Source code for spynnaker.pyNN.models.neuron.input_types.input_type_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
# 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/>.

from spinn_utilities.overrides import overrides
from data_specification.enums import DataType
from .abstract_input_type import AbstractInputType


[docs]class InputTypeDelta(AbstractInputType): """ The delta input type """ __slots__ = [] def __init__(self): """ """ super().__init__([ DataType.S1615]) # scale_factor, calculated from timestep
[docs] @overrides(AbstractInputType.get_n_cpu_cycles) def get_n_cpu_cycles(self, n_neurons): return 1 * n_neurons
[docs] @overrides(AbstractInputType.add_parameters) def add_parameters(self, parameters): pass
[docs] @overrides(AbstractInputType.add_state_variables) def add_state_variables(self, state_variables): pass
[docs] @overrides(AbstractInputType.get_values) def get_values(self, parameters, state_variables, vertex_slice, ts): # pylint: disable=arguments-differ scale_factor = 1000.0 / float(ts) return [scale_factor]
[docs] @overrides(AbstractInputType.update_values) def update_values(self, values, parameters, state_variables): pass
[docs] @overrides(AbstractInputType.get_units) def get_units(self, variable): raise KeyError(variable)
[docs] @overrides(AbstractInputType.has_variable) def has_variable(self, variable): return False
[docs] @overrides(AbstractInputType.get_global_weight_scale) def get_global_weight_scale(self): return 1.0