Breakdown of Basico

1. array_tools.py
   1. compartment_names(**kwargs)
   2. remove_template(**kwargs)
   3. remove_arrays(**kwargs):
   4. plot_arrays_1d(df, species, **kwargs)
2. biomodels.py
   1. download_from(url)
   2. download_json(url)
   3. get_model_info(model_id)
   4. get_files_for_model(model_id)
   5. get_content_for_model(model_id, file_name=None)
   6. search_for_model(query, offset=0, num_results=10, sort='id-asc')
3. compartment_array_tools.py
   1. plot_linear_time_course(data, prefix=None, metab_names=None, shading='gouraud', min_range=np.nan, max_range=np.nan, **kwargs)
   2. _split_ranges(names)
   3. plot_rectangular_time_course(data, times=None, prefix=None, shading='gouraud', min_range=np.nan, max_range=np.nan, **kwargs)
   4. _extract_metabolite_data(cur, metab, prefix, x_range, y_range)
   5. animate_rectangular_time_course_as_image(data, metabs=None, prefix=None, min_range=np.nan, max_range=np.nan, filename=None, **kwargs)
   6. _create_image(metab_data, vmax)
   7. _get_ranges(arr, min_range=np.nan, max_range=np.nan, vmin=np.inf, vmax=-np.inf)
   8. animate_rectangular_time_course(data, metab=None, prefix=None, shading='gouraud', min_range=np.nan, max_range=np.nan, filename=None, **kwargs)
   9. delete_compartments(selection, **kwargs)
   10. _create_array(dm, num_steps_x, num_steps_y, linear=True, species=None, diffusion_coefficients=None, compartment_names=None, delete_template=False)
   11. create_linear_array(num_steps, species=None, diffusion_coefficients=None, compartment_names=None, delete_template=False, **kwargs)
   12. create_rectangular_array(num_steps_x, num_steps_y, species=None, diffusion_coefficients=None, compartment_names=None, delete_template=False, **kwargs)
4. jws_online.py
   1. download_from(url)
   2. download_json(url)
   3. get_model_info(model_id)
   4. get_sbml_model(model_id)
   5. get_mathematica_model(model_id)
   6. get_manuscript(model_id)
   7. get_models_for_species(species)
   8. get_models_for_reaction(reaction)
   9. get_all_models()
5. model_info.py
   1. T class
      1. _create_name_map(cls)
      2. _create_value_map(cls)
      3. from_enum(cls, int_value)
      4. to_enum(cls, value)
      5. all_task_names(cls)
   2. __status_to_int(status)
   3. __status_to_string(status)
   4. __xml_task_type_to_string(type)
   5. __task_name_to_xml_type(name)
   6. __line_type_to_int(line_type)
   7. __line_type_to_string(line_type)
   8. __line_subtype_to_int(sub_type)
   9. __line_subtype_to_string(sub_type)
   10. __symbol_to_int(symbol_type)
   11. __symbol_to_string(symbol_type)
   12. __curve_type_to_int(curve_type)
   13. __curve_type_to_string(curve_type)
   14. __function_type_to_int(function_type)
   15. __function_type_to_string(function_type)
   16. __usage_to_int(usage)
   17. __usage_to_string(usage)
   18. get_species(name=None, exact=False, **kwargs)
   19. get_events(name=None, exact=False, **kwargs)
   20. get_plots(name=None, **kwargs)
   21. get_reports(name=None, ignore_automatic=False, task=None, **kwargs)
   22. get_report_dict(report, **kwargs)
   23. _add_report_items_to_list(result, num_elements, get_nth_function, dm)
   24. get_plot_dict(plot_spec, **kwargs)
   25. set_plot_curves(plot_spec, curves, **kwargs)
   26. add_plot(name, **kwargs)
   27. add_default_plot(name, **kwargs)
   28. get_default_plot_names(filter=None, **kwargs)
   29. set_plot_dict(plot_spec, active=True, log_x=False, log_y=False, tasks='', **kwargs)
   30. add_report(name, **kwargs)
   31. set_report_dict(spec, precision=None, separator=None, table=None, print_headers=True, header=None, body=None, footer=None, task=None, comment=None, **kwargs)
   32. _set_report_vector(vec, list_of_cns, dm)
   33. _replace_names_with_cns(expression, **kwargs)
   34. _split_by_cn(expression)
   35. _replace_cns_with_names(expression, **kwargs)
   36. set_notes(notes, **kwargs)
   37. get_notes(**kwargs)
   38. get_miriam_annotation(**kwargs)
