/dports/science/dakota/dakota-6.13.0-release-public.src-UI/src/ |
H A D | FSUDesignCompExp.cpp | 60 sequenceStart.resize(numContinuousVars); in FSUDesignCompExp() 68 sequenceLeap.resize(numContinuousVars); in FSUDesignCompExp() 76 primeBase.resize(numContinuousVars); in FSUDesignCompExp() 78 for (size_t i=0; i<numContinuousVars; i++) in FSUDesignCompExp() 82 for (size_t i=1; i<numContinuousVars; i++) in FSUDesignCompExp() 98 primeBase.resize(numContinuousVars); in FSUDesignCompExp() 142 sequenceStart.resize(numContinuousVars); in FSUDesignCompExp() 144 sequenceLeap.resize(numContinuousVars); in FSUDesignCompExp() 146 primeBase.resize(numContinuousVars); in FSUDesignCompExp() 272 for (i=0; i<numContinuousVars; i++) { in get_parameter_sets() [all …]
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H A D | PSUADEDesignCompExp.cpp | 109 psuade_adata.nInputs_ = numContinuousVars; in post_run() 118 for (int i=0; i<numContinuousVars; i++) { in post_run() 126 for (int j=0; j<numContinuousVars; j++) in post_run() 181 c_u_bnds.length() != numContinuousVars) { in get_parameter_sets() 187 RealVector c_bnds_range(numContinuousVars); in get_parameter_sets() 189 for (i=0; i<numContinuousVars; i++) { in get_parameter_sets() 253 for (i=0; i<numContinuousVars; i++) { in get_parameter_sets() 269 for (j=0; j<numContinuousVars; ++j) in get_parameter_sets() 282 if (i>0 && i%(numContinuousVars+1) == 0) in get_parameter_sets() 298 numSamples = 10*(numContinuousVars+1); in enforce_input_rules() [all …]
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H A D | DDACEDesignCompExp.cpp | 54 maxEvalConcurrency *= 1 + 4*numContinuousVars*(numContinuousVars-1)/2; in DDACEDesignCompExp() 56 maxEvalConcurrency *= 1 + 2*numContinuousVars in DDACEDesignCompExp() 239 for (int j=0; j<numContinuousVars; ++j) in get_parameter_sets() 248 for (int i=0; i<numContinuousVars; i++) { in get_parameter_sets() 252 dace_points[i+j*numContinuousVars] in get_parameter_sets() 279 for (int i=0; i<numContinuousVars; i++) { in create_sampler() 290 for (int i=0; i<numContinuousVars; i++) in create_sampler() 429 int num_samples_bb = 1 + 4*numContinuousVars*(numContinuousVars-1)/2; in resolve_samples_symbols() 450 = 1 + 2*numContinuousVars + (int)std::pow(2.0,(double)numContinuousVars); in resolve_samples_symbols() 477 1./(double)numContinuousVars)); in resolve_samples_symbols() [all …]
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H A D | NonDQUESOBayesCalibration.cpp | 555 numContinuousVars + numHyperparams); in cache_chain() 559 numContinuousVars); in cache_chain() 876 for (size_t i=0; i<numContinuousVars; ++i) { in init_parameter_domain() 922 (*proposalCovMatrix)(numContinuousVars + i, numContinuousVars + i) = in init_proposal_covariance() 950 for (int i=0; i<numContinuousVars; ++i) in prior_proposal_covariance() 1046 for( int i=0; i<numContinuousVars; ++i ) in user_proposal_covariance() 1062 for( int i=0; i<numContinuousVars; ++i ) in user_proposal_covariance() 1068 if( numContinuousVars*numContinuousVars != cov_data.length() ) in user_proposal_covariance() 1072 for( int i=0; i<numContinuousVars; ++i ) in user_proposal_covariance() 1303 for (size_t j=0; j<numContinuousVars; ++j) in print_variables() [all …]
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H A D | NonDMUQBayesCalibration.cpp | 118 size_t i, num_cv = numContinuousVars; in calibrate() 213 RealVector mcmc_rv(numContinuousVars, false); in log_best() 224 for (int j=0; j<numContinuousVars; ++j) in log_best() 297 for (size_t j=0; j<numContinuousVars; ++j) in print_variables() 303 << c_vars[numContinuousVars+j] << ' ' in print_variables() 344 RealVector u_rv(numContinuousVars, false); in cache_chain() 345 for (int j=0; j<numContinuousVars; ++j) in cache_chain() 351 for (int j=numContinuousVars; j<num_params; ++j){ in cache_chain() 367 numContinuousVars + numHyperparams); in cache_chain() 368 for (int j=0; j<numContinuousVars; ++j){ in cache_chain() [all …]
