Large-scale neural data analysis in Spark
Project description
Thunder
Large-scale neural data analysis with Spark
About
Thunder is a library for analyzing large-scale spatial and temopral neural data. It’s fast to run, easy to extend, and designed for interactivity. It is built on Spark, a new framework for cluster computing.
Thunder includes utilties for loading and saving different formats, classes for working with distributed spatial and temporal data, and modular functions for time series analysis, factorization, and model fitting. Analyses can easily be scripted or combined. It is written against Spark’s Python API (Pyspark), making use of scipy, numpy, and scikit-learn.
To learn more, follow these links to the primary documentation:
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