local_reliability
- pydantic model dakota.spec.method.local_reliability.LocalReliabilitySelection
Generated model for LocalReliabilitySelection
Show JSON schema
{ "title": "LocalReliabilitySelection", "description": "Generated model for LocalReliabilitySelection", "type": "object", "properties": { "local_reliability": { "$ref": "#/$defs/LocalReliabilityConfig", "x-aliases": [ "nond_local_reliability" ], "x-materialization": [ { "ir_key": "method.algorithm", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "LOCAL_RELIABILITY" } ] } }, "$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" }, "DefaultFinalMomentsCentral": { "additionalProperties": false, "description": "Output central moments and include them within the set of final statistics.", "properties": { "central": { "const": true, "default": true, "description": "Output central moments and include them within the set of final statistics.", "title": "Central", "type": "boolean", "x-materialization": [ { "enum_scope": "Pecos", "ir_key": "method.nond.final_moments", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "CENTRAL_MOMENTS" } ] } }, "title": "DefaultFinalMomentsCentral", "type": "object" }, "DefaultFinalMomentsNoneKeyword": { "additionalProperties": false, "description": "Omit moments from the set of final statistics.", "properties": { "none": { "const": true, "default": true, "description": "Omit moments from the set of final statistics.", "title": "None", "type": "boolean", "x-materialization": [ { "enum_scope": "Pecos", "ir_key": "method.nond.final_moments", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "NO_MOMENTS" } ] } }, "title": "DefaultFinalMomentsNoneKeyword", "type": "object" }, "DefaultFinalMomentsStandard": { "additionalProperties": false, "description": "Output standardized moments and include them within the set of final statistics.", "properties": { "standard": { "const": true, "default": true, "description": "Output standardized moments and include them within the set of final statistics.", "title": "Standard", "type": "boolean", "x-materialization": [ { "enum_scope": "Pecos", "ir_key": "method.nond.final_moments", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "STANDARD_MOMENTS" } ] } }, "title": "DefaultFinalMomentsStandard", "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" } ] }, "Integration": { "additionalProperties": false, "description": "Integration approach", "properties": { "order": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/IntegrationFirstOrder" }, { "$ref": "#/$defs/IntegrationSecondOrder" } ], "description": "Integration Order", "title": "Order", "x-union-pattern": 4 }, "probability_refinement": { "anyOf": [ { "$ref": "#/$defs/IntegrationProbabilityRefinement" }, { "type": "null" } ], "default": null, "description": "Allow refinement of probability and generalized reliability results using importance sampling", "x-aliases": [ "sample_refinement" ] } }, "required": [ "order" ], "title": "Integration", "type": "object" }, "IntegrationFirstOrder": { "additionalProperties": false, "description": "First-order integration scheme", "properties": { "first_order": { "const": true, "default": true, "description": "First-order integration scheme", "title": "First Order", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.reliability_integration", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "first_order" } ] } }, "title": "IntegrationFirstOrder", "type": "object" }, "IntegrationProbabilityRefinement": { "additionalProperties": false, "description": "Allow refinement of probability and generalized reliability results using importance sampling", "properties": { "approach": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/IntegrationProbabilityRefinementImportance" }, { "$ref": "#/$defs/IntegrationProbabilityRefinementAdaptImport" }, { "$ref": "#/$defs/IntegrationProbabilityRefinementMmAdaptImport" } ], "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" } ] }, "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" } ] } }, "required": [ "approach" ], "title": "IntegrationProbabilityRefinement", "type": "object" }, "IntegrationProbabilityRefinementAdaptImport": { "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": "IntegrationProbabilityRefinementAdaptImport", "type": "object" }, "IntegrationProbabilityRefinementImportance": { "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": "IntegrationProbabilityRefinementImportance", "type": "object" }, "IntegrationProbabilityRefinementMmAdaptImport": { "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": "IntegrationProbabilityRefinementMmAdaptImport", "type": "object" }, "IntegrationSecondOrder": { "additionalProperties": false, "description": "Second-order integration scheme", "properties": { "second_order": { "const": true, "default": true, "description": "Second-order integration scheme", "title": "Second Order", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.reliability_integration", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "second_order" } ] } }, "title": "IntegrationSecondOrder", "type": "object" }, "LocalReliabilityConfig": { "additionalProperties": false, "description": "Local reliability method", "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" } ] }, "final_moments": { "anyOf": [ { "$ref": "#/$defs/DefaultFinalMomentsNoneKeyword" }, { "$ref": "#/$defs/DefaultFinalMomentsStandard" }, { "$ref": "#/$defs/DefaultFinalMomentsCentral" } ], "description": "Output moments of the specified type and include them within the set of final statistics.", "title": "Final Moments", "x-model-default": "DefaultFinalMomentsStandard", "x-union-pattern": 1 }, "convergence_tolerance": { "default": -1.7976931348623157e+308, "description": "Stopping criterion based on objective function or statistics convergence", "title": "Convergence Tolerance", "type": "number", "x-materialization": [ { "ir_key": "method.convergence_tolerance", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" }, { "ir_key": "method.jega.percent_change", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "max_iterations": { "default": 9223372036854775807, "description": "Number of iterations allowed for optimizers and adaptive UQ methods", "minimum": 0, "title": "Max Iterations", "type": "integer", "x-materialization": [ { "ir_key": "method.max_iterations", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] }, "response_levels": { "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenResponseLevels" }, { "type": "null" } ], "argument": "values", "default": null, "description": "Values at which to estimate desired statistics for each response", "x-materialization": [ { "ir_key": "method.nond.response_levels", "ir_value_type": "RealVectorArray", "storage_type": "RESPONSE_LEVELS_ARRAY" } ] }, "reliability_levels": { "anyOf": [ { "$ref": "#/$defs/ReliabilityLevelsReliabilityLevels" }, { "type": "null" } ], "argument": "values", "default": null, "description": "Specify reliability levels at which the response values will be estimated", "x-materialization": [ { "ir_key": "method.nond.reliability_levels", "ir_value_type": "RealVectorArray", "storage_type": "RESPONSE_LEVELS_ARRAY" } ] }, "probability_levels": { "anyOf": [ { "$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": "#/$defs/DistributionCumulComplContext1Complementary" } ], "description": "Selection of cumulative or complementary cumulative functions", "title": "Distribution", "x-model-default": "DistributionCumulComplContext1Cumulative", "x-union-pattern": 