importance_sampling
- pydantic model dakota.spec.method.importance_sampling.ImportanceSamplingSelection
Generated model for ImportanceSamplingSelection
Show JSON schema
{ "title": "ImportanceSamplingSelection", "description": "Generated model for ImportanceSamplingSelection", "type": "object", "properties": { "importance_sampling": { "$ref": "#/$defs/ImportanceSamplingConfig", "x-aliases": [ "nond_importance_sampling" ], "x-materialization": [ { "ir_key": "method.algorithm", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "IMPORTANCE_SAMPLING" } ] } }, "$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" }, "DistributionCumulComplContext1Complementary": { "additionalProperties": false, "description": "Computes statistics according to complementary cumulative functions", "properties": { "complementary": { "const": true, "default": true, "description": "Computes statistics according to complementary cumulative functions", "title": "Complementary", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.distribution", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "COMPLEMENTARY" } ] } }, "title": "DistributionCumulComplContext1Complementary", "type": "object" }, "DistributionCumulComplContext1Cumulative": { "additionalProperties": false, "description": "Computes statistics according to cumulative functions", "properties": { "cumulative": { "const": true, "default": true, "description": "Computes statistics according to cumulative functions", "title": "Cumulative", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.distribution", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "CUMULATIVE" } ] } }, "title": "DistributionCumulComplContext1Cumulative", "type": "object" }, "GenReliabilityLevelsGenReliabilityLevels": { "additionalProperties": false, "description": "Specify generalized relability levels at which to estimate the corresponding response value", "properties": { "values": { "description": "Specify generalized relability levels at which to estimate the corresponding response value", "items": { "type": "number" }, "title": "Values", "type": "array" }, "num_gen_reliability_levels": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Specify which ``gen_reliability_levels`` correspond to which response", "title": "Num Gen Reliability Levels" } }, "required": [ "values" ], "title": "GenReliabilityLevelsGenReliabilityLevels", "type": "object", "x-model-validations": [ { "validationContext": "genreliabilitylevelsgenreliabilitylevels", "validationErrorMessage": "For genreliabilitylevelsgenreliabilitylevels, sum of num_gen_reliability_levels must equal length of values.", "validationFields": [ "num_gen_reliability_levels", "values" ], "validationLiterals": [], "validationRuleName": "check_sum_equals_length" } ] }, "ImportanceSamplingAdaptImport": { "additionalProperties": false, "description": "Importance sampling option for probability refinement", "properties": { "adapt_import": { "const": true, "default": true, "description": "Importance sampling option for probability refinement", "title": "Adapt Import", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.integration_refinement", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "AIS" } ] } }, "title": "ImportanceSamplingAdaptImport", "type": "object" }, "ImportanceSamplingConfig": { "additionalProperties": false, "description": "Importance sampling", "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" } ] }, "rng": { "anyOf": [ { "$ref": "#/$defs/RngOptionsContext2Mt19937" }, { "$ref": "#/$defs/RngOptionsContext2Rnum2" } ], "description": "Selection of a random number generator", "title": "Rng", "x-model-default": "RngOptionsContext2Mt19937", "x-union-pattern": 1 }, "response_levels": { "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbGenContext1ResponseLevels" }, { "type": "null" } ], "argument": "values", "default": null, "description": "Values at which to estimate desired statistics for each response", "x-materialization": [ { "ir_key": "method.nond.response_levels", "ir_value_type": "RealVectorArray", "storage_type": "RESPONSE_LEVELS_ARRAY" } ] }, "probability_levels": { "anyOf": [ { "$ref": "#/$defs/ProbabilityLevelsContext2ProbabilityLevels" }, { "type": "null" } ], "argument": "values", "default": null, "description": "Specify probability levels at which to estimate the corresponding response value", "x-materialization": [ { "ir_key": "method.nond.probability_levels", "ir_value_type": "RealVectorArray", "storage_type": "RESPONSE_LEVELS_ARRAY" } ] }, "gen_reliability_levels": { "anyOf": [ { "$ref": "#/$defs/GenReliabilityLevelsGenReliabilityLevels" }, { "type": "null" } ], "argument": "values", "default": null, "description": "Specify generalized relability levels at which to estimate the corresponding response value", "x-materialization": [ { "ir_key": "method.nond.gen_reliability_levels", "ir_value_type": "RealVectorArray", "storage_type": "RESPONSE_LEVELS_ARRAY" } ] }, "distribution": { "anyOf": [ { "$ref": "#/$defs/DistributionCumulComplContext1Cumulative" }, { "$ref": "#/$defs/DistributionCumulComplContext1Complementary" } ], "description": "Selection of cumulative or complementary cumulative functions", "title": "Distribution", "x-model-default": "DistributionCumulComplContext1Cumulative", "x-union-pattern": 1 }, "convergence_tolerance": { "default": -1.7976931348623157e+308, "description": "Stopping criterion based on objective function or statistics convergence", "title": "Convergence Tolerance", "type": "number", "x-materialization": [ { "ir_key": "method.convergence_tolerance", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" }, { "ir_key": "method.jega.percent_change", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "max_iterations": { "default": 9223372036854775807, "description": "Number of iterations allowed for optimizers and adaptive UQ methods", "minimum": 0, "title": "Max Iterations", "type": "integer", "x-materialization": [ { "ir_key": "method.max_iterations", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] }, "id_method": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Name the method block; helpful when there are multiple", "title": "Id Method", "x-materialization": [ { "ir_key": "method.id", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "output": { "anyOf": [ { "$ref": "#/$defs/Debug" }, { "$ref": "#/$defs/Verbose" }, { "$ref": "#/$defs/Normal" }, { "$ref": "#/$defs/Quiet" }, { "$ref": "#/$defs/Silent" } ], "description": "Control how much method information is written to the screen and output file", "title": "Output", "x-model-default": "Normal", "x-union-pattern": 1 }, "final_solutions": { "default": 0, "description": "Number of designs returned as the best solutions", "minimum": 0, "title": "Final Solutions", "type": "integer", "x-materialization": [ { "ir_key": "method.final_solutions", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] }, "samples": { "default": 0, "description": "Number of samples for sampling-based methods", "title": "Samples", "type": "integer", "x-aliases": [ "initial_samples" ], "x-materialization": [ { "ir_key": "method.samples", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "seed": { "anyOf": [ { "exclusiveMinimum": 0, "type": "integer" }, { "type": "null" } ], "default": null, "description": "Seed of the random number generator", "title": "Seed", "x-materialization": [ { "ir_key": "method.random_seed", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "approach": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/ImportanceSamplingImportance" }, { "$ref": "#/$defs/ImportanceSamplingAdaptImport" }, { "$ref": "#/$defs/ImportanceSamplingMmAdaptImport" } ], "description": "Importance Sampling Approach", "title": "Approach", "x-union-pattern": 4 }, "refinement_samples": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Number of samples used to refine a probability estimate or sampling design.", "title": "Refinement Samples", "x-materialization": [ { "ir_key": "method.nond.refinement_samples", "ir_value_type": "IntVector", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "approach" ], "title": "ImportanceSamplingConfig", "type": "object" }, "ImportanceSamplingImportance": { "additionalProperties": false, "description": "Importance sampling option for probability refinement", "properties": { "importance": { "const": true, "default": true, "description": "Importance sampling option for probability refinement", "title": "Importance", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.integration_refinement", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "IS" } ] } }, "title": "ImportanceSamplingImportance", "type": "object" }, "ImportanceSamplingMmAdaptImport": { "additionalProperties": false, "description": "Importance sampling option for probability refinement", "properties": { "mm_adapt_import": { "const": true, "default": true, "description": "Importance sampling option for probability refinement", "title": "Mm Adapt Import", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.integration_refinement", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "MMAIS" } ] } }, "title": "ImportanceSamplingMmAdaptImport", "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" }, "ProbabilityLevelsContext2ProbabilityLevels": { "additionalProperties": false, "description": "Specify probability levels at which to estimate the corresponding response value", "properties": { "values": { "description": "Specify probability levels at which to estimate the corresponding response value", "items": { "type": "number" }, "title": "Values", "type": "array" }, "num_probability_levels": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Specify which ``probability_levels`` correspond to which response", "title": "Num Probability Levels" } }, "required": [ "values" ], "title": "ProbabilityLevelsContext2ProbabilityLevels", "type": "object", "x-model-validations": [ { "validationContext": "probabilitylevelscontext2probabilitylevels", "validationErrorMessage": "For probabilitylevelscontext2probabilitylevels, all elements of values