Before any run

Instructions on how to begin engaging with flepiMoP locally by covering GitHub setup, conda installation, and finally installation of flepiMoP itself.

Before any run

⇅ Get set up to use Github

You need to interact with Github to run and edit flepiMoP code. Github is a web platform for people to share and manage software, and it is based on a 'version control' software called git that helps programmers keep track of changes to code. Flepimop core code as well as example projects using flepimop code are all stored on Github, and frequently being updated. The first step to using flepimop for your own project is making sure you're set up to interact with code shared on Github.

If you are totally new to Github, navigate to Github.com and Sign Up for a new account. Read about the basics of git.

To work with flepimop code, you can do some tasks from the Github website, but you'll also need a way to 'clone' the code to your own local computer and keep it up to date with versions hosted online. You can do this either using a user interface like Github Desktop, or, using git commands from the command line. Make sure you have one or both installed.

If you are a veteran user, make sure you're signed in on Github.com and through whatever method you use locally on your computer to interact with Github.

🔐 Access the flepiMoP model code

In order to run a model with flepiMoP, you will need to clone the flepiMoP code to your machine.

To clone the flepiMoP code repository:

• If you're using the command line in a terminal, first navigate to the local directory you'll use as the directory for the files that make up flepiMoP. Then, use the command: git clone https://github.com/HopkinsIDD/flepiMoP

• If you're using Github Desktop, go File -> Clone Repository, switch to the "URL" tab and copy the URL https://github.com/HopkinsIDD/flepiMoP there. For the "Local Path" option, make sure you choose your desired directory.

You can routinely ensure that your local clone of the flepiMoP code is up to date with upstream flepiMoP by navigating in terminal to your flepiMoP directory and using the command: git pull

Locally install flepiMoP

🐍 Install conda

In order to complete flepiMoP installation, you must have conda installed on your machine. conda is a tool that will assist you in managing software environments and code packages on your device, and it will be very helpful in ensuring consistent, reproducible environments across different projects. To install conda follow the directions according to your operating system. We would recommend selecting the Anaconda Distribution installer of conda.

Installation of conda may take a few minutes.

⬇️ Install flepiMoP packages and dependencies

This installation script is currently only designed for Linux/MacOS operating systems or linux shells for windows. If you need windows native installation please reach out for assistance.

To install flepiMoP locally navigate to the flepiMoP directory and run the following command:

./build/local_install_or_update

This script will do the following:

1. Determine $FLEPI_PATH and $FLEPI_CONDA environment variables,

2. Create and activate a conda environment to install flepiMoP into,

3. Install gempyor and related Python dependencies to the conda environment from (2), and

4. Install necessary R packages and dependencies to the conda environment from (2).

Please inspect the output to ensure that the installation has gone smoothly. If you encounter any issues please report them in a GitHub issue. After this step you should be clear to move on to the Quick Start Guide to activate your installation and do some test runs.

🤔 Deciding how to run

The code is written in a combination of R and Python. The Python part of the model is a package called gempyor, and includes all the code to simulate the epidemic model and the observational model and apply time-dependent interventions. The R component conducts the (optional) parameter inference, and all the (optional) provided pre and post processing scripts are also written in R. Most uses of the code require interacting with components written in both languages, and thus making sure that both are installed along with a set of required packages. However, Python alone can be used to do forward simulations of the model using gempyor.

Because of the need for multiple software packages and dependencies, we describe different ways you can run the model, depending on the requirements of your model setup. See Quick Start Guide for a quick introduction to using gempyor and flepiMoP. We also provide some more advanced ways to run our model, particularly for doing more complex model inference tasks.