ezmsg.event.poissonevents

Classes

class PoissonEventSettings(output_fs: float = 30000, layout: str = 'coo', compress_dims: list[int] | None = None, assume_counts: bool = False, min_rate: float = 1e-06, max_rate: float = 500.0)

Bases: Settings

Parameters:

• output_fs (float)

• layout (str)

• compress_dims (list[int] | None)

• assume_counts (bool)

• min_rate (float)

• max_rate (float)

output_fs: float = 30000

Output sampling rate.

layout: str = 'coo'

Layout of the output event train sparse array. Options are ‘coo’ or ‘gcxs’

compress_dims: list[int] | None = None

Dimensions to compress. Ignored if layout is ‘coo’.

assume_counts: bool = False

If True, input is event counts per bin. If False, input is firing rate in Hz.

min_rate: float = 1e-06

Minimum rate to avoid division by zero.

max_rate: float = 500.0

Maximum expected firing rate (Hz). Used to pre-allocate event arrays.

__init__(output_fs=30000, layout='coo', compress_dims=None, assume_counts=False, min_rate=1e-06, max_rate=500.0)

Parameters:

• output_fs (float)

• layout (str)

• compress_dims (list[int] | None)

• assume_counts (bool)

• min_rate (float)

• max_rate (float)

Return type:

None

class PoissonEventState

Bases: object

accumulated: ndarray[tuple[Any, ...], dtype[_ScalarT]] | None = None

Integrated rate since last event for each channel.

threshold: ndarray[tuple[Any, ...], dtype[_ScalarT]] | None = None

Exp(1) threshold for next event for each channel.

class PoissonEventTransformer(*args, **kwargs)

Bases: BaseStatefulTransformer[PoissonEventSettings, AxisArray, AxisArray, PoissonEventState]

class PoissonEventUnit(*args, settings=None, **kwargs)

Bases: BaseTransformerUnit[PoissonEventSettings, AxisArray, AxisArray, PoissonEventTransformer]

Parameters:

settings (Settings | None)

SETTINGS

alias of PoissonEventSettings