A More Complex Ciw Example with Backgrounds

import pandas as pd
# Import the wrapper objects for model interaction.
from examples.example_10_advanced_ciw.ex_10_ciw_model import N
from vidigi.ciw import event_log_from_ciw_recs
from vidigi.utils import EventPosition, create_event_position_df
from vidigi.animation import animate_activity_log
import plotly.io as pio
pio.renderers.default = "notebook"
import os
import ciw
import ciw

# From https://ciw.readthedocs.io/en/latest/Tutorial/tutorial_ii.html

N = ciw.create_network(

    arrival_distributions=[ciw.dists.Exponential(rate=0.3 / 60),

                           ciw.dists.Exponential(rate=0.2 / 60),

                           None],

    service_distributions=[ciw.dists.Exponential(rate=2.0 / 60),

                           ciw.dists.Exponential(rate=1.4 / 60),

                           ciw.dists.Exponential(rate=1.0 / 60)],

    routing=[[0.0, 0.3, 0.7],

             [0.0, 0.0, 1.0],

             [0.0, 0.0, 0.0]],

    number_of_servers=[1, 2, 2]

)
ciw.seed(42)

Q = ciw.Simulation(N)

RESULTS_COLLECTION_PERIOD = 180 * 60 # 180 minutes x 60 seconds

Q.simulate_until_max_time(RESULTS_COLLECTION_PERIOD)

recs = Q.get_all_records()

pd.DataFrame(recs).sort_values(['id_number', 'service_start_date']).head(20)
id_number customer_class original_customer_class node arrival_date waiting_time service_start_date service_time service_end_date time_blocked exit_date destination queue_size_at_arrival queue_size_at_departure server_id record_type
0 1 Customer Customer 2 7.598652 0.000000 7.598652 13.783888 21.382540 0.0 21.382540 3 0 0 1 service
1 1 Customer Customer 3 21.382540 0.000000 21.382540 67.750381 89.132921 0.0 89.132921 -1 0 0 1 service
6 2 Customer Customer 2 83.374507 0.000000 83.374507 95.455204 178.829712 0.0 178.829712 3 0 0 1 service
7 2 Customer Customer 3 178.829712 0.000000 178.829712 53.388522 232.218234 0.0 232.218234 -1 1 1 1 service
2 3 Customer Customer 2 110.660229 0.000000 110.660229 23.487693 134.147921 0.0 134.147921 3 1 2 2 service
3 3 Customer Customer 3 134.147921 0.000000 134.147921 13.301500 147.449421 0.0 147.449421 -1 0 1 1 service
4 4 Customer Customer 2 119.735282 14.412639 134.147921 1.152617 135.300539 0.0 135.300539 3 2 1 2 service
5 4 Customer Customer 3 135.300539 0.000000 135.300539 47.239755 182.540294 0.0 182.540294 -1 1 1 2 service
16 5 Customer Customer 2 193.750291 0.000000 193.750291 71.045918 264.796209 0.0 264.796209 3 0 1 1 service
17 5 Customer Customer 3 264.796209 0.000000 264.796209 216.972911 481.769120 0.0 481.769120 -1 1 0 2 service
12 6 Customer Customer 2 195.706281 0.000000 195.706281 70.241394 265.947675 0.0 265.947675 3 1 0 2 service
13 6 Customer Customer 3 265.947675 30.320583 296.268259 48.183165 344.451423 0.0 344.451423 -1 2 2 1 service
8 7 Customer Customer 1 204.012057 0.000000 204.012057 12.476853 216.488910 0.0 216.488910 3 0 0 1 service
9 7 Customer Customer 3 216.488910 0.000000 216.488910 24.622136 241.111046 0.0 241.111046 -1 1 1 2 service
10 8 Customer Customer 1 237.809311 0.000000 237.809311 2.919980 240.729291 0.0 240.729291 3 0 0 1 service
11 8 Customer Customer 3 240.729291 0.000000 240.729291 55.538968 296.268259 0.0 296.268259 -1 1 2 1 service
14 9 Customer Customer 1 258.153048 0.000000 258.153048 49.371898 307.524946 0.0 307.524946 3 0 0 1 service
15 9 Customer Customer 3 307.524946 36.926477 344.451423 57.821772 402.273196 0.0 402.273196 -1 2 1 1 service
20 10 Customer Customer 1 519.821134 0.000000 519.821134 59.351398 579.172532 0.0 579.172532 2 0 0 1 service
21 10 Customer Customer 2 579.172532 1.027521 580.200053 4.563164 584.763217 0.0 584.763217 3 2 1 2 service 
event_log = event_log_from_ciw_recs(
    recs,
    node_name_list=["cold_food", "hot_food", "till"]
    )

