Getting Started

The USEEIO modeling framework uses a combination of R and Python and pre-processed data files.

Use of R and Python

R is primarily used to generate the model components.

Python is used to assemble and generate results for a model.

Running the R code

After downloading and unzipping the USEEIO files, we recommend creating a new R project in the main directory (the one with the example, R, SI, and useeiopy subfolders). In R Studio, this can be done with the File>New Project>Existing Directory selection. We use the .Rprofile to pre-load R packages used and set some global variables. This will automatically search for R packages needed - the first use will take longer to download and install all needed packages. Simply browse and then open up R files in the R subdirectory and using the Run command to begin executing R code. The Model Build Scripts R files will pull in other files to build components for a USEEIO model.

Installing the useeiopy Python package

useeiopy is the Python package included in the repository. Once the USEEIO files are downloaded and unzipped, we recommend using pip to install it easily. Open a command prompt and enter:

pip install -e path_to_unzipped_useeio_folder

This will identify dependencies (IO-Model-Builder, pandas) and perform the install. To test it, open python window and try

import useeiopy

If no error is returned then it is installed. T

Running the module requires that the proper files are in the appropriate model folder under useeiopy/Model Builds/. See the example script for more on its use.