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


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)