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H A D | NonDQuadrature.cpp | 175 for (size_t i=0; i<numContinuousVars; ++i) { in initialize_grid() 214 numContinuousVars, ref_quad_order); in initialize_dimension_quadrature_order() 248 for (i=0; i<numContinuousVars; ++i) in get_parameter_sets() 288 for (i=0; i<numContinuousVars; ++i) in get_parameter_sets() 292 for (i=0; i<numContinuousVars; ++i) { in get_parameter_sets() 301 for (j=0; j<numContinuousVars; ++j) in get_parameter_sets() 315 for (j=0; j<numContinuousVars; ++j) in get_parameter_sets() 435 for (size_t i=0; i<numContinuousVars; ++i) in increment_reference_quadrature_order() 448 for (size_t i=1; i<numContinuousVars; ++i) in increment_reference_quadrature_order() 470 for (size_t i=1; i<numContinuousVars; ++i) { in update_anisotropic_order() [all …]
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H A D | DakotaLeastSq.cpp | 266 for (size_t i = 0; i < numContinuousVars; i++) in print_results() 472 (int)numContinuousVars, (int)numLeastSqTerms); in post_run() 523 (int)numContinuousVars, (int)numLeastSqTerms); in post_run() 579 if (numLeastSqTerms < numContinuousVars) { in get_confidence_intervals() 608 int N = numContinuousVars; in get_confidence_intervals() 635 for (int j=0; j<numContinuousVars; j++) in get_confidence_intervals() 659 RealVector standard_error(numContinuousVars); in get_confidence_intervals() 660 RealVector diag(numContinuousVars, true); in get_confidence_intervals() 661 for (int i=0; i<numContinuousVars; i++) { in get_confidence_intervals() 662 for (int j=i; j<numContinuousVars; j++) in get_confidence_intervals() [all …]
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H A D | NonDGPMSABayesCalibration.cpp | 452 numContinuousVars + userConfigVars + numFunctions); in acquire_simulation_data() 470 for (int j=0; j<numContinuousVars; ++j) in acquire_simulation_data() 473 sim_data(i, numContinuousVars + j) = in acquire_simulation_data() 474 all_samples(numContinuousVars + j, i); in acquire_simulation_data() 476 sim_data(i, numContinuousVars + userConfigVars + j) = in acquire_simulation_data() 488 numContinuousVars + numFunctions : in acquire_simulation_data() 492 << "'\n with " << numContinuousVars in acquire_simulation_data() 530 for (int j=0; j<numContinuousVars; ++j) in fill_simulation_data() 541 sim_data(i, numContinuousVars + userConfigVars + j); in fill_simulation_data() 610 int num_params = numContinuousVars + numHyperparams; in cache_acceptance_chain() [all …]
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H A D | NonDBayesCalibration.hpp | 548 << numContinuousVars << " provided." << std::endl; in prior_density() 574 pdf *= invGammaDists[i].pdf(vec[numContinuousVars + i]); in prior_density() 629 << numContinuousVars << " provided." << std::endl; in log_prior_density() 706 for (size_t i=0; i<numContinuousVars; ++i) in prior_sample() 729 for (size_t i=0; i<numContinuousVars; ++i) in prior_mean() 748 for (size_t i=0; i<numContinuousVars; ++i) in prior_variance() 759 for (i=0; i<numContinuousVars; ++i) { in prior_variance() 773 for (size_t i=0; i<numContinuousVars; ++i) in prior_variance() 779 var_mat(numContinuousVars + i, numContinuousVars + i) = in prior_variance() 796 for (size_t i=0; i<numContinuousVars; ++i) in augment_gradient_with_log_prior() [all …]
