`dace`

pydantic model dakota.spec.method.dace.DaceSelection

Generated model for DaceSelection

Show JSON schema

{
   "title": "DaceSelection",
   "description": "Generated model for DaceSelection",
   "type": "object",
   "properties": {
      "dace": {
         "$ref": "#/$defs/DaceConfig",
         "x-materialization": [
            {
               "ir_key": "method.algorithm",
               "ir_value_type": "unsigned short",
               "storage_type": "PRESENCE_ENUM",
               "stored_value": "DACE"
            }
         ]
      }
   },
   "$defs": {
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         "additionalProperties": false,
         "description": "Computes Sobol' main effects using a binned approach",
         "properties": {
            "binned": {
               "$ref": "#/$defs/BinnedConfig",
               "x-materialization": [
                  {
                     "ir_key": "method.vbd_via_sampling_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "VBD_BINNED"
                  }
               ]
            }
         },
         "required": [
            "binned"
         ],
         "title": "Binned",
         "type": "object"
      },
      "BinnedConfig": {
         "additionalProperties": false,
         "description": "Computes Sobol' main effects using a binned approach",
         "properties": {
            "num_bins": {
               "default": -1,
               "description": "Number of bins used to compute the variance-based decomposition",
               "title": "Num Bins",
               "type": "integer",
               "x-materialization": [
                  {
                     "ir_key": "method.vbd_via_sampling_num_bins",
                     "ir_value_type": "int",
                     "storage_type": "DIRECT_VALUE"
                  }
               ]
            }
         },
         "title": "BinnedConfig",
         "type": "object"
      },
      "BoxBehnken": {
         "additionalProperties": false,
         "description": "Box-Behnken Design",
         "properties": {
            "box_behnken": {
               "const": true,
               "default": true,
               "description": "Box-Behnken Design",
               "title": "Box Behnken",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_BOX_BEHNKEN"
                  }
               ]
            }
         },
         "title": "BoxBehnken",
         "type": "object"
      },
      "CentralComposite": {
         "additionalProperties": false,
         "description": "Central Composite Design",
         "properties": {
            "central_composite": {
               "const": true,
               "default": true,
               "description": "Central Composite Design",
               "title": "Central Composite",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_CENTRAL_COMPOSITE"
                  }
               ]
            }
         },
         "title": "CentralComposite",
         "type": "object"
      },
      "DaceConfig": {
         "additionalProperties": false,
         "description": "Design and Analysis of Computer Experiments",
         "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"
                  }
               ]
            },
            "variance_based_decomp": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/VbdSamplingVarianceBasedDecomp"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "Activates global sensitivity analysis based on decomposition of response variance into contributions from variables",
               "x-materialization": [
                  {
                     "ir_key": "method.variance_based_decomp",
                     "ir_value_type": "bool",
                     "storage_type": "PRESENCE_TRUE"
                  }
               ]
            },
            "seed": {
               "anyOf": [
                  {
                     "exclusiveMinimum": 0,
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "Seed of the random number generator",
               "title": "Seed",
               "x-materialization": [
                  {
                     "ir_key": "method.random_seed",
                     "ir_value_type": "int",
                     "storage_type": "DIRECT_VALUE"
                  }
               ]
            },
            "fixed_seed": {
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                  {
                     "const": true,
                     "type": "boolean"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "Reuses the same seed value for multiple random sampling sets",
               "title": "Fixed Seed",
               "x-materialization": [
                  {
                     "ir_key": "method.fixed_seed",
                     "ir_value_type": "bool",
                     "storage_type": "PRESENCE_TRUE"
                  }
               ]
            },
            "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": "#/$defs/DaceGrid"
                  },
                  {
                     "$ref": "#/$defs/DaceRandom"
                  },
                  {
                     "$ref": "#/$defs/Oas"
                  },
                  {
                     "$ref": "#/$defs/DaceLhs"
                  },
                  {
                     "$ref": "#/$defs/OaLhs"
                  },
                  {
                     "$ref": "#/$defs/BoxBehnken"
                  },
                  {
                     "$ref": "#/$defs/CentralComposite"
                  }
               ],
               "description": "DACE type",
               "title": "Sub Method",
               "x-union-pattern": 4
            },
            "samples": {
               "default": 0,
               "description": "Number of samples for sampling-based methods",
               "title": "Samples",
               "type": "integer",
               "x-materialization": [
                  {
                     "ir_key": "method.samples",
                     "ir_value_type": "int",
                     "storage_type": "DIRECT_VALUE"
                  }
               ]
            },
            "main_effects": {
               "anyOf": [
                  {
                     "const": true,
                     "type": "boolean"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "ANOVA",
               "title": "Main Effects",
               "x-materialization": [
                  {
                     "ir_key": "method.main_effects",
                     "ir_value_type": "bool",
                     "storage_type": "PRESENCE_TRUE"
                  }
               ]
            },
            "quality_metrics": {
               "anyOf": [
