| /dports/science/dakota/dakota-6.13.0-release-public.src-UI/src/ |
| H A D | DakotaIterator.cpp | 162 probDescDB(problem_db), parallelLib(problem_db.parallel_library()), in Iterator()
187 methodId(problem_db.get_string("method.id")), execNum(0), in Iterator()
272 Iterator::Iterator(ProblemDescDB& problem_db, in Iterator() argument
274 probDescDB(problem_db), parallelLib(problem_db.parallel_library()), in Iterator()
277 iteratorRep(get_iterator(problem_db)) in Iterator()
320 switch (problem_db.get_ushort("method.sub_method")) { in get_iterator()
338 Model the_model = problem_db.get_model(); in get_iterator()
339 return get_iterator(problem_db, the_model); break; in get_iterator()
352 probDescDB(problem_db), parallelLib(problem_db.parallel_library()), in Iterator()
355 iteratorRep(get_iterator(problem_db, model)) in Iterator()
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| H A D | IteratorScheduler.cpp | 63 if (light_wt) problem_db.set_db_model_nodes(model_ptr); in construct_sub_iterator()
64 else problem_db.set_db_list_nodes(method_ptr); in construct_sub_iterator()
68 problem_db.get_iterator(sub_model); //(ctor_model); in construct_sub_iterator()
83 return configure(problem_db, sub_iterator); in configure()
90 configure(ProblemDescDB& problem_db, const String& method_string, in configure() argument
99 return configure(problem_db, sub_iterator); in configure()
106 configure(ProblemDescDB& problem_db, Iterator& sub_iterator) in configure() argument
219 sub_iterator = problem_db.get_iterator(); // all procs in init_iterator()
240 sub_model = problem_db.get_model(); in init_iterator()
253 sub_iterator = problem_db.get_iterator(sub_model); in init_iterator()
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| H A D | MixedVarConstraints.cpp | 29 MixedVarConstraints(const ProblemDescDB& problem_db, in MixedVarConstraints() argument
31 Constraints(BaseConstructor(), problem_db, svd) in MixedVarConstraints()
34 const RealVector& cdv_l_bnds = problem_db.get_rv( in MixedVarConstraints()
36 const RealVector& cdv_u_bnds = problem_db.get_rv( in MixedVarConstraints()
38 const RealVector& cauv_l_bnds = problem_db.get_rv( in MixedVarConstraints()
40 const RealVector& cauv_u_bnds = problem_db.get_rv( in MixedVarConstraints()
42 const RealVector& ceuv_l_bnds = problem_db.get_rv( in MixedVarConstraints()
44 const RealVector& ceuv_u_bnds = problem_db.get_rv( in MixedVarConstraints()
46 const RealVector& csv_l_bnds = problem_db.get_rv( in MixedVarConstraints()
64 const IntVector& ddrv_l_bnds = problem_db.get_iv( in MixedVarConstraints()
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| H A D | SharedResponseData.cpp | 36 SharedResponseDataRep(const ProblemDescDB& problem_db): in SharedResponseDataRep() argument
39 responsesId(problem_db.get_string("responses.id")), in SharedResponseDataRep()
40 functionLabels(problem_db.get_sa("responses.labels")), in SharedResponseDataRep()
47 ( problem_db.get_sizet("responses.num_scalar_objectives"), in SharedResponseDataRep()
49 problem_db.get_sizet("responses.num_scalar_responses") ) in SharedResponseDataRep()
57 ( problem_db.get_sizet("responses.num_field_objectives"), in SharedResponseDataRep()
59 problem_db.get_sizet("responses.num_field_responses") ) in SharedResponseDataRep()
67 ( problem_db.get_sizet("responses.num_objective_functions"), in SharedResponseDataRep()
69 problem_db.get_sizet("responses.num_response_functions") ) in SharedResponseDataRep()
76 if (problem_db.get_sizet("responses.num_objective_functions") > 0) in SharedResponseDataRep()
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| H A D | AdaptedBasisModel.cpp | 21 AdaptedBasisModel(ProblemDescDB& problem_db): in AdaptedBasisModel() argument
