enb 0.2.7

Library to gather and disseminate computer-based experimental results.

# Experiment Notebook Python library to design, run and plot experiments.

Ideal for cases where:

• multiple inputs need to be processed by one or more customizable tasks, producing a table of data

• one wants to apply custom code to existing data to produce new columns

• analysis tables and plots are needed for one or more data columns

## Installation

On most Linux distributions, you can simply run

pip install enb

On Windows, you may encounter a dependency problem with the ray library. To solve it, install ray manually (https://docs.ray.io/en/master/installation.html) and then run pip install enb normally.

## Documentation

A [user manual](https://miguelinux314.github.io/experiment-notebook) is available that explains the basics and introduces some ready-to-adapt experiment examples.

You can also take a look at the templates/ and plugins/ code folders for some useful examples.

You are welcome to submit your extensions via a pull request to the dev branch.

See [CHANGELOG.md](https://github.com/miguelinux314/experiment-notebook/blob/master/CHANGELOG.md) for a summary of changes compared to recent versions.