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NeuroTools is a collection of tools for representing and anlyzing neuroscientific data.
NeuroTools is written in Python, and works best with PyNN, or one of the growing list of simulation engines with a Python front-end such as NEURON, NEST, PCSIM, VLSI, Brian, MOOSE/GENESIS, Neurospaces/GENESIS. NeuroTools provides modules to facilitate simulation setup, parameterization, data management, analysis and visualization. The data-related tools are equally suited to analysis of experimental data, although that is not the primary motivation for their development.
NeuroTools aims to:
- increase the productivity of individual modellers by automating, simplifying, and establishing best-practices for common tasks,
- increase the productivity of the neuroscience modelling community by reducing the amount of code duplication across simulation communities,
increase the reliability of data analysis tools leveraging Linus's law: "given enough eyeballs, all bugs are shallow."