   39. set_miriam_annotation(created=None, creators=None, references=None, descriptions=None, modifications=None, replace=True, **kwargs)
   40. _remove_modifications(info)
   41. _remove_descriptions(info)
   42. _remove_references(info)
   43. _remove_creators(info)
   44. add_compartment(name, initial_size=1.0, **kwargs)
   45. add_function(name, infix, type='general', mapping=None, **kwargs)
   46. remove_function(name, **kwargs)
   47. remove_user_defined_functions()
   48. add_species(name, compartment_name='', initial_concentration=1.0, **kwargs)
   49. add_parameter(name, initial_value=1.0, **kwargs)
   50. add_event(name, trigger, assignments, **kwargs)
   51. set_event(name, exact=False, trigger=None, assignments=None, **kwargs)
   52. add_event_assignment(name, assignment, exact=False, **kwargs)
   53. add_reaction(name, scheme, **kwargs)
   54. get_compartments(name=None, exact=False, **kwargs)
   55. get_parameters(name=None, exact=False, **kwargs)
   56. get_functions(name=None, **kwargs)
   57. get_reaction_parameters(name=None, **kwargs)
   58. get_reactions(name=None, exact=False, **kwargs)
   59. get_time_unit(**kwargs)
   60. set_compartment(name=None, exact=False, **kwargs)
   61. _set_initial_expression(element, expression)
   62. _set_expression(element, expression)
   63. _set_safe(fun, expression)
   64. set_parameters(name=None, exact=False, **kwargs)
   65. set_reaction_parameters(name=None, **kwargs)
   66. set_reaction(name=None, exact=False, **kwargs)
   67. get_reaction_mapping(reaction, **kwargs)
   68. set_reaction_mapping(reaction, mapping, **kwargs)
   69. remove_species(name, **kwargs)
   70. remove_parameter(name, **kwargs)
   71. remove_compartment(name, **kwargs)
   72. remove_event(name, **kwargs)
   73. remove_plot(name, **kwargs)
   74. remove_report(name, **kwargs)
   75. remove_reaction(name, **kwargs)
   76. set_species(name=None, exact=False, **kwargs)
   77. set_time_unit(unit, **kwargs)
   78. get_model_units(**kwargs)
   79. set_element_name(element, new_name, **kwargs)
   80. set_model_unit(**kwargs)
   81. set_model_name(new_name, **kwargs)
   82. add_amount_expressions(**kwargs)
   83. remove_amount_expressions(**kwargs)
   84. have_miriam_resources()
   85. get_miriam_resources()
   86. update_miriam_resources()
   87. _is_number(x)
   88. _tokenize_eqn(eqn)
   89. _store_variable(parameters, species, tokens, var, var_is_initial, var_is_species)
   90. add_equation(eqn, time_symbol='t', **kwargs)
   91. _annotated_matrix_to_df(ann_matrix)
   92. get_stoichiometry_matrix(**kwargs)
   93. get_reduced_stoichiometry_matrix(**kwargs)
   94. get_jacobian_matrix(apply_initial_values=False, **kwargs)
   95. get_reduced_jacobian_matrix(apply_initial_values=False, **kwargs)
   96. _get_group_as_dict(group, basic_only=True)
   97. _set_group_from_dict(group, values)
   98. get_task_settings(task, basic_only=True, **kwargs)
   99. set_task_settings(task, settings, **kwargs)
   100. _collect_data(names=None, cns=None, **kwargs)
   101. _get_value_from_reference(obj)
   102. _get_named_value(obj, name)
   103. _get_object(name_or_reference, **kwargs)
   104. get_value(name_or_reference, **kwargs)
   105. get_cn(name_or_reference, **kwargs)
   106. assign_report(name, task, filename='', append=True, confirm_overwrite=True, **kwargs)
   107. remove_report_from_task(task, **kwargs)
   108. get_scheduled_tasks(**kwargs)
   109. set_scheduled_tasks(task_name, **kwargs)
6. model_io.py
   1. set_current_model(model)
   2. get_current_model()
   3. create_datamodel()
   4. remove_datamodel(model)
   5. get_num_loaded_models()
   6. new_model(**kwargs)
   7. load_model_from_string(content)
   8. load_model_from_url(url)
   9. load_model(location)
   10. load_biomodel(model_id)
   11. get_examples(selector='')
   12. load_example(selector)
   13. overview(model=None)
   14. print_model(model=None)
   15. save_model(filename, **kwargs)
   16. save_model_to_string(**kwargs)
   17. save_model_and_data(filename, **kwargs)
   18. open_copasi(filename='', **kwargs)
