Engine implementations shipped with NRP-coreΒΆ
This page lists Engine implementations currently available with NRP-core. These implementations provide out-of-the-box functionality for use with NRP-core, and also represent good examples to study for users interested in implementing their own engines. For each engine implementation, a general description of the provided functionality is offered first, followed by the engine configuration parameters, and finally a list of datapack types supported by the engine.
Additionally, in order to make it easier to implement new engines, we propose a way to leverage code reusability: for new engine implementations, interested users can therefore refer to one of the available Engine Communication Protocols. These are Engine templates implementing all aspects of engine client / server communication for a given protocol.
List of available engines:
Gazebo : engine implementation for the Gazebo physics simulator
NEST : two different implementations that integrate the NEST Simulator into NRP-core
Python JSON Engine : generic Python-based mechanism that imports and executes a simulator inside a user-defined python script. Ideal for simulators with a Python API.
Python GRPC Engine : This engine is similar to the Python JSON Engine but uses GRPC as the communication mechanism. Compared to Python JSON Engine, this kind of engine has a faster data transfer rate.
PySim : engine implementation based on the Python JSON Engine wrapping different simulators (Mujoco, Opensim and OpenAI) with a python API
The Virtual Brain : engine implementation based on the Python JSON Engine and TVB Python API
Data Transfer Engine : engine implementation designed to transfer data from NRP-core experiments to file or the network.
Related Pages: