py_neuromodulation The py_neuromodulation toolbox allows for real time capable processing of multimodal electrophysiological data. The primary use is movement prediction for adaptive deep brain stimulation. Find the documentation here https://neuromodulation.github.io/py_neuromodulation/ for example usage and parametrization. Setup For running this toolbox first create a new virtual conda environment: conda env create –file=env.yml –user The main modules include running real time enabled feature preprocessing based on iEEG BIDS data. Different features can be enabled/disabled and parametrized in the `https://github.com/neuromodulation/py_neuromodulation/blob/main/pyneuromodulation/nm_settings.json>`_. The current implementation […]

lazycluster is a Python library intended to liberate data scientists and machine learning engineers by abstracting away cluster management and configuration so that they are able to focus on their actual tasks. Especially, the easy and convenient cluster setup with Python for various distributed machine learning frameworks is emphasized. Highlights High-Level API for starting clusters: DASK Hyperopt More lazyclusters (e.g. Ray, PyTorch, Tensorflow, Horovod, Spark) to come … Lower-level API for: Managing Runtimes or RuntimeGroups to: A-/synchronously execute RuntimeTasks by […]