Utilities

Simulation base

class emsa.utils.simulation_base.SimulationBase(data, model_struct_path, sampling_config_path)

Bases: ABC

calculate_all_p_values()

calculate_all_prcc()

calculate_p_values(filename, significance=0.05)

calculate_prcc(filename: str, target: str) → None

Calculates PRCC (Partial Rank Correlation Coefficient) values from saved LHS tables and simulation results.

This method reads the saved LHS tables and simulation results for each parameter combination and calculates the PRCC values. The PRCC values are saved in separate files in the ‘sens_data_”folder_name”/prcc’ directory.

flatten_dict(d, key)

static flatten_dict_in_dict(d, key)

static flatten_list_in_dict(d, key)

get_beta_from_r0(base_r0)

get_filename(variable_params)

static merge_dicts(ds)

static parse_param_name(variable_params: dict, key)

plot_all_prcc()

plot_prcc(filename: str, labels=None)

Parameters:

filename
labels

Returns: None

process_variable_params()

run_func_for_all_configs(func)

abstract run_sampling()

property susceptibles

DataLoaderBase

class emsa.utils.dataloader.DataLoaderBase

Bases: ABC

property n_age

Plotter

emsa.utils.plotter.construct_triangle_grid(n_age)

emsa.utils.plotter.generate_tornado_plot(sim_object, labels, prcc: ndarray, p_val, filename: str, title=None, verbose=True): Generate a tornado plot to visualize the Partial Rank Correlation Coefficient (PRCC) values.

emsa.utils.plotter.get_age_groups()

emsa.utils.plotter.get_prcc_and_p_values(n_age, prcc_vector, p_values)

emsa.utils.plotter.plot_prcc_p_values_as_heatmap(n_age, prcc_vector, p_values, filename_to_save, plot_title)

emsa.utils.plotter.visualize_transmission_graph(state_data, trans_data, tms_rules)