coliny_cobyla

pydantic model dakota.spec.method.coliny_cobyla.ColinyCobylaSelection

Generated model for ColinyCobylaSelection

Show JSON schema
{
   "title": "ColinyCobylaSelection",
   "description": "Generated model for ColinyCobylaSelection",
   "type": "object",
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         },
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               "title": "Verbose",
               "type": "boolean",
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                  {
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         "title": "Verbose",
         "type": "object"
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   },
   "additionalProperties": false,
   "required": [
      "coliny_cobyla"
   ]
}

Fields:
field coliny_cobyla: ColinyCobylaConfig [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.coliny_cobyla.ColinyCobylaConfig

Constrained Optimization BY Linear Approximations (COBYLA)

Show JSON schema
{
   "title": "ColinyCobylaConfig",
   "description": "Constrained Optimization BY Linear Approximations (COBYLA)",
   "type": "object",
   "properties": {
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         ],
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         "description": "Stopping criteria based on objective function value",
         "title": "Solution Target",
         "type": "number",
         "x-aliases": [
            "solution_accuracy"
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         "x-materialization": [
            {
               "ir_key": "method.asynch_pattern_search.solution_target",
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            {
               "ir_key": "method.solution_target",
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            }
         ]
      },
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            },
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               "type": "null"
            }
         ],
         "default": null,
         "description": "Seed of the random number generator",
         "title": "Seed",
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         ]
      },
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            },
            {
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         ],
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         "description": "Show algorithm parameters not exposed in Dakota input",
         "title": "Show Misc Options",
         "x-materialization": [
            {
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         ]
      },
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         ],
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         "description": "Set method options not available through Dakota spec",
         "title": "Misc Options",
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            {
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      "convergence_tolerance": {
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         "title": "Convergence Tolerance",
         "type": "number",
         "x-materialization": [
            {
               "ir_key": "method.convergence_tolerance",
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               "ir_key": "method.jega.percent_change",
               "ir_value_type": "Real",
               "storage_type": "DIRECT_VALUE"
            }
         ]
      },
      "max_function_evaluations": {
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         "minimum": 0,
         "title": "Max Function Evaluations",
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         "description": "Turn on scaling for variables, responses, and constraints",
         "title": "Scaling",
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            {
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         ],
         "default": null,
         "description": "Name the method block; helpful when there are multiple",
         "title": "Id Method",
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            },
            {
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            },
            {
               "$ref": "#/$defs/Silent"
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         ],
         "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"
            }
         ]
      },
      "initial_delta": {
         "default": -1.0,
         "description": "Reasonable initial changes to optimization variables",
         "title": "Initial Delta",
         "type": "number",
         "x-materialization": [
            {
               "ir_key": "method.coliny.initial_delta",
               "ir_value_type": "Real",
               "storage_type": "DIRECT_VALUE"
            }
         ]
      },
      "variable_tolerance": {
         "default": -1.0,
         "description": "Required or expected accuracy in optimization variables.",
         "title": "Variable Tolerance",
         "type": "number",
         "x-materialization": [
            {
               "ir_key": "method.coliny.variable_tolerance",
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               "storage_type": "DIRECT_VALUE"
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         ]
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   },
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         "properties": {
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               "const": true,
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               "description": "Level 2 of 5 - less than normal",
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               "type": "boolean",
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                  {
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                     "stored_value": "QUIET_OUTPUT"
                  }
               ]
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         },
         "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"
                  }
               ]
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         },
         "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"
                  }
               ]
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         },
         "title": "Verbose",
         "type": "object"
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}

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 initial_delta: DakotaFloat = -1.0

Reasonable initial changes to optimization variables

Constraints:
  • func = <function _serialize_dakota_float at 0x7f2a3de76700>

  • return_type = float | str

  • when_used = json

field max_function_evaluations: int = 9223372036854775807

Number of function evaluations allowed for optimizers

Constraints:
  • ge = 0

field max_iterations: int = 9223372036854775807

Number of iterations allowed for optimizers and adaptive UQ methods

Constraints:
  • ge = 0

field misc_options: list[str] | None = None

Set method options not available through Dakota spec

field model_pointer: str | None = None

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 scaling: Literal[True] | None = None

Turn on scaling for variables, responses, and constraints

field seed: int | None = None

Seed of the random number generator

Constraints:
  • gt = 0

field show_misc_options: Literal[True] | None = None

Show algorithm parameters not exposed in Dakota input

field solution_target: DakotaFloat = -1.7976931348623157e+308

Stopping criteria based on objective function value

Constraints:
  • func = <function _serialize_dakota_float at 0x7f2a3de76700>

  • return_type = float | str

  • when_used = json

field variable_tolerance: DakotaFloat = -1.0

Required or expected accuracy in optimization variables.

Constraints:
  • func = <function _serialize_dakota_float at 0x7f2a3de76700>

  • return_type = float | str

  • when_used = json

Generated Pydantic models for method.coliny_cobyla