must be in [0, 1].", "validationFields": [ "values" ], "validationLiterals": [], "validationRuleName": "check_probability_list" }, { "validationContext": "probabilitylevelscontext2probabilitylevels", "validationErrorMessage": "For probabilitylevelscontext2probabilitylevels, sum of num_probability_levels must equal length of values.", "validationFields": [ "num_probability_levels", "values" ], "validationLiterals": [], "validationRuleName": "check_sum_equals_length" } ] }, "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" }, "ResponseLevelsComputeProbGenContext1Compute": { "additionalProperties": false, "description": "Selection of statistics to compute at each response level", "properties": { "statistic": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbGenContext1Probabilities" }, { "$ref": "#/$defs/ResponseLevelsComputeProbGenContext1GenReliabilities" } ], "description": "Statistics to Compute", "title": "Statistic", "x-union-pattern": 4 }, "system": { "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbGenContext1SystemSeries" }, { "$ref": "#/$defs/ResponseLevelsComputeProbGenContext1SystemParallel" }, { "type": "null" } ], "default": null, "description": "Compute system reliability (series or parallel)", "title": "System", "x-union-pattern": 2 } }, "required": [ "statistic" ], "title": "ResponseLevelsComputeProbGenContext1Compute", "type": "object" }, "ResponseLevelsComputeProbGenContext1GenReliabilities": { "additionalProperties": false, "description": "Computes generalized reliabilities associated with response levels", "properties": { "gen_reliabilities": { "const": true, "default": true, "description": "Computes generalized reliabilities associated with response levels", "title": "Gen Reliabilities", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.response_level_target", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "GEN_RELIABILITIES" } ] } }, "title": "ResponseLevelsComputeProbGenContext1GenReliabilities", "type": "object" }, "ResponseLevelsComputeProbGenContext1Probabilities": { "additionalProperties": false, "description": "Computes probabilities associated with response levels", "properties": { "probabilities": { "const": true, "default": true, "description": "Computes probabilities associated with response levels", "title": "Probabilities", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.response_level_target", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "PROBABILITIES" } ] } }, "title": "ResponseLevelsComputeProbGenContext1Probabilities", "type": "object" }, "ResponseLevelsComputeProbGenContext1ResponseLevels": { "additionalProperties": false, "description": "Values at which to estimate desired statistics for each response", "properties": { "values": { "description": "Values at which to estimate desired statistics for each response", "items": { "type": "number" }, "title": "Values", "type": "array" }, "num_response_levels": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Number of values at which to estimate desired statistics for each response", "title": "Num Response Levels" }, "compute": { "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbGenContext1Compute" }, { "type": "null" } ], "default": null, "description": "Selection of statistics to compute at each response level" } }, "required": [ "values" ], "title": "ResponseLevelsComputeProbGenContext1ResponseLevels", "type": "object", "x-model-validations": [ { "validationContext": "responselevelscomputeprobgencontext1responselevels", "validationErrorMessage": "For responselevelscomputeprobgencontext1responselevels, sum of num_response_levels must equal length of values.", "validationFields": [ "num_response_levels", "values" ], "validationLiterals": [], "validationRuleName": "check_sum_equals_length" } ] }, "ResponseLevelsComputeProbGenContext1SystemParallel": { "additionalProperties": false, "description": "Aggregate response statistics assuming a parallel system", "properties": { "parallel": { "const": true, "default": true, "description": "Aggregate response statistics assuming a parallel system", "title": "Parallel", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.response_level_target_reduce", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SYSTEM_PARALLEL" } ] } }, "title": "ResponseLevelsComputeProbGenContext1SystemParallel", "type": "object" }, "ResponseLevelsComputeProbGenContext1SystemSeries": { "additionalProperties": false, "description": "Aggregate response statistics assuming a series system", "properties": { "series": { "const": true, "default": true, "description": "Aggregate response statistics assuming a series system", "title": "Series", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.response_level_target_reduce", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SYSTEM_SERIES" } ] } }, "title": "ResponseLevelsComputeProbGenContext1SystemSeries", "type": "object" }, "RngOptionsContext2Mt19937": { "additionalProperties": false, "description": "Generates random numbers using the Mersenne