22 SubspaceModel(problem_db, get_sub_model(problem_db)) in AdaptedBasisModel()
47 Model AdaptedBasisModel::get_sub_model(ProblemDescDB& problem_db) in get_sub_model() argument
50 = problem_db.get_string("model.surrogate.actual_model_pointer"); in get_sub_model()
52 = problem_db.get_ushort("model.adapted_basis.sparse_grid_level"); in get_sub_model()
54 = problem_db.get_ushort("model.adapted_basis.expansion_order"); in get_sub_model()
56 = problem_db.get_real("model.adapted_basis.collocation_ratio"); in get_sub_model()
65 use_derivs = problem_db.get_bool("method.derivative_usage"); in get_sub_model()
68 problem_db.set_db_model_nodes(actual_model_pointer); in get_sub_model()
70 Model actual_model(problem_db.get_model()); in get_sub_model()
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| H A D | SharedApproxData.cpp | 42 buildDataOrder(1), outputLevel(problem_db.get_short("method.output")), in SharedApproxData()
44 problem_db.get_string("model.surrogate.model_export_prefix")), in SharedApproxData()
46 problem_db.get_ushort("model.surrogate.model_export_format")) in SharedApproxData()
59 = problem_db.get_string("model.surrogate.actual_model_pointer"); in SharedApproxData()
61 problem_db.set_db_model_nodes(actual_model_ptr); in SharedApproxData()
63 if (problem_db.get_string("responses.gradient_type") != "none") { in SharedApproxData()
78 if (problem_db.get_string("responses.hessian_type") != "none") { in SharedApproxData()
87 problem_db.set_db_model_nodes(model_index); in SharedApproxData()
150 dataRep(get_shared_data(problem_db, num_vars)) in SharedApproxData()
160 get_shared_data(ProblemDescDB& problem_db, size_t num_vars) in get_shared_data() argument
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| H A D | MetaIterator.cpp | 23 MetaIterator::MetaIterator(ProblemDescDB& problem_db): in MetaIterator() argument
24 Iterator(BaseConstructor(), problem_db), in MetaIterator()
25 iterSched(problem_db.parallel_library(), in MetaIterator()
27 problem_db.get_int("method.iterator_servers"), in MetaIterator()
28 problem_db.get_int("method.processors_per_iterator"), in MetaIterator()
29 problem_db.get_short("method.iterator_scheduling")) in MetaIterator()
40 Iterator(BaseConstructor(), problem_db), in MetaIterator()
41 iterSched(problem_db.parallel_library(), in MetaIterator()
43 problem_db.get_int("method.iterator_servers"), in MetaIterator()
44 problem_db.get_int("method.processors_per_iterator"), in MetaIterator()
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| H A D | NonDPolynomialChaos.cpp | 37 NonDPolynomialChaos(ProblemDescDB& problem_db, Model& model): in NonDPolynomialChaos() argument
38 NonDExpansion(problem_db, model), in NonDPolynomialChaos()
55 problem_db.get_string("method.import_build_points_file")), in NonDPolynomialChaos()
102 problem_db.get_short("method.nond.regression_type"), in NonDPolynomialChaos()
127 problem_db.get_ushort("method.import_build_format"), in NonDPolynomialChaos()
128 problem_db.get_bool("method.import_build_active_only"), in NonDPolynomialChaos()
130 problem_db.get_ushort("method.export_approx_format"))); in NonDPolynomialChaos()
137 problem_db.get_string("method.random_number_generator"), in NonDPolynomialChaos()
139 problem_db.get_iv("method.nond.refinement_samples"), in NonDPolynomialChaos()
141 problem_db.get_ushort("method.import_approx_format"), in NonDPolynomialChaos()
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| H A D | ProgramOptions.cpp | 320 void ProgramOptions::parse(const ProblemDescDB& problem_db) in parse() argument
329 set_option(problem_db, "output_file", outputFile); in parse()
330 set_option(problem_db, "error_file", errorFile); in parse()
