Side classes

class nngt.Shape(parent=None)

Class containing the shape of the area where neurons will be distributed to form a network.

area

double

Area of the shape in mm^2.

com

tuple of doubles

Position of the center of mass of the current shape.

add_subshape: void

Add a AGNet.generation.Shape to a preexisting one.

add_subshape(subshape, position, unit='mm')

Add a AGNet.generation.Shape to the current one.

Parameters:

• subshape (AGNet.generation.Shape) – Length of the rectangle (by default in mm).
• position (tuple of doubles) – Position of the subshape’s center of gravity in space.
• unit (string (default ‘mm’)) – Unit in the metric system among ‘um’, ‘mm’, ‘cm’, ‘dm’, ‘m’

Returns:

None

area

com

rnd_distrib(nodes=None)

class nngt.NeuralPop(size=None, parent=None, with_models=True, **kwargs)

The basic class that contains groups of neurons and their properties.

Variables:has_models – bool, True if every group has a model attribute.

add_to_group(group_name, id_list)

classmethod copy(pop)

Copy an existing NeuralPop

classmethod ei_population(size, iratio=0.2, parent=None, en_model='iaf_neuron', en_param={}, es_model='static_synapse', es_param={}, in_model='iaf_neuron', in_param={}, is_model='static_synapse', is_param={})

Make a NeuralPop with a given ratio of inhibitory and excitatory neurons.

has_models

is_valid

new_group(name, id_list, ntype=1, neuron_model=None, neuron_param={}, syn_model='static_synapse', syn_param={})

classmethod pop_from_network(graph, *args)

Make a NeuralPop object from a network. The groups of neurons are determined using instructions from an arbitrary number of GroupProperties.

set_models(models=None)

size

classmethod uniform_population(size, parent=None, neuron_model='iaf_neuron', neuron_param={}, syn_model='static_synapse', syn_param={})

Make a NeuralPop of identical neurons