1 }, "id_method": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Name the method block; helpful when there are multiple", "title": "Id Method", "x-materialization": [ { "ir_key": "method.id", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "output": { "anyOf": [ { "$ref": "#/$defs/Debug" }, { "$ref": "#/$defs/Verbose" }, { "$ref": "#/$defs/Normal" }, { "$ref": "#/$defs/Quiet" }, { "$ref": "#/$defs/Silent" } ], "description": "Control how much method information is written to the screen and output file", "title": "Output", "x-model-default": "Normal", "x-union-pattern": 1 }, "final_solutions": { "default": 0, "description": "Number of designs returned as the best solutions", "minimum": 0, "title": "Final Solutions", "type": "integer", "x-materialization": [ { "ir_key": "method.final_solutions", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] }, "mpp_search": { "anyOf": [ { "$ref": "#/$defs/MppSearch" }, { "type": "null" } ], "default": null, "description": "Specify which MPP search option to use" } }, "title": "LocalReliabilityConfig", "type": "object" }, "MethodGradientSubProblemSolverNip": { "additionalProperties": false, "description": "Use a nonlinear interior point method for solving an optimization sub-problem", "properties": { "nip": { "const": true, "default": true, "description": "Use a nonlinear interior point method for solving an optimization sub-problem", "title": "Nip", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.opt_subproblem_solver", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_OPTPP" } ] } }, "title": "MethodGradientSubProblemSolverNip", "type": "object" }, "MethodGradientSubProblemSolverSqp": { "additionalProperties": false, "description": "Use a sequential quadratic programming method for solving an optimization sub-problem", "properties": { "sqp": { "const": true, "default": true, "description": "Use a sequential quadratic programming method for solving an optimization sub-problem", "title": "Sqp", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.opt_subproblem_solver", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_NPSOL" } ] } }, "title": "MethodGradientSubProblemSolverSqp", "type": "object" }, "MppSearch": { "additionalProperties": false, "description": "Specify which MPP search option to use", "properties": { "optimization_solver": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/MethodGradientSubProblemSolverSqp" }, { "$ref": "#/$defs/MethodGradientSubProblemSolverNip" }, { "type": "null" } ], "default": null, "description": "Optimization Solver", "title": "Optimization Solver", "x-union-pattern": 2 }, "sub_method": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/XTaylorMean" }, { "$ref": "#/$defs/UTaylorMean" }, { "$ref": "#/$defs/XTaylorMpp" }, { "$ref": "#/$defs/UTaylorMpp" }, { "$ref": "#/$defs/XTwoPoint" }, { "$ref": "#/$defs/UTwoPoint" }, { "$ref": "#/$defs/XMultiPoint" }, { "$ref": "#/$defs/UMultiPoint" }, { "$ref": "#/$defs/NoApprox" } ], "description": "MPP Approximation", "title": "Sub Method", "x-union-pattern": 4 }, "integration": { "anyOf": [ { "$ref": "#/$defs/Integration" }, { "type": "null" } ], "default": null, "description": "Integration approach" } }, "required": [ "sub_method" ], "title": "MppSearch", "type": "object" }, "NoApprox": { "additionalProperties": false, "description": "Perform MPP search on original response functions (use no approximation)", "properties": { "no_approx": { "const": true, "default": true, "description": "Perform MPP search on original response functions (use no approximation)", "title": "No Approx", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_NO_APPROX" } ] } }, "title": "NoApprox", "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" }, "ReliabilityLevelsReliabilityLevels": { "additionalProperties": false, "description": "Specify reliability levels at which the response values will be estimated", "properties": { "values": { "description": "Specify reliability levels at which the response values will be estimated", "items": { "type": "number" }, "title": "Values", "type": "array" }, "num_reliability_levels": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Specify which ``reliability_levels`` correspond to which response", "title": "Num Reliability Levels" } }, "required": [ "values" ], "title": "ReliabilityLevelsReliabilityLevels", "type": "object", "x-model-validations": [ { "validationContext": "reliabilitylevelsreliabilitylevels", "validationErrorMessage": "For reliabilitylevelsreliabilitylevels, sum of num_reliability_levels must equal length of values.", "validationFields": [ "num_reliability_levels", "values" ], "validationLiterals": [], "validationRuleName": "check_sum_equals_length" } ] }, "ResponseLevelsComputeProbRelGenCompute": { "additionalProperties": false, "description": "Selection of statistics to compute at each response level", "properties": { "statistic": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenProbabilities" }, { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenReliabilities" }, { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenGenReliabilities" } ], "description": "Statistics to Compute", "title": "Statistic", "x-union-pattern": 4 }, "system": { "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenSystemSeries" }, { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenSystemParallel" }, { "type": "null" } ], "default": null, "description": "Compute system reliability (series or parallel)", "title": "System", "x-union-pattern": 2 } }, "required": [ "statistic" ], "title": "ResponseLevelsComputeProbRelGenCompute", "type": "object" }, "ResponseLevelsComputeProbRelGenGenReliabilities": { "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": "ResponseLevelsComputeProbRelGenGenReliabilities", "type": "object" }, "ResponseLevelsComputeProbRelGenProbabilities": { "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": "ResponseLevelsComputeProbRelGenProbabilities", "type": "object" }, "ResponseLevelsComputeProbRelGenReliabilities": { "additionalProperties": false, "description": "Computes reliabilities associated with response levels", "properties": { "reliabilities": { "const": true, "default": true, "description": "Computes reliabilities associated with response levels", "title": "Reliabilities", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.response_level_target", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "RELIABILITIES" } ] } }, "title": "ResponseLevelsComputeProbRelGenReliabilities", "type": "object" }, "ResponseLevelsComputeProbRelGenResponseLevels": { "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/ResponseLevelsComputeProbRelGenCompute" }, { "type": "null" } ], "default": null, "description": "Selection of statistics to compute at each response level" } }, "required": [ "values" ], "title": "ResponseLevelsComputeProbRelGenResponseLevels", "type": "object", "x-model-validations": [ { "validationContext": "responselevelscomputeprobrelgenresponselevels", "validationErrorMessage": "For responselevelscomputeprobrelgenresponselevels, sum of num_response_levels must equal length of values.", "validationFields": [ "num_response_levels", "values" ], "validationLiterals": [], "validationRuleName": "check_sum_equals_length" } ] }, "ResponseLevelsComputeProbRelGenSystemParallel": { "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": "ResponseLevelsComputeProbRelGenSystemParallel", "type": "object" }, "ResponseLevelsComputeProbRelGenSystemSeries": { "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": "ResponseLevelsComputeProbRelGenSystemSeries", "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" }, "UMultiPoint": { "additionalProperties": false, "description": "MPP