Source code for spynnaker.pyNN.models.abstract_models.abstract_max_spikes

# 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
#
#     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.abstract_base import AbstractBase, abstractmethod
from spinn_utilities.require_subclass import require_subclass
from pacman.model.graphs.machine import MachineVertex


@require_subclass(MachineVertex)
class AbstractMaxSpikes(object, metaclass=AbstractBase):
    """
    Indicates a class (a
    :py:class:`~pacman.model.graphs.machine.MachineVertex`)
    that can describe the maximum rate that it sends spikes.

    The :py:class:`~.SynapticManager` assumes that all machine vertexes
    share the same synapse_information will have the same rates.
    """

    __slots__ = ()


[docs]
    @abstractmethod
    def max_spikes_per_ts(self) -> float:
        """
        Get maximum expected number of spikes per timestep.
        """
        raise NotImplementedError



[docs]
    @abstractmethod
    def max_spikes_per_second(self) -> float:
        """
        Get maximum expected number of spikes per second.
        """
        raise NotImplementedError