prep.reshape_for_animations

prep.reshape_for_animations(
    event_log,
    every_x_time_units=10,
    limit_duration=10 * 60 * 24,
    step_snapshot_max=50,
    debug_mode=False,
)

Reshape event log data for animation purposes.

This function processes an event log to create a series of snapshots at regular time intervals, suitable for creating animations of patient flow through a system.

Parameters

Name	Type	Description	Default
event_log	pd.DataFrame	The input event log containing patient events and timestamps.	required
every_x_time_units	int	The time interval between snapshots in minutes (default is 10).	10
limit_duration	int	The maximum duration to consider in minutes (default is 10 days).	10 * 60 * 24
step_snapshot_max	int	The maximum number of patients to include in each snapshot for each event (default is 50).	50
debug_mode	bool	If True, print debug information during processing (default is False).	False

Returns

Name	Type	Description
	DataFrame	A reshaped DataFrame containing snapshots of patient positions at regular time intervals, sorted by minute and event.

Notes

• The function creates snapshots of patient positions at specified time intervals.
• It handles patients who are present in the system at each snapshot time.
• Patients are ranked within each event based on their arrival order.
• A maximum number of patients per event can be set to limit the number of patients who will be displayed on screen within any one event type at a time.
• An ‘exit’ event is added for each patient at the end of their journey.
• The function uses memory management techniques (del and gc.collect()) to handle large datasets.

TODO

• Add behavior for when limit_duration is None.
• Consider adding ‘first step’ and ‘last step’ parameters.
• Implement pathway order and precedence columns.
• Fix the automatic exit at the end of the simulation run for all patients.