search for local reliability based on QMEA multi-point approximation in x-space", "properties": { "u_multi_point": { "const": true, "default": true, "description": "MPP search for local reliability based on QMEA multi-point approximation in x-space", "title": "U Multi Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_QMEA_U" } ] } }, "title": "UMultiPoint", "type": "object" }, "UTaylorMean": { "additionalProperties": false, "description": "Form Taylor series approximation in \\\"u-space\\\" at variable means", "properties": { "u_taylor_mean": { "const": true, "default": true, "description": "Form Taylor series approximation in \"u-space\" at variable means", "title": "U Taylor Mean", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_U" } ] } }, "title": "UTaylorMean", "type": "object" }, "UTaylorMpp": { "additionalProperties": false, "description": "U-space Taylor series approximation with iterative updates", "properties": { "u_taylor_mpp": { "const": true, "default": true, "description": "U-space Taylor series approximation with iterative updates", "title": "U Taylor Mpp", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_PLUS_U" } ] } }, "title": "UTaylorMpp", "type": "object" }, "UTwoPoint": { "additionalProperties": false, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \\\"u-space\\\"", "properties": { "u_two_point": { "const": true, "default": true, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \"u-space\"", "title": "U Two Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_TANA_U" } ] } }, "title": "UTwoPoint", "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" }, "XMultiPoint": { "additionalProperties": false, "description": "MPP search for local reliability based on QMEA multi-point approximation in u-space", "properties": { "x_multi_point": { "const": true, "default": true, "description": "MPP search for local reliability based on QMEA multi-point approximation in u-space", "title": "X Multi Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_QMEA_X" } ] } }, "title": "XMultiPoint", "type": "object" }, "XTaylorMean": { "additionalProperties": false, "description": "Form Taylor series approximation in \\\"x-space\\\" at variable means", "properties": { "x_taylor_mean": { "const": true, "default": true, "description": "Form Taylor series approximation in \"x-space\" at variable means", "title": "X Taylor Mean", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_X" } ] } }, "title": "XTaylorMean", "type": "object" }, "XTaylorMpp": { "additionalProperties": false, "description": "X-space Taylor series approximation with iterative updates", "properties": { "x_taylor_mpp": { "const": true, "default": true, "description": "X-space Taylor series approximation with iterative updates", "title": "X Taylor Mpp", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_PLUS_X" } ] } }, "title": "XTaylorMpp", "type": "object" }, "XTwoPoint": { "additionalProperties": false, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \\\"x-space\\\"", "properties": { "x_two_point": { "const": true, "default": true, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \"x-space\"", "title": "X Two Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_TANA_X" } ] } }, "title": "XTwoPoint", "type": "object" } }, "additionalProperties": false, "required": [ "local_reliability" ] }
- field local_reliability: LocalReliabilityConfig [Required]
- classmethod get_registry() dict[str, type[MethodSelection]]
Get registry, performing deferred registration on first call
- classmethod get_union()
Generate Union from all registered selections
- pydantic model dakota.spec.method.local_reliability.LocalReliabilityConfig
Local reliability method
Show JSON schema
{ "title": "LocalReliabilityConfig", "description": "Local reliability method", "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" } ] }, "final_moments": { "anyOf": [ { "$ref": "#/$defs/DefaultFinalMomentsNoneKeyword" }, { "$ref": "#/$defs/DefaultFinalMomentsStandard" }, { "$ref": "#/$defs/DefaultFinalMomentsCentral" } ], "description": "Output moments of the specified type and include them within the set of final statistics.", "title": "Final Moments", "x-model-default": "DefaultFinalMomentsStandard", "x-union-pattern": 1 }, "convergence_tolerance": { "default": -1.7976931348623157e+308, "description": "Stopping criterion based on objective function or statistics convergence", "title": "Convergence Tolerance", "type": "number", "x-materialization": [ { "ir_key": "method.convergence_tolerance", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" }, { "ir_key": "method.jega.percent_change", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "max_iterations": { "default": 9223372036854775807, "description": "Number of iterations allowed for optimizers and adaptive UQ methods", "minimum": 0, "title": "Max Iterations", "type": "integer", "x-materialization": [ { "ir_key": "method.max_iterations", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] }, "response_levels": { "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenResponseLevels" }, { "type": "null" } ], "argument": "values", "default": null, "description": "Values at which to estimate desired statistics for each response", "x-materialization": [ { "ir_key": "method.nond.response_levels", "ir_value_type": "RealVectorArray", "storage_type": "RESPONSE_LEVELS_ARRAY" } ] }, "reliability_levels": { "anyOf": [ { "$ref": "#/$defs/ReliabilityLevelsReliabilityLevels" }, { "type": "null" } ], "argument": "values", "default": null, "description": "Specify reliability levels at which the response values will be estimated", "x-materialization": [ { "ir_key": "method.nond.reliability_levels", "ir_value_type": "RealVectorArray", "storage_type": "RESPONSE_LEVELS_ARRAY" } ] }, "probability_levels": { "anyOf": [ { "$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": "#/$defs/DistributionCumulComplContext1Complementary" } ], "description": "Selection of cumulative or complementary cumulative functions", "title": "Distribution", "x-model-default": "DistributionCumulComplContext1Cumulative", "x-union-pattern": 1 }, "id_method": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Name the method block; helpful when there are multiple", "title": "Id Method", "x-materialization": [ { "ir_key": "method.id", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "output": { "anyOf": [ { "$ref": "#/$defs/Debug" }, { "$ref": "#/$defs/Verbose" }, { "$ref": "#/$defs/Normal" }, { "$ref": "#/$defs/Quiet" }, { "$ref": "#/$defs/Silent" } ], "description": "Control how much method information is written to the screen and output file", "title": "Output", "x-model-default": "Normal", "x-union-pattern": 1 }, "final_solutions": { "default": 0, "description": "Number of designs returned as the best solutions", "minimum": 0, "title": "Final Solutions", "type": "integer", "x-materialization": [ { "ir_key": "method.final_solutions", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] }, "mpp_search": { "anyOf": [ { "$ref": "#/$defs/MppSearch" }, { "type": "null" } ], "default": null, "description": "Specify which MPP search option to use" } }, "$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" }, "DefaultFinalMomentsCentral": { "additionalProperties": false, "description": "Output central moments