Source code for spynnaker.pyNN.models.neuron.synapse_dynamics.abstract_plastic_synapse_dynamics

# Copyright (c) 2017-2019 The University of Manchester
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# This program is free software: you can redistribute it and/or modify
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# the Free Software Foundation, either version 3 of the License, or
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# This program is distributed in the hope that it will be useful,
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# GNU General Public License for more details.
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from spinn_utilities.abstract_base import AbstractBase, abstractmethod
from .abstract_synapse_dynamics import AbstractSynapseDynamics


[docs]class AbstractPlasticSynapseDynamics( AbstractSynapseDynamics, metaclass=AbstractBase): """ Synapses which change over time """ # pylint: disable=too-many-arguments __slots__ = ()
[docs] @abstractmethod def get_n_words_for_plastic_connections(self, n_connections): """ Get the number of 32-bit words for `n_connections` in a single row. :param int n_connections: :rtype: int """
[docs] @abstractmethod def get_plastic_synaptic_data( self, connections, connection_row_indices, n_rows, post_vertex_slice, n_synapse_types, max_n_synapses): """ Get the fixed-plastic data, and plastic-plastic data for each row,\ and lengths for the fixed_plastic and plastic-plastic parts of\ each row. Data is returned as an array made up of an array of 32-bit words for\ each row, for each of the fixed-plastic and plastic-plastic data\ regions. The row into which connection should go is given by\ `connection_row_indices`, and the total number of rows is given by\ `n_rows`. Lengths are returned as an array made up of an integer for each row,\ for each of the fixed-plastic and plastic-plastic regions. :param ~numpy.ndarray connections: The connections to get data for :param ~numpy.ndarray connection_row_indices: The row into which each connection should go :param int n_rows: The total number of rows :param ~pacman.model.graphs.common.Slice post_vertex_slice: The slice of the post vertex to get the connections for :param int n_synapse_types: The number of synapse types :param int max_n_synapses: The maximum number of synapses to generate :return: (fp_data, pp_data, fp_size, pp_size) :rtype: tuple(~numpy.ndarray, ~numpy.ndarray, ~numpy.ndarray, ~numpy.ndarray) """
[docs] @abstractmethod def get_n_plastic_plastic_words_per_row(self, pp_size): """ Get the number of plastic plastic words to be read from each row. :param ~numpy.ndarray pp_size: """
[docs] @abstractmethod def get_n_fixed_plastic_words_per_row(self, fp_size): """ Get the number of fixed plastic words to be read from each row. :param ~numpy.ndarray fp_size: """
[docs] @abstractmethod def get_n_synapses_in_rows(self, pp_size, fp_size): """ Get the number of synapses in each of the rows with plastic sizes\ `pp_size` and `fp_size`. :param ~numpy.ndarray pp_size: :param ~numpy.ndarray fp_size: """
[docs] @abstractmethod def read_plastic_synaptic_data( self, post_vertex_slice, n_synapse_types, pp_size, pp_data, fp_size, fp_data): """ Read the connections indicated in the connection indices from the\ data in `pp_data` and `fp_data`. :param ~pacman.model.graphs.common.Slice post_vertex_slice: :param int n_synapse_types: :param ~numpy.ndarray pp_size: 1D :param ~numpy.ndarray pp_data: 2D :param ~numpy.ndarray fp_size: 1D :param ~numpy.ndarray fp_data: 2D :return: array with columns ``source``, ``target``, ``weight``, ``delay`` :rtype: ~numpy.ndarray """