation", "properties": { "lagrangian_objective": { "const": true, "default": true, "description": "Lagrangian approximate subproblem formulation", "title": "Lagrangian Objective", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "LAGRANGIAN_OBJECTIVE" } ] } }, "title": "LagrangianObjective", "type": "object" }, "LinearizedConstraints": { "additionalProperties": false, "description": "Use linearized approximations to the constraints", "properties": { "linearized_constraints": { "const": true, "default": true, "description": "Use linearized approximations to the constraints", "title": "Linearized Constraints", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_constraints", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "LINEARIZED_CONSTRAINTS" } ] } }, "title": "LinearizedConstraints", "type": "object" }, "NoConstraints": { "additionalProperties": false, "description": "Don't use constraints", "properties": { "no_constraints": { "const": true, "default": true, "description": "Don't use constraints", "title": "No Constraints", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_constraints", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "NO_CONSTRAINTS" } ] } }, "title": "NoConstraints", "type": "object" }, "Normal": { "additionalProperties": false, "description": "Level 3 of 5 - default", "properties": { "normal": { "const": true, "default": true, "description": "Level 3 of 5 - default", "title": "Normal", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "NORMAL_OUTPUT" } ] } }, "title": "Normal", "type": "object" }, "OriginalConstraints": { "additionalProperties": false, "description": "Use the constraints directly", "properties": { "original_constraints": { "const": true, "default": true, "description": "Use the constraints directly", "title": "Original Constraints", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_constraints", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ORIGINAL_CONSTRAINTS" } ] } }, "title": "OriginalConstraints", "type": "object" }, "OriginalPrimary": { "additionalProperties": false, "description": "Construct approximations of all primary functions", "properties": { "original_primary": { "const": true, "default": true, "description": "Construct approximations of all primary functions", "title": "Original Primary", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ORIGINAL_PRIMARY" } ] } }, "title": "OriginalPrimary", "type": "object" }, "PenaltyMerit": { "additionalProperties": false, "description": "Use penalty merit function", "properties": { "penalty_merit": { "const": true, "default": true, "description": "Use penalty merit function", "title": "Penalty Merit", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.merit_function", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "PENALTY_MERIT" } ] } }, "title": "PenaltyMerit", "type": "object" }, "Quiet": { "additionalProperties": false, "description": "Level 2 of 5 - less than normal", "properties": { "quiet": { "const": true, "default": true, "description": "Level 2 of 5 - less than normal", "title": "Quiet", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "QUIET_OUTPUT" } ] } }, "title": "Quiet", "type": "object" }, "Silent": { "additionalProperties": false, "description": "Level 1 of 5 - minimum", "properties": { "silent": { "const": true, "default": true, "description": "Level 1 of 5 - minimum", "title": "Silent", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SILENT_OUTPUT" } ] } }, "title": "Silent", "type": "object" }, "SingleObjective": { "additionalProperties": false, "description": "Construct approximation a single objective functions only", "properties": { "single_objective": { "const": true, "default": true, "description": "Construct approximation a single objective functions only", "title": "Single Objective", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SINGLE_OBJECTIVE" } ] } }, "title": "SingleObjective", "type": "object" }, "SurrogateBasedLocalMethodName": { "additionalProperties": false, "description": "Specify sub-method by name", "properties": { "method_name": { "description": "Specify sub-method by name", "title": "Method Name", "type": "string", "x-aliases": [ "approx_method_name" ], "x-materialization": [ { "ir_key": "method.sub_method_name", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "method_name" ], "title": "SurrogateBasedLocalMethodName", "type": "object" }, "SurrogateBasedLocalMethodPointer": { "additionalProperties": false, "description": "Pointer to sub-method to apply to a surrogate or branch-and-bound sub-problem", "properties": { "method_pointer": { "description": "Pointer to sub-method to apply to a surrogate or branch-and-bound