331 set_option(problem_db, "read_restart", readRestartFile); in parse()
343 set_option(problem_db, "write_restart", writeRestartFile); in parse()
353 const bool& run = problem_db.get_bool("environment.run"); in parse()
369 set_option(problem_db, "pre_run_input", preRunInput); in parse()
371 set_option(problem_db, "run_input", runInput); in parse()
372 set_option(problem_db, "run_output", runOutput); in parse()
377 problem_db.get_ushort("environment.pre_run_output_format"); in parse()
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| H A D | SharedC3ApproxData.cpp | 28 SharedC3ApproxData(ProblemDescDB& problem_db, size_t num_vars): in SharedC3ApproxData() argument
29 SharedApproxData(BaseConstructor(), problem_db, num_vars), in SharedC3ApproxData()
30 kickOrder(problem_db.get_ushort("model.c3function_train.kick_order")), in SharedC3ApproxData()
31 maxOrder(problem_db.get_ushort("model.c3function_train.max_order")), in SharedC3ApproxData()
32 adaptOrder(problem_db.get_bool("model.c3function_train.adapt_order")), in SharedC3ApproxData()
33 startRank(problem_db.get_sizet("model.c3function_train.start_rank")), in SharedC3ApproxData()
34 kickRank(problem_db.get_sizet("model.c3function_train.kick_rank")), in SharedC3ApproxData()
35 maxRank(problem_db.get_sizet("model.c3function_train.max_rank")), in SharedC3ApproxData()
36 adaptRank(problem_db.get_bool("model.c3function_train.adapt_rank")), in SharedC3ApproxData()
37 regressType(problem_db.get_short("model.surrogate.regression_type")), in SharedC3ApproxData()
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| H A D | RelaxedVarConstraints.cpp | 31 Constraints(BaseConstructor(), problem_db, svd) in RelaxedVarConstraints()
33 const RealVector& cdv_l_bnds = problem_db.get_rv( in RelaxedVarConstraints()
35 const RealVector& cdv_u_bnds = problem_db.get_rv( in RelaxedVarConstraints()
37 const RealVector& cauv_l_bnds = problem_db.get_rv( in RelaxedVarConstraints()
39 const RealVector& cauv_u_bnds = problem_db.get_rv( in RelaxedVarConstraints()
41 const RealVector& ceuv_l_bnds = problem_db.get_rv( in RelaxedVarConstraints()
43 const RealVector& ceuv_u_bnds = problem_db.get_rv( in RelaxedVarConstraints()
45 const RealVector& csv_l_bnds = problem_db.get_rv( in RelaxedVarConstraints()
50 const IntVector& ddrv_l_bnds = problem_db.get_iv( in RelaxedVarConstraints()
52 const IntVector& ddrv_u_bnds = problem_db.get_iv( in RelaxedVarConstraints()
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| H A D | EmbedHybridMetaIterator.cpp | 23 EmbedHybridMetaIterator::EmbedHybridMetaIterator(ProblemDescDB& problem_db): in EmbedHybridMetaIterator() argument
24 MetaIterator(problem_db), singlePassedModel(false), in EmbedHybridMetaIterator()
25 localSearchProb(problem_db.get_real("method.hybrid.local_search_probability")) in EmbedHybridMetaIterator()
30 EmbedHybridMetaIterator(ProblemDescDB& problem_db, Model& model): in EmbedHybridMetaIterator() argument
31 MetaIterator(problem_db, model), singlePassedModel(true), in EmbedHybridMetaIterator()
32 localSearchProb(problem_db.get_real("method.hybrid.local_search_probability")) in EmbedHybridMetaIterator()
35 check_model(problem_db.get_string("method.hybrid.global_method_pointer"), in EmbedHybridMetaIterator()
36 problem_db.get_string("method.hybrid.global_model_pointer")); in EmbedHybridMetaIterator()
37 check_model(problem_db.get_string("method.hybrid.local_method_pointer"), in EmbedHybridMetaIterator()
38 problem_db.get_string("method.hybrid.local_model_pointer")); in EmbedHybridMetaIterator()
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| H A D | MixedVariables.cpp | 28 MixedVariables(const ProblemDescDB& problem_db, in MixedVariables() argument
