Library to gather and disseminate computer-based experimental results.
Project description
# 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.
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