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# This file is part of the Neurorobotics Platform software
# Copyright (C) 2014,2015,2016,2017 Human Brain Project
# https://www.humanbrainproject.eu
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# The Human Brain Project is a European Commission funded project
# in the frame of the Horizon2020 FET Flagship plan.
# http://ec.europa.eu/programmes/horizon2020/en/h2020-section/fet-flagships
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
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'''
PyNNCommunicationAdapter.py
moduleauthor: probst@fzi.de
'''
import logging
from hbp_nrp_cle.brainsim.BrainInterface import ILeakyIntegratorAlpha, \
IDCSource, IACSource, INCSource, ILeakyIntegratorExp, IPopulationRate, \
IFixedSpikeGenerator, ISpikeRecorder, IPoissonSpikeGenerator
from hbp_nrp_cle.brainsim.pynn.PyNNCommunicationAdapter import PyNNCommunicationAdapter
from .devices import PyNNNestACSource, PyNNNestDCSource, PyNNNestNCSource, \
PyNNNestLeakyIntegratorAlpha, PyNNNestLeakyIntegratorExp, PyNNNestFixedSpikeGenerator, \
PyNNNestPopulationRate, PyNNNestSpikeRecorder, PyNNNestPoissonSpikeGenerator
logger = logging.getLogger(__name__)
__author__ = 'Dimitri Probst, Sebastian Krach'
# Pylint for some reason does not see that the methods is_population and create_view are already
# overridden
# pylint: disable=abstract-method
[docs]class PyNNNestCommunicationAdapter(PyNNCommunicationAdapter):
"""
Represents the communication adapter to the neuronal simulator
"""
# In this dictionary, the association of spike generator types to classes
# implementing their functionality is established
__device_dict = {IFixedSpikeGenerator: PyNNNestFixedSpikeGenerator,
IDCSource: PyNNNestDCSource,
IACSource: PyNNNestACSource,
INCSource: PyNNNestNCSource,
ILeakyIntegratorAlpha: PyNNNestLeakyIntegratorAlpha,
ILeakyIntegratorExp: PyNNNestLeakyIntegratorExp,
IPopulationRate: PyNNNestPopulationRate,
ISpikeRecorder: PyNNNestSpikeRecorder,
IPoissonSpikeGenerator: PyNNNestPoissonSpikeGenerator}
[docs] def initialize(self):
"""
Marks the PyNN adapter as initialized
"""
super(PyNNNestCommunicationAdapter, self).initialize()
def _get_device_type(self, device_type):
"""
Returns the pynn specific implementation for specified device type
:param device_type: the device type for which the implementation type is requested
:return: the concrete type
"""
if device_type in self.__device_dict:
return self.__device_dict[device_type]
return super(PyNNNestCommunicationAdapter, self)._get_device_type(device_type)