twister", "properties": { "mt19937": { "const": true, "default": true, "description": "Generates random numbers using the Mersenne twister", "title": "Mt19937", "type": "boolean", "x-materialization": [ { "ir_key": "method.random_number_generator", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "mt19937" } ] } }, "title": "RngOptionsContext2Mt19937", "type": "object" }, "RngOptionsContext2Rnum2": { "additionalProperties": false, "description": "Generates pseudo-random numbers using the Pecos package", "properties": { "rnum2": { "const": true, "default": true, "description": "Generates pseudo-random numbers using the Pecos package", "title": "Rnum2", "type": "boolean", "x-materialization": [ { "ir_key": "method.random_number_generator", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "rnum2" } ] } }, "title": "RngOptionsContext2Rnum2", "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": [ "importance_sampling" ] }
- field importance_sampling: ImportanceSamplingConfig [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.importance_sampling.ImportanceSamplingConfig
Importance sampling
Show JSON schema
{ "title": "ImportanceSamplingConfig", "description": "Importance sampling", "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" } ] }, "rng": { "anyOf": [ { "$ref": "#/$defs/RngOptionsContext2Mt19937" }, { "$ref": "#/$defs/RngOptionsContext2Rnum2" } ], "description": "Selection of a random number generator", "title": "Rng", "x-model-default": "RngOptionsContext2Mt19937", "x-union-pattern": 1 }, "response_levels": { "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbGenContext1ResponseLevels" }, { "type": "null" } ], "argument": "values", "default": null, "description": "Values at which to estimate desired statistics for each response", "x-materialization": [ { "ir_key": "method.nond.response_levels", "ir_value_type": "RealVectorArray", "storage_type": "RESPONSE_LEVELS_ARRAY" } ] }, "probability_levels": { "anyOf": [ { "$ref": "#/$defs/ProbabilityLevelsContext2ProbabilityLevels" }, { "type": "null" } ], "argument": "values", "default": null, "description": "Specify probability levels at which to estimate the corresponding response value", "x-materialization": [ { "ir_key": "method.nond.probability_levels", "ir_value_type": "RealVectorArray", "storage_type": "RESPONSE_LEVELS_ARRAY" } ] }, "gen_reliability_levels": { "anyOf": [ { "$ref": "#/$defs/GenReliabilityLevelsGenReliabilityLevels" }, { "type": "null" } ], "argument": "values", "default": null, "description": "Specify generalized relability levels at which to estimate the corresponding response value", "x-materialization": [ { "ir_key": "method.nond.gen_reliability_levels", "ir_value_type": "RealVectorArray", "storage_type": "RESPONSE_LEVELS_ARRAY" } ] }, "distribution": { "anyOf": [ { "$ref": "#/$defs/DistributionCumulComplContext1Cumulative" }, { "$ref": "#/$defs/DistributionCumulComplContext1Complementary" } ], "description": "Selection of cumulative or complementary cumulative functions", "title": "Distribution", "x-model-default": "DistributionCumulComplContext1Cumulative", "x-union-pattern": 1 }, "convergence_tolerance": { "default": -1.7976931348623157e+308, "description": "Stopping criterion based on objective function or statistics convergence", "title": "Convergence Tolerance", "type": "number", "x-materialization": [ { "ir_key": "method.convergence_tolerance", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" }, { "ir_key": "method.jega.percent_change", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "max_iterations": { "default": 9223372036854775807, "description": "Number of iterations allowed for optimizers and adaptive UQ methods", "minimum": 0, "title": "Max Iterations", "type": "integer", "x-materialization": [ { "ir_key": "method.max_iterations", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] }, "id_method": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Name the method block; helpful when there are multiple", "title": "Id Method", "x-materialization": [ { "ir_key": "method.id", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "output": { "anyOf": [ { "$ref": "#/$defs/Debug" }, { "$ref": "#/$defs/Verbose" }, { "$ref": "#/$defs/Normal" }, { "$ref": "#/$defs/Quiet" }, { "$ref": "#/$defs/Silent" } ], "description": "Control how much method information is written to the screen and output file", "title": "Output", "x-model-default": "Normal", "x-union-pattern": 1 }, "final_solutions": { "default": 0, "description": "Number of designs returned as the best solutions", "minimum": 0, "title": "Final Solutions", "type": "integer", "x-materialization": [ { "ir_key": "method.final_solutions", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] }, "samples": { "default": 0, "description": "Number of samples for sampling-based methods", "title": "Samples", "type": "integer", "x-aliases": [ "initial_samples" ], "x-materialization": [ { "ir_key": "method.samples", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "seed": { "anyOf": [ { "exclusiveMinimum": 