PyReCo Library

PyReCo is a Python based library built by researchers for researchers: we aim to develop new RC methods that allow for fast and efficient learning for sequential data. The main focus is time series prediction, mostly performed in an auto-regressive fashion based on learning discrete flow maps. Another core aspect that motivates the implementation of a new library is structure-function-relationships in functional networks.

Installation

pip install pyreco

PyReCo allows to implement novel ways to generate better reservoir networks than the classical random choice. Overview of the core capabilities of pyReCo:

• Classical reservoir computing: using random reservoir layers and training readout-layer weights using Ridge regression
• Cross-validation: built-in functions to k-fold cross-validate any ResPy model for performance evaluation
• auto-regressive time stepping through feeding the predictions into the input layer (closed-loop prediction system)
• automated hyper-parameter tuning for leakage rate, activation function, reservoir network properties, etc.