The Model Container is used as an abstraction layer on top of a simulator and deals with biological entities and end-user concepts instead of mathematical equations.
The Model Container is used as an abstraction layer on top of a simulator and deals with biological entities and end-user concepts instead of mathematical equations. It provides a solver independent internal storage format for models that allows user independent optimizations of the numerical core. By containing the biological model, the Model Container makes the implementation of the numerical core independent of software implementation. The Model Container API abstracts away all the mathematical and computational details of the simulator. Optimized to store large models in little memory it stores neuronal models in a fraction of the memory that would be used by conventional simulators and provides automatic partitioning of the model such that simulations can be run in parallel. From the modeler’s perspective, the Model Container will be able to import and export NeuroML files to facilitate model exchange and ideas.
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|Filename, size & hash SHA256 hash help||File type||Python version||Upload date|
|model_container-0.0.0_alpha-py2.5-linux-i686.egg (3.3 MB) Copy SHA256 hash SHA256||Egg||2.5||Sep 13, 2011|
|model_container-0.0.0_alpha-py2.5-macosx-10.6-i386.egg (526.3 kB) Copy SHA256 hash SHA256||Egg||2.5||Sep 14, 2011|
|model_container-0.0.0_alpha-py2.6-linux-i686.egg (3.4 MB) Copy SHA256 hash SHA256||Egg||2.6||Sep 13, 2011|
|model_container-0.0.0_alpha-py2.6-macosx-10.3-fat.egg (1.0 MB) Copy SHA256 hash SHA256||Egg||2.6||Sep 14, 2011|