Source code for spynnaker.pyNN.models.neuron.builds.if_curr_delta

# 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 spynnaker.pyNN.models.neuron import AbstractPyNNNeuronModelStandard
from spynnaker.pyNN.models.defaults import default_initial_values
from spynnaker.pyNN.models.neuron.neuron_models import (
from spynnaker.pyNN.models.neuron.input_types import InputTypeDelta
from spynnaker.pyNN.models.neuron.threshold_types import ThresholdTypeStatic
from spynnaker.pyNN.models.neuron.synapse_types import SynapseTypeDelta

[docs]class IFCurrDelta(AbstractPyNNNeuronModelStandard): """ Leaky integrate and fire neuron with an instantaneous current input. :param tau_m: :math:`\\tau_m` :type tau_m: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param cm: :math:`C_m` :type cm: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param v_rest: :math:`V_{rest}` :type v_rest: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param v_reset: :math:`V_{reset}` :type v_reset: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param v_thresh: :math:`V_{thresh}` :type v_thresh: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param tau_refrac: :math:`\\tau_{refrac}` :type tau_refrac: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param i_offset: :math:`I_{offset}` :type i_offset: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param v: :math:`V_{init}` :type v: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param isyn_exc: :math:`I^{syn}_e` :type isyn_exc: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param isyn_inh: :math:`I^{syn}_i` :type: isyn_inh: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function """ # noinspection PyPep8Naming @default_initial_values({"v", "isyn_exc", "isyn_inh"}) def __init__( self, tau_m=20.0, cm=1.0, v_rest=-65.0, v_reset=-65.0, v_thresh=-50.0, tau_refrac=0.1, i_offset=0.0, v=-65.0, isyn_exc=0.0, isyn_inh=0.0): # pylint: disable=too-many-arguments, too-many-locals neuron_model = NeuronModelLeakyIntegrateAndFire( v, v_rest, tau_m, cm, i_offset, v_reset, tau_refrac) synapse_type = SynapseTypeDelta(isyn_exc, isyn_inh) input_type = InputTypeDelta() threshold_type = ThresholdTypeStatic(v_thresh) super().__init__( model_name="IF_curr_delta", binary="IF_curr_delta.aplx", neuron_model=neuron_model, input_type=input_type, synapse_type=synapse_type, threshold_type=threshold_type)