and include them within the set of final statistics.", "properties": { "central": { "const": true, "default": true, "description": "Output central moments and include them within the set of final statistics.", "title": "Central", "type": "boolean", "x-materialization": [ { "enum_scope": "Pecos", "ir_key": "method.nond.final_moments", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "CENTRAL_MOMENTS" } ] } }, "title": "DefaultFinalMomentsCentral", "type": "object" }, "DefaultFinalMomentsNoneKeyword": { "additionalProperties": false, "description": "Omit moments from the set of final statistics.", "properties": { "none": { "const": true, "default": true, "description": "Omit moments from the set of final statistics.", "title": "None", "type": "boolean", "x-materialization": [ { "enum_scope": "Pecos", "ir_key": "method.nond.final_moments", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "NO_MOMENTS" } ] } }, "title": "DefaultFinalMomentsNoneKeyword", "type": "object" }, "DefaultFinalMomentsStandard": { "additionalProperties": false, "description": "Output standardized moments and include them within the set of final statistics.", "properties": { "standard": { "const": true, "default": true, "description": "Output standardized moments and include them within the set of final statistics.", "title": "Standard", "type": "boolean", "x-materialization": [ { "enum_scope": "Pecos", "ir_key": "method.nond.final_moments", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "STANDARD_MOMENTS" } ] } }, "title": "DefaultFinalMomentsStandard", "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" } ] }, "Integration": { "additionalProperties": false, "description": "Integration approach", "properties": { "order": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/IntegrationFirstOrder" }, { "$ref": "#/$defs/IntegrationSecondOrder" } ], "description": "Integration Order", "title": "Order", "x-union-pattern": 4 }, "probability_refinement": { "anyOf": [ { "$ref": "#/$defs/IntegrationProbabilityRefinement" }, { "type": "null" } ], "default": null, "description": "Allow refinement of probability and generalized reliability results using importance sampling", "x-aliases": [ "sample_refinement" ] } }, "required": [ "order" ], "title": "Integration", "type": "object" }, "IntegrationFirstOrder": { "additionalProperties": false, "description": "First-order integration scheme", "properties": { "first_order": { "const": true, "default": true, "description": "First-order integration scheme", "title": "First Order", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.reliability_integration", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "first_order" } ] } }, "title": "IntegrationFirstOrder", "type": "object" }, "IntegrationProbabilityRefinement": { "additionalProperties": false, "description": "Allow refinement of probability and generalized reliability results using importance sampling", "properties": { "approach": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/IntegrationProbabilityRefinementImportance" }, { "$ref": "#/$defs/IntegrationProbabilityRefinementAdaptImport" }, { "$ref": "#/$defs/IntegrationProbabilityRefinementMmAdaptImport" } ], "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" } ] }, "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" } ] } }, "required": [ "approach" ], "title": "IntegrationProbabilityRefinement", "type": "object" }, "IntegrationProbabilityRefinementAdaptImport": { "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": "IntegrationProbabilityRefinementAdaptImport", "type": "object" }, "IntegrationProbabilityRefinementImportance": { "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": "IntegrationProbabilityRefinementImportance", "type": "object" }, "IntegrationProbabilityRefinementMmAdaptImport": { "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": "IntegrationProbabilityRefinementMmAdaptImport", "type": "object" }, "IntegrationSecondOrder": { "additionalProperties": false, "description": "Second-order integration scheme", "properties": { "second_order": { "const": true, "default": true, "description": "Second-order integration scheme", "title": "Second Order", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.reliability_integration", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "second_order" } ] } }, "title": "IntegrationSecondOrder", "type": "object" }, "MethodGradientSubProblemSolverNip": { "additionalProperties": false, "description": "Use a nonlinear interior point method for solving an optimization sub-problem", "properties": { "nip": { "const": true, "default": true, "description": "Use a nonlinear interior point method for solving an optimization sub-problem", "title": "Nip", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.opt_subproblem_solver", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_OPTPP" } ] } }, "title": "MethodGradientSubProblemSolverNip", "type": "object" }, "MethodGradientSubProblemSolverSqp": { "additionalProperties": false, "description": "Use a sequential quadratic programming method for solving an optimization sub-problem", "properties": { "sqp": { "const": true, "default": true, "description": "Use a sequential quadratic programming method for solving an optimization sub-problem", "title": "Sqp", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.opt_subproblem_solver", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_NPSOL" } ] } }, "title": "MethodGradientSubProblemSolverSqp", "type": "object" }, "MppSearch": { "additionalProperties": false, "description": "Specify which MPP search option to use", "properties": { "optimization_solver": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/MethodGradientSubProblemSolverSqp" }, { "$ref": "#/$defs/MethodGradientSubProblemSolverNip" }, { "type": "null" } ], "default": null, "description": "Optimization Solver", "title": "Optimization Solver", "x-union-pattern": 2 }, "sub_method": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/XTaylorMean" }, { "$ref": "#/$defs/UTaylorMean" }, { "$ref": "#/$defs/XTaylorMpp" }, { "$ref": "#/$defs/UTaylorMpp" }, { "$ref": "#/$defs/XTwoPoint" }, { "$ref": "#/$defs/UTwoPoint" }, { "$ref": "#/$defs/XMultiPoint" }, { "$ref": "#/$defs/UMultiPoint" }, { "$ref": "#/$defs/NoApprox" } ], "description": "MPP Approximation", "title": "Sub Method", "x-union-pattern": 4 }, "integration": { "anyOf": [ { "$ref": "#/$defs/Integration" }, { "type": "null" } ], "default": null, "description": "Integration approach" } }, "required": [ "sub_method" ], "title": "MppSearch", "type": "object" }, "NoApprox": { "additionalProperties": false, "description": "Perform MPP search on original response functions (use no approximation)", "properties": { "no_approx": { "const": true, "default": true, "description": "Perform MPP search on original response functions (use no approximation)", "title": "No Approx", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_NO_APPROX" } ] } }, "title": "NoApprox", "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" }, "ReliabilityLevelsReliabilityLevels": { "additionalProperties": false, "description": "Specify reliability levels at which the response values will be estimated", "properties": { "values": { "description": "Specify reliability levels at which the response values will be estimated", "items": { "type": "number" }, "title": "Values", "type": "array" }, "num_reliability_levels": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Specify which ``reliability_levels`` correspond