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

# Copyright (c) 2015 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
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# 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 spynnaker.pyNN.data 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"
TIMESTEP_MS = "timestep_ms"


class SynapseTypeDualExponential(AbstractSynapseType):
    __slots__ = [
        "__tau_syn_E",
        "__tau_syn_E2",
        "__tau_syn_I",
        "__isyn_exc",
        "__isyn_exc2",
        "__isyn_inh"]

    def __init__(
            self, tau_syn_E, tau_syn_E2, tau_syn_I, isyn_exc, isyn_exc2,
            isyn_inh):
        r"""
        :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
        """
        super().__init__(
            [Struct([
                (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, TIMESTEP_MS)])],
            {TAU_SYN_E: "mV", TAU_SYN_E2: "mV", TAU_SYN_I: 'mV', ISYN_EXC: "",
             ISYN_EXC2: "", ISYN_INH: ""})
        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



    @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())




    @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




    @overrides(AbstractSynapseType.get_n_synapse_types)
    def get_n_synapse_types(self):
        return 3




    @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




    @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