event_log[event_log["entity_id"]==13]
entity_id pathway event_type event time resource_id
99 13 Model arrival_departure arrival 671.604123 NaN
100 13 Model queue hot_food_wait_begins 671.604123 NaN
101 13 Model resource_use hot_food_begins 671.604123 1.0
102 13 Model resource_use_end hot_food_ends 684.914665 1.0
103 13 Model queue till_wait_begins 684.914665 NaN
104 13 Model resource_use till_begins 684.914665 1.0
105 13 Model resource_use_end till_ends 741.277635 1.0
106 13 Model arrival_departure depart 741.277635 NaN 
# Create a suitable class to pass in the resource numbers to the animation function
class model_params():
    def __init__(self):
        self.cold_food_servers = 1
        self.hot_food_servers = 2
        self.tills = 2

params = model_params()
# # Create required event_position_df for vidigi animation
# event_position_df = pd.DataFrame([
#                     {'event': 'arrival',
#                      'x':  30, 'y': 550,
#                      'label': "Arrival"},

#                     {'event': 'cold_food_wait_begins',
#                      'x':  200, 'y': 510,
#                      'label': "Waiting for Cold Food"},

#                     {'event': 'cold_food_begins',
#                      'x':  210, 'y': 370,
#                      'resource':'cold_food_servers',
#                      'label': "Being Served Cold Food"},

#                     {'event': 'hot_food_wait_begins',
#                      'x':  505, 'y': 510,
#                      'label': "Waiting for Hot Food"},

#                     {'event': 'hot_food_begins',
#                      'x':  505, 'y': 370,
#                      'resource':'hot_food_servers',
#                      'label': "Being Served Hot Food"},

#                     {'event': 'till_wait_begins',
#                      'x':  350, 'y': 170,
#                      'label': "Waiting for Till"},

#                     {'event': 'till_begins',
#                      'x':  350, 'y': 120,
#                      'resource':'tills',
#                      'label': "Being Served at Till"},

#                     {'event': 'depart',
#                      'x':  600, 'y': 10,
#                      'label': "Exit"}

#                 ])

# event_position_df

event_position_df = create_event_position_df( [
    EventPosition(event='arrival', x=30, y=550, label="Arrival"),
    EventPosition(event='cold_food_wait_begins', x=200, y=510, label="Waiting for Cold Food"),
    EventPosition(event='cold_food_begins', x=210, y=370, resource='cold_food_servers', label="Being Served Cold Food"),
    EventPosition(event='hot_food_wait_begins', x=505, y=510, label="Waiting for Hot Food"),
    EventPosition(event='hot_food_begins', x=505, y=370, resource='hot_food_servers', label="Being Served Hot Food"),
    EventPosition(event='till_wait_begins', x=350, y=170, label="Waiting for Till"),
    EventPosition(event='till_begins', x=350, y=120, resource='tills', label="Being Served at Till"),
    EventPosition(event='depart', x=600, y=10, label="Exit")
]
)
# Create animation
params = model_params()

animate_activity_log(
        event_log=event_log,
        event_position_df=event_position_df,
        scenario=model_params(),
        simulation_time_unit="seconds",
        time_display_units="dhms",
        debug_mode=True,
        setup_mode=False,
        every_x_time_units=5, # 20 seconds
        include_play_button=True,
        entity_icon_size=20,
        gap_between_entities=15,
        gap_between_queue_rows=25,
        gap_between_resources=30,
        plotly_height=525,
        frame_duration=200,
        frame_transition_duration=600,
        plotly_width=900,
        override_x_max=700,
        override_y_max=600,
        limit_duration=RESULTS_COLLECTION_PERIOD,
        wrap_queues_at=25,
        wrap_resources_at=50,
        step_snapshot_max=75,
        start_time="12:00:00",
        text_size=20,
        display_stage_labels=False,
        add_background_image="https://raw.githubusercontent.com/Bergam0t/vidigi/refs/heads/main/examples/example_10_advanced_ciw/cafe_floorplan.drawio%20(1).png"
    )
Animation function called at 15:19:45
Iteration through time-unit-by-time-unit logs complete 15:19:49
Snapshot df concatenation complete at 15:19:50
Reshaped animation dataframe finished construction at 15:19:50
Placement dataframe finished construction at 15:19:50
Output animation generation complete at 15:19:57
Total Time Elapsed: 12.62 seconds