# Source code for spynnaker.pyNN.models.neuron.synapse_dynamics.abstract_supports_signed_weights

```
# Copyright (c) 2021 The University of Manchester
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from spinn_utilities.abstract_base import AbstractBase, abstractmethod
class AbstractSupportsSignedWeights(object, metaclass=AbstractBase):
"""
A synapse dynamics object that supports signed weights.
"""
[docs]
@abstractmethod
def get_positive_synapse_index(self, incoming_projection):
"""
Get the synapse type that positive weights will arrive at.
:param incoming_projection: The projection targeted
:type incoming_projection: ~spynnaker.pyNN.models.projection.Projection
:rtype: int
"""
[docs]
@abstractmethod
def get_negative_synapse_index(self, incoming_projection):
"""
Get the synapse type that negative weights will arrive at.
:param incoming_projection: The projection targeted
:type incoming_projection: ~spynnaker.pyNN.models.projection.Projection
:rtype: int
"""
[docs]
@abstractmethod
def get_maximum_positive_weight(self, incoming_projection):
"""
Get the maximum likely positive weight.
.. note::
This must be a value >= 0.
:param incoming_projection: The projection targeted
:type incoming_projection: ~spynnaker.pyNN.models.projection.Projection
:rtype: float
"""
[docs]
@abstractmethod
def get_minimum_negative_weight(self, incoming_projection):
"""
Get the minimum likely negative weight.
.. note::
This must be a value <= 0.
:param incoming_projection: The projection targeted
:type incoming_projection: ~spynnaker.pyNN.models.projection.Projection
:rtype: int
"""
[docs]
@abstractmethod
def get_mean_positive_weight(self, incoming_projection):
"""
Get the mean of the positive weights.
.. note::
This must be a value >= 0.
:param incoming_projection: The projection targeted
:type incoming_projection: ~spynnaker.pyNN.models.projection.Projection
:rtype: float
"""
[docs]
@abstractmethod
def get_mean_negative_weight(self, incoming_projection):
"""
Get the mean of the negative weights.
.. note::
This must be a value <= 0.
:param incoming_projection: The projection targeted
:type incoming_projection: ~spynnaker.pyNN.models.projection.Projection
:rtype: float
"""
[docs]
@abstractmethod
def get_variance_positive_weight(self, incoming_projection):
"""
Get the variance of the positive weights.
.. note::
This must be a value >= 0.
:param incoming_projection: The projection targeted
:type incoming_projection: ~spynnaker.pyNN.models.projection.Projection
:rtype: float
"""
[docs]
@abstractmethod
def get_variance_negative_weight(self, incoming_projection):
"""
Get the variance of the negative weights.
.. note::
This must be a value <= 0.
:param incoming_projection: The projection targeted
:type incoming_projection: ~spynnaker.pyNN.models.projection.Projection
:rtype: float
"""
```