local_interval_est
- pydantic model dakota.spec.method.local_interval_est.LocalIntervalEstSelection
Generated model for LocalIntervalEstSelection
Show JSON schema
{ "title": "LocalIntervalEstSelection", "description": "Generated model for LocalIntervalEstSelection", "type": "object", "properties": { "local_interval_est": { "$ref": "#/$defs/LocalIntervalEstConfig", "x-aliases": [ "nond_local_interval_est" ], "x-materialization": [ { "ir_key": "method.algorithm", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "LOCAL_INTERVAL_EST" } ] } }, "$defs": { "Debug": { "additionalProperties": false, "description": "Level 5 of 5 - maximum", "properties": { "debug": { "const": true, "default": true, "description": "Level 5 of 5 - maximum", "title": "Debug", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "DEBUG_OUTPUT" } ] } }, "title": "Debug", "type": "object" }, "LocalIntervalEstConfig": { "additionalProperties": false, "description": "Interval analysis using local optimization", "properties": { "model_pointer": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Identifier for model block to be used by a method", "title": "Model Pointer", "x-block-pointer": "model", "x-materialization": [ { "ir_key": "method.model_pointer", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "convergence_tolerance": { "default": -1.7976931348623157e+308, "description": "Stopping criterion based on objective function or statistics convergence", "title": "Convergence Tolerance", "type": "number", "x-materialization": [ { "ir_key": "method.convergence_tolerance", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" }, { "ir_key": "method.jega.percent_change", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "optimization_solver": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/MethodGradientSubProblemSolverSqp" }, { "$ref": "#/$defs/MethodGradientSubProblemSolverNip" }, { "type": "null" } ], "default": null, "description": "Optimization Solver", "title": "Optimization Solver", "x-union-pattern": 2 }, "id_method": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Name the method block; helpful when there are multiple", "title": "Id Method", "x-materialization": [ { "ir_key": "method.id", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "output": { "anyOf": [ { "$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" } ] } }, "title": "LocalIntervalEstConfig", "type": "object" }, "MethodGradientSubProblemSolverNip": { "additionalProperties": false, "description": "Use a nonlinear interior point method for solving an optimization sub-problem", "properties": { "nip": { "const": true, "default": true, "description": "Use a nonlinear interior point method for solving an optimization sub-problem", "title": "Nip", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.opt_subproblem_solver", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_OPTPP" } ] } }, "title": "MethodGradientSubProblemSolverNip", "type": "object" }, "MethodGradientSubProblemSolverSqp": { "additionalProperties": false, "description": "Use a sequential quadratic programming method for solving an optimization sub-problem", "properties": { "sqp": { "const": true, "default": true, "description": "Use a sequential quadratic programming method for solving an optimization sub-problem", "title": "Sqp", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.opt_subproblem_solver", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_NPSOL" } ] } }, "title": "MethodGradientSubProblemSolverSqp", "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" }, "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" }, "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": [ "local_interval_est" ] }
- field local_interval_est: LocalIntervalEstConfig [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.local_interval_est.LocalIntervalEstConfig
Interval analysis using local optimization
Show JSON schema
{ "title": "LocalIntervalEstConfig", "description": "Interval analysis using local optimization", "type": "object", "properties": { "model_pointer": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Identifier for model block to be used by a method", "title": "Model Pointer", "x-block-pointer": "model", "x-materialization": [ { "ir_key": "method.model_pointer", "ir_value_type": "String", "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" } ] }, "optimization_solver": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/MethodGradientSubProblemSolverSqp" }, { "$ref": "#/$defs/MethodGradientSubProblemSolverNip" }, { "type": "null" } ], "default": null, "description": "Optimization Solver", "title": "Optimization Solver", "x-union-pattern": 2 }, "id_method": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Name the method block; helpful when there are multiple", "title": "Id Method", "x-materialization": [ { "ir_key": "method.id", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "output": { "anyOf": [ { "$ref": "#/$defs/Debug" }, { "$ref": "#/$defs/Verbose" }, { "$ref": "#/$defs/Normal" }, { "$ref": "#/$defs/Quiet" }, { "$ref": "#/$defs/Silent" } ], "description": "Control how much method information is written to the screen and output file", "title": "Output", "x-model-default": "Normal", "x-union-pattern": 1 }, "final_solutions": { "default": 0, "description": "Number of designs returned as the best solutions", "minimum": 0, "title": "Final Solutions", "type": "integer", "x-materialization": [ { "ir_key": "method.final_solutions", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] } }, "$defs": { "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" }, "MethodGradientSubProblemSolverNip": { "additionalProperties": false, "description": "Use a nonlinear interior point method for solving an optimization sub-problem", "properties": { "nip": { "const": true, "default": true, "description": "Use a nonlinear interior point method for solving an optimization sub-problem", "title": "Nip", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.opt_subproblem_solver", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_OPTPP" } ] } }, "title": "MethodGradientSubProblemSolverNip", "type": "object" }, "MethodGradientSubProblemSolverSqp": { "additionalProperties": false, "description": "Use a sequential quadratic programming method for solving an optimization sub-problem", "properties": { "sqp": { "const": true, "default": true, "description": "Use a sequential quadratic programming method for solving an optimization sub-problem", "title": "Sqp", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.opt_subproblem_solver", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_NPSOL" } ] } }, "title": "MethodGradientSubProblemSolverSqp", "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" }, "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" }, "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 }
- Fields:
- 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 model_pointer: str | None = None
Identifier for model block to be used by a method
- field optimization_solver: MethodGradientSubProblemSolverSqp | MethodGradientSubProblemSolverNip | None = None
Optimization Solver
Generated Pydantic models for method.local_interval_est