0, "type": "integer" }, { "type": "null" } ], "default": null, "description": "Seed of the random number generator", "title": "Seed", "x-materialization": [ { "ir_key": "method.random_seed", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "approach": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/ImportanceSamplingImportance" }, { "$ref": "#/$defs/ImportanceSamplingAdaptImport" }, { "$ref": "#/$defs/ImportanceSamplingMmAdaptImport" } ], "description": "Importance Sampling Approach", "title": "Approach", "x-union-pattern": 4 }, "refinement_samples": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Number of samples used to refine a probability estimate or sampling design.", "title": "Refinement Samples", "x-materialization": [ { "ir_key": "method.nond.refinement_samples", "ir_value_type": "IntVector", "storage_type": "DIRECT_VALUE" } ] } }, "$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" }, "DistributionCumulComplContext1Complementary": { "additionalProperties": false, "description": "Computes statistics according to complementary cumulative functions", "properties": { "complementary": { "const": true, "default": true, "description": "Computes statistics according to complementary cumulative functions", "title": "Complementary", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.distribution", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "COMPLEMENTARY" } ] } }, "title": "DistributionCumulComplContext1Complementary", "type": "object" }, "DistributionCumulComplContext1Cumulative": { "additionalProperties": false, "description": "Computes statistics according to cumulative functions", "properties": { "cumulative": { "const": true, "default": true, "description": "Computes statistics according to cumulative functions", "title": "Cumulative", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.distribution", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "CUMULATIVE" } ] } }, "title": "DistributionCumulComplContext1Cumulative", "type": "object" }, "GenReliabilityLevelsGenReliabilityLevels": { "additionalProperties": false, "description": "Specify generalized relability levels at which to estimate the corresponding response value", "properties": { "values": { "description": "Specify generalized relability levels at which to estimate the corresponding response value", "items": { "type": "number" }, "title": "Values", "type": "array" }, "num_gen_reliability_levels": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Specify which ``gen_reliability_levels`` correspond to which response", "title": "Num Gen Reliability Levels" } }, "required": [ "values" ], "title": "GenReliabilityLevelsGenReliabilityLevels", "type": "object", "x-model-validations": [ { "validationContext": "genreliabilitylevelsgenreliabilitylevels", "validationErrorMessage": "For genreliabilitylevelsgenreliabilitylevels, sum of num_gen_reliability_levels must equal length of values.", "validationFields": [ "num_gen_reliability_levels", "values" ], "validationLiterals": [], "validationRuleName": "check_sum_equals_length" } ] }, "ImportanceSamplingAdaptImport": { "additionalProperties": false, "description": "Importance sampling option for probability refinement", "properties": { "adapt_import": { "const": true, "default": true, "description": "Importance sampling option for probability refinement", "title": "Adapt Import", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.integration_refinement", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "AIS" } ] } }, "title": "ImportanceSamplingAdaptImport", "type": "object" }, "ImportanceSamplingImportance": { "additionalProperties": false, "description": "Importance sampling option for probability refinement", "properties": { "importance": { "const": true, "default": true, "description": "Importance sampling option for probability refinement", "title": "Importance", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.integration_refinement", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "IS" } ] } }, "title": "ImportanceSamplingImportance", "type": "object" }, "ImportanceSamplingMmAdaptImport": { "additionalProperties": false, "description": "Importance sampling option for probability refinement", "properties": { "mm_adapt_import": { "const": true, "default": true, "description": "Importance sampling option for probability refinement", "title": "Mm Adapt Import", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.integration_refinement", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "MMAIS" } ] } }, "title": "ImportanceSamplingMmAdaptImport", "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" }, "ProbabilityLevelsContext2ProbabilityLevels": { "additionalProperties": false, "description": "Specify probability levels at which to estimate the corresponding response value", "properties": { "values": { "description": "Specify probability levels at which to estimate the corresponding response value", "items": { "type": "number" }, "title": "Values", "type": "array" }, "num_probability_levels": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Specify