                  {
                     "const": true,
                     "type": "boolean"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "Calculate metrics to assess the quality of quasi-Monte Carlo samples",
               "title": "Quality Metrics",
               "x-materialization": [
                  {
                     "ir_key": "method.quality_metrics",
                     "ir_value_type": "bool",
                     "storage_type": "PRESENCE_TRUE"
                  }
               ]
            },
            "symbols": {
               "default": 0,
               "description": "Number of replications in the sample set",
               "title": "Symbols",
               "type": "integer",
               "x-materialization": [
                  {
                     "ir_key": "method.symbols",
                     "ir_value_type": "int",
                     "storage_type": "DIRECT_VALUE"
                  }
               ]
            }
         },
         "required": [
            "sub_method"
         ],
         "title": "DaceConfig",
         "type": "object"
      },
      "DaceGrid": {
         "additionalProperties": false,
         "description": "Grid Sampling",
         "properties": {
            "grid": {
               "const": true,
               "default": true,
               "description": "Grid Sampling",
               "title": "Grid",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_GRID"
                  }
               ]
            }
         },
         "title": "DaceGrid",
         "type": "object"
      },
      "DaceLhs": {
         "additionalProperties": false,
         "description": "Uses Latin Hypercube Sampling (LHS) to sample variables",
         "properties": {
            "lhs": {
               "const": true,
               "default": true,
               "description": "Uses Latin Hypercube Sampling (LHS) to sample variables",
               "title": "Lhs",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_LHS"
                  }
               ]
            }
         },
         "title": "DaceLhs",
         "type": "object"
      },
      "DaceRandom": {
         "additionalProperties": false,
         "description": "Uses purely random Monte Carlo sampling to sample variables",
         "properties": {
            "random": {
               "const": true,
               "default": true,
               "description": "Uses purely random Monte Carlo sampling to sample variables",
               "title": "Random",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_RANDOM"
                  }
               ]
            }
         },
         "title": "DaceRandom",
         "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"
      },
      "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"
      },
      "OaLhs": {
         "additionalProperties": false,
         "description": "Orthogonal Array Latin Hypercube Sampling",
         "properties": {
            "oa_lhs": {
               "const": true,
               "default": true,
               "description": "Orthogonal Array Latin Hypercube Sampling",
               "title": "Oa Lhs",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_OA_LHS"
                  }
               ]
            }
         },
         "title": "OaLhs",
         "type": "object"
      },
      "Oas": {
         "additionalProperties": false,
         "description": "Orthogonal Array Sampling",
         "properties": {
            "oas": {
               "const": true,
               "default": true,
               "description": "Orthogonal Array Sampling",
               "title": "Oas",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_OAS"
                  }
               ]
            }
         },
         "title": "Oas",
         "type": "object"
      },
      "PickAndFreeze": {
         "additionalProperties": false,
         "description": "Use the pick-and-freeze variance-based decomposition method",
         "properties": {
            "pick_and_freeze": {
               "const": true,
               "default": true,
               "description": "Use the pick-and-freeze variance-based decomposition method",
               "title": "Pick And Freeze",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.vbd_via_sampling_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
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                  }
               ]
            }
         },
         "title": "PickAndFreeze",
         "type": "object"
      },
      "Quiet": {
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         "description": "Level 2 of 5 - less than normal",
         "properties": {
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               "const": true,
               "default": true,
               "description": "Level 2 of 5 - less than normal",
               "title": "Quiet",
               "type": "boolean",
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                  {
                     "ir_key": "method.output",
                     "ir_value_type": "short",
                     "storage_type": "PRESENCE_ENUM",
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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"
                  }
               ]
            }
         },
         "title": "Silent",
         "type": "object"
      },
      "VbdSamplingVarianceBasedDecomp": {
         "additionalProperties": false,
         "description": "Activates global sensitivity analysis based on decomposition of response variance into contributions from variables",
         "properties": {
            "drop_tolerance": {
               "default": -1.0,
               "description": "Suppresses output of sensitivity indices with values lower than this tolerance",
               "title": "Drop Tolerance",
               "type": "number",
               "x-materialization": [
                  {
                     "ir_key": "method.vbd_drop_tolerance",
                     "ir_value_type": "Real",
                     "storage_type": "DIRECT_VALUE"
                  }
               ]
            },
            "vbd_sampling_method": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/Binned"
                  },
                  {
                     "$ref": "#/$defs/PickAndFreeze"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "The method to use for variance-based decomposition",
               "title": "Vbd Sampling Method",
               "x-union-pattern": 2
            }
         },
         "title": "VbdSamplingVarianceBasedDecomp",
         "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": [
      "dace"
   ]
}

