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Searched refs:numContinuousVars (Results 1 – 25 of 60) sorted by relevance

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/dports/science/dakota/dakota-6.13.0-release-public.src-UI/src/
H A DFSUDesignCompExp.cpp60 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()
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H A DPSUADEDesignCompExp.cpp109 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()
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H A DDDACEDesignCompExp.cpp54 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()
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H A DNonDQUESOBayesCalibration.cpp555 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()
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H A DNonDMUQBayesCalibration.cpp118 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()
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H A DNonDQuadrature.cpp175 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()
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H A DDakotaLeastSq.cpp266 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()
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H A DNonDGPMSABayesCalibration.cpp452 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()
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H A DNonDBayesCalibration.hpp548 << 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()
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H A DNomadOptimizer.cpp157 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()
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H A DParamStudy.cpp278 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()
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H A DCONMINOptimizer.cpp207 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()
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H A DSNLLOptimizer.cpp131 = 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()
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H A DParamStudy.hpp288 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()
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H A DNonDWASABIBayesCalibration.cpp102 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()
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H A DSurrBasedMinimizer.cpp267 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()
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H A DDakotaMinimizer.cpp143 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()
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H A DNonDDREAMBayesCalibration.cpp196 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()
H A DNLPQLPOptimizer.cpp167 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()
H A DNPSOLOptimizer.cpp151 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()
H A DNonDLocalReliability.cpp537 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()
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H A DNonDPolynomialChaos.cpp543 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()
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H A DNLSSOLLeastSq.cpp161 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()
H A DDakotaAnalyzer.cpp83 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()
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H A DDakotaOptimizer.cpp64 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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