to which response", "title": "Num Reliability Levels" } }, "required": [ "values" ], "title": "ReliabilityLevelsReliabilityLevels", "type": "object", "x-model-validations": [ { "validationContext": "reliabilitylevelsreliabilitylevels", "validationErrorMessage": "For reliabilitylevelsreliabilitylevels, sum of num_reliability_levels must equal length of values.", "validationFields": [ "num_reliability_levels", "values" ], "validationLiterals": [], "validationRuleName": "check_sum_equals_length" } ] }, "ResponseLevelsComputeProbRelGenCompute": { "additionalProperties": false, "description": "Selection of statistics to compute at each response level", "properties": { "statistic": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenProbabilities" }, { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenReliabilities" }, { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenGenReliabilities" } ], "description": "Statistics to Compute", "title": "Statistic", "x-union-pattern": 4 }, "system": { "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenSystemSeries" }, { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenSystemParallel" }, { "type": "null" } ], "default": null, "description": "Compute system reliability (series or parallel)", "title": "System", "x-union-pattern": 2 } }, "required": [ "statistic" ], "title": "ResponseLevelsComputeProbRelGenCompute", "type": "object" }, "ResponseLevelsComputeProbRelGenGenReliabilities": { "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": "ResponseLevelsComputeProbRelGenGenReliabilities", "type": "object" }, "ResponseLevelsComputeProbRelGenProbabilities": { "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": "ResponseLevelsComputeProbRelGenProbabilities", "type": "object" }, "ResponseLevelsComputeProbRelGenReliabilities": { "additionalProperties": false, "description": "Computes reliabilities associated with response levels", "properties": { "reliabilities": { "const": true, "default": true, "description": "Computes reliabilities associated with response levels", "title": "Reliabilities", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.response_level_target", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "RELIABILITIES" } ] } }, "title": "ResponseLevelsComputeProbRelGenReliabilities", "type": "object" }, "ResponseLevelsComputeProbRelGenResponseLevels": { "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/ResponseLevelsComputeProbRelGenCompute" }, { "type": "null" } ], "default": null, "description": "Selection of statistics to compute at each response level" } }, "required": [ "values" ], "title": "ResponseLevelsComputeProbRelGenResponseLevels", "type": "object", "x-model-validations": [ { "validationContext": "responselevelscomputeprobrelgenresponselevels", "validationErrorMessage": "For responselevelscomputeprobrelgenresponselevels, sum of num_response_levels must equal length of values.", "validationFields": [ "num_response_levels", "values" ], "validationLiterals": [], "validationRuleName": "check_sum_equals_length" } ] }, "ResponseLevelsComputeProbRelGenSystemParallel": { "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": "ResponseLevelsComputeProbRelGenSystemParallel", "type": "object" }, "ResponseLevelsComputeProbRelGenSystemSeries": { "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": "ResponseLevelsComputeProbRelGenSystemSeries", "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" }, "UMultiPoint": { "additionalProperties": false, "description": "MPP search for local reliability based on QMEA multi-point approximation in x-space", "properties": { "u_multi_point": { "const": true, "default": true, "description": "MPP search for local reliability based on QMEA multi-point approximation in x-space", "title": "U Multi Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_QMEA_U" } ] } }, "title": "UMultiPoint", "type": "object" }, "UTaylorMean": { "additionalProperties": false, "description": "Form Taylor series approximation in \\\"u-space\\\" at variable means", "properties": { "u_taylor_mean": { "const": true, "default": true, "description": "Form Taylor series approximation in \"u-space\" at variable means", "title": "U Taylor Mean", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_U" } ] } }, "title": "UTaylorMean", "type": "object" }, "UTaylorMpp": { "additionalProperties": false, "description": "U-space Taylor series approximation with iterative updates", "properties": { "u_taylor_mpp": { "const": true, "default": true, "description": "U-space Taylor series approximation with iterative updates", "title": "U Taylor Mpp", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_PLUS_U" } ] } }, "title": "UTaylorMpp", "type": "object" }, "UTwoPoint": { "additionalProperties": false, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \\\"u-space\\\"", "properties": { "u_two_point": { "const": true, "default": true, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \"u-space\"", "title": "U Two Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_TANA_U" } ] } }, "title": "UTwoPoint", "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" }, "XMultiPoint": { "additionalProperties": false, "description": "MPP search for local reliability based on QMEA multi-point approximation in u-space", "properties": { "x_multi_point": { "const": true, "default": true, "description": "MPP search for local reliability based on QMEA multi-point approximation in u-space", "title": "X Multi Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_QMEA_X" } ] } }, "title": "XMultiPoint", "type": "object" }, "XTaylorMean": { "additionalProperties": false, "description": "Form Taylor series approximation in \\\"x-space\\\" at variable means", "properties": { "x_taylor_mean": { "const": true, "default": true, "description": "Form Taylor series approximation in \"x-space\" at variable means", "title": "X Taylor Mean", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_X" } ] } }, "title": "XTaylorMean", "type": "object" }, "XTaylorMpp": { "additionalProperties": false, "description": "X-space Taylor series approximation with iterative updates", "properties": { "x_taylor_mpp": { "const": true, "default": true, "description": "X-space Taylor series approximation with iterative updates", "title": "X Taylor Mpp", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_PLUS_X" } ] } }, "title": "XTaylorMpp", "type": "object" }, "XTwoPoint": { "additionalProperties": false, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \\\"x-space\\\"", "properties": { "x_two_point": { "const": true, "default": true, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \"x-space\"", "title": "X Two Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_TANA_X" } ] } }, "title": "XTwoPoint", "type": "object" } }, "additionalProperties": false }
- Fields:
gen_reliability_levels (dakota.spec.shared.misc.GenReliabilityLevelsGenReliabilityLevels | None)mpp_search (dakota.spec.method.local_reliability.MppSearch | None)probability_levels (dakota.spec.shared.misc.ProbabilityLevelsContext2ProbabilityLevels | None)reliability_levels (dakota.spec.shared.misc.ReliabilityLevelsReliabilityLevels | None)response_levels (dakota.spec.shared.core.ResponseLevelsComputeProbRelGenResponseLevels | None)
- 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_moments: DefaultFinalMomentsNoneKeyword | DefaultFinalMomentsStandard | DefaultFinalMomentsCentral [Optional]
Output moments of the specified type and include them within the set of final statistics.
