Source code for spynnaker8.models.synapse_dynamics.synapse_dynamics_structural_static

# 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
# 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 <>.

from pyNN.standardmodels.synapses import StaticSynapse as PyNNStaticSynapse
from spinn_front_end_common.utilities import globals_variables
from spynnaker.pyNN.models.neuron.synapse_dynamics \
    import SynapseDynamicsStructuralStatic as StaticStructuralBaseClass
from spynnaker.pyNN.models.neuron.synapse_dynamics.\
    synapse_dynamics_structural_common import (

[docs]class SynapseDynamicsStructuralStatic(StaticStructuralBaseClass): __slots__ = [] def __init__( self, partner_selection, formation, elimination, f_rew=DEFAULT_F_REW, initial_weight=DEFAULT_INITIAL_WEIGHT, initial_delay=DEFAULT_INITIAL_DELAY, s_max=DEFAULT_S_MAX, seed=None, weight=PyNNStaticSynapse.default_parameters['weight'], delay=None): """ :param partner_selection: The partner selection rule :type partner_selection: ~spynnaker.pyNN.models.neuron.structural_plasticity.synaptogenesis.partner_selection.AbstractPartnerSelection :param formation: The formation rule :type formation: ~spynnaker.pyNN.models.neuron.structural_plasticity.synaptogenesis.formation.AbstractFormation :param elimination: The elimination rule :type elimination: ~spynnaker.pyNN.models.neuron.structural_plasticity.synaptogenesis.elimination.AbstractElimination :param int f_rew: How many rewiring attempts will be done per second. :param float initial_weight: Weight assigned to a newly formed connection :param initial_delay: Delay assigned to a newly formed connection; a single value means\ a fixed delay value, or a tuple of two values means the delay will\ be chosen at random from a uniform distribution between the given\ values :type initial_delay: float or tuple(float, float) :param int s_max: Maximum fan-in per target layer neuron :param int seed: seed the random number generators :param float weight: The weight of connections formed by the connector :param delay: The delay of connections formed by the connector :type delay: float or None """ if delay is None: delay = globals_variables.get_simulator().min_delay StaticStructuralBaseClass.__init__( self, partner_selection, formation, elimination, f_rew=f_rew, initial_weight=initial_weight, initial_delay=initial_delay, s_max=s_max, seed=seed, weight=weight, delay=delay)