which ``probability_levels`` correspond to which response", "title": "Num Probability Levels" } }, "required": [ "values" ], "title": "ProbabilityLevelsContext2ProbabilityLevels", "type": "object", "x-model-validations": [ { "validationContext": "probabilitylevelscontext2probabilitylevels", "validationErrorMessage": "For probabilitylevelscontext2probabilitylevels, all elements of values must be in [0, 1].", "validationFields": [ "values" ], "validationLiterals": [], "validationRuleName": "check_probability_list" }, { "validationContext": "probabilitylevelscontext2probabilitylevels", "validationErrorMessage": "For probabilitylevelscontext2probabilitylevels, sum of num_probability_levels must equal length of values.", "validationFields": [ "num_probability_levels", "values" ], "validationLiterals": [], "validationRuleName": "check_sum_equals_length" } ] }, "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" }, "ResponseLevelsComputeProbGenContext1Compute": { "additionalProperties": false, "description": "Selection of statistics to compute at each response level", "properties": { "statistic": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbGenContext1Probabilities" }, { "$ref": "#/$defs/ResponseLevelsComputeProbGenContext1GenReliabilities" } ], "description": "Statistics to Compute", "title": "Statistic", "x-union-pattern": 4 }, "system": { "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbGenContext1SystemSeries" }, { "$ref": "#/$defs/ResponseLevelsComputeProbGenContext1SystemParallel" }, { "type": "null" } ], "default": null, "description": "Compute system reliability (series or parallel)", "title": "System", "x-union-pattern": 2 } }, "required": [ "statistic" ], "title": "ResponseLevelsComputeProbGenContext1Compute", "type": "object" }, "ResponseLevelsComputeProbGenContext1GenReliabilities": { "additionalProperties": false, "description": "Computes generalized reliabilities associated with response levels", "properties": { "gen_reliabilities": { "const": true, "default": true, "description": "Computes generalized reliabilities associated with response levels", "title": "Gen Reliabilities", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.response_level_target", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "GEN_RELIABILITIES" } ] } }, "title": "ResponseLevelsComputeProbGenContext1GenReliabilities", "type": "object" }, "ResponseLevelsComputeProbGenContext1Probabilities": { "additionalProperties": false, "description": "Computes probabilities associated with response levels", "properties": { "probabilities": { "const": true, "default": true, "description": "Computes probabilities associated with response levels", "title": "Probabilities", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.response_level_target", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "PROBABILITIES" } ] } }, "title": "ResponseLevelsComputeProbGenContext1Probabilities", "type": "object" }, "ResponseLevelsComputeProbGenContext1ResponseLevels": { "additionalProperties": false, "description": "Values at which to estimate desired statistics for each response", "properties": { "values": { "description": "Values at which to estimate desired statistics for each response", "items": { "type": "number" }, "title": "Values", "type": "array" }, "num_response_levels": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Number of values at which to estimate desired statistics for each response", "title": "Num Response Levels" }, "compute": { "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbGenContext1Compute" }, { "type": "null" } ], "default": null, "description": "Selection of statistics to compute at each response level" } }, "required": [ "values" ], "title": "ResponseLevelsComputeProbGenContext1ResponseLevels", "type": "object", "x-model-validations": [ { "validationContext": "responselevelscomputeprobgencontext1responselevels", "validationErrorMessage": "For responselevelscomputeprobgencontext1responselevels, sum of num_response_levels must equal length of values.", "validationFields": [ "num_response_levels", "values" ], "validationLiterals": [], "validationRuleName": "check_sum_equals_length" } ] }, "ResponseLevelsComputeProbGenContext1SystemParallel": { "additionalProperties": false, "description": "Aggregate response statistics assuming a parallel system", "properties": { "parallel": { "const": true, "default": true, "description": "Aggregate response statistics assuming a parallel system", "title": "Parallel", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.response_level_target_reduce", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SYSTEM_PARALLEL" } ] } }, "title": "ResponseLevelsComputeProbGenContext1SystemParallel", "type": "object" }, "ResponseLevelsComputeProbGenContext1SystemSeries": { "additionalProperties": false, "description": "Aggregate response statistics assuming a series system", "properties": { "series": { "const": true, "default": true, "description": "Aggregate