sampling
- pydantic model dakota.spec.method.sampling.SamplingSelection
Generated model for SamplingSelection
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{ "title": "SamplingSelection", "description": "Generated model for SamplingSelection", "type": "object", "properties": { "sampling": { "$ref": "#/$defs/SamplingConfig", "x-aliases": [ "nond_sampling" ], "x-materialization": [ { "ir_key": "method.algorithm", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "RANDOM_SAMPLING" } ] } }, "$defs": { "Binned": { "additionalProperties": false, "description": "Computes Sobol' main effects using a binned approach", "properties": { "binned": { "$ref": "#/$defs/BinnedConfig", "x-materialization": [ { "ir_key": "method.vbd_via_sampling_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "VBD_BINNED" } ] } }, "required": [ "binned" ], "title": "Binned", "type": "object" }, "BinnedConfig": { "additionalProperties": false, "description": "Computes Sobol' main effects using a binned approach", "properties": { "num_bins": { "default": -1, "description": "Number of bins used to compute the variance-based decomposition", "title": "Num Bins", "type": "integer", "x-materialization": [ { "ir_key": "method.vbd_via_sampling_num_bins", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] } }, "title": "BinnedConfig", "type": "object" }, "CandidateDesigns": { "additionalProperties": false, "description": "Number of candidate sampling designs from which to select the most D-optimal", "properties": { "candidate_designs": { "description": "Number of candidate sampling designs from which to select the most D-optimal", "exclusiveMinimum": 0, "title": "Candidate Designs", "type": "integer", "x-materialization": [ { "ir_key": "method.num_candidate_designs", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "candidate_designs" ], "title": "CandidateDesigns", "type": "object" }, "CoolsKuoNuyens": { "additionalProperties": false, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 250 dimensions", "properties": { "cools_kuo_nuyens": { "const": true, "default": true, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 250 dimensions", "title": "Cools Kuo Nuyens", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.generating_vector_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "GEN_VECTOR_COOLS_KUO_NUYENS" } ] } }, "title": "CoolsKuoNuyens", "type": "object" }, "Debug": { "additionalProperties": false, "description": "Level 5 of 5 - maximum", "properties": { "debug": { "const": true, "default": true, "description": "Level 5 of 5 - maximum", "title": "Debug", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "DEBUG_OUTPUT" } ] } }, "title": "Debug", "type": "object" }, "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" }, "DigitalNet": { "additionalProperties": false, "description": "Uses digital net points to sample variables", "properties": { "no_digital_shift": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Do not shift this digital net", "title": "No Digital Shift", "x-materialization": [ { "ir_key": "method.no_digital_shift", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "no_scrambling": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Do not scramble this digital net", "title": "No Scrambling", "x-materialization": [ { "ir_key": "method.no_scrambling", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "integer_format": { "anyOf": [ { "$ref": "#/$defs/MostSignificantBitFirst" }, { "$ref": "#/$defs/LeastSignificantBitFirst" }, { "type": "null" } ], "default": null, "description": "Specify format of integers in the generating matrices", "title": "Integer Format", "x-union-pattern": 2 }, "m_max": { "default": 0, "description": "log2 of the maximum number of points in the digital net", "minimum": 0, "title": "M Max", "type": "integer", "x-materialization": [ { "ir_key": "method.m_max", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "t_max": { "default": 0, "description": "Bit depth of the generating matrices", "minimum": 0, "title": "T Max", "type": "integer", "x-materialization": [ { "ir_key": "method.t_max", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "t_scramble": { "default": 64, "description": "Number of rows in the affine scramble matrices", "minimum": 0, "title": "T Scramble", "type": "integer", "x-materialization": [ { "ir_key": "method.t_scramble", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "generating_matrices": { "anyOf": [ { "$ref": "#/$defs/GeneratingMatricesInline" }, { "$ref": "#/$defs/GeneratingMatricesFile" }, { "$ref": "#/$defs/GeneratingMatricesPredefined" }, { "type": "null" } ], "default": null, "description": "Specify the generating matrices of this digital net", "title": "Generating Matrices", "x-union-pattern": 2 }, "ordering": { "anyOf": [ { "$ref": "#/$defs/DigitalNetOptionsOrderingNatural" }, { "$ref": "#/$defs/GrayCode" }, { "type": "null" } ], "default": null, "description": "Ordering of the points of this digital net", "title": "Ordering", "x-union-pattern": 2 } }, "title": "DigitalNet", "type": "object" }, "DigitalNetOptionsOrderingNatural": { "additionalProperties": false, "description": "Natural ordering of the points of this digital net", "properties": { "natural": { "const": true, "default": true, "description": "Natural ordering of the points of this digital net", "title": "Natural", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "DIGITAL_NET_NATURAL_ORDERING" } ] } }, "title": "DigitalNetOptionsOrderingNatural", "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" } ] }, "GeneratingMatricesFile": { "additionalProperties": false, "description": "Specify generating matrices read from file", "properties": { "file": { "description": "Specify generating matrices read from file", "title": "File", "type": "string", "x-materialization": [ { "ir_key": "method.generating_matrices.file", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "file" ], "title": "GeneratingMatricesFile", "type": "object" }, "GeneratingMatricesInline": { "additionalProperties": false, "description": "Specify inline generating matrices", "properties": { "inline": { "description": "Specify inline generating matrices", "items": { "type": "integer" }, "title": "Inline", "type": "array", "x-materialization": [ { "ir_key": "method.generating_matrices.inline", "ir_value_type": "IntVector", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "inline" ], "title": "GeneratingMatricesInline", "type": "object" }, "GeneratingMatricesPredefined": { "additionalProperties": false, "description": "Specify predefined generating matrices", "properties": { "predefined": { "anyOf": [ { "$ref": "#/$defs/JoeKuo" }, { "$ref": "#/$defs/SobolOrder2" } ], "description": "Specify predefined generating matrices", "title": "Predefined" } }, "required": [ "predefined" ], "title": "GeneratingMatricesPredefined", "type": "object" }, "GeneratingVectorFile": { "additionalProperties": false, "description": "Specify a generating vector read from file", "properties": { "file": { "description": "Specify a generating vector read from file", "title": "File", "type": "string", "x-materialization": [ { "ir_key": "method.generating_vector.file", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "file" ], "title": "GeneratingVectorFile", "type": "object" }, "GeneratingVectorInline": { "additionalProperties": false, "description": "Specify an inline generating vector", "properties": { "inline": { "description": "Specify an inline generating vector", "items": { "type": "integer" }, "title": "Inline", "type": "array", "x-materialization": [ { "ir_key": "method.generating_vector.inline", "ir_value_type": "IntVector", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "inline" ], "title": "GeneratingVectorInline", "type": "object" }, "GeneratingVectorPredefined": { "additionalProperties": false, "description": "Specify a predefined generating vector", "properties": { "predefined": { "anyOf": [ { "$ref": "#/$defs/Kuo" }, { "$ref": "#/$defs/CoolsKuoNuyens" } ], "description": "Specify a predefined generating vector", "title": "Predefined" } }, "required": [ "predefined" ], "title": "GeneratingVectorPredefined", "type": "object" }, "GrayCode": { "additionalProperties": false, "description": "Gray code ordering of the points of this digital net", "properties": { "gray_code": { "const": true, "default": true, "description": "Gray code ordering of the points of this digital net", "title": "Gray Code", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "DIGITAL_NET_GRAY_CODE_ORDERING" } ] } }, "title": "GrayCode", "type": "object" }, "IncrementalLhs": { "additionalProperties": false, "description": "(Deprecated keyword) Augments an existing Latin Hypercube Sampling (LHS) study", "properties": { "incremental_lhs": { "const": true, "default": true, "description": "(Deprecated keyword) Augments an existing Latin Hypercube Sampling (LHS) study", "title": "Incremental Lhs", "type": "boolean", "x-materialization": [ { "ir_key": "method.sample_type", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_LHS" } ] } }, "title": "IncrementalLhs", "type": "object" }, "IncrementalRandom": { "additionalProperties": false, "description": "(Deprecated keyword) Augments an existing random sampling study", "properties": { "incremental_random": { "const": true, "default": true, "description": "(Deprecated keyword) Augments an existing random sampling study", "title": "Incremental Random", "type": "boolean", "x-materialization": [ { "ir_key": "method.sample_type", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_RANDOM" } ] } }, "title": "IncrementalRandom", "type": "object" }, "JoeKuo": { "additionalProperties": false, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 250 dimensions", "properties": { "joe_kuo": { "const": true, "default": true, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 250 dimensions", "title": "Joe Kuo", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.generating_matrix_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "JOE_KUO" } ] } }, "title": "JoeKuo", "type": "object" }, "Kuo": { "additionalProperties": false, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 3600 dimensions", "properties": { "kuo": { "const": true, "default": true, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 3600 dimensions", "title": "Kuo", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.generating_vector_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "GEN_VECTOR_KUO" } ] } }, "title": "Kuo", "type": "object" }, "LeastSignificantBitFirst": { "additionalProperties": false, "description": "Assume integers are stored with least significant bit first", "properties": { "least_significant_bit_first": { "const": true, "default": true, "description": "Assume integers are stored with least significant bit first", "title": "Least Significant Bit First", "type": "boolean", "x-materialization": [ { "ir_key": "method.least_significant_bit_first", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] } }, "title": "LeastSignificantBitFirst", "type": "object" }, "LejaOversampleRatio": { "additionalProperties": false, "description": "Oversampling ratio for generating candidate point set", "properties": { "leja_oversample_ratio": { "description": "Oversampling ratio for generating candidate point