pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface.
For obtaining a zip file of the current state use: https://github.com/pyspace/pyspace/archive/master.zip
- more than 200 algorithms
- machine learning AND signal processing support
- support of several EEG data formats
- parameter optimization
- simple documentation and testing interfaces
- simple configuration with YAML
- parallel processing on high performance clusters possible
- details: http://pyspace.github.io/pyspace/index.html
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