# 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
# 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
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# 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 <http://www.gnu.org/licenses/>.
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
"""
__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)