Breakdown of Basico

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  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