sub-problem", "title": "Method Pointer", "type": "string", "x-aliases": [ "approx_method_pointer" ], "x-block-pointer": "method", "x-materialization": [ { "ir_key": "method.sub_method_pointer", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "method_pointer" ], "title": "SurrogateBasedLocalMethodPointer", "type": "object" }, "TrRatio": { "additionalProperties": false, "description": "Surrogate-Based Local iterate acceptance logic", "properties": { "tr_ratio": { "const": true, "default": true, "description": "Surrogate-Based Local iterate acceptance logic", "title": "Tr Ratio", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.acceptance_logic", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "TR_RATIO" } ] } }, "title": "TrRatio", "type": "object" }, "Verbose": { "additionalProperties": false, "description": "Level 4 of 5 - more than normal", "properties": { "verbose": { "const": true, "default": true, "description": "Level 4 of 5 - more than normal", "title": "Verbose", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "VERBOSE_OUTPUT" } ] } }, "title": "Verbose", "type": "object" } }, "additionalProperties": false, "required": [ "sub_method", "model_pointer" ] }
- Fields:
- field approx_subproblem: ApproxSubproblem | None = None
Identify functions to be included in surrogate merit function
- field constraint_relax: ConstraintRelax | None = None
Enable constraint relaxation
- field constraint_tolerance: DakotaFloat = 0.0
Maximum allowable constraint violation still considered feasible
- Constraints:
func = <function _serialize_dakota_float at 0x7f2a3de76700>
return_type = float | str
when_used = json
- field convergence_tolerance: DakotaFloat = -1.7976931348623157e+308
Stopping criterion based on objective function or statistics convergence
- Constraints:
func = <function _serialize_dakota_float at 0x7f2a3de76700>
return_type = float | str
when_used = json
- field final_solutions: int = 0
Number of designs returned as the best solutions
- Constraints:
ge = 0
- field id_method: str | None = None
Name the method block; helpful when there are multiple
- field max_iterations: int = 9223372036854775807
Number of iterations allowed for optimizers and adaptive UQ methods
- Constraints:
ge = 0
- field merit_function: PenaltyMerit | AdaptivePenaltyMerit | LagrangianMerit | AugmentedLagrangianMerit [Optional]
Select type of penalty or merit function
- field model_pointer: str [Required]
Identifier for model block to be used by a method
- field output: Debug | Verbose | Normal | Quiet | Silent [Optional]
Control how much method information is written to the screen and output file
- field soft_convergence_limit: int = 0
Limit number of iterations w/ little improvement
- field sub_method: SurrogateBasedLocalMethodPointer | SurrogateBasedLocalMethodName [Required]
Subproblem Optimizer Selection
- field trust_region: DefaultTrustRegionContext1TrustRegion | None = None
Specification group for trust region model management
- field truth_surrogate_bypass: Literal[True] | None = None
Bypass lower level surrogates when performing truth verifications on a top level surrogate
Generated Pydantic models for method.surrogate_based_local
- pydantic model dakota.spec.method.surrogate_based_local.AdaptivePenaltyMerit
Use adaptive penalty merit function
Show JSON schema
{ "title": "AdaptivePenaltyMerit", "description": "Use adaptive penalty merit function", "type": "object", "properties": { "adaptive_penalty_merit": { "const": true, "default": true, "description": "Use adaptive penalty merit function", "title": "Adaptive Penalty Merit", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.merit_function", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ADAPTIVE_PENALTY_MERIT" } ] } }, "additionalProperties": false }
- field adaptive_penalty_merit: Literal[True] = True
Use adaptive penalty merit function
- pydantic model dakota.spec.method.surrogate_based_local.ApproxSubproblem
Identify functions to be included in surrogate merit function
Show JSON schema
