bsb_arbor package¶

Subpackages¶

bsb_arbor.devices package

Submodules¶

bsb_arbor.adapter module¶

class bsb_arbor.adapter.ArborAdapter(comm=None)¶

Bases: SimulatorAdapter

Parameters:: comm – The mpi4py MPI communicator to use. Only nodes in the communicator will participate in the simulation. The first node will idle as the main node.

get_gid_manager(simulation, simdata)¶

get_recipe(simulation, simdata=None)¶

prepare(simulation: ArborSimulation) → ArborSimulationData¶

Prepares the arbor simulation engine with the given simulation.

Parameters:: simulation (ArborSimulation)
Return type:: ArborSimulationData

run(*simulations)¶

Fire up the prepared adapter.

Parameters:: simulations (Simulation) – One or a list of simulation configurations to simulate.
Returns:: List of simulation results.
Return type:: list[SimulationResult]

class bsb_arbor.adapter.ArborRecipe(*args: Any, **kwargs: Any)¶

Bases: recipe

cell_description(gid)¶

cell_kind(gid)¶

connections_on(gid)¶

event_generators(gid)¶

gap_junctions_on(gid)¶

global_properties(kind)¶

num_cells()¶

probes(gid)¶

class bsb_arbor.adapter.ArborSimulationData(simulation)¶

Bases: SimulationData

Container class for simulation data.

class bsb_arbor.adapter.GIDManager(simulation, simdata)¶

Bases: object

all()¶

get_populations()¶

lookup_kind(gid)¶

lookup_model(gid)¶

lookup_offset(gid)¶

sort_models(models)¶

class bsb_arbor.adapter.Population(simdata, cell_model, offset)¶

Bases: object

Represents a population of cells for the Arbor simulator.

This class manages a collection of cells from a specific cell model, handling their GID ranges and providing methods to access and manipulate subsets of the population.

Initialize a population of cells.

Parameters:

simdata – The simulation data container
cell_model – The cell model for this population
offset – The GID offset for this population

copy()¶

Create a copy of this population.

Returns:: A new Population instance with the same properties

property model¶

Get the cell model associated with this population.

Returns:: The cell model object

property offset¶

Get the GID offset for this population.

Returns:: The GID offset value

class bsb_arbor.adapter.ReceiverCollection¶

Bases: list

Receiver collections store the incoming connections and deduplicate them into multiple targets.

append(rcv)¶: Append object to the end of the list.

class bsb_arbor.adapter.SingleReceiverCollection(iterable=(), /)¶

Bases: list

The single receiver collection redirects all incoming connections to the same receiver.

append(rcv)¶: Append object to the end of the list.

bsb_arbor.cell module¶

class bsb_arbor.cell.ArborCell(*args, _parent=None, _key=None, **kwargs)¶

Bases: CellModel

abstractmethod cache_population_data(simdata, ps: PlacementSet)¶

Parameters:: ps (PlacementSet)

abstractmethod discard_population_data()¶

gap¶: Is this synapse a gap junction?

abstractmethod get_cell_kind(gid)¶

get_description(gid)¶

get_node_name()¶

abstractmethod get_prefixed_catalogue()¶

abstractmethod make_receiver_collection()¶

model¶: Importable reference to the arborize model describing the cell type.

model_strategy: ConfigurationAttribute¶: Optional importable reference to a different modelling strategy than the default Arborize strategy.

class bsb_arbor.cell.LIFCell(*args, _parent=None, _key=None, **kwargs)¶

Bases: ArborCell

cache_population_data(simdata, ps: PlacementSet)¶

Parameters:: ps (PlacementSet)

constants¶: Dictionary linking the parameters’ name to its value.

discard_population_data()¶

get_cell_kind(gid)¶

get_description(gid)¶

get_node_name()¶

get_prefixed_catalogue()¶

make_receiver_collection()¶

bsb_arbor.connection module¶

class bsb_arbor.connection.ArborConnection(*args, _parent=None, _key=None, **kwargs)¶