set", "title": "Leja Oversample Ratio", "type": "number", "x-materialization": [ { "ir_key": "method.nond.collocation_ratio", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "leja_oversample_ratio" ], "title": "LejaOversampleRatio", "type": "object" }, "LowDiscrepancy": { "additionalProperties": false, "description": "Uses low-discrepancy points to sample variables", "properties": { "low_discrepancy": { "$ref": "#/$defs/LowDiscrepancyConfig", "x-aliases": [ "qmc" ], "x-materialization": [ { "ir_key": "method.sample_type", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_LOW_DISCREPANCY_SAMPLING" } ] } }, "required": [ "low_discrepancy" ], "title": "LowDiscrepancy", "type": "object" }, "LowDiscrepancyConfig": { "additionalProperties": false, "description": "Uses low-discrepancy points to sample variables", "properties": { "rank_1_lattice": { "anyOf": [ { "$ref": "#/$defs/Rank1Lattice" }, { "type": "null" } ], "default": null, "description": "Uses rank-1 lattice points to sample variables", "x-materialization": [ { "ir_key": "method.rank_1_lattice", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "digital_net": { "anyOf": [ { "$ref": "#/$defs/DigitalNet" }, { "type": "null" } ], "default": null, "description": "Uses digital net points to sample variables", "x-aliases": [ "sobol_sequence" ], "x-materialization": [ { "ir_key": "method.digital_net", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] } }, "title": "LowDiscrepancyConfig", "type": "object" }, "MostSignificantBitFirst": { "additionalProperties": false, "description": "Assume integers are stored with most significant bit first", "properties": { "most_significant_bit_first": { "const": true, "default": true, "description": "Assume integers are stored with most significant bit first", "title": "Most Significant Bit First", "type": "boolean", "x-materialization": [ { "ir_key": "method.most_significant_bit_first", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] } }, "title": "MostSignificantBitFirst", "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" }, "PickAndFreeze": { "additionalProperties": false, "description": "Use the pick-and-freeze variance-based decomposition method", "properties": { "pick_and_freeze": { "const": true, "default": true, "description": "Use the pick-and-freeze variance-based decomposition method", "title": "Pick And Freeze", "type": "boolean", "x-materialization": [ { "ir_key": "method.vbd_via_sampling_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "VBD_PICK_AND_FREEZE" } ] } }, "title": "PickAndFreeze", "type": "object" }, "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" }, "RadicalInverse": { "additionalProperties": false, "description": "Radical inverse ordering of the points of this rank-1 lattice", "properties": { "radical_inverse": { "const": true, "default": true, "description": "Radical inverse ordering of the points of this rank-1 lattice", "title": "Radical Inverse", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "RANK_1_LATTICE_RADICAL_INVERSE_ORDERING" } ] } }, "title": "RadicalInverse", "type": "object" }, "Rank1Lattice": { "additionalProperties": false, "description": "Uses rank-1 lattice points to sample variables", "properties": { "no_random_shift": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Do not shift this rank-1 lattice", "title": "No Random Shift", "x-materialization": [ { "ir_key": "method.no_random_shift", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "m_max": { "default": 0, "description": "log2 of the maximum number of points in the lattice", "minimum": 0, "title": "M Max", "type": "integer", "x-materialization": [ { "ir_key": "method.m_max", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "generating_vector": { "anyOf": [ { "$ref": "#/$defs/GeneratingVectorInline" }, { "$ref": "#/$defs/GeneratingVectorFile" }, { "$ref": "#/$defs/GeneratingVectorPredefined" }, { "type": "null" } ], "default": null, "description": "Specify the generating vector of this rank-1 lattice rule", "title": "Generating Vector", "x-union-pattern": 2 }, "ordering": { "anyOf": [ { "$ref": "#/$defs/Rank1LatticeOptionsOrderingNatural" }, { "$ref": "#/$defs/RadicalInverse" }, { "type": "null" } ], "default": null, "description": "Ordering of the points of this rank-1 lattice", "title": "Ordering", "x-union-pattern": 2 } }, "title": "Rank1Lattice", "type": "object" }, "Rank1LatticeOptionsOrderingNatural": { "additionalProperties": false, "description": "Natural ordering of the points of this rank-1 lattice", "properties": { "natural": { "const": true, "default": true, "description": "Natural ordering of the points of this rank-1 lattice", "title": "Natural", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "RANK_1_LATTICE_NATURAL_ORDERING" } ] } }, "title": "Rank1LatticeOptionsOrderingNatural", "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" }, "RngOptionsContext2Mt19937": { "additionalProperties": false, "description": "Generates random numbers using the Mersenne twister", "properties": { "mt19937": { "const": true, "default": true, "description": "Generates random numbers using the Mersenne twister", "title": "Mt19937", "type": "boolean", "x-materialization": [ { "ir_key": "method.random_number_generator", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "mt19937" } ] } }, "title": "RngOptionsContext2Mt19937", "type": "object" }, "RngOptionsContext2Rnum2": { "additionalProperties": false, "description": "Generates pseudo-random numbers using the Pecos package", "properties": { "rnum2": { "const": true, "default": true, "description": "Generates pseudo-random numbers using the Pecos package", "title": "Rnum2", "type": "boolean", "x-materialization": [ { "ir_key": "method.random_number_generator", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "rnum2" } ] } }, "title": "RngOptionsContext2Rnum2", "type": "object" }, "SamplingConfig": { "additionalProperties": false, "description": "Randomly samples variables according to their distributions", "properties": { "model_pointer": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Identifier for model block to be used by a method", "title": "Model Pointer", "x-block-pointer": "model", "x-materialization": [ { "ir_key": "method.model_pointer", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "rng": { "anyOf": [ { "$ref": "#/$defs/RngOptionsContext2Mt19937" }, { "$ref": "#/$defs/RngOptionsContext2Rnum2" } ], "description": "Selection of a random number generator", "title": "Rng", "x-model-default": "RngOptionsContext2Mt19937", "x-union-pattern": 1 }, "response_levels": { "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenResponseLevels" }, { "type": "null" } ], "argument": "values", "default": null, "description": "Values at which to estimate desired statistics for each response", "x-materialization": [ { "ir_key": "method.nond.response_levels", "ir_value_type": "RealVectorArray", "storage_type": "RESPONSE_LEVELS_ARRAY" } ] }, "reliability_levels": { "anyOf": [ { "$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": "#/$defs/DistributionCumulComplContext1Complementary" } ], "description": "Selection of cumulative or complementary cumulative functions", "title": "Distribution", "x-model-default": "DistributionCumulComplContext1Cumulative", "x-union-pattern": 1 }, "final_moments": { "anyOf": [ { "$ref": "#/$defs/DefaultFinalMomentsNoneKeyword" }, { "$ref": "#/$defs/DefaultFinalMomentsStandard" }, { "$ref": "#/$defs/DefaultFinalMomentsCentral" } ], "description": "Output moments of the specified type and include them within the set of final statistics.", "title": "Final Moments", "x-model-default": "DefaultFinalMomentsStandard", "x-union-pattern": 1 }, "variance_based_decomp": { "anyOf": [ { "$ref": "#/$defs/VbdSamplingVarianceBasedDecomp" }, { "type": "null" } ], "default": null, "description": "Activates global sensitivity analysis based on decomposition of response variance into contributions from variables", "x-materialization": [ { "ir_key": "method.variance_based_decomp", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "seed": { "anyOf": [ { "exclusiveMinimum": 0, "type": "integer" }, { "type": "null" } ], "default": null, "description": "Seed of the random number generator", "title": "Seed", "x-materialization": [ { "ir_key": "method.random_seed", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "fixed_seed": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Reuses the same seed value for multiple random sampling sets", "title": "Fixed Seed", "x-materialization": [ { "ir_key": "method.fixed_seed", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "id_method": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Name the method block; helpful when there are multiple", "title": "Id Method", "x-materialization": [ { "ir_key": "method.id", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "output": { "anyOf": [ { "$ref": "#/$defs/Debug" }, { "$ref": "#/$defs/Verbose" }, { "$ref": "#/$defs/Normal" }, { "$ref": "#/$defs/Quiet" }, { "$ref": "#/$defs/Silent" } ], "description": "Control how much method information is written to the screen and output file", "title": "Output", "x-model-default": "Normal", "x-union-pattern": 1 }, "final_solutions": { "default": 0, "description": "Number of designs returned as the best solutions", "minimum": 0, "title": "Final Solutions", "type": "integer", "x-materialization": [ { "ir_key": "method.final_solutions", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] }, "samples": { "default": 0, "description": "Number of samples for sampling-based methods", "title": "Samples", "type": "integer", "x-aliases": [ "initial_samples" ], "x-materialization": [ { "ir_key": "method.samples", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "sample_type": { "anyOf": [ { "$ref": "#/$defs/SamplingSampleTypeLhs" }, { "$ref": "#/$defs/SamplingSampleTypeRandom" }, { "$ref": "#/$defs/IncrementalLhs" }, { "$ref": "#/$defs/IncrementalRandom" }, { "$ref": "#/$defs/LowDiscrepancy" }, { "type": "null" } ], "default": null, "description": "Selection of sampling strategy", "title": "Sample Type", "x-union-pattern": 2 }, "refinement_samples": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "description": "Performs an incremental Latin Hypercube Sampling (LHS) study", "title": "Refinement Samples", "x-materialization": [ { "ir_key": "method.nond.refinement_samples", "ir_value_type": "IntVector", "storage_type": "DIRECT_VALUE" } ] }, "d_optimal": { "anyOf": [ { "$ref": "#/$defs/CandidateDesigns" }, { "$ref": "#/$defs/LejaOversampleRatio" }, { "additionalProperties": true, "type": "object" }, { "type": "null" } ], "default": null, "description": "Generate a D-optimal sampling design", "title": "D Optimal", "x-materialization": [ { "ir_key": "method.nond.d_optimal", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ], "x-union-pattern": 5 }, "backfill": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Ensures that the samples of discrete variables with finite support are unique", "title": "Backfill", "x-materialization": [ { "ir_key": "method.backfill", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "principal_components": { "anyOf": [ { "$ref": "#/$defs/SamplingPrincipalComponents" }, { "type": "null" } ], "default": null, "description": "Activates principal