def _init_bioproperties(self, population):
''' Set the population attribute and link each neuron to its group. '''
if issubclass(population.__class__, NeuralPop):
if population.is_valid:
self._population = population
nodes = population.size
# create the delay attribute
Connections.delays(self)
else:
raise AttributeError("NeuralPop is not valid (not all \
neurons are associated to a group).")
else:
raise AttributeError("Expected NeuralPop but received \
{}".format(pop.__class__.__name__))
def set_delays(self, delay=None, elist=None, distribution=None,
parameters=None, noise_scale=None):
'''
Set the delay for spike propagation between neurons.
..todo ::
take elist into account in Connections.delays
Parameters
----------
delay : float or class:`numpy.array`, optional (default: None)
Value or list of delays (for user defined delays).
elist : class:`numpy.array`, optional (default: None)
List of the edges (for user defined delays).
distribution : class:`string`, optional (default: None)
Type of distribution (choose among "constant", "uniform",
"gaussian", "lognormal", "lin_corr", "log_corr").
parameters : dict, optional (default: {})
Dictionary containing the properties of the delay distribution.
noise_scale : class:`int`, optional (default: None)
Scale of the multiplicative Gaussian noise that should be applied
on the delays.
'''
if isinstance(delay, float):
size = self.edge_nb() if elist is None else len(elist)
delay = np.repeat(delay, size)
elif not hasattr(delay, "__len__") and delay is not None:
raise AttributeError('''Invalid `delay` value: must be either
float, array-like or None.''')
if distribution is None:
distribution = self._w["distribution"]
if parameters is None:
parameters = self._w
return Connections.delays(self, elist=elist, dlist=delay,
distribution=distribution, parameters=parameters,
noise_scale=noise_scale)
def make_network(graph, neural_pop):
'''
Turn a :class:`~nngt.Graph` object into a :class:`~nngt.Network`, or a
:class:`~nngt.SpatialGraph` into a :class:`~nngt.SpatialNetwork`.
Parameters
----------
graph : :class:`~nngt.Graph` or :class:`~nngt.SpatialGraph`
Graph to convert
neural_pop : :class:`~nngt.NeuralPop`
Population to associate to the new :class:`~nngt.Network`
Notes
-----
In-place operation that directly converts the original graph.
'''
if isinstance(graph, SpatialGraph):
graph.__class__ = SpatialNetwork
else:
graph.__class__ = Network
graph.population = neural_pop
Connections.delays(graph)