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H A D | NomadOptimizer.cpp | 157 numTotalVars = numContinuousVars + numDiscreteIntVars in core_run() 273 RealVector contVars(numContinuousVars); in core_run() 284 for(j=0; j<numContinuousVars; j++) in core_run() 299 discIntVars[j] = (*bestX)[j+numContinuousVars].value(); in core_run() 655 for(i=0;i<numContinuousVars;i++) in load_parameters() 687 _initial_point[i+numContinuousVars] = (int)index; in load_parameters() 713 p.set_BB_INPUT_TYPE(i+numContinuousVars,NOMAD::INTEGER); in load_parameters() 714 _lower_bound[i+numContinuousVars] = 0; in load_parameters() 715 _upper_bound[i+numContinuousVars] = in load_parameters() 724 _lower_bound[i+numContinuousVars] = lower_bound_int[i]; in load_parameters() [all …]
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H A D | ParamStudy.cpp | 278 if( numContinuousVars ) in archive_model_variables() 339 if( numContinuousVars ) { in archive_allocate_sets() 423 if (numContinuousVars) in sample() 458 for (j=0; j<numContinuousVars; ++j) in vector_loop() 500 if (numContinuousVars) in centered_loop() 841 if (numContinuousVars) in distribute_list_of_points() 933 if (numContinuousVars) in distribute_partitions() 970 for (j=0; j<numContinuousVars; ++j) in final_point_to_step_vector() 1011 if (numContinuousVars) in final_point_to_step_vector() 1204 if (var_idx < numContinuousVars) { in archive_cps_vars() [all …]
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H A D | CONMINOptimizer.cpp | 207 N1 = numContinuousVars + 2; in allocate_workspace() 208 N2 = numContinuousVars*2 + numConminConstr; in allocate_workspace() 214 N3 = 1 + numConminConstr + numContinuousVars; in allocate_workspace() 215 N4 = (N3 >= numContinuousVars) ? N3 : numContinuousVars; // always N3 in allocate_workspace() 283 for (i=0; i<numContinuousVars; i++) { in initialize_run() 289 for (i=numContinuousVars; i<N1; i++) in initialize_run() 297 int num_cv = numContinuousVars; in core_run() 309 for (i=0; i<numContinuousVars; i++) { in core_run() 337 RealVector local_cdv(numContinuousVars); in core_run() 468 for (j=0; j<numContinuousVars; j++) in core_run() [all …]
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H A D | SNLLOptimizer.cpp | 131 = new OPTPP::FDNLF1(numContinuousVars, numNonlinearConstraints, in SNLLOptimizer() 145 if (numContinuousVars < LARGE_SCALE) { in SNLLOptimizer() 176 = new OPTPP::FDNLF1(numContinuousVars, numNonlinearConstraints, in SNLLOptimizer() 250 snll_post_instantiate(numContinuousVars, vendorNumericalGradFlag, in SNLLOptimizer() 285 snll_post_instantiate(numContinuousVars, vendorNumericalGradFlag, in SNLLOptimizer() 317 for (size_t i=0; i<numContinuousVars; i++) in SNLLOptimizer() 368 for (size_t i=0; i<numContinuousVars; i++) in SNLLOptimizer() 418 = new OPTPP::NLF1(numContinuousVars, obj_eval, init_fn); in default_instantiate_q_newton() 429 = new OPTPP::NLF1(numContinuousVars, numNonlinearConstraints, in default_instantiate_q_newton() 441 if (numContinuousVars < LARGE_SCALE) { in default_instantiate_q_newton() [all …]
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H A D | ParamStudy.hpp | 288 c_data.sizeUninitialized(numContinuousVars); in distribute() 365 size_t num_vars = numContinuousVars + numDiscreteIntVars in distribute() 372 c_data.resize(numContinuousVars); in distribute() 500 numContinuousVars); in check_steps_per_variable() 502 numContinuousVars + numDiscreteIntVars); in check_steps_per_variable() 504 numContinuousVars + numDiscreteIntVars + in check_steps_per_variable() 526 for (i=0; i<numContinuousVars; ++i) in check_steps_per_variable() 549 contVarPartitions.assign(numContinuousVars, part); in check_variable_partitions() 561 for (i=0; i<numContinuousVars; ++i) in check_variable_partitions() 580 if (numContinuousVars) { in check_finite_bounds() [all …]
