CircuitML is an extension to NeuroML 2.0 that enables one to define reusable heterogeneous circuit motifs and connectivity patterns and use them to construct complex networks.
This package contains the following:
- An XML schema defining the CircuitML extensions to NeuroML 2.0. This schema
defines the following major constructs:
- subcircuit: a reusable heterogeneous circuit container.
- interface: a subcircuit interface that enables addressing of circuit elements contributed by multiple constituent subcircuits via a unified namespace specific to the outermost subcircuit.
- connectivity: a synaptic connectivity pattern that describes connections between potentially heterogeneous elements in two subcircuits.
- A Python parser that extends libNeuroML [2] to enable processing of files containing CircuitML constructs.
- A libNeuroML backend for storing data specified using CircuitML to GPU-based data structures using PyCUDA [3].
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- lxml 2.3 or later.
- NumPy 1.2.0 or later.
- SciPy 0.11.0 or later.
- libNeuroML 0.1.9 or later.
- PyCUDA 2011.1.2 or later.
This software is licensed under the BSD License. See the included LICENSE file for more information. >>>>>>> 2345d31a05228ced955f22fde8009b65a1d3fdfb
| [1] | http://neuroml.org/neuroml2.php |
| [2] | https://github.com/NeuralEnsemble/libNeuroML |
| [3] | http://mathema.tician.de/software/pycuda |