close_contacts_calculator

Module Contents

Classes

CloseContactsCalculator

Helper class that provides a standard way to create an ABC using
class close_contacts_calculator.CloseContactsCalculator(facility: citam.engine.facility.indoor_facility.Facility, contact_distance: float = 6.0)

Bases: citam.engine.calculators.calculator.Calculator

Helper class that provides a standard way to create an ABC using inheritance.

initialize(agents: OrderedDict[int, citam.engine.core.agent.Agent], workdir: Optional[Union[os.PathLike, str]] = None)
run(current_step: int, active_agents: List[citam.engine.core.agent.Agent]) → None

Iterate over agents, compute whether they fall within the contact distance or not and verify that they are indeed making contact (based on whether they are in the same space or not).

Parameters:

  • agents (List[Agent]) – list of agents under consideration for contact statistics

  • contact_outfiles (List[TextIO], optional) – Files to write contact data, one per floor, defaults to None

finalize(agents: List[citam.engine.core.agent.Agent], work_directory: Optional[Union[str, bytes, os.PathLike]] = None) → None
identify_xy_proximity(positions_vector: numpy.ndarray) → numpy.ndarray

Compute pairwise distances, given a vector of xy positions, and return the indices of the ones that fall within the given contact distance.

Parameters:

positions_vector (np.ndarray) – Array of current xy positions of all active agents

Returns:

Array of indices of agents that are within the contact distance of each other

Return type:

np.ndarray

verify_and_add_contact(current_step: int, floor_number: int, agent1: citam.engine.core.agent.Agent, agent2: citam.engine.core.agent.Agent)

Verify if agents are in nearby hallways before creating contact event.

Parameters:

  • floor_number (int) – [description]

  • agent1 (Agent) – First agent

  • agent2 (Agent) – Second agent

add_contact_event(current_step: int, agent1: citam.engine.core.agent.Agent, agent2: citam.engine.core.agent.Agent) → None

Record contact event between agent1 and agent2.

Parameters:

  • agent1 (Agent) – The first agent.

  • agent2 (Agent) – The second agent.

extract_contact_distribution_per_agent(agents: List[citam.engine.core.agent.Agent]) → Tuple[List[str], List[int]]

Compute and return total contacts per agent.

Returns:

List of agent ids and their total contacts

Return type:

Tuple[List[int], List[int]]

save_to_files(agents: List[citam.engine.core.agent.Agent], work_directory: Union[str, bytes, os.PathLike])

Write output files to the output directory

Parameters:

work_directory (str) – directory where all output files are to be saved.

create_svg_heatmap(contacts_per_coord: Dict[Tuple[int, int], int], floor_directory: str) → None

Create and save a heatmap from coordinate contact data.

Parameters:

  • contacts_per_coord (Dict[Tuple[int, int], int]) – dictionary where each key is an (x,y ) tuple and values are the number of contacts in that location.

  • floor_directory (str) – directory to save the heatmap file.

Raises:

FileNotFoundError – if the floor svg map file is not found.