components analysis of the response matrix of N samples * L responses.", "x-materialization": [ { "ir_key": "method.principal_components", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "wilks": { "anyOf": [ { "$ref": "#/$defs/Wilks" }, { "type": "null" } ], "default": null, "description": "Number of samples for random sampling using Wilks statistics", "x-materialization": [ { "ir_key": "method.wilks", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "std_regression_coeffs": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Output Standardized Regression Coefficients and R^2 for samples", "title": "Std Regression Coeffs", "x-materialization": [ { "ir_key": "method.std_regression_coeffs", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "tolerance_intervals": { "anyOf": [ { "$ref": "#/$defs/SamplingTolIntervals" }, { "type": "null" } ], "default": null, "description": "Computes the double sided tolerance interval equivalent normal distribuion.", "x-materialization": [ { "ir_key": "method.tolerance_intervals", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] } }, "title": "SamplingConfig", "type": "object" }, "SamplingPrincipalComponents": { "additionalProperties": false, "description": "Activates principal components analysis of the response matrix of N samples * L responses.", "properties": { "percent_variance_explained": { "default": 0.95, "description": "Specifies the number of components to retain to explain the specified percent variance.", "title": "Percent Variance Explained", "type": "number", "x-materialization": [ { "ir_key": "method.percent_variance_explained", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] } }, "title": "SamplingPrincipalComponents", "type": "object" }, "SamplingSampleTypeLhs": { "additionalProperties": false, "description": "Uses Latin Hypercube Sampling (LHS) to sample variables", "properties": { "lhs": { "const": true, "default": true, "description": "Uses Latin Hypercube Sampling (LHS) to sample variables", "title": "Lhs", "type": "boolean", "x-materialization": [ { "ir_key": "method.sample_type", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_LHS" } ] } }, "title": "SamplingSampleTypeLhs", "type": "object" }, "SamplingSampleTypeRandom": { "additionalProperties": false, "description": "Uses purely random Monte Carlo sampling to sample variables", "properties": { "random": { "const": true, "default": true, "description": "Uses purely random Monte Carlo sampling to sample variables", "title": "Random", "type": "boolean", "x-materialization": [ { "ir_key": "method.sample_type", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_RANDOM" } ] } }, "title": "SamplingSampleTypeRandom", "type": "object" }, "SamplingTolIntervals": { "additionalProperties": false, "description": "Computes the double sided tolerance interval equivalent normal distribuion.", "properties": { "coverage": { "default": 0.95, "description": "The coverage to be used for the calculation of the lower and upper ends of the interval covering the user supplied samples.", "maximum": 1, "minimum": 0, "title": "Coverage", "type": "number", "x-materialization": [ { "ir_key": "method.ti_coverage", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "confidence_level": { "default": 0.9, "description": "The confidence level to be used to determine the standard deviation of the equivalent normal distribution.", "maximum": 1, "minimum": 0, "title": "Confidence Level", "type": "number", "x-materialization": [ { "ir_key": "method.ti_confidence_level", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] } }, "title": "SamplingTolIntervals", "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" }, "SobolOrder2": { "additionalProperties": false, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 1024 dimensions", "properties": { "sobol_order_2": { "const": true, "default": true, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 1024 dimensions", "title": "Sobol Order 2", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.generating_matrix_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SOBOL_ORDER_2" } ] } }, "title": "SobolOrder2", "type": "object" }, "VbdSamplingVarianceBasedDecomp": { "additionalProperties": false, "description": "Activates global sensitivity analysis based on decomposition of response variance into contributions from variables", "properties": { "drop_tolerance": { "default": -1.0, "description": "Suppresses output of sensitivity indices with values lower than this tolerance", "title": "Drop Tolerance", "type": "number", "x-materialization": [ { "ir_key": "method.vbd_drop_tolerance", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "vbd_sampling_method": { "anyOf": [ { "$ref": "#/$defs/Binned" }, { "$ref": "#/$defs/PickAndFreeze" }, { "type": "null" } ], "default": null, "description": "The method to use for variance-based decomposition", "title": "Vbd Sampling Method", "x-union-pattern": 2 } }, "title": "VbdSamplingVarianceBasedDecomp", "type": "object" }, "Verbose": { "additionalProperties": false, "description": "Level 4 of 5 - more than normal", "properties": { "verbose": { "const": true, "default": true, "description": "Level 4 of 5 - more than normal", "title": "Verbose", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "VERBOSE_OUTPUT" } ] } }, "title": "Verbose", "type": "object" }, "Wilks": { "additionalProperties": false, "description": "Number of samples for random sampling using Wilks statistics", "properties": { "order": { "default": 1, "description": "The order of the statistics to use when determining sample sizes for random sampling using Wilks order statistics.", "title": "Order", "type": "integer", "x-materialization": [ { "ir_key": "method.order", "ir_value_type": "unsigned short", "storage_type": "DIRECT_VALUE" } ] }, "confidence_level": { "default": 0.95, "description": "The confidence level to be used when determining sample sizes for random sampling using Wilks order statistics.", "title": "Confidence Level", "type": "number", "x-materialization": [ { "ir_key": "method.confidence_level", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "one_sided_lower": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Specifies one-sided lower portion order statistics to be used when determining sample sizes for random sampling using Wilks order statistics.", "title": "One Sided Lower", "x-materialization": [ { "ir_key": "method.wilks.sided_interval", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ONE_SIDED_LOWER" } ] }, "one_sided_upper": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Specifies one-sided upper portion order statistics to be used when determining sample sizes for random sampling using Wilks order statistics.", "title": "One Sided Upper", "x-materialization": [ { "ir_key": "method.wilks.sided_interval", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ONE_SIDED_UPPER" } ] }, "two_sided": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Specifies two-sided order statistics (an interval) to be used when determining sample sizes for random sampling using Wilks order statistics.", "title": "Two Sided", "x-materialization": [ { "ir_key": "method.wilks.sided_interval", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "TWO_SIDED" } ] } }, "title": "Wilks", "type": "object" } }, "additionalProperties": false, "required": [ "sampling" ] }
- field sampling: SamplingConfig [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.sampling.SamplingConfig
Randomly samples variables according to their distributions
Show JSON schema
{ "title": "SamplingConfig", "description": "Randomly samples variables according to their distributions", "type": "object", "properties": { "model_pointer": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Identifier for model block to be used by a method", "title": "Model Pointer", "x-block-pointer": "model", "x-materialization": [ { "ir_key": "method.model_pointer", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "rng": { "anyOf": [ { "$ref": "#/$defs/RngOptionsContext2Mt19937" }, { "$ref": "#/$defs/RngOptionsContext2Rnum2" } ], "description": "Selection of a random number generator", "title": "Rng", "x-model-default": "RngOptionsContext2Mt19937", "x-union-pattern": 1 }, "response_levels": { "anyOf": [ { "$ref": "#/$defs/ResponseLevelsComputeProbRelGenResponseLevels" }, { "type": "null" } ], "argument": "values", "default": null, "description": "Values at which to estimate desired statistics for each response", "x-materialization": [ { "ir_key": "method.nond.response_levels", "ir_value_type": "RealVectorArray", "storage_type": "RESPONSE_LEVELS_ARRAY" } ] }, "reliability_levels": { "anyOf": [ { "$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": "#/$defs/DistributionCumulComplContext1Complementary" } ], "description": "Selection of cumulative or complementary cumulative functions", "title": "Distribution", "x-model-default": "DistributionCumulComplContext1Cumulative", "x-union-pattern": 1 }, "final_moments": { "anyOf": [ { "$ref": "#/$defs/DefaultFinalMomentsNoneKeyword" }, { "$ref": "#/$defs/DefaultFinalMomentsStandard" }, { "$ref": "#/$defs/DefaultFinalMomentsCentral" } ], "description": "Output moments of the specified type and include them within the set of final statistics.", "title": "Final Moments", "x-model-default": "DefaultFinalMomentsStandard", "x-union-pattern": 1 }, "variance_based_decomp": { "anyOf": [ { "$ref": "#/$defs/VbdSamplingVarianceBasedDecomp" }, { "type": "null" } ], "default": null, "description": "Activates global sensitivity analysis based on decomposition of response variance into contributions from variables", "x-materialization": [ { "ir_key": "method.variance_based_decomp", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "seed": { "anyOf": [ { "exclusiveMinimum": 0, "type": "integer" }, { "type": "null" } ], "default": null, "description": "Seed of the random number generator", "title": "Seed", "x-materialization": [ { "ir_key": "method.random_seed", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "fixed_seed": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Reuses the same seed value for multiple random sampling sets", "title": "Fixed Seed", "x-materialization": [ { "ir_key": "method.fixed_seed", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "id_method": { "anyOf": [ { "type": "string" }, { "type": "null" } ], "default": null, "description": "Name the method block; helpful when there are multiple", "title": "Id Method", "x-materialization": [ { "ir_key": "method.id", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] }, "output": { "anyOf": [ { "$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": 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"x-materialization": [ { "ir_key": "method.vbd_via_sampling_method", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "VBD_PICK_AND_FREEZE" } ] } }, "title": "PickAndFreeze", "type": "object" }, "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" }, "RadicalInverse": { "additionalProperties": false, "description": "Radical inverse ordering of the points of this rank-1 lattice", "properties": { "radical_inverse": { "const": true, "default": true, "description": "Radical inverse ordering of the points of this rank-1 lattice", "title": "Radical