{ "title": "ApproxSubproblem", "description": "Identify functions to be included in surrogate merit function", "type": "object", "properties": { "objective_formulation": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/OriginalPrimary" }, { "$ref": "#/$defs/SingleObjective" }, { "$ref": "#/$defs/AugmentedLagrangianObjective" }, { "$ref": "#/$defs/LagrangianObjective" } ], "description": "Objective Formulation", "title": "Objective Formulation", "x-union-pattern": 4 }, "constraint_formulation": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/OriginalConstraints" }, { "$ref": "#/$defs/LinearizedConstraints" }, { "$ref": "#/$defs/NoConstraints" } ], "description": "Constraint Formulation", "title": "Constraint Formulation", "x-union-pattern": 4 } }, "$defs": { "AugmentedLagrangianObjective": { "additionalProperties": false, "description": "Augmented Lagrangian approximate subproblem formulation", "properties": { "augmented_lagrangian_objective": { "const": true, "default": true, "description": "Augmented Lagrangian approximate subproblem formulation", "title": "Augmented Lagrangian Objective", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "AUGMENTED_LAGRANGIAN_OBJECTIVE" } ] } }, "title": "AugmentedLagrangianObjective", "type": "object" }, "LagrangianObjective": { "additionalProperties": false, "description": "Lagrangian approximate subproblem formulation", "properties": { "lagrangian_objective": { "const": true, "default": true, "description": "Lagrangian approximate subproblem formulation", "title": "Lagrangian Objective", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "LAGRANGIAN_OBJECTIVE" } ] } }, "title": "LagrangianObjective", "type": "object" }, "LinearizedConstraints": { "additionalProperties": false, "description": "Use linearized approximations to the constraints", "properties": { "linearized_constraints": { "const": true, "default": true, "description": "Use linearized approximations to the constraints", "title": "Linearized Constraints", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_constraints", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "LINEARIZED_CONSTRAINTS" } ] } }, "title": "LinearizedConstraints", "type": "object" }, "NoConstraints": { "additionalProperties": false, "description": "Don't use constraints", "properties": { "no_constraints": { "const": true, "default": true, "description": "Don't use constraints", "title": "No Constraints", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_constraints", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "NO_CONSTRAINTS" } ] } }, "title": "NoConstraints", "type": "object" }, "OriginalConstraints": { "additionalProperties": false, "description": "Use the constraints directly", "properties": { "original_constraints": { "const": true, "default": true, "description": "Use the constraints directly", "title": "Original Constraints", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_constraints", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ORIGINAL_CONSTRAINTS" } ] } }, "title": "OriginalConstraints", "type": "object" }, "OriginalPrimary": { "additionalProperties": false, "description": "Construct approximations of all primary functions", "properties": { "original_primary": { "const": true, "default": true, "description": "Construct approximations of all primary functions", "title": "Original Primary", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ORIGINAL_PRIMARY" } ] } }, "title": "OriginalPrimary", "type": "object" }, "SingleObjective": { "additionalProperties": false, "description": "Construct approximation a single objective functions only", "properties": { "single_objective": { "const": true, "default": true, "description": "Construct approximation a single objective functions only", "title": "Single Objective", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SINGLE_OBJECTIVE" } ] } }, "title": "SingleObjective", "type": "object" } }, "additionalProperties": false, "required": [ "objective_formulation", "constraint_formulation" ] }
- Fields:
- field constraint_formulation: OriginalConstraints | LinearizedConstraints | NoConstraints [Required]
Constraint Formulation
- field objective_formulation: OriginalPrimary | SingleObjective | AugmentedLagrangianObjective | LagrangianObjective [Required]
Objective Formulation
- pydantic model dakota.spec.method.surrogate_based_local.AugmentedLagrangianMerit
Use combined penalty and zeroth-order Lagrangian merit function
Show JSON schema
{ "title": "AugmentedLagrangianMerit", "description": "Use combined penalty and zeroth-order Lagrangian merit function", "type": "object", "properties": { "augmented_lagrangian_merit": { "const": true, "default": true, "description": "Use combined penalty and zeroth-order Lagrangian merit function", "title": "Augmented Lagrangian Merit", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.merit_function", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "AUGMENTED_LAGRANGIAN_MERIT" } ] } }, "additionalProperties": false }
- field augmented_lagrangian_merit: Literal[True] = True
Use combined penalty and zeroth-order Lagrangian merit function
- pydantic model dakota.spec.method.surrogate_based_local.AugmentedLagrangianObjective
Augmented Lagrangian approximate subproblem formulation
Show JSON schema