response statistics assuming a series system", "title": "Series", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.response_level_target_reduce", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SYSTEM_SERIES" } ] } }, "title": "ResponseLevelsComputeProbGenContext1SystemSeries", "type": "object" }, "RngOptionsContext2Mt19937": { "additionalProperties": false, "description": "Generates random numbers using the Mersenne twister", "properties": { "mt19937": { "const": true, "default": true, "description": "Generates random numbers using the Mersenne twister", "title": "Mt19937", "type": "boolean", "x-materialization": [ { "ir_key": "method.random_number_generator", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "mt19937" } ] } }, "title": "RngOptionsContext2Mt19937", "type": "object" }, "RngOptionsContext2Rnum2": { "additionalProperties": false, "description": "Generates pseudo-random numbers using the Pecos package", "properties": { "rnum2": { "const": true, "default": true, "description": "Generates pseudo-random numbers using the Pecos package", "title": "Rnum2", "type": "boolean", "x-materialization": [ { "ir_key": "method.random_number_generator", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "rnum2" } ] } }, "title": "RngOptionsContext2Rnum2", "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": [ "approach" ] }
- Fields:
- field approach: ImportanceSamplingImportance | ImportanceSamplingAdaptImport | ImportanceSamplingMmAdaptImport [Required]
Importance Sampling Approach
- 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 distribution: DistributionCumulComplContext1Cumulative | DistributionCumulComplContext1Complementary [Optional]
Selection of cumulative or complementary cumulative functions
- field final_solutions: int = 0
Number of designs returned as the best solutions
- Constraints:
ge = 0
- field gen_reliability_levels: GenReliabilityLevelsGenReliabilityLevels | None = None
Specify generalized relability levels at which to estimate the corresponding response value
- 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 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 probability_levels: ProbabilityLevelsContext2ProbabilityLevels | None = None
Specify probability levels at which to estimate the corresponding response value
- field refinement_samples: list[int] | None = None
Number of samples used to refine a probability estimate or sampling design.
- field response_levels: ResponseLevelsComputeProbGenContext1ResponseLevels | None = None
Values at which to estimate desired statistics for each response
- field rng: RngOptionsContext2Mt19937 | RngOptionsContext2Rnum2 [Optional]
Selection of a random number generator
- 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
Generated Pydantic models for method.importance_sampling
- pydantic model dakota.spec.method.importance_sampling.ImportanceSamplingAdaptImport
Importance sampling option for probability refinement
Show JSON schema
{ "title": "ImportanceSamplingAdaptImport", "description": "Importance sampling option for probability refinement", "type": "object", "properties": { "adapt_import": { "const": true, "default": true, "description": "Importance sampling option for probability refinement", "title": "Adapt Import", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.integration_refinement", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "AIS" } ] } }, "additionalProperties": false }
- Fields:
- field adapt_import: Literal[True] = True
Importance sampling option for probability refinement
- pydantic model dakota.spec.method.importance_sampling.ImportanceSamplingImportance
Importance sampling option for probability refinement
Show JSON schema
{ "title": "ImportanceSamplingImportance", "description": "Importance sampling option for probability refinement", "type": "object", "properties": { "importance": { "const": true, "default": true, "description": "Importance sampling option for probability refinement", "title": "Importance", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.integration_refinement", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "IS" } ] } }, "additionalProperties": false }
- Fields:
- field importance: Literal[True] = True
Importance sampling option for probability refinement
- pydantic model dakota.spec.method.importance_sampling.ImportanceSamplingMmAdaptImport
Importance sampling option for probability refinement
Show JSON schema
{ "title": "ImportanceSamplingMmAdaptImport", "description": "Importance sampling option for probability refinement", "type": "object", "properties": { "mm_adapt_import": { "const": true, "default": true, "description": "Importance sampling option for probability refinement", "title": "Mm Adapt Import", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.integration_refinement", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "MMAIS" } ] } }, "additionalProperties": false }
- Fields:
- field mm_adapt_import: Literal[True] = True
Importance sampling option for probability refinement
