treat-sim 1.1.1

A free and open implementation of the Treatment Centre Model from Nelson (2013)

Towards Sharing Tools, and Artifacts, for Reusable Simulation: a minimal model example

Overview

The materials and methods in this repository support work towards developing the S.T.A.R.S healthcare framework (Sharing Tools and Artifacts for Reuable Simulations in healthcare). The code and written materials here demonstrate the application of S.T.A.R.S' version 1 to sharing a simpy discrete-event simuilation model and associated research artifacts.

• All artifacts in this repository are linked to study researchers via ORCIDs;
• Model code is made available under an MIT license;
• Python dependencies are managed through conda;`
• Documentation of the model is enhanced using a Jupyter notebook.
• The python code itself can be viewed and executed in Jupyter notebooks via Binder;
• The materials are deposited and made citatable using Zenodo;
• The model is sharable with other researchers and the NHS without the need to install software.

Author ORCIDs

Funding

This code is part of independent research supported by the National Institute for Health Research Applied Research Collaboration South West Peninsula. The views expressed in this publication are those of the author(s) and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care.

Instructions to run the model

Online Notebooks via Binder

The python code for the model has been setup to run online in Jupyter notebooks via binder

mybinder.org is a free tier service. If it has not been used in a while Binder will need to re-containerise the code repository, and push to binderhub. This will take several minutes. After that the online environment will be quick to load.

To download code and run locally

Downloading the code

Either clone the repository using git or click on the green "code" button and select "Download Zip".

git clone https://github.com/pythonhealthdatascience/stars-treat-sim

Installing dependencies

All dependencies can be found in binder/environment.yml and are pulled from conda-forge. To run the code locally, we recommend install mini-conda; navigating your terminal (or cmd prompt) to the directory containing the repo and issuing the following command:

conda env create -f binder/environment.yml

Activate the conda environment using the following command

conda activate stars_treat_sim

Running the model

To run 50 multiple replications of across a number of example experiments use the following code

from treat_sim.model import (get_scenarios, run_scenario_analysis,
                             scenario_summary_frame, 
                             DEFAULT_RESULTS_COLLECTION_PERIOD)

if __name__ == '__main__':

    results = run_scenario_analysis(get_scenarios(), 
                                    DEFAULT_RESULTS_COLLECTION_PERIOD,
                                    n_reps=50)

    results_summary = scenario_summary_frame(results)
    print(results_summary)

Alternative you can design and execute individual experiments by creating a Scenario object

from treat_sim.model import Scenario, multiple_replications

if __name__ == '__main__':

    # use all default parameter values
    base_case = Scenario()

    results = multiple_replications(base_case).describe().round(2).T
    print(results)

Repo overview

.
├── binder
│   └── environment.yml
├── LICENSE
├── MANIFEST.in
├── notebooks
│   └── test_package.ipynb
├── README.md
├── requirements.txt
├── setup.py
└── treat_sim
    ├── data
    │   └── ed_arrivals.csv
    ├── distributions.py
    ├── __init__.py
    └── model.py

• binder - contains the environment.yml file (sim) and all dependencies managed via conda
• data - directory containing data files used by analysis notebooks.
• LICENSE - details of the MIT permissive license of this work.
• notebooks - contains a notebook to run the model and provides basic enhanced model documentation.
• main.py - an example simpy model to use to test the virtual environment
• README - what you are reading now!
• treat_sim - contains a packaged version of the model.

Citation

If you use the materials within this repository we would appreciate a citation.

@software{monks_2023_10026327,
  author       = {Monks, Thomas and
                  Harper, Alison},
  title        = {{Towards Sharing Tools, and Artifacts, for Reusable 
                   Simulation: a minimal model examplar}},
  month        = oct,
  year         = 2023,
  publisher    = {Zenodo},
  version      = {v1.0.0},
  url 	       = {https://zenodo.org/records/10026327}
}