Source code for spynnaker.pyNN.models.neuron.additional_inputs.additional_input_ca2_adaptive

# 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/>.

import numpy
from spinn_utilities.overrides import overrides
from data_specification.enums import DataType
from .abstract_additional_input import AbstractAdditionalInput

I_ALPHA = "i_alpha"
I_CA2 = "i_ca2"
TAU_CA2 = "tau_ca2"

UNITS = {
    I_ALPHA: "nA",
    I_CA2: "nA",
    TAU_CA2: "ms"
}


[docs]class AdditionalInputCa2Adaptive(AbstractAdditionalInput): __slots__ = [ "__tau_ca2", "__i_ca2", "__i_alpha"] def __init__(self, tau_ca2, i_ca2, i_alpha): r""" :param tau_ca2: :math:`\tau_{\mathrm{Ca}^{+2}}` :type tau_ca2: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param i_ca2: :math:`I_{\mathrm{Ca}^{+2}}` :type i_ca2: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function :param i_alpha: :math:`I_{\alpha}` :type i_alpha: float, iterable(float), ~pyNN.random.RandomDistribution or (mapping) function """ super().__init__([ DataType.S1615, # e^(-ts / tau_ca2) DataType.S1615, # i_ca_2 DataType.S1615]) # i_alpha self.__tau_ca2 = tau_ca2 self.__i_ca2 = i_ca2 self.__i_alpha = i_alpha
[docs] @overrides(AbstractAdditionalInput.get_n_cpu_cycles) def get_n_cpu_cycles(self, n_neurons): # A bit of a guess return 3 * n_neurons
[docs] @overrides(AbstractAdditionalInput.add_parameters) def add_parameters(self, parameters): parameters[TAU_CA2] = self.__tau_ca2 parameters[I_ALPHA] = self.__i_alpha
[docs] @overrides(AbstractAdditionalInput.add_state_variables) def add_state_variables(self, state_variables): state_variables[I_CA2] = self.__i_ca2
[docs] @overrides(AbstractAdditionalInput.get_units) def get_units(self, variable): return UNITS[variable]
[docs] @overrides(AbstractAdditionalInput.has_variable) def has_variable(self, variable): return variable in UNITS
[docs] @overrides(AbstractAdditionalInput.get_values) def get_values(self, parameters, state_variables, vertex_slice, ts): """ :param int ts: machine time step """ # pylint: disable=arguments-differ # Add the rest of the data return [parameters[TAU_CA2].apply_operation( operation=lambda x: numpy.exp(float(-ts) / (1000.0 * x))), state_variables[I_CA2], parameters[I_ALPHA]]
[docs] @overrides(AbstractAdditionalInput.update_values) def update_values(self, values, parameters, state_variables): # Read the data (_exp_tau_ca2, i_ca2, _i_alpha) = values # Copy the changed data only state_variables[I_CA2] = i_ca2
@property def tau_ca2(self): r""" Settable model parameter: :math:`\tau_{\mathrm{Ca}^{+2}}` :rtype: float """ return self.__tau_ca2 @property def i_ca2(self): r""" Settable model parameter: :math:`I_{\mathrm{Ca}^{+2}}` :rtype: float """ return self.__i_ca2 @property def i_alpha(self): r""" Settable model parameter: :math:`I_{\alpha}` :rtype: float """ return self.__i_alpha