{ "title": "AugmentedLagrangianObjective", "description": "Augmented Lagrangian approximate subproblem formulation", "type": "object", "properties": { "augmented_lagrangian_objective": { "const": true, "default": true, "description": "Augmented Lagrangian approximate subproblem formulation", "title": "Augmented Lagrangian Objective", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "AUGMENTED_LAGRANGIAN_OBJECTIVE" } ] } }, "additionalProperties": false }
- field augmented_lagrangian_objective: Literal[True] = True
Augmented Lagrangian approximate subproblem formulation
- pydantic model dakota.spec.method.surrogate_based_local.ConstraintRelax
Enable constraint relaxation
Show JSON schema
{ "title": "ConstraintRelax", "description": "Enable constraint relaxation", "type": "object", "properties": { "homotopy": { "const": true, "description": "Surrogate-Based local constraint relaxation method for infeasible iterates", "title": "Homotopy", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.constraint_relax", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "HOMOTOPY" } ] } }, "additionalProperties": false, "required": [ "homotopy" ] }
- Fields:
- field homotopy: Literal[True] [Required]
Surrogate-Based local constraint relaxation method for infeasible iterates
- pydantic model dakota.spec.method.surrogate_based_local.Filter
Surrogate-Based Local iterate acceptance logic
Show JSON schema
{ "title": "Filter", "description": "Surrogate-Based Local iterate acceptance logic", "type": "object", "properties": { "filter": { "const": true, "default": true, "description": "Surrogate-Based Local iterate acceptance logic", "title": "Filter", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.acceptance_logic", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "FILTER" } ] } }, "additionalProperties": false }
- Fields:
- field filter: Literal[True] = True
Surrogate-Based Local iterate acceptance logic
- pydantic model dakota.spec.method.surrogate_based_local.LagrangianMerit
Use first-order Lagrangian merit function
Show JSON schema
{ "title": "LagrangianMerit", "description": "Use first-order Lagrangian merit function", "type": "object", "properties": { "lagrangian_merit": { "const": true, "default": true, "description": "Use first-order Lagrangian merit function", "title": "Lagrangian Merit", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.merit_function", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "LAGRANGIAN_MERIT" } ] } }, "additionalProperties": false }
- Fields:
- field lagrangian_merit: Literal[True] = True
Use first-order Lagrangian merit function
- pydantic model dakota.spec.method.surrogate_based_local.LagrangianObjective
Lagrangian approximate subproblem formulation
Show JSON schema
{ "title": "LagrangianObjective", "description": "Lagrangian approximate subproblem formulation", "type": "object", "properties": { "lagrangian_objective": { "const": true, "default": true, "description": "Lagrangian approximate subproblem formulation", "title": "Lagrangian Objective", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "LAGRANGIAN_OBJECTIVE" } ] } }, "additionalProperties": false }
- field lagrangian_objective: Literal[True] = True
Lagrangian approximate subproblem formulation
- pydantic model dakota.spec.method.surrogate_based_local.LinearizedConstraints
Use linearized approximations to the constraints
Show JSON schema
{ "title": "LinearizedConstraints", "description": "Use linearized approximations to the constraints", "type": "object", "properties": { "linearized_constraints": { "const": true, "default": true, "description": "Use linearized approximations to the constraints", "title": "Linearized Constraints", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_constraints", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "LINEARIZED_CONSTRAINTS" } ] } }, "additionalProperties": false }
- field linearized_constraints: Literal[True] = True
Use linearized approximations to the constraints
- pydantic model dakota.spec.method.surrogate_based_local.NoConstraints
Don’t use constraints
Show JSON schema
{ "title": "NoConstraints", "description": "Don't use constraints", "type": "object", "properties": { "no_constraints": { "const": true, "default": true, "description": "Don't use constraints", "title": "No Constraints", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_constraints", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "NO_CONSTRAINTS" } ] } }, "additionalProperties": false }
- Fields:
- field no_constraints: Literal[True] = True
Don’t use constraints
- pydantic model dakota.spec.method.surrogate_based_local.OriginalConstraints
Use the constraints directly
Show JSON schema