33 const RealVector& cdv = problem_db.get_rv( in MixedVariables()
35 const RealVector& cauv = problem_db.get_rv( in MixedVariables()
37 const RealVector& ceuv = problem_db.get_rv( in MixedVariables()
39 const RealVector& csv = problem_db.get_rv( in MixedVariables()
47 const IntVector& ddrv = problem_db.get_iv( in MixedVariables()
49 const IntVector& ddsiv = problem_db.get_iv( in MixedVariables()
51 const IntVector& dauiv = problem_db.get_iv( in MixedVariables()
53 const IntVector& deuiv = problem_db.get_iv( in MixedVariables()
55 const IntVector& dsrv = problem_db.get_iv( in MixedVariables()
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| H A D | NonDSurrogateExpansion.cpp | 29 NonDSurrogateExpansion(ProblemDescDB& problem_db, Model& model): in NonDSurrogateExpansion() argument
30 NonDExpansion(problem_db, model) in NonDSurrogateExpansion()
95 construct_expansion_sampler(problem_db.get_ushort("method.sample_type"), in NonDSurrogateExpansion()
96 problem_db.get_string("method.random_number_generator"), in NonDSurrogateExpansion()
97 problem_db.get_ushort("method.nond.integration_refinement"), in NonDSurrogateExpansion()
98 problem_db.get_iv("method.nond.refinement_samples"), in NonDSurrogateExpansion()
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| H A D | ConcurrentMetaIterator.cpp | 27 MetaIterator(problem_db), in ConcurrentMetaIterator()
46 = problem_db.get_rv("method.concurrent.parameter_sets"); in ConcurrentMetaIterator()
49 = problem_db.get_string("method.sub_method_pointer"); in ConcurrentMetaIterator()
52 = problem_db.get_string("method.sub_model_pointer"); in ConcurrentMetaIterator()
64 problem_db.set_db_list_nodes(sub_meth_ptr); in ConcurrentMetaIterator()
73 problem_db.set_db_model_nodes(sub_model_ptr); in ConcurrentMetaIterator()
83 iteratedModel = problem_db.get_model(); in ConcurrentMetaIterator()
109 MetaIterator(problem_db, model), in ConcurrentMetaIterator()
118 problem_db.get_string("method.sub_model_pointer")); in ConcurrentMetaIterator()
122 problem_db.set_db_model_nodes(iteratedModel.model_id()); in ConcurrentMetaIterator()
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| H A D | RandomFieldModel.cpp | 20 RandomFieldModel::RandomFieldModel(ProblemDescDB& problem_db): in RandomFieldModel() argument
21 RecastModel(problem_db, get_sub_model(problem_db)), in RandomFieldModel()
24 expansionForm(problem_db.get_ushort("model.rf.expansion_form")), in RandomFieldModel()
32 init_dace_iterator(problem_db); in RandomFieldModel()
42 Model RandomFieldModel::get_sub_model(ProblemDescDB& problem_db) in get_sub_model() argument
49 problem_db.set_db_model_nodes(propagation_model_pointer); in get_sub_model()
50 sub_model = problem_db.get_model(); in get_sub_model()
52 problem_db.set_db_model_nodes(model_index); // restore in get_sub_model()
61 = problem_db.get_string("model.dace_method_pointer"); in init_dace_iterator()
66 problem_db.set_db_list_nodes(dace_method_pointer); in init_dace_iterator()
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| H A D | DakotaConstraints.cpp | 32 Constraints(BaseConstructor, const ProblemDescDB& problem_db, in Constraints() argument
38 problem_db.get_rv("responses.nonlinear_inequality_lower_bounds")), in Constraints()
40 problem_db.get_rv("responses.nonlinear_inequality_upper_bounds")), in Constraints()
44 problem_db.get_rv("responses.nonlinear_equality_targets")), in Constraints()
47 problem_db.get_rv("variables.linear_inequality_lower_bounds")), in Constraints()
49 problem_db.get_rv("variables.linear_inequality_upper_bounds")), in Constraints()
51 problem_db.get_rv("variables.linear_equality_targets")) in Constraints()
55 manage_linear_constraints(problem_db); // manage linear constraints in Constraints()