Bases: ConnectionModel

create_connections_from(conns_from_gid, conns, pop_pre, pop_post)¶

create_connections_on(conns_on_gid, conns, pop_pre, pop_post)¶

create_gap_junctions_on(gj_on_gid, conns)¶

delay¶: Delay of the transmission between the presynaptic and the postsynaptic cells.

gap¶: Is this synapce a gap junction?

gap_junction(conn)¶

get_node_name()¶

weight¶: Weight of the connection between the presynaptic and the postsynaptic cells.

class bsb_arbor.connection.Connection(pre_loc, post_loc)¶: Bases: object

class bsb_arbor.connection.Receiver(conn_model, from_gid, loc_from, loc_on, index=-1)¶

Bases: object

property delay¶

from_()¶

on()¶

property weight¶

bsb_arbor.device module¶

class bsb_arbor.device.ArborDevice(*args, _parent=None, _key=None, **kwargs)¶

Bases: DeviceModel

device: ConfigurationAttribute¶: Optional importable reference to the device strategy.

get_meta()¶

get_node_name()¶

get_samples(sim)¶

implement(adapter, simulation, simdata)¶: Method called when simulation is being set up. Can be used for components to set themselves up and store the context they need to operate.

abstractmethod implement_generators(simdata, target)¶

abstractmethod implement_probes(simdata, target)¶

register_probe_id(gid, tag)¶

resolution¶: Time resolution of the device.

sample(sim, probe_id)¶

sampling_policy¶: Policy used to sample simulation data from the device.

targetting¶: Targets of the device, which should be either a population or a nest rule.

bsb_arbor.simulation module¶

class bsb_arbor.simulation.ArborSimulation(*args, _parent=None, _key=None, **kwargs)¶

Bases: Simulation

Interface between the scaffold model and the Arbor simulator.

cell_models: cfgdict[ArborCell]¶: Dictionary of cell models in the simulation.

connection_models: cfgdict[ArborConnection]¶: Dictionary of connection models in the simulation.

devices: cfgdict[ArborDevice]¶: Dictionary of devices in the simulation.

get_node_name()¶

profiling¶: Flag to perform profiling during the simulation.

resolution¶: Simulation time step size in milliseconds.

threads¶

Module contents¶

Arbor simulation adapter for the BSB framework.

class bsb_arbor.ArborAdapter(comm=None)¶

Bases: SimulatorAdapter

Parameters:: comm – The mpi4py MPI communicator to use. Only nodes in the communicator will participate in the simulation. The first node will idle as the main node.

get_gid_manager(simulation, simdata)¶

get_recipe(simulation, simdata=None)¶

prepare(simulation: ArborSimulation) → ArborSimulationData¶

Prepares the arbor simulation engine with the given simulation.

Parameters:: simulation (ArborSimulation)
Return type:: ArborSimulationData

run(*simulations)¶

Fire up the prepared adapter.

Parameters:: simulations (Simulation) – One or a list of simulation configurations to simulate.
Returns:: List of simulation results.
Return type:: list[SimulationResult]

class bsb_arbor.PoissonGenerator(*args, _parent=None, _key=None, **kwargs)¶

Bases: ArborDevice

delay¶: Delay of the transmission between the device and its target.

get_node_name()¶

implement_generators(simdata, gid)¶

implement_probes(simdata, gid)¶

rate¶: Frequency of the poisson generator.

record¶: Flag to save the spikes generated to file.

weight¶: Weight of the connection between the device and its target.

class bsb_arbor.Probe(*args, _parent=None, _key=None, **kwargs)¶

Bases: ArborDevice

get_probe_name()¶

implement(adapter, simulation, simdata)¶: Method called when simulation is being set up. Can be used for components to set themselves up and store the context they need to operate.

required = ['targetting', 'probe_type']¶

validate_specifics()¶

class bsb_arbor.SpikeRecorder(*args, _parent=None, _key=None, **kwargs)¶

Bases: ArborDevice

boot()¶

get_node_name()¶

implement(adapter, simulation, simdata)¶: Method called when simulation is being set up. Can be used for components to set themselves up and store the context they need to operate.

implement_generators(simdata, gid)¶

implement_probes(simdata, gid)¶