Source code for spynnaker8.models.connectors.distance_dependent_prob_connector

# Copyright (c) 2017-2021 The University of Manchester
#
# 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 spynnaker.pyNN.models.neural_projections.connectors import (
    DistanceDependentProbabilityConnector as
    _BaseClass)
from spynnaker.pyNN.utilities.utility_calls import moved_in_v6


[docs]class DistanceDependentProbabilityConnector(_BaseClass): """ Make connections using a distribution which varies with distance. .. deprecated:: 6.0 Use :py:class:`spynnaker.pyNN.models.neural_projections.connectors.DistanceDependentProbabilityConnector` instead. """ __slots__ = [] def __init__( self, d_expression, allow_self_connections=True, safe=True, verbose=False, n_connections=None, rng=None, callback=None): """ :param str d_expression: the right-hand side of a valid python expression for probability, involving `d`, e.g. ``"exp(-abs(d))"``, or ``"d<3"``, that can be parsed by :py:func:`eval`, that computes the distance dependent distribution :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 bool verbose: Whether to output extra information about the connectivity to a CSV file :param int n_connections: The number of efferent synaptic connections per neuron. :param ~pyNN.random.NumpyRNG rng: random number generator :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" ".DistanceDependentProbabilityConnector", "spynnaker.pyNN.models.neural_projections.connectors" ".DistanceDependentProbabilityConnector") _BaseClass.__init__( self, d_expression=d_expression, allow_self_connections=allow_self_connections, safe=safe, verbose=verbose, n_connections=n_connections)