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H A D | NonDWASABIBayesCalibration.cpp | 102 paramMins.size(numContinuousVars); in calibrate() 103 paramMaxs.size(numContinuousVars); in calibrate() 108 for (size_t i=0; i<numContinuousVars; ++i) { in calibrate() 130 RealMatrix samples_from_prior((int)numContinuousVars, numPushforwardSamples, false); in calibrate() 133 RealVector samp_j(Teuchos::View, samples_from_prior[j], numContinuousVars); in calibrate() 192 numContinuousVars); in calibrate() 373 numContinuousVars + 1 ); in extract_selected_posterior_samples() 375 num_points_to_keep, numContinuousVars ); in extract_selected_posterior_samples() 377 for (size_t j=0;j<numContinuousVars;j++) in extract_selected_posterior_samples() 381 posterior_data[numContinuousVars], in extract_selected_posterior_samples() [all …]
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H A D | SurrBasedMinimizer.cpp | 267 int mda = numContinuousVars, mode; in update_lagrange_multipliers() 268 RealVector zz(numContinuousVars); in update_lagrange_multipliers() 472 for (j=0; j<numContinuousVars; j++) in lagrangian_gradient() 523 for (j=0; j<numContinuousVars; j++) in lagrangian_hessian() 609 for (j=0; j<numContinuousVars; j++) in augmented_lagrangian_gradient() 618 for (j=0; j<numContinuousVars; j++) in augmented_lagrangian_gradient() 630 for (j=0; j<numContinuousVars; j++) in augmented_lagrangian_gradient() 670 for (j=0; j<numContinuousVars; j++) in augmented_lagrangian_hessian() 681 for (j=0; j<numContinuousVars; j++) in augmented_lagrangian_hessian() 738 for (j=0; j<numContinuousVars; j++) in penalty_gradient() [all …]
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H A D | DakotaMinimizer.cpp | 143 if (!numContinuousVars) { in update_from_model() 250 for (i=0; i<numContinuousVars; ++i) in update_from_model() 597 for (j=0; j<numContinuousVars; ++j) in objective_hessian() 601 for (j=0; j<numContinuousVars; ++j) in objective_hessian() 613 for (j=0; j<numContinuousVars; ++j) in objective_hessian() 631 for (j=0; j<numContinuousVars; ++j) in objective_hessian() 639 for (j=0; j<numContinuousVars; ++j) in objective_hessian() 650 for (j=0; j<numContinuousVars; ++j) in objective_hessian() 659 for (j=0; j<numContinuousVars; ++j) in objective_hessian() 692 if(numContinuousVars) { in archive_best_variables() [all …]
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H A D | NonDDREAMBayesCalibration.cpp | 196 int total_num_params = numContinuousVars + numHyperparams; in calibrate() 208 for (size_t i=0; i<numContinuousVars; ++i) { in calibrate() 217 paramMins[numContinuousVars + i] = .01; in calibrate() 218 paramMaxs[numContinuousVars + i] = 2.; in calibrate() 342 par_num = nonDDREAMInstance->numContinuousVars + in problem_size() 444 nonDDREAMInstance->numContinuousVars + nonDDREAMInstance->numHyperparams; in cache_chain() 482 numContinuousVars); in archive_acceptance_chain() 484 numContinuousVars); in archive_acceptance_chain() 496 numContinuousVars); in archive_acceptance_chain()
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H A D | NLPQLPOptimizer.cpp | 167 N = numContinuousVars; in allocate_workspace() 221 for (size_t i=0; i<numContinuousVars; i++) in initialize_run() 298 for (j=0; j<numContinuousVars; j++) in core_run() 319 for (j=0; j<numContinuousVars; j++) in core_run() 330 for (j=0; j<numContinuousVars; j++) in core_run() 333 for (j=0; j<numContinuousVars; j++) in core_run() 339 for (j=0; j<numContinuousVars; j++) in core_run() 344 for (j=0; j<numContinuousVars; j++) in core_run() 362 for (j=0; j<numContinuousVars; j++) in core_run() 377 for (j=0; j<numContinuousVars; j++) in core_run()
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H A D | NPSOLOptimizer.cpp | 151 allocate_arrays(numContinuousVars, numNonlinearConstraints, lin_ineq_coeffs, in NPSOLOptimizer() 153 allocate_workspace(numContinuousVars, numNonlinearConstraints, in NPSOLOptimizer() 214 allocate_arrays(numContinuousVars, numNonlinearConstraints, lin_ineq_coeffs, in NPSOLOptimizer() 216 allocate_workspace(numContinuousVars, numNonlinearConstraints, in NPSOLOptimizer() 437 int num_cv = numContinuousVars; in find_optimum_on_model() 442 RealVector local_f_grad(numContinuousVars, true); in find_optimum_on_model() 444 allocate_arrays(numContinuousVars, numNonlinearConstraints, in find_optimum_on_model() 447 allocate_workspace(numContinuousVars, numNonlinearConstraints, in find_optimum_on_model() 535 int num_cv = numContinuousVars; in find_optimum_on_user_functions() 540 RealVector local_f_grad(numContinuousVars, true); in find_optimum_on_user_functions()
