1. Installation

1.1. Overview

EONR is an open-source package written in Python. It runs on all major platforms (i.e., Windows, Linux, Mac).

1.2. Install Python

If you don’t have Python (or don’t know), don’t worry. The EONR package was designed to be used with as little Python expertise as possible.

There are many ways to download and install Python. As a scientist, my recommendation is definitely through the Anaconda distribution. Anaconda will have the more popular packages already installed in your Python environment, and it comes with Spyder and Jupyter notebooks. Spyder and Jupyter make working with Python quite easy.

Although I think you’ll find EONR to be pretty user-friendly, you may find it to your benefit to become a bit more familiar with Python before using EONR. If you’re a beginner, it will be helpful to read the Python Tutorial and/or get some hands-on practice with this Python Tutorial by w3Schools.

The best way to learn is to do.

1.3. Install EONR

To install the latest release of EONR, you can use Anaconda:

conda install -c conda-forge eonr

or pip:

pip install eonr

Alternatively, you can use pip to install the development version directly from github:

pip install git+https://github.com/tnigon/eonr

Another option is to clone the github repository and install from your local copy. After navigating to the directory of your local copy:

pip install .

The recommended folder directory for the EONR package is in the site-packages folder in your Python Path (alongside all other Python packages).

1.4. Dependencies

EONR requires the following packages:

Seaborn and Uncertainties are available on Anaconda Cloud (can be installed via conda install), but Scikits.bootstrap is only available on the PyPI and must be installed via pip install.