Inverse", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "RANK_1_LATTICE_RADICAL_INVERSE_ORDERING" } ] } }, "title": "RadicalInverse", "type": "object" }, "Rank1Lattice": { "additionalProperties": false, "description": "Uses rank-1 lattice points to sample variables", "properties": { "no_random_shift": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Do not shift this rank-1 lattice", "title": "No Random Shift", "x-materialization": [ { "ir_key": "method.no_random_shift", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "m_max": { "default": 0, "description": "log2 of the maximum number of points in the lattice", "minimum": 0, "title": "M Max", "type": "integer", "x-materialization": [ { "ir_key": "method.m_max", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "generating_vector": { "anyOf": [ { "$ref": "#/$defs/GeneratingVectorInline" }, { "$ref": "#/$defs/GeneratingVectorFile" }, { "$ref": "#/$defs/GeneratingVectorPredefined" }, { "type": "null" } ], "default": null, "description": "Specify the generating vector of this rank-1 lattice rule", "title": "Generating Vector", "x-union-pattern": 2 }, "ordering": { "anyOf": [ { "$ref": "#/$defs/Rank1LatticeOptionsOrderingNatural" }, { "$ref": "#/$defs/RadicalInverse" }, { "type": "null" } ], "default": null, "description": "Ordering of the points of this rank-1 lattice", "title": "Ordering", "x-union-pattern": 2 } }, "title": "Rank1Lattice", "type": "object" }, "Rank1LatticeOptionsOrderingNatural": { "additionalProperties": false, "description": "Natural ordering of the points of this rank-1 lattice", "properties": { "natural": { "const": true, "default": true, "description": "Natural ordering of the points of this rank-1 lattice", "title": "Natural", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "RANK_1_LATTICE_NATURAL_ORDERING" } ] } }, "title": "Rank1LatticeOptionsOrderingNatural", "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" }, "RngOptionsContext2Mt19937": { "additionalProperties": false, "description": "Generates random numbers using the Mersenne twister", "properties": { "mt19937": { "const": true, "default": true, "description": "Generates random numbers using the Mersenne twister", "title": "Mt19937", "type": "boolean", "x-materialization": [ { "ir_key": "method.random_number_generator", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "mt19937" } ] } }, "title": "RngOptionsContext2Mt19937", "type": "object" }, "RngOptionsContext2Rnum2": { "additionalProperties": false, "description": "Generates pseudo-random numbers using the Pecos package", "properties": { "rnum2": { "const": true, "default": true, "description": "Generates pseudo-random numbers using the Pecos package", "title": "Rnum2", "type": "boolean", "x-materialization": [ { "ir_key": "method.random_number_generator", "ir_value_type": "String", "storage_type": "PRESENCE_LITERAL", "stored_value": "rnum2" } ] } }, "title": "RngOptionsContext2Rnum2", "type": "object" }, "SamplingPrincipalComponents": { "additionalProperties": false, "description": "Activates principal components analysis of the response matrix of N samples * L responses.", "properties": { "percent_variance_explained": { "default": 0.95, "description": "Specifies the number of components to retain to explain the specified percent variance.", "title": "Percent Variance Explained", "type": "number", "x-materialization": [ { "ir_key": "method.percent_variance_explained", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] } }, "title": "SamplingPrincipalComponents", "type": "object" }, "SamplingSampleTypeLhs": { "additionalProperties": false, "description": "Uses Latin Hypercube Sampling (LHS) to sample variables", "properties": { "lhs": { "const": true, "default": true, "description": "Uses Latin Hypercube Sampling (LHS) to sample variables", "title": "Lhs", "type": "boolean", "x-materialization": [ { "ir_key": "method.sample_type", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_LHS" } ] } }, "title": "SamplingSampleTypeLhs", "type": "object" }, "SamplingSampleTypeRandom": { "additionalProperties": false, "description": "Uses purely random Monte Carlo sampling to sample variables", "properties": { "random": { "const": true, "default": true, "description": "Uses purely random Monte Carlo sampling to sample variables", "title": "Random", "type": "boolean", "x-materialization": [ { "ir_key": "method.sample_type", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_RANDOM" } ] } }, "title": "SamplingSampleTypeRandom", "type": "object" }, "SamplingTolIntervals": { "additionalProperties": false, "description": "Computes the double sided tolerance interval equivalent normal distribuion.", "properties": { "coverage": { "default": 0.95, "description": "The coverage to be used for the calculation of the lower and upper ends of the interval covering the user supplied samples.", "maximum": 1, "minimum": 0, "title": "Coverage", "type": "number", "x-materialization": [ { "ir_key": "method.ti_coverage", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "confidence_level": { "default": 0.9, "description": "The confidence level to be used to determine the standard deviation of the equivalent normal distribution.", "maximum": 1, "minimum": 0, "title": "Confidence Level", "type": "number", "x-materialization": [ { "ir_key": "method.ti_confidence_level", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] } }, "title": "SamplingTolIntervals", "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" }, "SobolOrder2": { "additionalProperties": false, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 1024 dimensions", "properties": { "sobol_order_2": { "const": true, "default": true, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 1024 dimensions", "title": "Sobol Order 2", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.generating_matrix_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SOBOL_ORDER_2" } ] } }, "title": "SobolOrder2", "type": "object" }, "VbdSamplingVarianceBasedDecomp": { "additionalProperties": false, "description": "Activates global sensitivity analysis based on decomposition of response variance into contributions from variables", "properties": { "drop_tolerance": { "default": -1.0, "description": "Suppresses output of sensitivity indices with values lower than this tolerance", "title": "Drop Tolerance", "type": "number", "x-materialization": [ { "ir_key": "method.vbd_drop_tolerance", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "vbd_sampling_method": { "anyOf": [ { "$ref": "#/$defs/Binned" }, { "$ref": "#/$defs/PickAndFreeze" }, { "type": "null" } ], "default": null, "description": "The method to use for variance-based decomposition", "title": "Vbd Sampling Method", "x-union-pattern": 2 } }, "title": "VbdSamplingVarianceBasedDecomp", "type": "object" }, "Verbose": { "additionalProperties": false, "description": "Level 4 of 5 - more than normal", "properties": { "verbose": { "const": true, "default": true, "description": "Level 4 of 5 - more than normal", "title": "Verbose", "type": "boolean", "x-materialization": [ { "ir_key": "method.output", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "VERBOSE_OUTPUT" } ] } }, "title": "Verbose", "type": "object" }, "Wilks": { "additionalProperties": false, "description": "Number of samples for random sampling using Wilks statistics", "properties": { "order": { "default": 1, "description": "The order of the statistics to use when determining sample sizes for random sampling using Wilks order statistics.", "title": "Order", "type": "integer", "x-materialization": [ { "ir_key": "method.order", "ir_value_type": "unsigned short", "storage_type": "DIRECT_VALUE" } ] }, "confidence_level": { "default": 0.95, "description": "The confidence level to be used when determining sample sizes for random sampling using Wilks order statistics.", "title": "Confidence Level", "type": "number", "x-materialization": [ { "ir_key": "method.confidence_level", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "one_sided_lower": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Specifies one-sided lower portion order statistics to be used when determining sample sizes for random sampling using Wilks order statistics.", "title": "One Sided Lower", "x-materialization": [ { "ir_key": "method.wilks.sided_interval", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ONE_SIDED_LOWER" } ] }, "one_sided_upper": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Specifies one-sided upper portion order statistics to be used when determining sample sizes for random sampling using Wilks order statistics.", "title": "One Sided Upper", "x-materialization": [ { "ir_key": "method.wilks.sided_interval", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ONE_SIDED_UPPER" } ] }, "two_sided": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Specifies two-sided order statistics (an interval) to be used when determining sample sizes for random sampling using Wilks order statistics.", "title": "Two Sided", "x-materialization": [ { "ir_key": "method.wilks.sided_interval", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "TWO_SIDED" } ] } }, "title": "Wilks", "type": "object" } }, "additionalProperties": false }
- Fields:
gen_reliability_levels (dakota.spec.shared.misc.GenReliabilityLevelsGenReliabilityLevels | None)principal_components (dakota.spec.method.sampling.SamplingPrincipalComponents | 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)tolerance_intervals (dakota.spec.method.sampling.SamplingTolIntervals | None)variance_based_decomp (dakota.spec.shared.misc.VbdSamplingVarianceBasedDecomp | None)
- field backfill: Literal[True] | None = None
Ensures that the samples of discrete variables with finite support are unique
- field d_optimal: CandidateDesigns | LejaOversampleRatio | dict | None = None
Generate a D-optimal sampling design
- 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 fixed_seed: Literal[True] | None = None
Reuses the same seed value for multiple random sampling sets
- 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 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 principal_components: SamplingPrincipalComponents | None = None
Activates principal components analysis of the response matrix of N samples * L responses.
- field probability_levels: ProbabilityLevelsContext2ProbabilityLevels | None = None
Specify probability levels at which to estimate the corresponding response value
- field refinement_samples: list[int] | None = None
Performs an incremental Latin Hypercube Sampling (LHS) study
- 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
- field rng: RngOptionsContext2Mt19937 | RngOptionsContext2Rnum2 [Optional]
Selection of a random number generator
- field sample_type: SamplingSampleTypeLhs | SamplingSampleTypeRandom | IncrementalLhs | IncrementalRandom | LowDiscrepancy | None = None
Selection of sampling strategy
- field samples: int = 0
Number of samples for sampling-based methods
- field seed: int | None = None
Seed of the random number generator
- Constraints:
gt = 0
- field std_regression_coeffs: Literal[True] | None = None
Output Standardized Regression Coefficients and R^2 for samples
- field tolerance_intervals: SamplingTolIntervals | None = None
Computes the double sided tolerance interval equivalent normal distribuion.
