API#
- Alchemy
- Analysis
gdml_mat52
gdml_mat52_wrk
RDF
ProblematicStructures
ProblematicStructures
ProblematicStructures.course_n_cl_e
ProblematicStructures.course_n_cl_r
ProblematicStructures.find()
ProblematicStructures.get_pd()
ProblematicStructures.kwargs_subplot
ProblematicStructures.loss_func
ProblematicStructures.loss_func_kwargs
ProblematicStructures.n_cl_samples()
ProblematicStructures.plot_annotate_cl_idx
ProblematicStructures.plot_cl_losses()
ProblematicStructures.plot_lolli_color
ProblematicStructures.prob_cl_indices()
ProblematicStructures.refine_min_r_ratio
ProblematicStructures.refine_n_cl
ProblematicStructures.select_prob_indices()
- Data sets
DataSet
DataSet.E
DataSet.E_max
DataSet.E_mean
DataSet.E_min
DataSet.E_var
DataSet.F
DataSet.F_max
DataSet.F_mean
DataSet.F_min
DataSet.F_var
DataSet.asdict()
DataSet.comp_ids
DataSet.convertE()
DataSet.convertF()
DataSet.convertR()
DataSet.e_unit
DataSet.entity_ids
DataSet.load()
DataSet.mb
DataSet.mb_dsets_md5
DataSet.mb_models_md5
DataSet.md5
DataSet.name
DataSet.print()
DataSet.r_prov_ids
DataSet.r_prov_specs
DataSet.theory
DataSet.write_xyz()
- Descriptors
- GDML
- Interfaces
- Logger
- Losses
- MBE
- Models
- Prediction Sets
- Periodic
- Predictors
- Stress
- Structure generation
- Switching functions
- Training
mbGDMLTrain
mbGDMLTrain
mbGDMLTrain.active_train()
mbGDMLTrain.bayes_opt()
mbGDMLTrain.bayes_opt_n_check_rising
mbGDMLTrain.bayes_opt_params
mbGDMLTrain.bayes_opt_params_final
mbGDMLTrain.check_energy_pred
mbGDMLTrain.create_task()
mbGDMLTrain.grid_search()
mbGDMLTrain.keep_tasks
mbGDMLTrain.loss_func
mbGDMLTrain.loss_kwargs
mbGDMLTrain.min_memory_analytic()
mbGDMLTrain.plot_bayes_opt_gp()
mbGDMLTrain.require_E_eval
mbGDMLTrain.save_idxs()
mbGDMLTrain.save_valid_csv()
mbGDMLTrain.sigma_bounds
mbGDMLTrain.sigma_grid
mbGDMLTrain.test_model()
mbGDMLTrain.train_model()
- Utilities