Source code for spynnaker8.models.connectors.fixed_prob_connector

# Copyright (c) 2017-2021 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
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from spynnaker.pyNN.models.neural_projections.connectors import (
    FixedProbabilityConnector as _BaseClass)
from spynnaker.pyNN.utilities.utility_calls import moved_in_v6

[docs]class FixedProbabilityConnector(_BaseClass): """ For each pair of pre-post cells, the connection probability is \ constant. .. deprecated:: 6.0 Use :py:class:`spynnaker.pyNN.models.neural_projections.connectors.FixedProbabilityConnector` instead. """ __slots__ = [] def __init__( self, p_connect, allow_self_connections=True, safe=True, verbose=False, rng=None, callback=None): """ :param float p_connect: a number between zero and one. Each potential connection is created with this probability. :param bool allow_self_connections: if the connector is used to connect a Population to itself, this flag determines whether a neuron is allowed to connect to itself, or only to other neurons in the Population. :param bool safe: if True, check that weights and delays have valid values. If False, this check is skipped. :param space: a Space object, needed if you wish to specify distance-dependent weights or delays - not implemented :param bool verbose: Whether to output extra information about the connectivity to a CSV file :param rng: random number generator :type rng: ~pyNN.random.NumpyRNG or None :param callable callback: if given, a callable that display a progress bar on the terminal. .. note:: Not supported by sPyNNaker. """ # pylint: disable=too-many-arguments moved_in_v6("spynnaker8.models.connectors", "spynnaker.pyNN.models.neural_projections.connectors") _BaseClass.__init__( self, p_connect=p_connect, allow_self_connections=allow_self_connections, safe=safe, verbose=verbose, rng=rng, callback=callback)