pynn_brainscales.brainscales2.standardmodels.cells_base.Population

class pynn_brainscales.brainscales2.standardmodels.cells_base.Population(size, cellclass, cellparams=None, structure=None, initial_values={}, label=None)

Bases: pyNN.common.populations.BasePopulation

A group of neurons all of the same type. “Population” is used as a generic term intended to include layers, columns, nuclei, etc., of cells.

Arguments:

size:: number of cells in the Population. For backwards-compatibility, size may also be a tuple giving the dimensions of a grid, e.g. size=(10,10) is equivalent to size=100 with structure=Grid2D().
cellclass:: a cell type (a class inheriting from pyNN.models.BaseCellType).
cellparams:: a dict, or other mapping, containing parameters, which is passed to the neuron model constructor.
structure:: a pyNN.space.Structure instance, used to specify the positions of neurons in space.
initial_values:: a dict, or other mapping, containing initial values for the neuron state variables.
label:: a name for the population. One will be auto-generated if this is not supplied.

__init__(size, cellclass, cellparams=None, structure=None, initial_values={}, label=None): Create a population of neurons all of the same type.

Methods

`__init__`(size, cellclass[, cellparams, …])	Create a population of neurons all of the same type.
`describe`([template, engine])	Returns a human-readable description of the population.
`id_to_index`(id)	Given the ID(s) of cell(s) in the Population, return its (their) index (order in the Population).
`id_to_local_index`(id)	Given the ID(s) of cell(s) in the Population, return its (their) index (order in the Population), counting only cells on the local MPI node.

Attributes

`local_cells`	An array containing cell ids for the local node.
`positions`	A 3xN array (where N is the number of neurons in the Population) giving the x,y,z coordinates of all the neurons (soma, in the case of non-point models).
`structure`	The spatial structure of the Population.

describe(template='population_default.txt', engine='default')

Returns a human-readable description of the population.

The output may be customized by specifying a different template together with an associated template engine (see pyNN.descriptions).

If template is None, then a dictionary containing the template context will be returned.

id_to_index(id)

Given the ID(s) of cell(s) in the Population, return its (their) index (order in the Population).

>>> assert p.id_to_index(p[5]) == 5

id_to_local_index(id): Given the ID(s) of cell(s) in the Population, return its (their) index (order in the Population), counting only cells on the local MPI node.

property local_cells: An array containing cell ids for the local node.

property positions: A 3xN array (where N is the number of neurons in the Population) giving the x,y,z coordinates of all the neurons (soma, in the case of non-point models).

property structure: The spatial structure of the Population.