Fields:

dace (dakota.spec.method.dace.DaceConfig)

field dace: DaceConfig [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.dace.DaceConfig

Design and Analysis of Computer Experiments

Show JSON schema

{
   "title": "DaceConfig",
   "description": "Design and Analysis of Computer Experiments",
   "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"
            }
         ]
      },
      "variance_based_decomp": {
         "anyOf": [
            {
               "$ref": "#/$defs/VbdSamplingVarianceBasedDecomp"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Activates global sensitivity analysis based on decomposition of response variance into contributions from variables",
         "x-materialization": [
            {
               "ir_key": "method.variance_based_decomp",
               "ir_value_type": "bool",
               "storage_type": "PRESENCE_TRUE"
            }
         ]
      },
      "seed": {
         "anyOf": [
            {
               "exclusiveMinimum": 0,
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Seed of the random number generator",
         "title": "Seed",
         "x-materialization": [
            {
               "ir_key": "method.random_seed",
               "ir_value_type": "int",
               "storage_type": "DIRECT_VALUE"
            }
         ]
      },
      "fixed_seed": {
         "anyOf": [
            {
               "const": true,
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Reuses the same seed value for multiple random sampling sets",
         "title": "Fixed Seed",
         "x-materialization": [
            {
               "ir_key": "method.fixed_seed",
               "ir_value_type": "bool",
               "storage_type": "PRESENCE_TRUE"
            }
         ]
      },
      "id_method": {
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            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Name the method block; helpful when there are multiple",
         "title": "Id Method",
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            {
               "ir_key": "method.id",
               "ir_value_type": "String",
               "storage_type": "DIRECT_VALUE"
            }
         ]
      },
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            },
            {
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            },
            {
               "$ref": "#/$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
      },
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         "default": 0,
         "description": "Number of designs returned as the best solutions",
         "minimum": 0,
         "title": "Final Solutions",
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            }
         ]
      },
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            },
            {
               "$ref": "#/$defs/DaceRandom"
            },
            {
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            },
            {
               "$ref": "#/$defs/DaceLhs"
            },
            {
               "$ref": "#/$defs/OaLhs"
            },
            {
               "$ref": "#/$defs/BoxBehnken"
            },
            {
               "$ref": "#/$defs/CentralComposite"
            }
         ],
         "description": "DACE type",
         "title": "Sub Method",
         "x-union-pattern": 4
      },
      "samples": {
         "default": 0,
         "description": "Number of samples for sampling-based methods",
         "title": "Samples",
         "type": "integer",
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            {
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               "ir_value_type": "int",
               "storage_type": "DIRECT_VALUE"
            }
         ]
      },
      "main_effects": {
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            {
               "const": true,
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "ANOVA",
         "title": "Main Effects",
         "x-materialization": [
            {
               "ir_key": "method.main_effects",
               "ir_value_type": "bool",
               "storage_type": "PRESENCE_TRUE"
            }
         ]
      },
      "quality_metrics": {
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            {
               "const": true,
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Calculate metrics to assess the quality of quasi-Monte Carlo samples",
         "title": "Quality Metrics",
         "x-materialization": [
            {
               "ir_key": "method.quality_metrics",
               "ir_value_type": "bool",
               "storage_type": "PRESENCE_TRUE"
            }
         ]
      },
      "symbols": {
         "default": 0,
         "description": "Number of replications in the sample set",
         "title": "Symbols",
         "type": "integer",
         "x-materialization": [
            {
               "ir_key": "method.symbols",
               "ir_value_type": "int",
               "storage_type": "DIRECT_VALUE"
            }
         ]
      }
   },
   "$defs": {
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         "additionalProperties": false,
         "description": "Computes Sobol' main effects using a binned approach",
         "properties": {
            "binned": {
               "$ref": "#/$defs/BinnedConfig",
               "x-materialization": [
                  {
                     "ir_key": "method.vbd_via_sampling_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "VBD_BINNED"
                  }
               ]
            }
         },
         "required": [
            "binned"
         ],
         "title": "Binned",
         "type": "object"
      },
      "BinnedConfig": {
         "additionalProperties": false,
         "description": "Computes Sobol' main effects using a binned approach",
         "properties": {
            "num_bins": {
               "default": -1,
               "description": "Number of bins used to compute the variance-based decomposition",
               "title": "Num Bins",
               "type": "integer",
               "x-materialization": [
                  {
                     "ir_key": "method.vbd_via_sampling_num_bins",
