prep.generate_animation_df

prep.generate_animation_df(
    full_entity_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_resource_rows=30,
    gap_between_queue_rows=30,
    time_col_name='time',
    entity_col_name='entity_id',
    event_type_col_name='event_type',
    event_col_name='event',
    resource_col_name='resource_id',
    debug_mode=False,
    custom_entity_icon_list=None,
    include_fun_emojis=False,
)

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

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

Parameters

Name	Type	Description	Default
full_entity_df	pd.DataFrame	Output of reshape_for_animation(), containing entity 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_queue_rows	int	Vertical spacing between rows in pixels (default is 30).	30
gap_between_resource_rows	int	Vertical spacing between rows in pixels (default is 30).	30
time_col_name	str	Name of the column in event_log that contains the timestamp of each event. Timestamps should represent the number of time units since the simulation began.	"time"
entity_col_name	str	Name of the column in event_log that contains the unique identifier for each entity (e.g., “entity_id”, “entity”, “patient”, “patient_id”, “customer”, “ID”).	"entity_id"
event_type_col_name	str	Name of the column in event_log that specifies the category of the event. Supported event types include ‘arrival_departure’, ‘resource_use’, ‘resource_use_end’, and ‘queue’.	"event_type"
resource_col_name	str	Name of the column for the resource identifier. Used for ‘resource_use’ events.	"resource_id"
event_col_name	str	Name of the column in event_log that specifies the actual event that occurred.	"event"
debug_mode	bool	If True, print debug information during processing (default is False).	False
custom_entity_icon_list	list	If provided, will be used as the list for entity icons. Once the end of the list is reached, it will loop back around to the beginning (so e.g. if a list of 8 icons is provided, entities 1 to 8 will use the provided emoji list, and then entity 9 will use the same icon as entity 1, and so on.)	None
include_fun_emojis	bool	If True, include the more ‘fun’ emojis, such as Santa Claus. Ignored if a custom entity icon list is passed.	False

Returns

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

Notes

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

TODO

• Write a test to ensure that no entity ID appears in multiple places at a single time unit.