- field variance_based_decomp: VbdSamplingVarianceBasedDecomp | None = None
Activates global sensitivity analysis based on decomposition of response variance into contributions from variables
Generated Pydantic models for method.sampling
- pydantic model dakota.spec.method.sampling.CandidateDesigns
Number of candidate sampling designs from which to select the most D-optimal
Show JSON schema
{ "title": "CandidateDesigns", "description": "Number of candidate sampling designs from which to select the most D-optimal", "type": "object", "properties": { "candidate_designs": { "description": "Number of candidate sampling designs from which to select the most D-optimal", "exclusiveMinimum": 0, "title": "Candidate Designs", "type": "integer", "x-materialization": [ { "ir_key": "method.num_candidate_designs", "ir_value_type": "size_t", "storage_type": "DIRECT_VALUE" } ] } }, "additionalProperties": false, "required": [ "candidate_designs" ] }
- Fields:
- field candidate_designs: int [Required]
Number of candidate sampling designs from which to select the most D-optimal
- Constraints:
gt = 0
- pydantic model dakota.spec.method.sampling.DigitalNet
Uses digital net points to sample variables
Show JSON schema
{ "title": "DigitalNet", "description": "Uses digital net points to sample variables", "type": "object", "properties": { "no_digital_shift": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Do not shift this digital net", "title": "No Digital Shift", "x-materialization": [ { "ir_key": "method.no_digital_shift", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "no_scrambling": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Do not scramble this digital net", "title": "No Scrambling", "x-materialization": [ { "ir_key": "method.no_scrambling", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "integer_format": { "anyOf": [ { "$ref": "#/$defs/MostSignificantBitFirst" }, { "$ref": "#/$defs/LeastSignificantBitFirst" }, { "type": "null" } ], "default": null, "description": "Specify format of integers in the generating matrices", "title": "Integer Format", "x-union-pattern": 2 }, "m_max": { "default": 0, "description": "log2 of the maximum number of points in the digital net", "minimum": 0, "title": "M Max", "type": "integer", "x-materialization": [ { "ir_key": "method.m_max", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "t_max": { "default": 0, "description": "Bit depth of the generating matrices", "minimum": 0, "title": "T Max", "type": "integer", "x-materialization": [ { "ir_key": "method.t_max", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "t_scramble": { "default": 64, "description": "Number of rows in the affine scramble matrices", "minimum": 0, "title": "T Scramble", "type": "integer", "x-materialization": [ { "ir_key": "method.t_scramble", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "generating_matrices": { "anyOf": [ { "$ref": "#/$defs/GeneratingMatricesInline" }, { "$ref": "#/$defs/GeneratingMatricesFile" }, { "$ref": "#/$defs/GeneratingMatricesPredefined" }, { "type": "null" } ], "default": null, "description": "Specify the generating matrices of this digital net", "title": "Generating Matrices", "x-union-pattern": 2 }, "ordering": { "anyOf": [ { "$ref": "#/$defs/DigitalNetOptionsOrderingNatural" }, { "$ref": "#/$defs/GrayCode" }, { "type": "null" } ], "default": null, "description": "Ordering of the points of this digital net", "title": "Ordering", "x-union-pattern": 2 } }, "$defs": { "DigitalNetOptionsOrderingNatural": { "additionalProperties": false, "description": "Natural ordering of the points of this digital net", "properties": { "natural": { "const": true, "default": true, "description": "Natural ordering of the points of this digital net", "title": "Natural", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "DIGITAL_NET_NATURAL_ORDERING" } ] } }, "title": "DigitalNetOptionsOrderingNatural", "type": "object" }, "GeneratingMatricesFile": { "additionalProperties": false, "description": "Specify generating matrices read from file", "properties": { "file": { "description": "Specify generating matrices read from file", "title": "File", "type": "string", "x-materialization": [ { "ir_key": "method.generating_matrices.file", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "file" ], "title": "GeneratingMatricesFile", "type": "object" }, "GeneratingMatricesInline": { "additionalProperties": false, "description": "Specify inline generating matrices", "properties": { "inline": { "description": "Specify inline generating matrices", "items": { "type": "integer" }, "title": "Inline", "type": "array", "x-materialization": [ { "ir_key": "method.generating_matrices.inline", "ir_value_type": "IntVector", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "inline" ], "title": "GeneratingMatricesInline", "type": "object" }, "GeneratingMatricesPredefined": { "additionalProperties": false, "description": "Specify predefined generating matrices", "properties": { "predefined": { "anyOf": [ { "$ref": "#/$defs/JoeKuo" }, { "$ref": "#/$defs/SobolOrder2" } ], "description": "Specify predefined generating matrices", "title": "Predefined" } }, "required": [ "predefined" ], "title": "GeneratingMatricesPredefined", "type": "object" }, "GrayCode": { "additionalProperties": false, "description": "Gray code ordering of the points of this digital net", "properties": { "gray_code": { "const": true, "default": true, "description": "Gray code ordering of the points of this digital net", "title": "Gray Code", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "DIGITAL_NET_GRAY_CODE_ORDERING" } ] } }, "title": "GrayCode", "type": "object" }, "JoeKuo": { "additionalProperties": false, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 250 dimensions", "properties": { "joe_kuo": { "const": true, "default": true, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 250 dimensions", "title": "Joe Kuo", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.generating_matrix_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "JOE_KUO" } ] } }, "title": "JoeKuo", "type": "object" }, "LeastSignificantBitFirst": { "additionalProperties": false, "description": "Assume integers are stored with least significant bit first", "properties": { "least_significant_bit_first": { "const": true, "default": true, "description": "Assume integers are stored with least significant bit first", "title": "Least Significant Bit First", "type": "boolean", "x-materialization": [ { "ir_key": "method.least_significant_bit_first", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] } }, "title": "LeastSignificantBitFirst", "type": "object" }, "MostSignificantBitFirst": { "additionalProperties": false, "description": "Assume integers are stored with most significant bit first", "properties": { "most_significant_bit_first": { "const": true, "default": true, "description": "Assume integers are stored with most significant bit first", "title": "Most Significant Bit First", "type": "boolean", "x-materialization": [ { "ir_key": "method.most_significant_bit_first", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] } }, "title": "MostSignificantBitFirst", "type": "object" }, "SobolOrder2": { "additionalProperties": false, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 1024 dimensions", "properties": { "sobol_order_2": { "const": true, "default": true, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 1024 dimensions", "title": "Sobol Order 2", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.generating_matrix_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SOBOL_ORDER_2" } ] } }, "title": "SobolOrder2", "type": "object" } }, "additionalProperties": false }
- Fields:
- field generating_matrices: GeneratingMatricesInline | GeneratingMatricesFile | GeneratingMatricesPredefined | None = None
Specify the generating matrices of this digital net
- field integer_format: MostSignificantBitFirst | LeastSignificantBitFirst | None = None
Specify format of integers in the generating matrices
- field m_max: int = 0
log2 of the maximum number of points in the digital net
- Constraints:
ge = 0
- field no_digital_shift: Literal[True] | None = None
Do not shift this digital net
- field no_scrambling: Literal[True] | None = None
Do not scramble this digital net
- field ordering: DigitalNetOptionsOrderingNatural | GrayCode | None = None
Ordering of the points of this digital net
- field t_max: int = 0
Bit depth of the generating matrices
- Constraints:
ge = 0
- field t_scramble: int = 64
Number of rows in the affine scramble matrices
- Constraints:
ge = 0
- pydantic model dakota.spec.method.sampling.IncrementalLhs
(Deprecated keyword) Augments an existing Latin Hypercube Sampling (LHS) study
Show JSON schema
{ "title": "IncrementalLhs", "description": "(Deprecated keyword) Augments an existing Latin Hypercube Sampling (LHS) study", "type": "object", "properties": { "incremental_lhs": { "const": true, "default": true, "description": "(Deprecated keyword) Augments an existing Latin Hypercube Sampling (LHS) study", "title": "Incremental Lhs", "type": "boolean", "x-materialization": [ { "ir_key": "method.sample_type", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_LHS" } ] } }, "additionalProperties": false }
- Fields:
- field incremental_lhs: Literal[True] = True
(Deprecated keyword) Augments an existing Latin Hypercube Sampling (LHS) study
- pydantic model dakota.spec.method.sampling.IncrementalRandom
(Deprecated keyword) Augments an existing random sampling study
Show JSON schema
{ "title": "IncrementalRandom", "description": "(Deprecated keyword) Augments an existing random sampling study", "type": "object", "properties": { "incremental_random": { "const": true, "default": true, "description": "(Deprecated keyword) Augments an existing random sampling study", "title": "Incremental Random", "type": "boolean", "x-materialization": [ { "ir_key": "method.sample_type", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_RANDOM" } ] } }, "additionalProperties": false }
- field incremental_random: Literal[True] = True
(Deprecated keyword) Augments an existing random sampling study
- pydantic model dakota.spec.method.sampling.LejaOversampleRatio
Oversampling ratio for generating candidate point set
Show JSON schema
{ "title": "LejaOversampleRatio", "description": "Oversampling ratio for generating candidate point set", "type": "object", "properties": { "leja_oversample_ratio": { "description": "Oversampling ratio for generating candidate point set", "title": "Leja Oversample Ratio", "type": "number", "x-materialization": [ { "ir_key": "method.nond.collocation_ratio", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] } }, "additionalProperties": false, "required": [ "leja_oversample_ratio" ] }
- Fields:
- field leja_oversample_ratio: DakotaFloat [Required]
Oversampling ratio for generating candidate point set
- Constraints:
func = <function _serialize_dakota_float at 0x7f2a3de76700>
return_type = float | str
when_used = json
- pydantic model dakota.spec.method.sampling.LowDiscrepancy
Uses low-discrepancy points to sample variables
Show JSON schema
