Simulation results

The Simulator Automatic Warehouse library allows you to simulate a real Vertimag and produce as output raw information. We provide an entire Python class with many services to process the raw data of the simulation into an organized Dataframe.

With the term DataFrame, we refer to the data object structure of Pandas.

How to instantiate

To instantiate the class, all that is required are the items obtained from a Pandas DataFrame. This object must be instantiated using the history of the warehouse simulation:

from pandas import DataFrame
from automatic_warehouse.utils.statistics.warehouse_statistics import WarehouseStatistics
from automatic_warehouse.simulation.simulation_type.warehouse_simulation import WarehouseSimulation
from automatic_warehouse.warehouse import Warehouse

warehouse = Warehouse()
simulation = WarehouseSimulation(warehouse)
simulation.run_simulation()
warehouse_statistics = WarehouseStatistics(
    DataFrame(simulation.get_store_history_dataframe())
)

Count the total number of actions at a given time

• actions_started_every(self, time: TimeEnum) -> DataFrame

  Given a certain time, the method calculates how many actions have only been started. The finish time is not considered.

  As you can see in the example below, the returned DataFrame contains two columns: the total number of actions performed and the time at which they were started.

  Start	Count
  2024-02-17 12:00	201
  2024-02-17 13:00	404
  2024-02-17 14:00	395

• actions_finished_every(self, time: TimeEnum) -> DataFrame

  The same logic as actions_started_every but with the actions that are only finished.

  Finish	Count
  2024-02-17 12:00	200
  2024-02-17 13:00	404
  2024-02-17 14:00	396

• actions_completed_every(self, time: TimeEnum) -> DataFrame

  A merge of the previous two, but this DataFrame counts how many actions are started and finished in the same time, given as a parameter.

  As you can see in the example, some rows contain the same start time. These rows show how many actions are started before the finish time.

  For example, if an action starts at (e.g.) 10:58 and ends at 11:05, it will not be counted in the 10-hour counter.

  Start	Finish	Count
  2024-02-17 12:00	2024-02-17 12:00	200
  2024-02-17 12:00	2024-02-17 13:00	1
  2024-02-17 13:00	2024-02-17 13:00	403
  2024-02-17 13:00	2024-02-17 14:00	1
  2024-02-17 14:00	2024-02-17 14:00	395

Count the total number of a given action at a given time

These methods have the same logic as the functions in Count the total number of actions at a given time section, but the following refers to a single action given as a parameter.

• action_started_every(self, action: ActionEnum, time: TimeEnum) -> DataFrame

  An example of how to call:

  warehouse_statistics.action_started_every(ActionEnum.EXTRACT_TRAY, TimeEnum.HOUR)
  

  Start	count
  2024-02-17 12:00	53
  2024-02-17 13:00	93
  2024-02-17 14:00	95

• action_finished_every(self, action: ActionEnum, time: TimeEnum) -> DataFrame

  An example of how to call:

  warehouse_statistics.action_finished_every(ActionEnum.EXTRACT_TRAY, TimeEnum.HOUR)
  

  Finish	count
  2024-02-17 12:00	52
  2024-02-17 13:00	94
  2024-02-17 14:00	95

• action_completed_every(self, action: ActionEnum, time: TimeEnum) -> DataFrame

  An example of how to call:

  warehouse_statistics.action_completed_every(ActionEnum.EXTRACT_TRAY, TimeEnum.HOUR)
  

  	Type of Action	Start	Finish	Count
  0	ExtractTray	2024-02-18 14:00	2024-02-18 14:00	82
  1	ExtractTray	2024-02-18 14:00	2024-02-18 15:00	1
  2	ExtractTray	2024-02-18 15:00	2024-02-18 15:00	93
  3	ExtractTray	2024-02-18 15:00	2024-02-18 16:00	1
  4	ExtractTray	2024-02-18 16:00	2024-02-18 16:00	73

Count the total amount of a given action in the whole simulation

• count_action_completed(self, action: ActionEnum) -> int

  The number of times an action has been completed.

  Note: any action that isn’t completed is not counted.

Simulation time

• start_time_simulation(self) -> Timestamp

  Return the start time of the simulation as a Pandas Timestamp.

  For example: pandas.Timestamp('2024-02-17 12:29:59.124635')

• finish_time_simulation(self) -> Timestamp

  Return the finish time of the simulation as a Pandas Timestamp.

  For example: pandas.Timestamp('2024-02-17 14:59:48.234510')

• total_simulation_time(self) -> Timedelta

  Return the total time of the simulation as a Pandas Timedelta.

  For example: pandas.Timedelta('0 days 02:29:49.109875')