                     "ir_value_type": "int",
                     "storage_type": "DIRECT_VALUE"
                  }
               ]
            }
         },
         "title": "BinnedConfig",
         "type": "object"
      },
      "BoxBehnken": {
         "additionalProperties": false,
         "description": "Box-Behnken Design",
         "properties": {
            "box_behnken": {
               "const": true,
               "default": true,
               "description": "Box-Behnken Design",
               "title": "Box Behnken",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_BOX_BEHNKEN"
                  }
               ]
            }
         },
         "title": "BoxBehnken",
         "type": "object"
      },
      "CentralComposite": {
         "additionalProperties": false,
         "description": "Central Composite Design",
         "properties": {
            "central_composite": {
               "const": true,
               "default": true,
               "description": "Central Composite Design",
               "title": "Central Composite",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_CENTRAL_COMPOSITE"
                  }
               ]
            }
         },
         "title": "CentralComposite",
         "type": "object"
      },
      "DaceGrid": {
         "additionalProperties": false,
         "description": "Grid Sampling",
         "properties": {
            "grid": {
               "const": true,
               "default": true,
               "description": "Grid Sampling",
               "title": "Grid",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_GRID"
                  }
               ]
            }
         },
         "title": "DaceGrid",
         "type": "object"
      },
      "DaceLhs": {
         "additionalProperties": false,
         "description": "Uses Latin Hypercube Sampling (LHS) to sample variables",
         "properties": {
            "lhs": {
               "const": true,
               "default": true,
               "description": "Uses Latin Hypercube Sampling (LHS) to sample variables",
               "title": "Lhs",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_LHS"
                  }
               ]
            }
         },
         "title": "DaceLhs",
         "type": "object"
      },
      "DaceRandom": {
         "additionalProperties": false,
         "description": "Uses purely random Monte Carlo sampling to sample variables",
         "properties": {
            "random": {
               "const": true,
               "default": true,
               "description": "Uses purely random Monte Carlo sampling to sample variables",
               "title": "Random",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_RANDOM"
                  }
               ]
            }
         },
         "title": "DaceRandom",
         "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"
      },
      "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"
      },
      "OaLhs": {
         "additionalProperties": false,
         "description": "Orthogonal Array Latin Hypercube Sampling",
         "properties": {
            "oa_lhs": {
               "const": true,
               "default": true,
               "description": "Orthogonal Array Latin Hypercube Sampling",
               "title": "Oa Lhs",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_OA_LHS"
                  }
               ]
            }
         },
         "title": "OaLhs",
         "type": "object"
      },
      "Oas": {
         "additionalProperties": false,
         "description": "Orthogonal Array Sampling",
         "properties": {
            "oas": {
               "const": true,
               "default": true,
               "description": "Orthogonal Array Sampling",
               "title": "Oas",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.sub_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "SUBMETHOD_OAS"
                  }
               ]
            }
         },
         "title": "Oas",
         "type": "object"
      },
      "PickAndFreeze": {
         "additionalProperties": false,
         "description": "Use the pick-and-freeze variance-based decomposition method",
         "properties": {
            "pick_and_freeze": {
               "const": true,
               "default": true,
               "description": "Use the pick-and-freeze variance-based decomposition method",
               "title": "Pick And Freeze",
               "type": "boolean",
               "x-materialization": [
                  {
                     "ir_key": "method.vbd_via_sampling_method",
                     "ir_value_type": "unsigned short",
                     "storage_type": "PRESENCE_ENUM",
                     "stored_value": "VBD_PICK_AND_FREEZE"
                  }
               ]
            }
         },
         "title": "PickAndFreeze",
         "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"
      },
      "VbdSamplingVarianceBasedDecomp": {
         "additionalProperties": false,
         "description": "Activates global sensitivity analysis based on decomposition of response variance into contributions from variables",
         "properties": {
            "drop_tolerance": {
               "default": -1.0,
               "description": "Suppresses output of sensitivity indices with values lower than this tolerance",
               "title": "Drop Tolerance",
               "type": "number",
               "x-materialization": [
                  {
                     "ir_key": "method.vbd_drop_tolerance",
                     "ir_value_type": "Real",
                     "storage_type": "DIRECT_VALUE"
                  }
               ]
            },
            "vbd_sampling_method": {
               "anyOf": [
                  {
                     "$ref": "#/$defs/Binned"
                  },
                  {
                     "$ref": "#/$defs/PickAndFreeze"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "description": "The method to use for variance-based decomposition",
               "title": "Vbd Sampling Method",
               "x-union-pattern": 2
            }
         },
         "title": "VbdSamplingVarianceBasedDecomp",
         "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"
   ]
}

