# 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
# 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 (
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
"""
__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)