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Difference between revisions of "Neo"
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The goal of Neo is to improve interoperability between Python tools for analyzing, visualizing and generating electrophysiology data (such as OpenElectrophy, Elephant, G-node, Helmholtz, PyNN) by providing a common, shared object model. In order to be as lightweight a dependency as possible, Neo is deliberately limited to represention of data, with no functions for data analysis or visualization. | The goal of Neo is to improve interoperability between Python tools for analyzing, visualizing and generating electrophysiology data (such as OpenElectrophy, Elephant, G-node, Helmholtz, PyNN) by providing a common, shared object model. In order to be as lightweight a dependency as possible, Neo is deliberately limited to represention of data, with no functions for data analysis or visualization. | ||
| + | |||
| + | ==Organizations== | ||
| + | *[[NeuralEnsemble|NeuralEnsemble]] | ||
==Links== | ==Links== | ||
[http://neuralensemble.org/neo/ Website] | [http://neuralensemble.org/neo/ Website] | ||
[https://neo.readthedocs.io/en/stable/ Docs] | [https://neo.readthedocs.io/en/stable/ Docs] | ||
Revision as of 01:38, 6 April 2022
Neo is a package for representing electrophysiology data in Python, together with support for reading a wide range of neurophysiology file formats, including Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock, Plexon, Tdt, and support for writing to a subset of these formats plus non-proprietary formats including HDF5.
The goal of Neo is to improve interoperability between Python tools for analyzing, visualizing and generating electrophysiology data (such as OpenElectrophy, Elephant, G-node, Helmholtz, PyNN) by providing a common, shared object model. In order to be as lightweight a dependency as possible, Neo is deliberately limited to represention of data, with no functions for data analysis or visualization.