90 constraintsRep(get_constraints(problem_db, svd)) in Constraints()
106 return std::make_shared<MixedVarConstraints>(problem_db, svd); in get_constraints()
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| H A D | SharedSurfpackApproxData.cpp | 36 SharedSurfpackApproxData(ProblemDescDB& problem_db, size_t num_vars): in SharedSurfpackApproxData() argument
37 SharedApproxData(BaseConstructor(), problem_db, num_vars), in SharedSurfpackApproxData()
38 diagnosticSet(problem_db.get_sa("model.metrics")), in SharedSurfpackApproxData()
39 crossValidateFlag(problem_db.get_bool("model.surrogate.cross_validate")), in SharedSurfpackApproxData()
40 numFolds(problem_db.get_int("model.surrogate.folds")), in SharedSurfpackApproxData()
41 percentFold(problem_db.get_real("model.surrogate.percent")), in SharedSurfpackApproxData()
42 pressFlag(problem_db.get_bool("model.surrogate.press")) in SharedSurfpackApproxData()
46 approxOrder = problem_db.get_short("model.surrogate.polynomial_order"); in SharedSurfpackApproxData()
49 problem_db.get_string("model.surrogate.trend_order"); in SharedSurfpackApproxData()
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| H A D | CollabHybridMetaIterator.cpp | 23 CollabHybridMetaIterator::CollabHybridMetaIterator(ProblemDescDB& problem_db): in CollabHybridMetaIterator() argument
24 MetaIterator(problem_db), singlePassedModel(false) in CollabHybridMetaIterator()
29 = problem_db.get_sa("method.hybrid.method_pointers"); in CollabHybridMetaIterator()
31 = problem_db.get_sa("method.hybrid.method_names"); in CollabHybridMetaIterator()
37 modelStrings = problem_db.get_sa("method.hybrid.model_pointers"); in CollabHybridMetaIterator()
59 CollabHybridMetaIterator(ProblemDescDB& problem_db, Model& model): in CollabHybridMetaIterator() argument
60 MetaIterator(problem_db, model), singlePassedModel(true) in CollabHybridMetaIterator()
65 = problem_db.get_sa("method.hybrid.method_pointers"); in CollabHybridMetaIterator()
67 = problem_db.get_sa("method.hybrid.method_names"); in CollabHybridMetaIterator()
69 = problem_db.get_sa("method.hybrid.model_pointers"); in CollabHybridMetaIterator()
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| H A D | DakotaVariables.cpp | 42 Variables(BaseConstructor, const ProblemDescDB& problem_db, in Variables() argument
44 sharedVarsData(problem_db, view) in Variables()
77 Variables::Variables(const ProblemDescDB& problem_db): in Variables() argument
79 variablesRep(get_variables(problem_db)) in Variables()
90 Variables::get_variables(const ProblemDescDB& problem_db) in get_variables() argument
92 std::pair<short,short> view = get_view(problem_db); in get_variables()
146 Variables::get_view(const ProblemDescDB& problem_db) const in get_view()
169 short view_spec = problem_db.get_short("variables.view"), in get_view()
170 domain_spec = problem_db.get_short("variables.domain"); in get_view()
173 method_domain(problem_db) == RELAXED_DOMAIN ) ); in get_view()
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| H A D | library_mode.cpp | 339 Dakota::ProblemDescDB& problem_db = env.problem_description_db(); in run_dakota_mixed() local
341 problem_db.resolve_top_method(); // allow DB set/get operations in run_dakota_mixed()
343 = problem_db.get_sa("interface.application.analysis_drivers"); in run_dakota_mixed()
347 problem_db.set("variables.continuous_design.initial_point", ip); in run_dakota_mixed()
399 Dakota::ProblemDescDB& problem_db = env.problem_description_db(); in serial_interface_plugin() local
401 new SIM::SerialDirectApplicInterface(problem_db); in serial_interface_plugin()
431 Dakota::ProblemDescDB& problem_db = env.problem_description_db(); in parallel_interface_plugin() local
