Supporting content for the Reservoir Computing paper with Bacteria paper

This repository contains code to support the Computing paper with Bacteria publication. See citation for details.

Table of Contents

• 1. Repository structure
• 2. Installation
• 3. Usage
• 4. Citation

1. Repository structure

.
├── Dataset_input       < placeholder for data files >
│   └── ..
├── Reservoir       < trained reservoir model>
│   └── ..
├── Result     
│   └── ..
├── Library       < supporting code for notebook >
│   └── ..
├── 1.Dataset-species.ipynb
├── 2.Fixed-prior.ipynb
├── 3.ML-covid.ipynb
├── 4.Reservoir-covid.ipynb
├── 5.Reservoir-species.ipynb
├── README.md
└── requirements.yaml

2. Installation

The following steps will set up a reservoir conda environment.

0. Install Conda:

   The conda package manager is required. If you do not have it installed, you can download it from here. Follow the instructions on the page to install Conda. For example, on Windows, you would download the installer and run it. On macOS and Linux, you might use a command like:

   bash ~/Downloads/Miniconda3-latest-Linux-x86_64.sh

   Follow the prompts on the installer to complete the installation.

1. Install dependencies:

   conda env create -f requirements.yaml
   conda activate reservoir

2. Download data:

   Trained reservoir models and most important datasets are available as a Zenodo archive: https://doi.org/10.5281/zenodo.14961168. Extract the files and place them in the Dataset-input, Reservoir, Result directory.

3. Usage

Dataset-sp:

4. Citation