spynnaker.pyNN.models.utility_models.spike_injector package

Submodules

spynnaker.pyNN.models.utility_models.spike_injector.spike_injector_vertex module

class spynnaker.pyNN.models.utility_models.spike_injector.spike_injector_vertex.SpikeInjectorVertex(n_neurons: int, label: str, port: int | None, virtual_key: int | None, reserve_reverse_ip_tag: bool, splitter: AbstractSplitterCommon | None, max_atoms_per_core: int | Tuple[int, ...] | None = 9223372036854775807)

Bases: ReverseIpTagMultiCastSource, PopulationApplicationVertex, SupportsStructure

An Injector of Spikes for PyNN populations. This only allows the user to specify the virtual_key of the population to identify the population.

Parameters:

label – The optional name of the vertex.

SPIKE_RECORDING_REGION_ID = 0

property atoms_shape: Tuple[int, ...]

The “shape” of the atoms in the vertex i.e. how the atoms are split between the dimensions of the vertex. By default everything is 1-dimensional, so the value will be a 1-tuple but can be overridden by a vertex that supports multiple dimensions.

default_parameters = {'label': 'spikeInjector', 'port': None, 'virtual_key': None}

describe() → Dict[str, str | Collection[str]]

Returns:

A human-readable description of the cell or synapse type.

get_buffer_data_type(name: str) → BufferDataType

Get the type of data recorded by the buffer manager.

The buffer data type controls how data returned by the cores is handled in NeoBufferDatabase.

Parameters:

name – The name of the variable recorded

Raises:

KeyError – if the variable isn’t being recorded

Returns:

Data type in the Buffer Database

get_data_type(name: str) → None

Get the type data returned by a recording of the variable.

This is the type of data the C code is returning. For instance data such as spikes this will be None.

Parameters:

name – The name of the variable to get the type of

Returns:

The data type used by the C code

Raises:

KeyError – If the variable isn’t recordable

get_neurons_recording(name: str, vertex_slice: Slice) → ndarray[tuple[Any, ...], dtype[integer]]

Gets the neurons being recorded on the core with this slice.

Typically vertex_slice.get_raster_ids(atoms_shape) but may be a sublist if doing selective recording.

Parameters:

• name – The name of the variable to get the region of

• vertex_slice

Returns:

A list of the global raster IDs of the atoms in recording named variable within this slice

get_recordable_variables() → List[str]

Get a list of the names of things that can be recorded.

This methods list the variable recorded via the Population.

Includes both neuron and synapse recordable things

Returns:

List of variable names

get_recording_region(name: str) → int

Parameters:

name – The name of the variable to get the region of

Returns:

The recording region for the named variable.

Raises:

KeyError – If the variable isn’t being recorded

get_recording_variables() → List[str]

Returns:

A list of variables that are currently being recorded.

get_sampling_interval_ms(name: str) → float

Get the sampling interval of the recording for the given variable.

The values is in ms and unless selective recording is used will be SpynnakerDataView.get_simulation_time_step_us()

Parameters:

name – The name of the variable

Returns:

Sampling rate in milliseconds for this variable

Raises:

KeyError – If the variable isn’t being recorded

get_units(name: str) → str

Get the units of the given parameter or state variable.

Parameters:

name – the name of the parameter to get the units of

Returns:

The unit or this variable. For example ‘mV’ or ‘uS’. Will be an empty string for things like spikes and probability

Raises:

KeyError – if the name isn’t recognised or the units cannot be identified

set_not_recording(name: str, indices: Collection[int] | None = None) → None

Set a variable not recording.

Parameters:

• name – The name of the variable to not record

• indices – The list of neuron indices to not record or None for all

Raises:

KeyError – if the variable cannot be stopped from recording

set_recording(name: str, sampling_interval: float | None = None, indices: Collection[int] | None = None) → None

Set a variable recording.

Parameters:

• name – The name of the variable to set the status of

• sampling_interval – How often the variable should be recorded or None for every time step, in milliseconds

• indices – The list of neuron indices to record or None for all

Raises:

KeyError – if the variable cannot be recorded

set_structure(structure: BaseStructure) → None

Set the structure of the object.

Parameters:

structure – The structure to set

Module contents

class spynnaker.pyNN.models.utility_models.spike_injector.SpikeInjector(*args: Any, **kwargs: Any)

Bases: AbstractPyNNModel

Model that creates a Spike Injector Vertex

create_vertex(n_neurons: int, label: str, *, port: int | None = None, virtual_key: int | None = None, reserve_reverse_ip_tag: bool = False, splitter: AbstractSplitterCommon | None = None) → SpikeInjectorVertex

Create a vertex for a population of the model.

Parameters:

• n_neurons – The number of neurons in the population

• label – The label to give to the vertex

• port

• virtual_key

• reserve_reverse_ip_tag

• splitter

Returns:

An application vertex for the population

default_population_parameters: Dict[str, Any] = {'port': None, 'reserve_reverse_ip_tag': False, 'splitter': None, 'virtual_key': None}

The default values for the parameters at the population level. These are parameters that can be passed in to the Population constructor in addition to the standard PyNN options.