Source code for spynnaker8.models.synapse_dynamics.synapse_dynamics_stdp
# Copyright (c) 2017-2019 The University of Manchester
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from pyNN.standardmodels.synapses import StaticSynapse as PyNNStaticSynapse
from spinn_front_end_common.utilities import globals_variables
from spinn_front_end_common.utilities.constants import BYTES_PER_WORD
from spynnaker.pyNN.models.neuron.synapse_dynamics import (
SynapseDynamicsSTDP as
_BaseClass)
TIME_STAMP_BYTES = BYTES_PER_WORD
# When not using the MAD scheme, how many pre-synaptic events are buffered
NUM_PRE_SYNAPTIC_EVENTS = 4
[docs]class SynapseDynamicsSTDP(_BaseClass):
__slots__ = []
def __init__(
self, timing_dependence, weight_dependence,
voltage_dependence=None, dendritic_delay_fraction=1.0,
weight=PyNNStaticSynapse.default_parameters['weight'], delay=None,
backprop_delay=True):
"""
:param timing_dependence:
:type timing_dependence:
~spynnaker.pyNN.models.neuron.plasticity.stdp.timing_dependence.AbstractTimingDependence
:param weight_dependence:
:type weight_dependence:
~spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.AbstractWeightDependence
:param None voltage_dependence: Unsupported
:param float dendritic_delay_fraction:
:param float weight:
:param delay:
:type delay: float or None
:param bool backprop_delay:
"""
# pylint: disable=too-many-arguments
# move data from timing to weight dependence over as needed to reflect
# standard structure underneath
a_plus = timing_dependence.A_plus
a_minus = timing_dependence.A_minus
weight_dependence.set_a_plus_a_minus(a_plus=a_plus, a_minus=a_minus)
if delay is None:
delay = globals_variables.get_simulator().min_delay
# instantiate common functionality.
super(SynapseDynamicsSTDP, self).__init__(
timing_dependence, weight_dependence, voltage_dependence,
dendritic_delay_fraction, weight, delay,
backprop_delay=backprop_delay)