{ "title": "LowDiscrepancy", "description": "Uses low-discrepancy points to sample variables", "type": "object", "properties": { "low_discrepancy": { "$ref": "#/$defs/LowDiscrepancyConfig", "x-aliases": [ "qmc" ], "x-materialization": [ { "ir_key": "method.sample_type", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_LOW_DISCREPANCY_SAMPLING" } ] } }, "$defs": { "CoolsKuoNuyens": { "additionalProperties": false, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 250 dimensions", "properties": { "cools_kuo_nuyens": { "const": true, "default": true, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 250 dimensions", "title": "Cools Kuo Nuyens", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.generating_vector_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "GEN_VECTOR_COOLS_KUO_NUYENS" } ] } }, "title": "CoolsKuoNuyens", "type": "object" }, "DigitalNet": { "additionalProperties": false, "description": "Uses digital net points to sample variables", "properties": { "no_digital_shift": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Do not shift this digital net", "title": "No Digital Shift", "x-materialization": [ { "ir_key": "method.no_digital_shift", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "no_scrambling": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Do not scramble this digital net", "title": "No Scrambling", "x-materialization": [ { "ir_key": "method.no_scrambling", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "integer_format": { "anyOf": [ { "$ref": "#/$defs/MostSignificantBitFirst" }, { "$ref": "#/$defs/LeastSignificantBitFirst" }, { "type": "null" } ], "default": null, "description": "Specify format of integers in the generating matrices", "title": "Integer Format", "x-union-pattern": 2 }, "m_max": { "default": 0, "description": "log2 of the maximum number of points in the digital net", "minimum": 0, "title": "M Max", "type": "integer", "x-materialization": [ { "ir_key": "method.m_max", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "t_max": { "default": 0, "description": "Bit depth of the generating matrices", "minimum": 0, "title": "T Max", "type": "integer", "x-materialization": [ { "ir_key": "method.t_max", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "t_scramble": { "default": 64, "description": "Number of rows in the affine scramble matrices", "minimum": 0, "title": "T Scramble", "type": "integer", "x-materialization": [ { "ir_key": "method.t_scramble", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "generating_matrices": { "anyOf": [ { "$ref": "#/$defs/GeneratingMatricesInline" }, { "$ref": "#/$defs/GeneratingMatricesFile" }, { "$ref": "#/$defs/GeneratingMatricesPredefined" }, { "type": "null" } ], "default": null, "description": "Specify the generating matrices of this digital net", "title": "Generating Matrices", "x-union-pattern": 2 }, "ordering": { "anyOf": [ { "$ref": "#/$defs/DigitalNetOptionsOrderingNatural" }, { "$ref": "#/$defs/GrayCode" }, { "type": "null" } ], "default": null, "description": "Ordering of the points of this digital net", "title": "Ordering", "x-union-pattern": 2 } }, "title": "DigitalNet", "type": "object" }, "DigitalNetOptionsOrderingNatural": { "additionalProperties": false, "description": "Natural ordering of the points of this digital net", "properties": { "natural": { "const": true, "default": true, "description": "Natural ordering of the points of this digital net", "title": "Natural", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "DIGITAL_NET_NATURAL_ORDERING" } ] } }, "title": "DigitalNetOptionsOrderingNatural", "type": "object" }, "GeneratingMatricesFile": { "additionalProperties": false, "description": "Specify generating matrices read from file", "properties": { "file": { "description": "Specify generating matrices read from file", "title": "File", "type": "string", "x-materialization": [ { "ir_key": "method.generating_matrices.file", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "file" ], "title": "GeneratingMatricesFile", "type": "object" }, "GeneratingMatricesInline": { "additionalProperties": false, "description": "Specify inline generating matrices", "properties": { "inline": { "description": "Specify inline generating matrices", "items": { "type": "integer" }, "title": "Inline", "type": "array", "x-materialization": [ { "ir_key": "method.generating_matrices.inline", "ir_value_type": "IntVector", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "inline" ], "title": "GeneratingMatricesInline", "type": "object" }, "GeneratingMatricesPredefined": { "additionalProperties": false, "description": "Specify predefined generating matrices", "properties": { "predefined": { "anyOf": [ { "$ref": "#/$defs/JoeKuo" }, { "$ref": "#/$defs/SobolOrder2" } ], "description": "Specify predefined generating matrices", "title": "Predefined" } }, "required": [ "predefined" ], "title": "GeneratingMatricesPredefined", "type": "object" }, "GeneratingVectorFile": { "additionalProperties": false, "description": "Specify a generating vector read from file", "properties": { "file": { "description": "Specify a generating vector read from file", "title": "File", "type": "string", "x-materialization": [ { "ir_key": "method.generating_vector.file", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "file" ], "title": "GeneratingVectorFile", "type": "object" }, "GeneratingVectorInline": { "additionalProperties": false, "description": "Specify an inline generating vector", "properties": { "inline": { "description": "Specify an inline generating vector", "items": { "type": "integer" }, "title": "Inline", "type": "array", "x-materialization": [ { "ir_key": "method.generating_vector.inline", "ir_value_type": "IntVector", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "inline" ], "title": "GeneratingVectorInline", "type": "object" }, "GeneratingVectorPredefined": { "additionalProperties": false, "description": "Specify a predefined generating vector", "properties": { "predefined": { "anyOf": [ { "$ref": "#/$defs/Kuo" }, { "$ref": "#/$defs/CoolsKuoNuyens" } ], "description": "Specify a predefined generating vector", "title": "Predefined" } }, "required": [ "predefined" ], "title": "GeneratingVectorPredefined", "type": "object" }, "GrayCode": { "additionalProperties": false, "description": "Gray code ordering of the points of this digital net", "properties": { "gray_code": { "const": true, "default": true, "description": "Gray code ordering of the points of this digital net", "title": "Gray Code", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "DIGITAL_NET_GRAY_CODE_ORDERING" } ] } }, "title": "GrayCode", "type": "object" }, "JoeKuo": { "additionalProperties": false, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 250 dimensions", "properties": { "joe_kuo": { "const": true, "default": true, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 250 dimensions", "title": "Joe Kuo", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.generating_matrix_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "JOE_KUO" } ] } }, "title": "JoeKuo", "type": "object" }, "Kuo": { "additionalProperties": false, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 3600 dimensions", "properties": { "kuo": { "const": true, "default": true, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 3600 dimensions", "title": "Kuo", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.generating_vector_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "GEN_VECTOR_KUO" } ] } }, "title": "Kuo", "type": "object" }, "LeastSignificantBitFirst": { "additionalProperties": false, "description": "Assume integers are stored with least significant bit first", "properties": { "least_significant_bit_first": { "const": true, "default": true, "description": "Assume integers are stored with least significant bit first", "title": "Least Significant Bit First", "type": "boolean", "x-materialization": [ { "ir_key": "method.least_significant_bit_first", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] } }, "title": "LeastSignificantBitFirst", "type": "object" }, "LowDiscrepancyConfig": { "additionalProperties": false, "description": "Uses low-discrepancy points to sample variables", "properties": { "rank_1_lattice": { "anyOf": [ { "$ref": "#/$defs/Rank1Lattice" }, { "type": "null" } ], "default": null, "description": "Uses rank-1 lattice points to sample variables", "x-materialization": [ { "ir_key": "method.rank_1_lattice", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "digital_net": { "anyOf": [ { "$ref": "#/$defs/DigitalNet" }, { "type": "null" } ], "default": null, "description": "Uses digital net points to sample variables", "x-aliases": [ "sobol_sequence" ], "x-materialization": [ { "ir_key": "method.digital_net", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] } }, "title": "LowDiscrepancyConfig", "type": "object" }, "MostSignificantBitFirst": { "additionalProperties": false, "description": "Assume integers are stored with most significant bit first", "properties": { "most_significant_bit_first": { "const": true, "default": true, "description": "Assume integers are stored with most significant bit first", "title": "Most Significant Bit First", "type": "boolean", "x-materialization": [ { "ir_key": "method.most_significant_bit_first", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] } }, "title": "MostSignificantBitFirst", "type": "object" }, "RadicalInverse": { "additionalProperties": false, "description": "Radical inverse ordering of the points of this rank-1 lattice", "properties": { "radical_inverse": { "const": true, "default": true, "description": "Radical inverse ordering of the points of this rank-1 lattice", "title": "Radical Inverse", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "RANK_1_LATTICE_RADICAL_INVERSE_ORDERING" } ] } }, "title": "RadicalInverse", "type": "object" }, "Rank1Lattice": { "additionalProperties": false, "description": "Uses rank-1 lattice points to sample variables", "properties": { "no_random_shift": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Do not shift this rank-1 lattice", "title": "No Random Shift", "x-materialization": [ { "ir_key": "method.no_random_shift", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "m_max": { "default": 0, "description": "log2 of the maximum number of points in the lattice", "minimum": 0, "title": "M Max", "type": "integer", "x-materialization": [ { "ir_key": "method.m_max", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "generating_vector": { "anyOf": [ { "$ref": "#/$defs/GeneratingVectorInline" }, { "$ref": "#/$defs/GeneratingVectorFile" }, { "$ref": "#/$defs/GeneratingVectorPredefined" }, { "type": "null" } ], "default": null, "description": "Specify the generating vector of this rank-1 lattice rule", "title": "Generating Vector", "x-union-pattern": 2 }, "ordering": { "anyOf": [ { "$ref": "#/$defs/Rank1LatticeOptionsOrderingNatural" }, { "$ref": "#/$defs/RadicalInverse" }, { "type": "null" } ], "default": null, "description": "Ordering of the points of this rank-1 lattice", "title": "Ordering", "x-union-pattern": 2 } }, "title": "Rank1Lattice", "type": "object" }, "Rank1LatticeOptionsOrderingNatural": { "additionalProperties": false, "description": "Natural ordering of the points of this rank-1 lattice", "properties": { "natural": { "const": true, "default": true, "description": "Natural ordering of the points of this rank-1 lattice", "title": "Natural", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "RANK_1_LATTICE_NATURAL_ORDERING" } ] } }, "title": "Rank1LatticeOptionsOrderingNatural", "type": "object" }, "SobolOrder2": { "additionalProperties": false, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 1024 dimensions", "properties": { "sobol_order_2": { "const": true, "default": true, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 1024 dimensions", "title": "Sobol Order 2", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.generating_matrix_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SOBOL_ORDER_2" } ] } }, "title": "SobolOrder2", "type": "object" } }, "additionalProperties": false, "required": [ "low_discrepancy" ] }
- field low_discrepancy: LowDiscrepancyConfig [Required]
Uses low-discrepancy points to sample variables
- pydantic model dakota.spec.method.sampling.LowDiscrepancyConfig
Uses low-discrepancy points to sample variables
Show JSON schema
{ "title": "LowDiscrepancyConfig", "description": "Uses low-discrepancy points to sample variables", "type": "object", "properties": { "rank_1_lattice": { "anyOf": [ { "$ref": "#/$defs/Rank1Lattice" }, { "type": "null" } ], "default": null, "description": "Uses rank-1 lattice points to sample variables", "x-materialization": [ { "ir_key": "method.rank_1_lattice", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "digital_net": { "anyOf": [ { "$ref": "#/$defs/DigitalNet" }, { "type": "null" } ], "default": null, "description": "Uses digital net points to sample variables", "x-aliases": [ "sobol_sequence" ], "x-materialization": [ { "ir_key": "method.digital_net", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] } }, "$defs": { "CoolsKuoNuyens": { "additionalProperties": false, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 250 dimensions", "properties": { "cools_kuo_nuyens": { "const": true, "default": true, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 250 dimensions", "title": "Cools Kuo Nuyens", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.generating_vector_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "GEN_VECTOR_COOLS_KUO_NUYENS" } ] } }, "title": "CoolsKuoNuyens", "type": "object" }, "DigitalNet": { "additionalProperties": false, "description": "Uses digital net points to sample variables", "properties": { "no_digital_shift": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Do not shift this digital net", "title": "No Digital Shift", "x-materialization": [ { "ir_key": "method.no_digital_shift", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "no_scrambling": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Do not scramble this digital net", "title": "No Scrambling", "x-materialization": [ { "ir_key": "method.no_scrambling", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "integer_format": { "anyOf": [ { "$ref": "#/$defs/MostSignificantBitFirst" }, { "$ref": "#/$defs/LeastSignificantBitFirst" }, { "type": "null" } ], "default": null, "description": "Specify format of integers in the generating matrices", "title": "Integer Format", "x-union-pattern": 2 }, "m_max": { "default": 0, "description": "log2 of the maximum number of points in the digital net", "minimum": 0, "title": "M Max", "type": "integer", "x-materialization": [ { "ir_key": "method.m_max", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "t_max": { "default": 0, "description": "Bit depth of the generating matrices", "minimum": 0, "title": "T Max", "type": "integer", "x-materialization": [ { "ir_key": "method.t_max", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "t_scramble": { "default": 64, "description": "Number of rows in the affine scramble matrices", "minimum": 0, "title": "T Scramble", "type": "integer", "x-materialization": [ { "ir_key": "method.t_scramble", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "generating_matrices": { "anyOf": [ { "$ref": "#/$defs/GeneratingMatricesInline" }, { "$ref": "#/$defs/GeneratingMatricesFile" }, { "$ref": "#/$defs/GeneratingMatricesPredefined" }, { "type": "null" } ], "default": null, "description": "Specify the generating matrices of this digital net", "title": "Generating Matrices", "x-union-pattern": 2 }, "ordering": { "anyOf": [ { "$ref": "#/$defs/DigitalNetOptionsOrderingNatural" }, { "$ref": "#/$defs/GrayCode" }, { "type": "null" } ], "default": null, "description": "Ordering of the points of this digital net", "title": "Ordering", "x-union-pattern": 2 } }, "title": "DigitalNet", "type": "object" }, "DigitalNetOptionsOrderingNatural": { "additionalProperties": false, "description": "Natural ordering of the points of this digital net", "properties": { "natural": { "const": true, "default": true, "description": "Natural ordering of the points of this digital net", "title": "Natural", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "DIGITAL_NET_NATURAL_ORDERING" } ] } }, "title": "DigitalNetOptionsOrderingNatural", "type": "object" }, "GeneratingMatricesFile": { "additionalProperties": false, "description": "Specify generating matrices read from file", "properties": { "file": { "description": "Specify generating matrices read from file", "title": "File", "type": "string", "x-materialization": [ { "ir_key": "method.generating_matrices.file", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "file" ], "title": "GeneratingMatricesFile", "type": "object" }, "GeneratingMatricesInline": { "additionalProperties": false, "description": "Specify inline generating matrices", "properties": { "inline": { "description": "Specify inline generating matrices", "items": { "type": "integer" }, "title": "Inline", "type": "array", "x-materialization": [ { "ir_key": "method.generating_matrices.inline", "ir_value_type": "IntVector", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "inline" ], "title": "GeneratingMatricesInline", "type": "object" }, "GeneratingMatricesPredefined": { "additionalProperties": false, "description": "Specify predefined generating matrices", "properties": { "predefined": { "anyOf": [ { "$ref": "#/$defs/JoeKuo" }, { "$ref": "#/$defs/SobolOrder2" } ], "description": "Specify predefined generating matrices", "title": "Predefined" } }, "required": [ "predefined" ], "title": "GeneratingMatricesPredefined", "type": "object" }, "GeneratingVectorFile": { "additionalProperties": false, "description": "Specify a generating vector read from file", "properties": { "file": { "description": "Specify a generating vector read from file", "title": "File", "type": "string", "x-materialization": [ { "ir_key": "method.generating_vector.file", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "file" ], "title": "GeneratingVectorFile", "type": "object" }, "GeneratingVectorInline": { "additionalProperties": false, "description": "Specify an inline generating vector", "properties": { "inline": { "description": "Specify an inline generating vector", "items": { "type": "integer" }, "title": "Inline", "type": "array", "x-materialization": [ { "ir_key": "method.generating_vector.inline", "ir_value_type": "IntVector", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "inline" ], "title": "GeneratingVectorInline", "type": "object" }, "GeneratingVectorPredefined": { "additionalProperties": false, "description": "Specify a predefined generating vector", "properties": { "predefined": { "anyOf": [ { "$ref": "#/$defs/Kuo" }, { "$ref": "#/$defs/CoolsKuoNuyens" } ], "description": "Specify a predefined generating vector", "title": "Predefined" } }, "required": [ "predefined" ], "title": "GeneratingVectorPredefined", "type": "object" }, "GrayCode": { "additionalProperties": false, "description": "Gray code ordering of the points of this digital net", "properties": { "gray_code": { "const": true, "default": true, "description": "Gray code ordering of the points of this digital net", "title": "Gray Code", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "DIGITAL_NET_GRAY_CODE_ORDERING" } ] } }, "title": "GrayCode", "type": "object" }, "JoeKuo": { "additionalProperties": false, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 250 dimensions", "properties": { "joe_kuo": { "const": true, "default": true, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 250 dimensions", "title": "Joe Kuo", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.generating_matrix_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "JOE_KUO" } ] } }, "title": "JoeKuo", "type": "object" }, "Kuo": { "additionalProperties": false, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 3600 dimensions", "properties": { "kuo": { "const": true, "default": true, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 3600 dimensions", "title": "Kuo", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.generating_vector_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "GEN_VECTOR_KUO" } ] } }, "title": "Kuo", "type": "object" }, "LeastSignificantBitFirst": { "additionalProperties": false, "description": "Assume integers are stored with least significant bit first", "properties": { "least_significant_bit_first": { "const": true, "default": true, "description": "Assume integers are stored with least significant bit first", "title": "Least Significant Bit First", "type": "boolean", "x-materialization": [ { "ir_key": "method.least_significant_bit_first", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] } }, "title": "LeastSignificantBitFirst", "type": "object" }, "MostSignificantBitFirst": { "additionalProperties": false, "description": "Assume integers are stored with most significant bit first", "properties": { "most_significant_bit_first": { "const": true, "default": true, "description": "Assume integers are stored with most significant bit first", "title": "Most Significant Bit First", "type": "boolean", "x-materialization": [ { "ir_key": "method.most_significant_bit_first", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] } }, "title": "MostSignificantBitFirst", "type": "object" }, "RadicalInverse": { "additionalProperties": false, "description": "Radical inverse ordering of the points of this rank-1 lattice", "properties": { "radical_inverse": { "const": true, "default": true, "description": "Radical inverse ordering of the points of this rank-1 lattice", "title": "Radical Inverse", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "RANK_1_LATTICE_RADICAL_INVERSE_ORDERING" } ] } }, "title": "RadicalInverse", "type": "object" }, "Rank1Lattice": { "additionalProperties": false, "description": "Uses rank-1 lattice points to sample variables", "properties": { "no_random_shift": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Do not shift this rank-1 lattice", "title": "No Random Shift", "x-materialization": [ { "ir_key": "method.no_random_shift", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "m_max": { "default": 0, "description": "log2 of the maximum number of points in the lattice", "minimum": 0, "title": "M Max", "type": "integer", "x-materialization": [ { "ir_key": "method.m_max", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "generating_vector": { "anyOf": [ { "$ref": "#/$defs/GeneratingVectorInline" }, { "$ref": "#/$defs/GeneratingVectorFile" }, { "$ref": "#/$defs/GeneratingVectorPredefined" }, { "type": "null" } ], "default": null, "description": "Specify the generating vector of this rank-1 lattice rule", "title": "Generating Vector", "x-union-pattern": 2 }, "ordering": { "anyOf": [ { "$ref": "#/$defs/Rank1LatticeOptionsOrderingNatural" }, { "$ref": "#/$defs/RadicalInverse" }, { "type": "null" } ], "default": null, "description": "Ordering of the points of this rank-1 lattice", "title": "Ordering", "x-union-pattern": 2 } }, "title": "Rank1Lattice", "type": "object" }, "Rank1LatticeOptionsOrderingNatural": { "additionalProperties": false, "description": "Natural ordering of the points of this rank-1 lattice", "properties": { "natural": { "const": true, "default": true, "description": "Natural ordering of the points of this rank-1 lattice", "title": "Natural", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "RANK_1_LATTICE_NATURAL_ORDERING" } ] } }, "title": "Rank1LatticeOptionsOrderingNatural", "type": "object" }, "SobolOrder2": { "additionalProperties": false, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 1024 dimensions", "properties": { "sobol_order_2": { "const": true, "default": true, "description": "Generating matrices that provide up to 2\\ :sup:`32` points in up to 1024 dimensions", "title": "Sobol Order 2", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.digitalnet.generating_matrix_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "SOBOL_ORDER_2" } ] } }, "title": "SobolOrder2", "type": "object" } }, "additionalProperties": false }
- Fields:
- field digital_net: DigitalNet | None = None
Uses digital net points to sample variables
- field rank_1_lattice: Rank1Lattice | None = None
Uses rank-1 lattice points to sample variables
- pydantic model dakota.spec.method.sampling.Rank1Lattice
Uses rank-1 lattice points to sample variables
Show JSON schema
