Source code for spynnaker8.models.connectors.index_based_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
# 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 spynnaker.pyNN.models.neural_projections.connectors import (
    IndexBasedProbabilityConnector as _BaseClass)
from spynnaker.pyNN.utilities.utility_calls import moved_in_v6

[docs]class IndexBasedProbabilityConnector(_BaseClass): """ Create an index-based probability connector. The `index_expression` must depend on the indices `i`, `j` of the\ populations. .. deprecated:: 6.0 Use :py:class:`spynnaker.pyNN.models.neural_projections.connectors.IndexBasedProbabilityConnector` instead. """ __slots__ = [] def __init__( self, index_expression, allow_self_connections=True, rng=None, safe=True, callback=None, verbose=False): """ :param str index_expression: A function of the indices of the populations, written as a Python expression; the indices will be given as variables ``i`` and ``j`` when the expression is evaluated. :param bool allow_self_connections: allow a neuron to connect to itself :param rng: random number generator :type rng: ~pyNN.random.NumpyRNG or None :param bool safe: Whether to check that weights and delays have valid values. If False, this check is skipped. :param callable callback: if given, a callable that display a progress bar on the terminal. .. note:: Not supported by sPyNNaker. :param bool verbose: Whether to output extra information about the connectivity to a CSV file """ # pylint: disable=too-many-arguments moved_in_v6("spynnaker8.models.connectors" ".IndexBasedProbabilityConnector", "spynnaker.pyNN.models.neural_projections.connectors" ".IndexBasedProbabilityConnector") super(IndexBasedProbabilityConnector, self).__init__( index_expression=index_expression, allow_self_connections=allow_self_connections, rng=rng, safe=safe, callback=callback, verbose=verbose)