433 size_t model_index = problem_db.get_db_model_node(); // for restoration in parallel_interface_plugin()
436 problem_db.set_db_model_nodes(ml_iter->model_id()); in parallel_interface_plugin()
450 (problem_db, analysis_comm)); in parallel_interface_plugin()
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| H A D | SharedVariablesData.cpp | 48 initialize_components_totals(problem_db); in SharedVariablesDataRep()
51 initialize_all_labels(problem_db); in SharedVariablesDataRep()
333 const BitArray& ddrv_cat = problem_db.get_ba( in relax_noncategorical()
335 const BitArray& ddsiv_cat = problem_db.get_ba( in relax_noncategorical()
340 const BitArray& puv_cat = problem_db.get_ba( in relax_noncategorical()
342 const BitArray& biuv_cat = problem_db.get_ba( in relax_noncategorical()
344 const BitArray& nbuv_cat = problem_db.get_ba( in relax_noncategorical()
346 const BitArray& geuv_cat = problem_db.get_ba( in relax_noncategorical()
348 const BitArray& hguv_cat = problem_db.get_ba( in relax_noncategorical()
355 const BitArray& diuv_cat = problem_db.get_ba( in relax_noncategorical()
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| H A D | RelaxedVariables.cpp | 36 const RealVector& cdv = problem_db.get_rv( in RelaxedVariables()
38 const RealVector& cauv = problem_db.get_rv( in RelaxedVariables()
40 const RealVector& ceuv = problem_db.get_rv( in RelaxedVariables()
42 const RealVector& csv = problem_db.get_rv( in RelaxedVariables()
45 const IntVector& ddrv = problem_db.get_iv( in RelaxedVariables()
47 const IntVector& ddsiv = problem_db.get_iv( in RelaxedVariables()
49 const IntVector& dauiv = problem_db.get_iv( in RelaxedVariables()
51 const IntVector& deuiv = problem_db.get_iv( in RelaxedVariables()
53 const IntVector& dsrv = problem_db.get_iv( in RelaxedVariables()
55 const IntVector& dssiv = problem_db.get_iv( in RelaxedVariables()
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| H A D | NonDMultilevelFunctionTrain.cpp | 30 NonDMultilevelFunctionTrain(ProblemDescDB& problem_db, Model& model): in NonDMultilevelFunctionTrain() argument
31 NonDC3FunctionTrain(DEFAULT_METHOD, problem_db, model), in NonDMultilevelFunctionTrain()
33 problem_db.get_sza("method.nond.c3function_train.start_rank_sequence")), in NonDMultilevelFunctionTrain()
35 problem_db.get_usa("method.nond.c3function_train.start_order_sequence")), in NonDMultilevelFunctionTrain()
38 randomSeedSeqSpec = problem_db.get_sza("method.random_seed_sequence"); in NonDMultilevelFunctionTrain()
103 construct_expansion_sampler(problem_db.get_ushort("method.sample_type"), in NonDMultilevelFunctionTrain()
104 problem_db.get_string("method.random_number_generator"), in NonDMultilevelFunctionTrain()
105 problem_db.get_ushort("method.nond.integration_refinement"), in NonDMultilevelFunctionTrain()
106 problem_db.get_iv("method.nond.refinement_samples"), in NonDMultilevelFunctionTrain()
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| H A D | dakota_dll_api.cpp | 120 ProblemDescDB& problem_db = dakotaEnv->problem_description_db(); in initialize_names() local
123 const VariablesList& vlist = problem_db.variables_list(); in initialize_names()
156 const ResponseList& rlist = problem_db.response_list(); in initialize_names()
207 ProblemDescDB& problem_db = dakotaEnv->problem_description_db(); in start() local
208 ModelList& models = problem_db.model_list(); in start()
209 size_t model_index = problem_db.get_db_model_node(); // for restoration in start()
215 problem_db.set_db_model_nodes(ml_iter->model_id()); in start()
218 (problem_db)); in start()
221 problem_db.set_db_model_nodes(model_index); // restore in start()
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