{ "title": "Rank1Lattice", "description": "Uses rank-1 lattice points to sample variables", "type": "object", "properties": { "no_random_shift": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Do not shift this rank-1 lattice", "title": "No Random Shift", "x-materialization": [ { "ir_key": "method.no_random_shift", "ir_value_type": "bool", "storage_type": "PRESENCE_TRUE" } ] }, "m_max": { "default": 0, "description": "log2 of the maximum number of points in the lattice", "minimum": 0, "title": "M Max", "type": "integer", "x-materialization": [ { "ir_key": "method.m_max", "ir_value_type": "int", "storage_type": "DIRECT_VALUE" } ] }, "generating_vector": { "anyOf": [ { "$ref": "#/$defs/GeneratingVectorInline" }, { "$ref": "#/$defs/GeneratingVectorFile" }, { "$ref": "#/$defs/GeneratingVectorPredefined" }, { "type": "null" } ], "default": null, "description": "Specify the generating vector of this rank-1 lattice rule", "title": "Generating Vector", "x-union-pattern": 2 }, "ordering": { "anyOf": [ { "$ref": "#/$defs/Rank1LatticeOptionsOrderingNatural" }, { "$ref": "#/$defs/RadicalInverse" }, { "type": "null" } ], "default": null, "description": "Ordering of the points of this rank-1 lattice", "title": "Ordering", "x-union-pattern": 2 } }, "$defs": { "CoolsKuoNuyens": { "additionalProperties": false, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 250 dimensions", "properties": { "cools_kuo_nuyens": { "const": true, "default": true, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 250 dimensions", "title": "Cools Kuo Nuyens", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.generating_vector_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "GEN_VECTOR_COOLS_KUO_NUYENS" } ] } }, "title": "CoolsKuoNuyens", "type": "object" }, "GeneratingVectorFile": { "additionalProperties": false, "description": "Specify a generating vector read from file", "properties": { "file": { "description": "Specify a generating vector read from file", "title": "File", "type": "string", "x-materialization": [ { "ir_key": "method.generating_vector.file", "ir_value_type": "String", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "file" ], "title": "GeneratingVectorFile", "type": "object" }, "GeneratingVectorInline": { "additionalProperties": false, "description": "Specify an inline generating vector", "properties": { "inline": { "description": "Specify an inline generating vector", "items": { "type": "integer" }, "title": "Inline", "type": "array", "x-materialization": [ { "ir_key": "method.generating_vector.inline", "ir_value_type": "IntVector", "storage_type": "DIRECT_VALUE" } ] } }, "required": [ "inline" ], "title": "GeneratingVectorInline", "type": "object" }, "GeneratingVectorPredefined": { "additionalProperties": false, "description": "Specify a predefined generating vector", "properties": { "predefined": { "anyOf": [ { "$ref": "#/$defs/Kuo" }, { "$ref": "#/$defs/CoolsKuoNuyens" } ], "description": "Specify a predefined generating vector", "title": "Predefined" } }, "required": [ "predefined" ], "title": "GeneratingVectorPredefined", "type": "object" }, "Kuo": { "additionalProperties": false, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 3600 dimensions", "properties": { "kuo": { "const": true, "default": true, "description": "A generating vector that provides up to 2\\ :sup:`20` points in up to 3600 dimensions", "title": "Kuo", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.generating_vector_scheme", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "GEN_VECTOR_KUO" } ] } }, "title": "Kuo", "type": "object" }, "RadicalInverse": { "additionalProperties": false, "description": "Radical inverse ordering of the points of this rank-1 lattice", "properties": { "radical_inverse": { "const": true, "default": true, "description": "Radical inverse ordering of the points of this rank-1 lattice", "title": "Radical Inverse", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "RANK_1_LATTICE_RADICAL_INVERSE_ORDERING" } ] } }, "title": "RadicalInverse", "type": "object" }, "Rank1LatticeOptionsOrderingNatural": { "additionalProperties": false, "description": "Natural ordering of the points of this rank-1 lattice", "properties": { "natural": { "const": true, "default": true, "description": "Natural ordering of the points of this rank-1 lattice", "title": "Natural", "type": "boolean", "x-materialization": [ { "ir_key": "method.ld.rank1.ordering", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "RANK_1_LATTICE_NATURAL_ORDERING" } ] } }, "title": "Rank1LatticeOptionsOrderingNatural", "type": "object" } }, "additionalProperties": false }
- Fields:
- field generating_vector: GeneratingVectorInline | GeneratingVectorFile | GeneratingVectorPredefined | None = None
Specify the generating vector of this rank-1 lattice rule
- field m_max: int = 0
log2 of the maximum number of points in the lattice
- Constraints:
ge = 0
- field no_random_shift: Literal[True] | None = None
Do not shift this rank-1 lattice
- field ordering: Rank1LatticeOptionsOrderingNatural | RadicalInverse | None = None
Ordering of the points of this rank-1 lattice
- pydantic model dakota.spec.method.sampling.SamplingPrincipalComponents
Activates principal components analysis of the response matrix of N samples * L responses.
Show JSON schema
{ "title": "SamplingPrincipalComponents", "description": "Activates principal components analysis of the response matrix of N samples * L responses.", "type": "object", "properties": { "percent_variance_explained": { "default": 0.95, "description": "Specifies the number of components to retain to explain the specified percent variance.", "title": "Percent Variance Explained", "type": "number", "x-materialization": [ { "ir_key": "method.percent_variance_explained", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] } }, "additionalProperties": false }
- field percent_variance_explained: DakotaFloat = 0.95
Specifies the number of components to retain to explain the specified percent variance.
- Constraints:
func = <function _serialize_dakota_float at 0x7f2a3de76700>
return_type = float | str
when_used = json
- pydantic model dakota.spec.method.sampling.SamplingSampleTypeLhs
Uses Latin Hypercube Sampling (LHS) to sample variables
Show JSON schema
{ "title": "SamplingSampleTypeLhs", "description": "Uses Latin Hypercube Sampling (LHS) to sample variables", "type": "object", "properties": { "lhs": { "const": true, "default": true, "description": "Uses Latin Hypercube Sampling (LHS) to sample variables", "title": "Lhs", "type": "boolean", "x-materialization": [ { "ir_key": "method.sample_type", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_LHS" } ] } }, "additionalProperties": false }
- Fields:
- field lhs: Literal[True] = True
Uses Latin Hypercube Sampling (LHS) to sample variables
- pydantic model dakota.spec.method.sampling.SamplingSampleTypeRandom
Uses purely random Monte Carlo sampling to sample variables
Show JSON schema
{ "title": "SamplingSampleTypeRandom", "description": "Uses purely random Monte Carlo sampling to sample variables", "type": "object", "properties": { "random": { "const": true, "default": true, "description": "Uses purely random Monte Carlo sampling to sample variables", "title": "Random", "type": "boolean", "x-materialization": [ { "ir_key": "method.sample_type", "ir_value_type": "unsigned short", "storage_type": "PRESENCE_ENUM", "stored_value": "SUBMETHOD_RANDOM" } ] } }, "additionalProperties": false }
- Fields:
- field random: Literal[True] = True
Uses purely random Monte Carlo sampling to sample variables
- pydantic model dakota.spec.method.sampling.SamplingTolIntervals
Computes the double sided tolerance interval equivalent normal distribuion.
Show JSON schema
{ "title": "SamplingTolIntervals", "description": "Computes the double sided tolerance interval equivalent normal distribuion.", "type": "object", "properties": { "coverage": { "default": 0.95, "description": "The coverage to be used for the calculation of the lower and upper ends of the interval covering the user supplied samples.", "maximum": 1, "minimum": 0, "title": "Coverage", "type": "number", "x-materialization": [ { "ir_key": "method.ti_coverage", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "confidence_level": { "default": 0.9, "description": "The confidence level to be used to determine the standard deviation of the equivalent normal distribution.", "maximum": 1, "minimum": 0, "title": "Confidence Level", "type": "number", "x-materialization": [ { "ir_key": "method.ti_confidence_level", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] } }, "additionalProperties": false }
- field confidence_level: DakotaFloat = 0.9
The confidence level to be used to determine the standard deviation of the equivalent normal distribution.
- Constraints:
ge = 0
le = 1
func = <function _serialize_dakota_float at 0x7f2a3de76700>
return_type = float | str
when_used = json
- field coverage: DakotaFloat = 0.95
The coverage to be used for the calculation of the lower and upper ends of the interval covering the user supplied samples.
- Constraints:
ge = 0
le = 1
func = <function _serialize_dakota_float at 0x7f2a3de76700>
return_type = float | str
when_used = json
- pydantic model dakota.spec.method.sampling.Wilks
Number of samples for random sampling using Wilks statistics
Show JSON schema
{ "title": "Wilks", "description": "Number of samples for random sampling using Wilks statistics", "type": "object", "properties": { "order": { "default": 1, "description": "The order of the statistics to use when determining sample sizes for random sampling using Wilks order statistics.", "title": "Order", "type": "integer", "x-materialization": [ { "ir_key": "method.order", "ir_value_type": "unsigned short", "storage_type": "DIRECT_VALUE" } ] }, "confidence_level": { "default": 0.95, "description": "The confidence level to be used when determining sample sizes for random sampling using Wilks order statistics.", "title": "Confidence Level", "type": "number", "x-materialization": [ { "ir_key": "method.confidence_level", "ir_value_type": "Real", "storage_type": "DIRECT_VALUE" } ] }, "one_sided_lower": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Specifies one-sided lower portion order statistics to be used when determining sample sizes for random sampling using Wilks order statistics.", "title": "One Sided Lower", "x-materialization": [ { "ir_key": "method.wilks.sided_interval", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ONE_SIDED_LOWER" } ] }, "one_sided_upper": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Specifies one-sided upper portion order statistics to be used when determining sample sizes for random sampling using Wilks order statistics.", "title": "One Sided Upper", "x-materialization": [ { "ir_key": "method.wilks.sided_interval", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "ONE_SIDED_UPPER" } ] }, "two_sided": { "anyOf": [ { "const": true, "type": "boolean" }, { "type": "null" } ], "default": null, "description": "Specifies two-sided order statistics (an interval) to be used when determining sample sizes for random sampling using Wilks order statistics.", "title": "Two Sided", "x-materialization": [ { "ir_key": "method.wilks.sided_interval", "ir_value_type": "short", "storage_type": "PRESENCE_ENUM", "stored_value": "TWO_SIDED" } ] } }, "additionalProperties": false }
- Fields:
- field confidence_level: DakotaFloat = 0.95
The confidence level to be used when determining sample sizes for random sampling using Wilks order statistics.
- Constraints:
func = <function _serialize_dakota_float at 0x7f2a3de76700>
return_type = float | str
when_used = json
- field one_sided_lower: Literal[True] | None = None
Specifies one-sided lower portion order statistics to be used when determining sample sizes for random sampling using Wilks order statistics.
- field one_sided_upper: Literal[True] | None = None
Specifies one-sided upper portion order statistics to be used when determining sample sizes for random sampling using Wilks order statistics.
- field order: int = 1
The order of the statistics to use when determining sample sizes for random sampling using Wilks order statistics.
- field two_sided: Literal[True] | None = None
Specifies two-sided order statistics (an interval) to be used when determining sample sizes for random sampling using Wilks order statistics.
