rSimpleModel

A simple example of an SEIRS epidemiological model using the FAIR Data Pipeline.

Installing the command line tools

If you don't already have the registry initialised and the fair command line tool configured, then you need to install that next - see here for more details. Briefly, with python and poetry (pip install poetry) installed:

git clone https://github.com/FAIRDataPipeline/FAIR-CLI.git
cd FAIR-CLI
poetry install
poetry shell

You are now running in a new shell created by poetry that has a copy of the fair executable in its path.

Installing the R API and simple model functions

Install the rDataPipeline package, in R:

install.packages(devtools)
devtools::install_github("FAIRDataPipeline/rDataPipeline")
library(rDataPipeline)

Then install rSimpleModel:

devtools::install_github("FAIRDataPipeline/rSimpleModel")
library(rSimpleModel)

Configuring the registry and setting up the example

At the terminal, in some suitable directory, clone the git repo:

git clone https://github.com/FAIRDataPipeline/rSimpleModel.git
cd rSimpleModel

At this point you can configure fair to run in this repo. Either run:

fair init

And fill in your own details.

Running the example

This is easy. The user configuration script for running the R SEIRS model can be found inside this repo - inst/extdata/SEIRSconfig.yaml - and for this self-contained example, it includes all of the information to register the input data that the model needs, so that you don't have to be connected to a registry that already knows about it. The code can be executed by first ensuring that all of the input data is available in the local registry (using fair pull) and then running the code (using fair run). So:

fair pull inst/extdata/SEIRSconfig.yaml
fair run inst/extdata/SEIRSconfig.yaml

That's it! If you go to the local registry in your browser now (by default at http://localhost:8000), you should see the input and output data recorded in the registry.