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H A D | NonDLocalReliability.cpp | 537 for (i=0; i<numContinuousVars; i++) in initialize_graphics() 612 (numContinuousVars * (numContinuousVars+1)) / 2 : numContinuousVars; in mean_value() 645 numContinuousVars); in mean_value() 687 for (i=0, cntr=numContinuousVars; i<numContinuousVars; ++i) { in mean_value() 697 for (i=0; i<numContinuousVars; ++i) in mean_value() 856 for (i=0; i<numContinuousVars; i++) in mpp_search() 1155 for (j=0; j<numContinuousVars; ++j) { in initial_taylor_series() 1299 for (i=0; i<numContinuousVars; i++) in initialize_level_data() 2451 num_kappa = numContinuousVars - 1; in dp2_dbeta_factor() 2808 for (j=0; j<numContinuousVars; j++) in print_results() [all …]
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H A D | NonDPolynomialChaos.cpp | 543 Pecos::inflate_scalar(dim_quad_order, numContinuousVars); in config_regression() 554 dim_quad_order.resize(numContinuousVars); in config_regression() 555 for (size_t i=0; i<numContinuousVars; ++i) in config_regression() 897 multi_index, tabular_format, numContinuousVars, in compute_expansion() 938 for (int i=0; i<numContinuousVars; ++i) in select_refinement_points() 1047 for (j=0; j<numContinuousVars; ++j) in select_refinement_points_deprecated() 1097 exp_order.assign(numContinuousVars, 0); in ratio_samples_to_order() 1102 num_samples * (numContinuousVars + 1) : num_samples; in ratio_samples_to_order() 1111 for (i=0; i<numContinuousVars; ++i) in ratio_samples_to_order() 1122 for (i=0; i<numContinuousVars; ++i) in ratio_samples_to_order() [all …]
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H A D | NLSSOLLeastSq.cpp | 161 int num_cv = numContinuousVars; in core_run() 169 double* local_lsq_grads = new double [numLeastSqTerms*numContinuousVars]; in core_run() 171 allocate_arrays(numContinuousVars, numNonlinearConstraints, in core_run() 174 allocate_workspace(numContinuousVars, numNonlinearConstraints, in core_run()
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H A D | DakotaAnalyzer.cpp | 83 numContinuousVars = iteratedModel.cv(); in resize() 96 numContinuousVars = model.cv(); numDiscreteIntVars = model.div(); in update_from_model() 122 if (!numContinuousVars) { in update_from_model() 307 for (size_t i=0; i<numContinuousVars; ++i) in sample_to_variables() 339 for (size_t i=0; i<numContinuousVars; ++i) in variables_to_sample() 350 if (sample_matrix.numRows() != numContinuousVars || in variables_array_to_samples() 371 size_t num_vars = numContinuousVars + numDiscreteIntVars + in get_vbd_parameter_sets() 793 for (i=0; i<numContinuousVars; ++i) { in print_sobol_indices() 800 offset = numContinuousVars; in print_sobol_indices() 840 for (i=0; i<numContinuousVars; ++i) { in archive_sobol_indices() [all …]
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H A D | DakotaOptimizer.cpp | 64 for (size_t i=0; i<numContinuousVars; ++i) in Optimizer() 162 numContinuousVars = num_cv; in Optimizer() 179 activeSet.reshape(numFunctions, numContinuousVars); in Optimizer() 211 ActiveSet search_set(orig_model.response_size(), numContinuousVars); in print_results() 308 Sizet2DArray var_map_indices(numContinuousVars), in reduce_model() 314 for (i=0; i<numContinuousVars; i++) { in reduce_model() 396 recast_resp.reshape(num_recast_fns, numContinuousVars, true, true); in reduce_model()
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