python-pyspike-0.9.0-4.fc45.src.rpm

PySpike is a Python library for the numerical analysis of spike train similarity. Its core functionality is the implementation of the ISI-distance[1] and SPIKE-distance[2], SPIKE-Synchronization [3], as well as their adaptive generalizations[4]. It provides functions to compute multivariate profiles, distance matrices, as well as averaging and general spike train processing. All computation intensive parts are implemented in C via Cython to reach a competitive performance (factor 100-200 over plain Python). PySpike provides the same fundamental functionality as the SPIKY framework for Matlab, which additionally contains spike-train generators, more spike train distance measures and many visualization routines. If you use PySpike in your research, please cite our SoftwareX publication on PySpike: Mario Mulansky, Thomas Kreuz, *PySpike - A Python library for analyzing spike train synchrony*, Software X 5, 183 (2016) Additionally, depending on the used methods: ISI-distance [1], SPIKE-distance [2], SPIKE-Synchronization [3], or their adaptive generalizations [4], please cite one or more of the following publications: [1] Kreuz T, Haas JS, Morelli A, Abarbanel HDI, Politi A, Measuring spike train synchrony. J Neurosci Methods 165, 151 (2007) [2] Kreuz T, Chicharro D, Houghton C, Andrzejak RG, Mormann F, Monitoring spike train synchrony. J Neurophysiol 109, 1457 (2013) [3] Kreuz T, Mulansky M and Bozanic N, *SPIKY: A graphical user interface for monitoring spike train synchrony*, J Neurophysiol 113, 3432 (2015) [4] Satuvuori E, Mulansky M, Bozanic N, Malvestio I, Zeldenrust F, Lenk K, and Kreuz T, Measures of spike train synchrony for data with multiple time-scales, J Neurosci Methods 287, 25 (2017) Documentation is available at http://mariomulansky.github.io/PySpike/