{ "title": "OriginalConstraints", "description": "Use the constraints directly", "type": "object", "properties": { "original_constraints": { "const": true, "default": true, "description": "Use the constraints directly", "title": "Original Constraints", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_constraints", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ORIGINAL_CONSTRAINTS" } ] } }, "additionalProperties": false }
- field original_constraints: Literal[True] = True
Use the constraints directly
- pydantic model dakota.spec.method.surrogate_based_local.OriginalPrimary
Construct approximations of all primary functions
Show JSON schema
{ "title": "OriginalPrimary", "description": "Construct approximations of all primary functions", "type": "object", "properties": { "original_primary": { "const": true, "default": true, "description": "Construct approximations of all primary functions", "title": "Original Primary", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ORIGINAL_PRIMARY" } ] } }, "additionalProperties": false }
- Fields:
- field original_primary: Literal[True] = True
Construct approximations of all primary functions
- pydantic model dakota.spec.method.surrogate_based_local.PenaltyMerit
Use penalty merit function
Show JSON schema
{ "title": "PenaltyMerit", "description": "Use penalty merit function", "type": "object", "properties": { "penalty_merit": { "const": true, "default": true, "description": "Use penalty merit function", "title": "Penalty Merit", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.merit_function", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "PENALTY_MERIT" } ] } }, "additionalProperties": false }
- Fields:
- field penalty_merit: Literal[True] = True
Use penalty merit function
- pydantic model dakota.spec.method.surrogate_based_local.SingleObjective
Construct approximation a single objective functions only
Show JSON schema
{ "title": "SingleObjective", "description": "Construct approximation a single objective functions only", "type": "object", "properties": { "single_objective": { "const": true, "default": true, "description": "Construct approximation a single objective functions only", "title": "Single Objective", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.subproblem_objective", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SINGLE_OBJECTIVE" } ] } }, "additionalProperties": false }
- Fields:
- field single_objective: Literal[True] = True
Construct approximation a single objective functions only
- pydantic model dakota.spec.method.surrogate_based_local.SurrogateBasedLocalMethodName
Specify sub-method by name
Show JSON schema
{ "title": "SurrogateBasedLocalMethodName", "description": "Specify sub-method by name", "type": "object", "properties": { "method_name": { "description": "Specify sub-method by name", "title": "Method Name", "type": "string", "x-aliases": [ "approx_method_name" ], "x-materialization": [ { "ir_key": "method.sub_method_name", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "additionalProperties": false, "required": [ "method_name" ] }
- Fields:
- field method_name: str [Required]
Specify sub-method by name
- pydantic model dakota.spec.method.surrogate_based_local.SurrogateBasedLocalMethodPointer
Pointer to sub-method to apply to a surrogate or branch-and-bound sub-problem
Show JSON schema
{ "title": "SurrogateBasedLocalMethodPointer", "description": "Pointer to sub-method to apply to a surrogate or branch-and-bound sub-problem", "type": "object", "properties": { "method_pointer": { "description": "Pointer to sub-method to apply to a surrogate or branch-and-bound sub-problem", "title": "Method Pointer", "type": "string", "x-aliases": [ "approx_method_pointer" ], "x-block-pointer": "method", "x-materialization": [ { "ir_key": "method.sub_method_pointer", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "additionalProperties": false, "required": [ "method_pointer" ] }
- Fields:
- field method_pointer: str [Required]
Pointer to sub-method to apply to a surrogate or branch-and-bound sub-problem
- pydantic model dakota.spec.method.surrogate_based_local.TrRatio
Surrogate-Based Local iterate acceptance logic
Show JSON schema
{ "title": "TrRatio", "description": "Surrogate-Based Local iterate acceptance logic", "type": "object", "properties": { "tr_ratio": { "const": true, "default": true, "description": "Surrogate-Based Local iterate acceptance logic", "title": "Tr Ratio", "type": "boolean", "x-materialization": [ { "ir_key": "method.sbl.acceptance_logic", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "TR_RATIO" } ] } }, "additionalProperties": false }
- Fields:
- field tr_ratio: Literal[True] = True
Surrogate-Based Local iterate acceptance logic
