Source code for spynnaker.pyNN.models.neuron.synapse_types.synapse_type_semd

# Copyright (c) 2017 The University of Manchester
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.

from spinn_utilities.overrides import overrides
from spinn_front_end_common.interface.ds import DataType
from .abstract_synapse_type import AbstractSynapseType
from spynnaker.pyNN.utilities.struct import Struct
from import SpynnakerDataView

TAU_SYN_E = 'tau_syn_E'
TAU_SYN_E2 = 'tau_syn_E2'
TAU_SYN_I = 'tau_syn_I'
ISYN_EXC = "isyn_exc"
ISYN_EXC2 = "isyn_exc2"
ISYN_INH = "isyn_inh"
MULTIPLICATOR = "multiplicator"
EXC2_OLD = "exc2_old"
SCALING_FACTOR = "scaling_factor"
TIMESTEP_MS = "timestep_ms"

class SynapseTypeSEMD(AbstractSynapseType):
    __slots__ = [

    def __init__(
            self, tau_syn_E, tau_syn_E2, tau_syn_I, isyn_exc, isyn_exc2,
            isyn_inh, multiplicator, exc2_old, scaling_factor):
        :param tau_syn_E: :math:`\tau^{syn}_{e_1}`
        :type tau_syn_E: float or iterable(float) or
            ~spynnaker.pyNN.RandomDistribution or (mapping) function
        :param tau_syn_E2: :math:`\tau^{syn}_{e_2}`
        :type tau_syn_E2: float or iterable(float) or
            ~spynnaker.pyNN.RandomDistribution or (mapping) function
        :param tau_syn_I: :math:`\tau^{syn}_i`
        :type tau_syn_I: float or iterable(float) or
            ~spynnaker.pyNN.RandomDistribution or (mapping) function
        :param isyn_exc: :math:`I^{syn}_{e_1}`
        :type isyn_exc: float or iterable(float) or
            ~spynnaker.pyNN.RandomDistribution or (mapping) function
        :param isyn_exc2: :math:`I^{syn}_{e_2}`
        :type isyn_exc2: float or iterable(float) or
            ~spynnaker.pyNN.RandomDistribution or (mapping) function
        :param isyn_inh: :math:`I^{syn}_i`
        :type isyn_inh: float or iterable(float) or
            ~spynnaker.pyNN.RandomDistribution or (mapping) function
        :param multiplicator:
        :type multiplicator: float or iterable(float) or
            ~spynnaker.pyNN.RandomDistribution or (mapping) function
        :param exc2_old:
        :type exc2_old: float or iterable(float) or
            ~spynnaker.pyNN.RandomDistribution or (mapping) function
        :param scaling_factor:
        :type scaling_factor: float or iterable(float) or
            ~spynnaker.pyNN.RandomDistribution or (mapping) function
                (DataType.S1615, TAU_SYN_E),
                (DataType.S1615, ISYN_EXC),
                (DataType.S1615, TAU_SYN_E2),
                (DataType.S1615, ISYN_EXC2),
                (DataType.S1615, TAU_SYN_I),
                (DataType.S1615, ISYN_INH),
                (DataType.S1615, MULTIPLICATOR),
                (DataType.S1615, EXC2_OLD),
                (DataType.S1615, SCALING_FACTOR),
                (DataType.S1615, TIMESTEP_MS)])],
            {TAU_SYN_E: "mV", TAU_SYN_E2: "mV", TAU_SYN_I: 'mV', ISYN_EXC: "",
             ISYN_EXC2: "", ISYN_INH: "", MULTIPLICATOR: "", EXC2_OLD: "",
             SCALING_FACTOR: ""})
        self.__tau_syn_E = tau_syn_E
        self.__tau_syn_E2 = tau_syn_E2
        self.__tau_syn_I = tau_syn_I
        self.__isyn_exc = isyn_exc
        self.__isyn_exc2 = isyn_exc2
        self.__isyn_inh = isyn_inh
        self.__multiplicator = multiplicator
        self.__exc2_old = exc2_old
        self.__scaling_factor = scaling_factor

[docs] @overrides(AbstractSynapseType.add_parameters) def add_parameters(self, parameters): parameters[TAU_SYN_E] = self.__tau_syn_E parameters[TAU_SYN_E2] = self.__tau_syn_E2 parameters[TAU_SYN_I] = self.__tau_syn_I parameters[TIMESTEP_MS] = ( SpynnakerDataView.get_simulation_time_step_ms()) parameters[SCALING_FACTOR] = self.__scaling_factor
[docs] @overrides(AbstractSynapseType.add_state_variables) def add_state_variables(self, state_variables): state_variables[ISYN_EXC] = self.__isyn_exc state_variables[ISYN_EXC2] = self.__isyn_exc2 state_variables[ISYN_INH] = self.__isyn_inh state_variables[EXC2_OLD] = self.__exc2_old state_variables[MULTIPLICATOR] = self.__multiplicator
[docs] @overrides(AbstractSynapseType.get_n_synapse_types) def get_n_synapse_types(self): return 3
[docs] @overrides(AbstractSynapseType.get_synapse_id_by_target) def get_synapse_id_by_target(self, target): if target == "excitatory": return 0 elif target == "excitatory2": return 1 elif target == "inhibitory": return 2 return None
[docs] @overrides(AbstractSynapseType.get_synapse_targets) def get_synapse_targets(self): return "excitatory", "excitatory2", "inhibitory"
@property def tau_syn_E(self): return self.__tau_syn_E @property def tau_syn_E2(self): return self.__tau_syn_E2 @property def tau_syn_I(self): return self.__tau_syn_I @property def isyn_exc(self): return self.__isyn_exc @property def isyn_inh(self): return self.__isyn_inh @property def isyn_exc2(self): return self.__isyn_exc2 @property def multiplicator(self): return self.__multiplicator @property def exc2_old(self): return self.__exc2_old @property def scaling_factor(self): return self.__scaling_factor