Fields:

final_solutions (int)
fixed_seed (Literal[True] | None)
id_method (str | None)
main_effects (Literal[True] | None)
model_pointer (str | None)
output (dakota.spec.shared.misc.Debug | dakota.spec.shared.misc.Verbose | dakota.spec.shared.misc.Normal | dakota.spec.shared.misc.Quiet | dakota.spec.shared.misc.Silent)
quality_metrics (Literal[True] | None)
samples (int)
seed (int | None)
sub_method (dakota.spec.method.dace.DaceGrid | dakota.spec.method.dace.DaceRandom | dakota.spec.method.dace.Oas | dakota.spec.method.dace.DaceLhs | dakota.spec.method.dace.OaLhs | dakota.spec.method.dace.BoxBehnken | dakota.spec.method.dace.CentralComposite)
symbols (int)
variance_based_decomp (dakota.spec.shared.misc.VbdSamplingVarianceBasedDecomp | None)

field final_solutions: int = 0

Number of designs returned as the best solutions

Constraints:

ge = 0

field fixed_seed: Literal[True] | None = None: Reuses the same seed value for multiple random sampling sets

field id_method: str | None = None: Name the method block; helpful when there are multiple

field main_effects: Literal[True] | None = None: ANOVA

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 quality_metrics: Literal[True] | None = None: Calculate metrics to assess the quality of quasi-Monte Carlo samples

field samples: int = 0: Number of samples for sampling-based methods

field seed: int | None = None

Seed of the random number generator

Constraints:

gt = 0

field sub_method: DaceGrid | DaceRandom | Oas | DaceLhs | OaLhs | BoxBehnken | CentralComposite [Required]: DACE type

field symbols: int = 0: Number of replications in the sample set

field variance_based_decomp: VbdSamplingVarianceBasedDecomp | None = None: Activates global sensitivity analysis based on decomposition of response variance into contributions from variables

Generated Pydantic models for method.dace

pydantic model dakota.spec.method.dace.BoxBehnken

Box-Behnken Design

Show JSON schema

{
   "title": "BoxBehnken",
   "description": "Box-Behnken Design",
   "type": "object",
   "properties": {
      "box_behnken": {
         "const": true,
         "default": true,
         "description": "Box-Behnken Design",
         "title": "Box Behnken",
         "type": "boolean",
         "x-materialization": [
            {
               "ir_key": "method.sub_method",
               "ir_value_type": "unsigned short",
               "storage_type": "PRESENCE_ENUM",
               "stored_value": "SUBMETHOD_BOX_BEHNKEN"
            }
         ]
      }
   },
   "additionalProperties": false
}

Fields:

box_behnken (Literal[True])

field box_behnken: Literal[True] = True: Box-Behnken Design

pydantic model dakota.spec.method.dace.CentralComposite

Central Composite Design

Show JSON schema

{
   "title": "CentralComposite",
   "description": "Central Composite Design",
   "type": "object",
   "properties": {
      "central_composite": {
         "const": true,
         "default": true,
         "description": "Central Composite Design",
         "title": "Central Composite",
         "type": "boolean",
         "x-materialization": [
            {
               "ir_key": "method.sub_method",
               "ir_value_type": "unsigned short",
               "storage_type": "PRESENCE_ENUM",
               "stored_value": "SUBMETHOD_CENTRAL_COMPOSITE"
            }
         ]
      }
   },
   "additionalProperties": false
}