- 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 reliability_levels: ReliabilityLevelsReliabilityLevels | None = None
Specify reliability levels at which the response values will be estimated
- field response_levels: ResponseLevelsComputeProbRelGenResponseLevels | None = None
Values at which to estimate desired statistics for each response
Generated Pydantic models for method.local_reliability
- pydantic model dakota.spec.method.local_reliability.Integration
Integration approach
Show JSON schema
{ "title": "Integration", "description": "Integration approach", "type": "object", "properties": { "order": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/IntegrationFirstOrder" }, { "$ref": "#/$defs/IntegrationSecondOrder" } ], "description": "Integration Order", "title": "Order", "x-union-pattern": 4 }, "probability_refinement": { "anyOf": [ { "$ref": "#/$defs/IntegrationProbabilityRefinement" }, { "type": "null" } ], "default": null, "description": "Allow refinement of probability and generalized reliability results using importance sampling", "x-aliases": [ "sample_refinement" ] } }, "$defs": { "IntegrationFirstOrder": { "additionalProperties": false, "description": "First-order integration scheme", "properties": { "first_order": { "const": true, "default": true, "description": "First-order integration scheme", "title": "First Order", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.reliability_integration", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "first_order" } ] } }, "title": "IntegrationFirstOrder", "type": "object" }, "IntegrationProbabilityRefinement": { "additionalProperties": false, "description": "Allow refinement of probability and generalized reliability results using importance sampling", "properties": { "approach": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/IntegrationProbabilityRefinementImportance" }, { "$ref": "#/$defs/IntegrationProbabilityRefinementAdaptImport" }, { "$ref": "#/$defs/IntegrationProbabilityRefinementMmAdaptImport" } ], "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" } ] }, "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" } ] } }, "required": [ "approach" ], "title": "IntegrationProbabilityRefinement", "type": "object" }, "IntegrationProbabilityRefinementAdaptImport": { "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": "IntegrationProbabilityRefinementAdaptImport", "type": "object" }, "IntegrationProbabilityRefinementImportance": { "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": "IntegrationProbabilityRefinementImportance", "type": "object" }, "IntegrationProbabilityRefinementMmAdaptImport": { "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": "IntegrationProbabilityRefinementMmAdaptImport", "type": "object" }, "IntegrationSecondOrder": { "additionalProperties": false, "description": "Second-order integration scheme", "properties": { "second_order": { "const": true, "default": true, "description": "Second-order integration scheme", "title": "Second Order", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.reliability_integration", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "second_order" } ] } }, "title": "IntegrationSecondOrder", "type": "object" } }, "additionalProperties": false, "required": [ "order" ] }
- Fields:
- field order: IntegrationFirstOrder | IntegrationSecondOrder [Required]
Integration Order
- field probability_refinement: IntegrationProbabilityRefinement | None = None
Allow refinement of probability and generalized reliability results using importance sampling
- pydantic model dakota.spec.method.local_reliability.IntegrationFirstOrder
First-order integration scheme
Show JSON schema
{ "title": "IntegrationFirstOrder", "description": "First-order integration scheme", "type": "object", "properties": { "first_order": { "const": true, "default": true, "description": "First-order integration scheme", "title": "First Order", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.reliability_integration", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "first_order" } ] } }, "additionalProperties": false }
- Fields:
- field first_order: Literal[True] = True
First-order integration scheme
- pydantic model dakota.spec.method.local_reliability.IntegrationProbabilityRefinement
Allow refinement of probability and generalized reliability results using importance sampling
Show JSON schema
{ "title": "IntegrationProbabilityRefinement", "description": "Allow refinement of probability and generalized reliability results using importance sampling", "type": "object", "properties": { "approach": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/IntegrationProbabilityRefinementImportance" }, { "$ref": "#/$defs/IntegrationProbabilityRefinementAdaptImport" }, { "$ref": "#/$defs/IntegrationProbabilityRefinementMmAdaptImport" } ], "description": "Importance Sampling Approach", "title": "Approach", "x-union-pattern": 4 }, "refinement_samples": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Number of samples used to refine a probability estimate or sampling design.", "title": "Refinement Samples", "x-materialization": [ { "ir_key": "method.nond.refinement_samples", "ir_value_type": "IntVector", "storage_type": "DIRECT_VALUE" } ] }, "seed": { "anyOf": [ { "exclusiveMinimum": 0, "type": "integer" }, { "type": "null" } ], "default": null, "description": "Seed of the random number generator", "title": "Seed", "x-materialization": [ { "ir_key": "method.random_seed", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] } }, "$defs": { "IntegrationProbabilityRefinementAdaptImport": { "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": "IntegrationProbabilityRefinementAdaptImport", "type": "object" }, "IntegrationProbabilityRefinementImportance": { "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": "IntegrationProbabilityRefinementImportance", "type": "object" }, "IntegrationProbabilityRefinementMmAdaptImport": { "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": "IntegrationProbabilityRefinementMmAdaptImport", "type": "object" } }, "additionalProperties": false, "required": [ "approach" ] }
- Fields:
- field approach: IntegrationProbabilityRefinementImportance | IntegrationProbabilityRefinementAdaptImport | IntegrationProbabilityRefinementMmAdaptImport [Required]
Importance Sampling Approach
- field refinement_samples: list[int] | None = None
Number of samples used to refine a probability estimate or sampling design.
