prep.generate_animation_df

prep.generate_animation_df(
    full_patient_df,
    event_position_df,
    wrap_queues_at=20,
    wrap_resources_at=20,
    step_snapshot_max=50,
    gap_between_entities=10,
    gap_between_resources=10,
    gap_between_rows=30,
    debug_mode=False,
    custom_entity_icon_list=None,
)

Generate a DataFrame for animation purposes by adding position information to patient data.

This function takes patient event data and adds positional information for visualization, handling both queuing and resource use events.

Parameters

Name	Type	Description	Default
full_patient_df	pd.DataFrame	Output of reshape_for_animation(), containing patient event data.	required
event_position_df	pd.DataFrame	DataFrame with columns ‘event’, ‘x’, and ‘y’, specifying initial positions for each event type.	required
wrap_queues_at	int	Number of entities in a queue before wrapping to a new row (default is 20).	20
wrap_resources_at	int	Number of resources to show before wrapping to a new row (default is 20).	20
step_snapshot_max	int	Maximum number of patients to show in each snapshot (default is 50).	50
gap_between_entities	int	Horizontal spacing between entities in pixels (default is 10).	10
gap_between_resources	int	Horizontal spacing between resources in pixels (default is 10).	10
gap_between_rows	int	Vertical spacing between rows in pixels (default is 30).	30
debug_mode	bool	If True, print debug information during processing (default is False).	False

Returns

Name	Type	Description
	pd.DataFrame	A DataFrame with added columns for x and y positions, and icons for each patient.

Notes

• The function handles both queuing and resource use events differently.
• It assigns unique icons to patients for visualization.
• Queues can be wrapped to multiple rows if they exceed a specified length.
• The function adds a visual indicator for additional patients when exceeding the snapshot limit.

TODO

• Write a test to ensure that no patient ID appears in multiple places at a single minute.