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Standalone Python wheels for the EDEN neural simulator

Project description

EDEN Python bindings + wheels

EDEN is a high-performance NeuroML-based neural simulator written in C++. This wheel package contains Python bindings to use the simulator, as well as win32, win_amd64, macosx_x86_64 and manylinux1 standalone builds of the simulator.


EDEN can be installed with one pip command:

pip install eden-simulator

The only non-pip requirement is for the GNU C compiler, Intel C compiler or Clang to be installed and available on PATH at run time.


EDEN directly runs NeuroML v2 models of neural networks.

The eden_simulator package exposes the runEden method, which takes the LEMS simulation file of the NeuroML model to be run as parameter:

import eden_simulator
results = eden_simulator.runEden('<LEMS simulation file>.xml')

This interface returns the recorded trajectories specified in the simulation files in a Python dictionary, same as pyNeuroML does with other simulation backends.

Thread-level parallelism can also be controlled with the threads keyword argument.

The recorded trajectories are also available relative to the working directory, as specified in the LEMS file. Some .gen.c and temporary files may also be generated in the working directory, these can be removed after the simulation is run.

For more information about the NeuroML model format, refer to .

The program's source code is available on GitLab: .

This software is released as open-source, under the GNU General Public License version 3.

If you have any questions, suggestions or issues with running EDEN, please submit a ticket on GitLab, or contact the developer at .

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eden_simulator-0.2.0-py3-none-win_amd64.whl (2.1 MB view hashes)

Uploaded Python 3 Windows x86-64

eden_simulator-0.2.0-py3-none-win32.whl (1.9 MB view hashes)

Uploaded Python 3 Windows x86

eden_simulator-0.2.0-py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (3.5 MB view hashes)

Uploaded Python 3 manylinux: glibc 2.5+ x86-64

eden_simulator-0.2.0-py3-none-macosx_10_6_x86_64.whl (1.6 MB view hashes)

Uploaded Python 3 macOS 10.6+ x86-64

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