- field seed: int | None = None
Seed of the random number generator
- Constraints:
gt = 0
- pydantic model dakota.spec.method.local_reliability.IntegrationProbabilityRefinementAdaptImport
Importance sampling option for probability refinement
Show JSON schema
{ "title": "IntegrationProbabilityRefinementAdaptImport", "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.local_reliability.IntegrationProbabilityRefinementImportance
Importance sampling option for probability refinement
Show JSON schema
{ "title": "IntegrationProbabilityRefinementImportance", "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.local_reliability.IntegrationProbabilityRefinementMmAdaptImport
Importance sampling option for probability refinement
Show JSON schema
{ "title": "IntegrationProbabilityRefinementMmAdaptImport", "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
- pydantic model dakota.spec.method.local_reliability.IntegrationSecondOrder
Second-order integration scheme
Show JSON schema
{ "title": "IntegrationSecondOrder", "description": "Second-order integration scheme", "type": "object", "properties": { "second_order": { "const": true, "default": true, "description": "Second-order integration scheme", "title": "Second Order", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.reliability_integration", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "second_order" } ] } }, "additionalProperties": false }
- Fields:
- field second_order: Literal[True] = True
Second-order integration scheme
- pydantic model dakota.spec.method.local_reliability.MppSearch
Specify which MPP search option to use
Show JSON schema
{ "title": "MppSearch", "description": "Specify which MPP search option to use", "type": "object", "properties": { "optimization_solver": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/MethodGradientSubProblemSolverSqp" }, { "$ref": "#/$defs/MethodGradientSubProblemSolverNip" }, { "type": "null" } ], "default": null, "description": "Optimization Solver", "title": "Optimization Solver", "x-union-pattern": 2 }, "sub_method": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/XTaylorMean" }, { "$ref": "#/$defs/UTaylorMean" }, { "$ref": "#/$defs/XTaylorMpp" }, { "$ref": "#/$defs/UTaylorMpp" }, { "$ref": "#/$defs/XTwoPoint" }, { "$ref": "#/$defs/UTwoPoint" }, { "$ref": "#/$defs/XMultiPoint" }, { "$ref": "#/$defs/UMultiPoint" }, { "$ref": "#/$defs/NoApprox" } ], "description": "MPP Approximation", "title": "Sub Method", "x-union-pattern": 4 }, "integration": { "anyOf": [ { "$ref": "#/$defs/Integration" }, { "type": "null" } ], "default": null, "description": "Integration approach" } }, "$defs": { "Integration": { "additionalProperties": false, "description": "Integration approach", "properties": { "order": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/IntegrationFirstOrder" }, { "$ref": "#/$defs/IntegrationSecondOrder" } ], "description": "Integration Order", "title": "Order", "x-union-pattern": 4 }, "probability_refinement": { "anyOf": [ { "$ref": "#/$defs/IntegrationProbabilityRefinement" }, { "type": "null" } ], "default": null, "description": "Allow refinement of probability and generalized reliability results using importance sampling", "x-aliases": [ "sample_refinement" ] } }, "required": [ "order" ], "title": "Integration", "type": "object" }, "IntegrationFirstOrder": { "additionalProperties": false, "description": "First-order integration scheme", "properties": { "first_order": { "const": true, "default": true, "description": "First-order integration scheme", "title": "First Order", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.reliability_integration", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "first_order" } ] } }, "title": "IntegrationFirstOrder", "type": "object" }, "IntegrationProbabilityRefinement": { "additionalProperties": false, "description": "Allow refinement of probability and generalized reliability results using importance sampling", "properties": { "approach": { "anchor": true, "anyOf": [ { "$ref": "#/$defs/IntegrationProbabilityRefinementImportance" }, { "$ref": "#/$defs/IntegrationProbabilityRefinementAdaptImport" }, { "$ref": "#/$defs/IntegrationProbabilityRefinementMmAdaptImport" } ], "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" } ] }, "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" } ] } }, "required": [ "approach" ], "title": "IntegrationProbabilityRefinement", "type": "object" }, "IntegrationProbabilityRefinementAdaptImport": { "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": "IntegrationProbabilityRefinementAdaptImport", "type": "object" }, "IntegrationProbabilityRefinementImportance": { "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": "IntegrationProbabilityRefinementImportance", "type": "object" }, "IntegrationProbabilityRefinementMmAdaptImport": { "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": "IntegrationProbabilityRefinementMmAdaptImport", "type": "object" }, "IntegrationSecondOrder": { "additionalProperties": false, "description": "Second-order integration scheme", "properties": { "second_order": { "const": true, "default": true, "description": "Second-order integration scheme", "title": "Second Order", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.reliability_integration", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "second_order" } ] } }, "title": "IntegrationSecondOrder", "type": "object" }, "MethodGradientSubProblemSolverNip": { "additionalProperties": false, "description": "Use a nonlinear interior point method for solving an optimization sub-problem", "properties": { "nip": { "const": true, "default": true, "description": "Use a nonlinear interior point method for solving an optimization sub-problem", "title": "Nip", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.opt_subproblem_solver", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_OPTPP" } ] } }, "title": "MethodGradientSubProblemSolverNip", "type": "object" }, "MethodGradientSubProblemSolverSqp": { "additionalProperties": false, "description": "Use a sequential quadratic programming method for solving an optimization sub-problem", "properties": { "sqp": { "const": true, "default": true, "description": "Use a sequential quadratic programming method for solving an optimization sub-problem", "title": "Sqp", "type": "boolean", "x-materialization": [ { "ir_key": "method.nond.opt_subproblem_solver", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_NPSOL" } ] } }, "title": "MethodGradientSubProblemSolverSqp", "type": "object" }, "NoApprox": { "additionalProperties": false, "description": "Perform MPP search on original response functions (use no approximation)", "properties": { "no_approx": { "const": true, "default": true, "description": "Perform MPP search on original response functions (use no approximation)", "title": "No Approx", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_NO_APPROX" } ] } }, "title": "NoApprox", "type": "object" }, "UMultiPoint": { "additionalProperties": false, "description": "MPP search for local reliability based on QMEA multi-point approximation in x-space", "properties": { "u_multi_point": { "const": true, "default": true, "description": "MPP search for local reliability based on QMEA multi-point approximation in x-space", "title": "U Multi Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_QMEA_U" } ] } }, "title": "UMultiPoint", "type": "object" }, "UTaylorMean": { "additionalProperties": false, "description": "Form Taylor series approximation in \\\"u-space\\\" at variable means", "properties": { "u_taylor_mean": { "const": true, "default": true, "description": "Form Taylor series approximation in \"u-space\" at variable means", "title": "U Taylor Mean", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_U" } ] } }, "title": "UTaylorMean", "type": "object" }, "UTaylorMpp": { "additionalProperties": false, "description": "U-space Taylor series approximation with iterative updates", "properties": { "u_taylor_mpp": { "const": true, "default": true, "description": "U-space Taylor series approximation with iterative updates", "title": "U Taylor Mpp", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_PLUS_U" } ] } }, "title": "UTaylorMpp", "type": "object" }, "UTwoPoint": { "additionalProperties": false, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \\\"u-space\\\"", "properties": { "u_two_point": { "const": true, "default": true, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \"u-space\"", "title": "U