Source code for spynnaker.pyNN.models.common.abstract_neuron_recordable

# 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
# 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 <>.

from spinn_utilities.abstract_base import AbstractBase, abstractmethod
from spinn_utilities.require_subclass import require_subclass
from pacman.model.graphs.application import ApplicationVertex

[docs]@require_subclass(ApplicationVertex) class AbstractNeuronRecordable(object, metaclass=AbstractBase): """ Indicates that a variable (e.g., membrane voltage) can be recorded\ from this object. """ __slots__ = ()
[docs] @abstractmethod def get_recordable_variables(self): """ Returns a list of the PyNN names of variables this model is \ expected to collect :rtype: list(str) """
[docs] @abstractmethod def is_recording(self, variable): """ Determines if variable is being recorded. :param str variable: PyNN name of the variable :return: True if variable are being recorded, False otherwise :rtype: bool """
[docs] @abstractmethod def set_recording(self, variable, new_state=True, sampling_interval=None, indexes=None): """ Sets variable to being recorded :param str variable: PyNN name of the variable :param bool new_state: :param sampling_interval: :type sampling_interval: int or None :param indexes: Which indices are to be recorded (or None for all) :type indexes: list or None """
[docs] @abstractmethod def clear_recording(self, variable, buffer_manager, placements): """ Clear the recorded data from the object :param str variable: PyNN name of the variable :param buffer_manager: the buffer manager object :type buffer_manager: ~spinn_front_end_common.interface.buffer_management.BufferManager :param ~pacman.model.placements.Placements placements: the placements object :rtype: None """
[docs] @abstractmethod def get_data( self, variable, n_machine_time_steps, placements, buffer_manager): """ Get the recorded data :param str variable: PyNN name of the variable :param int n_machine_time_steps: :param ~pacman.model.placements.Placements placements: :param buffer_manager: :type buffer_manager: ~spinn_front_end_common.interface.buffer_management.BufferManager :return: (data, recording_indices, sampling_interval) :rtype: tuple(~numpy.ndarray,list(int),float) """
# pylint: disable=too-many-arguments
[docs] @abstractmethod def get_neuron_sampling_interval(self, variable): """ Returns the current sampling interval for this variable :param str variable: PyNN name of the variable :return: Sampling interval in microseconds :rtype: float """
[docs] @abstractmethod def get_expected_n_rows( self, n_machine_time_steps, sampling_rate, vertex, variable): """ Returns the number of expected rows for a given runtime :param int n_machine_time_steps: map of vertex to steps. :param int sampling_rate: the sampling rate for this vertex :param ~pacman.model.graphs.machine.MachineVertex vertex: the machine vertex :param str variable: the variable being recorded :return: int the number of rows expected. """