src.simulation.load_simulation_inputs

Module Contents

Functions

load_simulation_inputs(scenario, start_date, end_date, debug, group_share_known_case_path=None, period_outputs=False, return_last_states=False, initial_states_path=None, is_resumed=False, rapid_test_statistics_path=None)	Load the simulation inputs.
get_simulation_dependencies(debug, is_resumed)	Collect paths on which the simulation depends.
create_period_outputs()
_calculate_share_ever_rapid_test(df, groupby)
_calculate_share_rapid_test_in_last_week(df, groupby)
_calculate_share_rapid_test_countdown_between(df, groupby, lower, upper, name)	Share by groupby with their last rapid test between lower and upper (inclusively).
calculate_period_virus_share(df, strain)
_calculate_share_doing_rapid_test(df, groupby)

load_simulation_inputs(scenario, start_date, end_date, debug, group_share_known_case_path=None, period_outputs=False, return_last_states=False, initial_states_path=None, is_resumed=False, rapid_test_statistics_path=None)

Load the simulation inputs.

Does not include: params, path, seed.

Parameters

• scenario (str) – string specifying the scenario. A function with the same name must exist in src.simulation.scenario_simulation_inputs.

• start_date (str) – date on which the simulation starts. Data must be available for at least a month before the start date for the burn in period.

• end_date (str) – date on which the simulation ends.

• debug (bool) – Whether to use the debug or the full initial states.

• group_share_known_case_path (pathlib.Path, str or None) – if not None, the group share known cases are loaded from this path and used for the creation of the initial conditions.

• period_outputs (bool, optional) – whether to use period_outputs instead of saving the time series. Default is False.

• return_last_states (bool, optional) – if True, the last states are returned as part of the simulation result.

• initial_states_path (pathlib.Path, optional) – Path to the initial states. If not given the standard initial states are used.

• is_resumed (bool, optional) – if True, the initial_states_path must be given. In that case no initial conditions are created

• rapid_test_statistics_path (Path, optional) – where to save rapid test statistics.

Returns

Dictionary with most arguments of get_simulate_func. Keys are:

• initial_states

• contact_models

• duration

• events

• saved_columns

• virus_strains

• derived_state_variables

• seasonality_factor_model

• initial_conditions

• susceptibility_factor_model

• testing_demand_models

• testing_allocation_models

• testing_processing_models

• period_outputs

• return_last_states

• return_time_series

• contact_policies

• vaccination_models

• rapid_test_models

• rapid_test_reaction_models

Return type

dict

get_simulation_dependencies(debug, is_resumed)

Collect paths on which the simulation depends.

This contains both paths to python modules and data paths. It only covers sid-germany specific paths, i.e. not sid.

Parameters

• debug (bool) – Whether to use the debug initial states.

• is_resumed (bool) – Whether the simulation is a resumed simulation. If False the path to the initial states from BLD / “data” are given.

Returns

Dictionary with the dependencies for the simulation.

Return type

paths (dict)

create_period_outputs()

_calculate_share_ever_rapid_test(df, groupby)

_calculate_share_rapid_test_in_last_week(df, groupby)

_calculate_share_rapid_test_countdown_between(df, groupby, lower, upper, name)

Share by groupby with their last rapid test between lower and upper (inclusively).

Parameters

• df (pandas.DataFrame) – states DataFrame

• groupby (str or None) – groupby column

• lower (int) – lower bound (individuals with this value are included)

• upper (int) – upper bound (individuals with this value are included)

• name (str) – name of the Series to be returned

calculate_period_virus_share(df, strain)

_calculate_share_doing_rapid_test(df, groupby)