   19. __cleanup()
7. task_optimization.py
   1. get_opt_parameters(model=None)
   2. set_opt_parameters(opt_parameters, model=None)
   3. get_opt_item_template(include_local=False, include_global=False, default_lb=0.001, default_ub=1000, model=None)
   4. set_objective_function(expression, maximize=None, minimize=None, model=None)
   5. get_opt_settings(model=None, basic_only=True)
   6. set_opt_settings(settings, model=None)
   7. get_opt_solution(model=None)
   8. run_optimization(expression=None, output=None, settings=None, **kwargs)
   9. get_opt_statistic(**kwargs)
8. task_parameterestimation.py
   1. PE class
      1. _create_name_map(cls)
      2. _create_value_map(cls)
      3. from_enum(cls, int_value)
      4. to_enum(cls, value)
      5. all_method_names(cls)
   2. num_experiment_files(**kwargs)
   3. get_experiment_names(**kwargs)
   4. _get_experiment_keys(**kwargs)
   5. num_validations_files(**kwargs)
   6. _role_to_string(role)
   7. get_experiment(experiment, **kwargs)
   8. get_experiment_mapping(experiment, **kwargs)
   9. _get_experiment_file(experiment)
   10. get_data_from_experiment(experiment, **kwargs)
   11. get_experiment_data_from_model(model=None)
   12. get_experiment_filenames(model=None)
   13. get_fit_item_template(include_local=False, include_global=False, default_lb=0.001, default_ub=1000, model=None)
   14. get_fit_parameters(model=None)
   15. set_fit_parameters(fit_parameters, model=None)
   16. _get_name_for_key(key)
   17. _get_affected_experiments(optitem)
   18. get_parameters_solution(model=None)
   19. _get_role_for_reference(reference_name)
   20. add_experiment(name, data, **kwargs)
   21. run_parameter_estimation(**kwargs)
   22. get_simulation_results(values_only=False, **kwargs)
   23. _update_fit_parameters_from(dm, solution, exp_name='')
   24. plot_per_experiment(**kwargs)
   25. plot_per_dependent_variable(**kwargs)
   26. prune_simulation_results(simulation_results)
   27. get_fit_statistic(**kwargs)
   28. remove_experiments(**kwargs)
   29. remove_fit_parameters(**kwargs)
9. task_scan.py
   1. _scan_type_to_name(type)
   2. _name_to_scan_type(name)
   3. _scan_distribution_type_to_name(type)
   4. _name_to_scan_distribution_type(name)
   5. get_scan_items_frame(**kwargs)
   6. get_scan_items(**kwargs)
   7. _scan_item_to_dict(item, model=None)
   8. get_scan_settings(**kwargs)
   9. _set_parameter_from_value(parameter, value)
   10. _set_parameter_from_dict(parameter, values_dict, key)
   11. add_scan_item(**kwargs)
   12. set_scan_items(scan_items, **kwargs)
   13. set_scan_settings(**kwargs)
   14. run_scan(**kwargs)
10. task_sensitivities.py
    1. EnumHelper class
       1. _create_name_map(cls)
       2. _create_value_map(cls)
       3. _convert_names_to_values(cls)
       4. from_enum(cls, int_value)
       5. to_enum(cls, value)
       6. get_all_names(cls)
    2. SENS(EnumHelper) class
       1. _create_name_map(cls)
    3. SENS_ST(EnumHelper) class
       1. _create_name_map(cls)
       2. _create_value_map(cls)
    4. get_sensitivity_settings(basic_only=True, **kwargs)
    5. set_sensitivity_settings(settings, **kwargs)
    6. _to_sens_item(name, model)
    7. _get_name_for_item(item, model)
    8. run_sensitivities(**kwargs)
    9. get_scaled_sensitivities(**kwargs)
    10. get_unscaled_sensitivities(**kwargs)
    11. get_summarized_sensitivities(**kwargs)
11. task_steadystate.py
    1. run_steadystate(**kwargs)'
12. task_timecourse.py
    1. __build_result_from_ts(time_series, use_concentrations=True, use_sbml_id=False, model=None)
    2. __method_name_to_type(method_name)
    3. run_time_course_with_output(output_selection, *args, **kwargs)
    4. get_data_from_data_handler(dh, columns)
    5. create_data_handler(output_selection, during=None, after=None, before=None, model=None)
    6. run_time_course(*args, **kwargs)
    7. _setup_timecourse(args, kwargs)

Variables

• model_id = either an integer, or a valid model id
• url = string with url

Unknown

• **kwargs