Wrapper functions

Wrapper functions#

Here we demonstrate how to use the Experiment class with the multiple_replications() function.

To see how the multiple_replications() function works see the replications notebook. This function simply wraps the the single_run() function. To see how single_run() initiates a simpy model replication see the experiments notebook

1. Imports#

To use and configure the model we need to import the Experiment class and the multiple_replications() function.

import pandas as pd
from model import Experiment, multiple_replications

2. Setup and run an experiment#

2.1 An experiment using default settings#

default_scenario = Experiment()
results = multiple_replications(default_scenario, n_reps=5)

results
01_mean_waiting_time 02_operator_util 03_mean_nurse_waiting_time 04_nurse_util
rep
1 1.319782 89.639845 33.380122 97.049530
2 4.302142 93.237355 71.507717 97.122986
3 3.107235 93.550804 83.747724 95.536969
4 2.275225 90.486654 44.769433 97.242503
5 3.544098 92.255403 26.263742 97.620733 
results.describe()
01_mean_waiting_time 02_operator_util 03_mean_nurse_waiting_time 04_nurse_util
count 5.000000 5.000000 5.000000 5.000000
mean 2.909696 91.834012 51.933748 96.914544
std 1.152256 1.712021 24.747641 0.800881
min 1.319782 89.639845 26.263742 95.536969
25% 2.275225 90.486654 33.380122 97.049530
50% 3.107235 92.255403 44.769433 97.122986
75% 3.544098 93.237355 71.507717 97.242503
max 4.302142 93.550804 83.747724 97.620733

2.2 An experiment with an extra operator#

extra_operator = Experiment(n_operators=14)
results = multiple_replications(default_scenario, n_reps=5)
results.describe()
01_mean_waiting_time 02_operator_util 03_mean_nurse_waiting_time 04_nurse_util
count 5.000000 5.000000 5.000000 5.000000
mean 2.894323 93.161093 46.279491 97.181621
std 1.036465 1.562844 23.985800 0.616801
min 1.759460 91.167445 17.008498 96.555626
25% 2.454142 92.167426 33.934782 96.838734
50% 2.562117 93.110410 43.988936 96.923999
75% 3.182290 94.371362 55.525038 97.483583
max 4.513608 94.988825 80.940201 98.106165

2.3 An experiment based on python script using variables#

Here we create a basic script for where a user can manually hard code parameters and run the simulation model.

# set number of resources
n_operators = 13
n_nurses = 9

# set chance of nurse
chance_callback = 0.4

# set number of replications
n_reps = 5

# create experiment
exp = Experiment(n_operators=n_operators, n_nurses=n_nurses,
                 chance_callback=chance_callback)

# run multiple replications of experment
results = multiple_replications(exp, n_reps=n_reps)

# show results
results.describe()
01_mean_waiting_time 02_operator_util 03_mean_nurse_waiting_time 04_nurse_util
count 5.000000 5.000000 5.000000 5.000000
mean 4.804836 94.485572 63.127092 97.338956
std 2.011857 1.250878 13.886811 0.652213
min 2.449658 92.943156 40.943340 96.347719
25% 3.377995 93.768985 60.577650 97.046899
50% 4.714585 94.609132 64.597415 97.582732
75% 5.998619 94.821548 74.677588 97.728423
max 7.483321 96.285041 74.839469 97.989007
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