ezmsg.sigproc.denormalize

Classes

class DenormalizeSettings(low_rate: float = 2.0, high_rate: float = 40.0, distribution: str = 'uniform')

Bases: Settings

Parameters:

• low_rate (float)

• high_rate (float)

• distribution (str)

low_rate: float = 2.0

Low end of probable rate after denormalization (Hz).

high_rate: float = 40.0

High end of probable rate after denormalization (Hz).

distribution: str = 'uniform'

Distribution to sample rates from. Options are ‘uniform’, ‘normal’, or ‘constant’.

__init__(low_rate=2.0, high_rate=40.0, distribution='uniform')

Parameters:

• low_rate (float)

• high_rate (float)

• distribution (str)

Return type:

None

class DenormalizeState

Bases: object

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

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

class DenormalizeTransformer(*args, **kwargs)

Bases: BaseStatefulTransformer[DenormalizeSettings, AxisArray, AxisArray, DenormalizeState]

Scales data from a normalized distribution (mean=0, std=1) to a denormalized distribution using random per-channel offsets and gains designed to keep the 99.9% CIs between 0 and 2x the offset.

This is useful for simulating realistic firing rates from normalized data.

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

Bases: BaseTransformerUnit[DenormalizeSettings, AxisArray, AxisArray, DenormalizeTransformer]

Parameters:

settings (Settings | None)

SETTINGS

alias of DenormalizeSettings

class DenormalizeSettings(low_rate: float = 2.0, high_rate: float = 40.0, distribution: str = 'uniform')

Bases: Settings

Parameters:

• low_rate (float)

• high_rate (float)

• distribution (str)

low_rate: float = 2.0

Low end of probable rate after denormalization (Hz).

high_rate: float = 40.0

High end of probable rate after denormalization (Hz).

distribution: str = 'uniform'

Distribution to sample rates from. Options are ‘uniform’, ‘normal’, or ‘constant’.

__init__(low_rate=2.0, high_rate=40.0, distribution='uniform')

Parameters:

• low_rate (float)

• high_rate (float)

• distribution (str)

Return type:

None

class DenormalizeState

Bases: object

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

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

class DenormalizeTransformer(*args, **kwargs)

Bases: BaseStatefulTransformer[DenormalizeSettings, AxisArray, AxisArray, DenormalizeState]

Scales data from a normalized distribution (mean=0, std=1) to a denormalized distribution using random per-channel offsets and gains designed to keep the 99.9% CIs between 0 and 2x the offset.

This is useful for simulating realistic firing rates from normalized data.

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

Bases: BaseTransformerUnit[DenormalizeSettings, AxisArray, AxisArray, DenormalizeTransformer]

Parameters:

settings (Settings | None)

SETTINGS

alias of DenormalizeSettings