Fields:

central_composite (Literal[True])

field central_composite: Literal[True] = True: Central Composite Design

pydantic model dakota.spec.method.dace.DaceGrid

Grid Sampling

Show JSON schema

{
   "title": "DaceGrid",
   "description": "Grid Sampling",
   "type": "object",
   "properties": {
      "grid": {
         "const": true,
         "default": true,
         "description": "Grid Sampling",
         "title": "Grid",
         "type": "boolean",
         "x-materialization": [
            {
               "ir_key": "method.sub_method",
               "ir_value_type": "unsigned short",
               "storage_type": "PRESENCE_ENUM",
               "stored_value": "SUBMETHOD_GRID"
            }
         ]
      }
   },
   "additionalProperties": false
}

Fields:

grid (Literal[True])

field grid: Literal[True] = True: Grid Sampling

pydantic model dakota.spec.method.dace.DaceLhs

Uses Latin Hypercube Sampling (LHS) to sample variables

Show JSON schema

{
   "title": "DaceLhs",
   "description": "Uses Latin Hypercube Sampling (LHS) to sample variables",
   "type": "object",
   "properties": {
      "lhs": {
         "const": true,
         "default": true,
         "description": "Uses Latin Hypercube Sampling (LHS) to sample variables",
         "title": "Lhs",
         "type": "boolean",
         "x-materialization": [
            {
               "ir_key": "method.sub_method",
               "ir_value_type": "unsigned short",
               "storage_type": "PRESENCE_ENUM",
               "stored_value": "SUBMETHOD_LHS"
            }
         ]
      }
   },
   "additionalProperties": false
}

Fields:

lhs (Literal[True])

field lhs: Literal[True] = True: Uses Latin Hypercube Sampling (LHS) to sample variables

pydantic model dakota.spec.method.dace.DaceRandom

Uses purely random Monte Carlo sampling to sample variables

Show JSON schema

{
   "title": "DaceRandom",
   "description": "Uses purely random Monte Carlo sampling to sample variables",
   "type": "object",
   "properties": {
      "random": {
         "const": true,
         "default": true,
         "description": "Uses purely random Monte Carlo sampling to sample variables",
         "title": "Random",
         "type": "boolean",
         "x-materialization": [
            {
               "ir_key": "method.sub_method",
               "ir_value_type": "unsigned short",
               "storage_type": "PRESENCE_ENUM",
               "stored_value": "SUBMETHOD_RANDOM"
            }
         ]
      }
   },
   "additionalProperties": false
}

Fields:

random (Literal[True])

field random: Literal[True] = True: Uses purely random Monte Carlo sampling to sample variables

pydantic model dakota.spec.method.dace.OaLhs

Orthogonal Array Latin Hypercube Sampling

Show JSON schema

{
   "title": "OaLhs",
   "description": "Orthogonal Array Latin Hypercube Sampling",
   "type": "object",
   "properties": {
      "oa_lhs": {
         "const": true,
         "default": true,
         "description": "Orthogonal Array Latin Hypercube Sampling",
         "title": "Oa Lhs",
         "type": "boolean",
         "x-materialization": [
            {
               "ir_key": "method.sub_method",
               "ir_value_type": "unsigned short",
               "storage_type": "PRESENCE_ENUM",
               "stored_value": "SUBMETHOD_OA_LHS"
            }
         ]
      }
   },
   "additionalProperties": false
}

Fields:

oa_lhs (Literal[True])

field oa_lhs: Literal[True] = True: Orthogonal Array Latin Hypercube Sampling

pydantic model dakota.spec.method.dace.Oas

Orthogonal Array Sampling

Show JSON schema

{
   "title": "Oas",
   "description": "Orthogonal Array Sampling",
   "type": "object",
   "properties": {
      "oas": {
         "const": true,
         "default": true,
         "description": "Orthogonal Array Sampling",
         "title": "Oas",
         "type": "boolean",
         "x-materialization": [
            {
               "ir_key": "method.sub_method",
               "ir_value_type": "unsigned short",
               "storage_type": "PRESENCE_ENUM",
               "stored_value": "SUBMETHOD_OAS"
            }
         ]
      }
   },
   "additionalProperties": false
}

Fields:

oas (Literal[True])

field oas: Literal[True] = True: Orthogonal Array Sampling

dace

Exceptional service in the national interest

`dace`