Two Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_TANA_U" } ] } }, "title": "UTwoPoint", "type": "object" }, "XMultiPoint": { "additionalProperties": false, "description": "MPP search for local reliability based on QMEA multi-point approximation in u-space", "properties": { "x_multi_point": { "const": true, "default": true, "description": "MPP search for local reliability based on QMEA multi-point approximation in u-space", "title": "X Multi Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_QMEA_X" } ] } }, "title": "XMultiPoint", "type": "object" }, "XTaylorMean": { "additionalProperties": false, "description": "Form Taylor series approximation in \\\"x-space\\\" at variable means", "properties": { "x_taylor_mean": { "const": true, "default": true, "description": "Form Taylor series approximation in \"x-space\" at variable means", "title": "X Taylor Mean", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_X" } ] } }, "title": "XTaylorMean", "type": "object" }, "XTaylorMpp": { "additionalProperties": false, "description": "X-space Taylor series approximation with iterative updates", "properties": { "x_taylor_mpp": { "const": true, "default": true, "description": "X-space Taylor series approximation with iterative updates", "title": "X Taylor Mpp", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_PLUS_X" } ] } }, "title": "XTaylorMpp", "type": "object" }, "XTwoPoint": { "additionalProperties": false, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \\\"x-space\\\"", "properties": { "x_two_point": { "const": true, "default": true, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \"x-space\"", "title": "X Two Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_TANA_X" } ] } }, "title": "XTwoPoint", "type": "object" } }, "additionalProperties": false, "required": [ "sub_method" ] }
- field integration: Integration | None = None
Integration approach
- field optimization_solver: MethodGradientSubProblemSolverSqp | MethodGradientSubProblemSolverNip | None = None
Optimization Solver
- field sub_method: XTaylorMean | UTaylorMean | XTaylorMpp | UTaylorMpp | XTwoPoint | UTwoPoint | XMultiPoint | UMultiPoint | NoApprox [Required]
MPP Approximation
- pydantic model dakota.spec.method.local_reliability.NoApprox
Perform MPP search on original response functions (use no approximation)
Show JSON schema
{ "title": "NoApprox", "description": "Perform MPP search on original response functions (use no approximation)", "type": "object", "properties": { "no_approx": { "const": true, "default": true, "description": "Perform MPP search on original response functions (use no approximation)", "title": "No Approx", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_NO_APPROX" } ] } }, "additionalProperties": false }
- Fields:
- field no_approx: Literal[True] = True
Perform MPP search on original response functions (use no approximation)
- pydantic model dakota.spec.method.local_reliability.UMultiPoint
MPP search for local reliability based on QMEA multi-point approximation in x-space
Show JSON schema
{ "title": "UMultiPoint", "description": "MPP search for local reliability based on QMEA multi-point approximation in x-space", "type": "object", "properties": { "u_multi_point": { "const": true, "default": true, "description": "MPP search for local reliability based on QMEA multi-point approximation in x-space", "title": "U Multi Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_QMEA_U" } ] } }, "additionalProperties": false }
- Fields:
- field u_multi_point: Literal[True] = True
MPP search for local reliability based on QMEA multi-point approximation in x-space
- pydantic model dakota.spec.method.local_reliability.UTaylorMean
Form Taylor series approximation in "u-space" at variable means
Show JSON schema
{ "title": "UTaylorMean", "description": "Form Taylor series approximation in \\\"u-space\\\" at variable means", "type": "object", "properties": { "u_taylor_mean": { "const": true, "default": true, "description": "Form Taylor series approximation in \"u-space\" at variable means", "title": "U Taylor Mean", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_U" } ] } }, "additionalProperties": false }
- Fields:
- field u_taylor_mean: Literal[True] = True
Form Taylor series approximation in “u-space” at variable means
- pydantic model dakota.spec.method.local_reliability.UTaylorMpp
U-space Taylor series approximation with iterative updates
Show JSON schema
{ "title": "UTaylorMpp", "description": "U-space Taylor series approximation with iterative updates", "type": "object", "properties": { "u_taylor_mpp": { "const": true, "default": true, "description": "U-space Taylor series approximation with iterative updates", "title": "U Taylor Mpp", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_PLUS_U" } ] } }, "additionalProperties": false }
- Fields:
- field u_taylor_mpp: Literal[True] = True
U-space Taylor series approximation with iterative updates
- pydantic model dakota.spec.method.local_reliability.UTwoPoint
Predict MPP using Two-point Adaptive Nonlinear Approximation in "u-space"
Show JSON schema
{ "title": "UTwoPoint", "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \\\"u-space\\\"", "type": "object", "properties": { "u_two_point": { "const": true, "default": true, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \"u-space\"", "title": "U Two Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_TANA_U" } ] } }, "additionalProperties": false }
- Fields:
- field u_two_point: Literal[True] = True
Predict MPP using Two-point Adaptive Nonlinear Approximation in “u-space”
- pydantic model dakota.spec.method.local_reliability.XMultiPoint
MPP search for local reliability based on QMEA multi-point approximation in u-space
Show JSON schema
{ "title": "XMultiPoint", "description": "MPP search for local reliability based on QMEA multi-point approximation in u-space", "type": "object", "properties": { "x_multi_point": { "const": true, "default": true, "description": "MPP search for local reliability based on QMEA multi-point approximation in u-space", "title": "X Multi Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_QMEA_X" } ] } }, "additionalProperties": false }
- Fields:
- field x_multi_point: Literal[True] = True
MPP search for local reliability based on QMEA multi-point approximation in u-space
- pydantic model dakota.spec.method.local_reliability.XTaylorMean
Form Taylor series approximation in "x-space" at variable means
Show JSON schema
{ "title": "XTaylorMean", "description": "Form Taylor series approximation in \\\"x-space\\\" at variable means", "type": "object", "properties": { "x_taylor_mean": { "const": true, "default": true, "description": "Form Taylor series approximation in \"x-space\" at variable means", "title": "X Taylor Mean", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_X" } ] } }, "additionalProperties": false }
- Fields:
- field x_taylor_mean: Literal[True] = True
Form Taylor series approximation in “x-space” at variable means
- pydantic model dakota.spec.method.local_reliability.XTaylorMpp
X-space Taylor series approximation with iterative updates
Show JSON schema
{ "title": "XTaylorMpp", "description": "X-space Taylor series approximation with iterative updates", "type": "object", "properties": { "x_taylor_mpp": { "const": true, "default": true, "description": "X-space Taylor series approximation with iterative updates", "title": "X Taylor Mpp", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_AMV_PLUS_X" } ] } }, "additionalProperties": false }
- Fields:
- field x_taylor_mpp: Literal[True] = True
X-space Taylor series approximation with iterative updates
- pydantic model dakota.spec.method.local_reliability.XTwoPoint
Predict MPP using Two-point Adaptive Nonlinear Approximation in "x-space"
Show JSON schema
{ "title": "XTwoPoint", "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \\\"x-space\\\"", "type": "object", "properties": { "x_two_point": { "const": true, "default": true, "description": "Predict MPP using Two-point Adaptive Nonlinear Approximation in \"x-space\"", "title": "X Two Point", "type": "boolean", "x-materialization": [ { "ir_key": "method.sub_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_TANA_X" } ] } }, "additionalProperties": false }
- Fields:
- field x_two_point: Literal[True] = True
Predict MPP using Two-point Adaptive Nonlinear Approximation in “x-space”
