elasticai.preprocessor.eventdetection.frame_alignment#

Module Contents#

Classes#

TargetsFrameAlignment

SettingsFrameAlignment

Class with settings for the FrameGenerator to configure his properties Attributes: type: Aligning mode of the detected spike frames [none, max, min, ptp (Positive turning point), ntp (Negative turning point), abs-max (Absolute maximum)] sampling_rate: Sampling rate of the transient signal [Hz] align_sec: Starting position for aligning the frame waveform [s] offset_sec: Offset for aligning the frame waveform [s]

FrameAligner

Data#

DefaultSettingsFrameAlignment

API#

class elasticai.preprocessor.eventdetection.frame_alignment.TargetsFrameAlignment(*args, **kwds)[source]#

Bases: enum.Enum

Normal#

‘none’

Max#

‘max’

Min#

‘min’

PositiveTurning#

‘ptp’

NegativeTurning#

‘ntp’

AbsMax#

‘absmax’

AbsMin#

‘absmin’

class elasticai.preprocessor.eventdetection.frame_alignment.SettingsFrameAlignment[source]#

Class with settings for the FrameGenerator to configure his properties Attributes: type: Aligning mode of the detected spike frames [none, max, min, ptp (Positive turning point), ntp (Negative turning point), abs-max (Absolute maximum)] sampling_rate: Sampling rate of the transient signal [Hz] align_sec: Starting position for aligning the frame waveform [s] offset_sec: Offset for aligning the frame waveform [s]

type: elasticai.preprocessor.eventdetection.frame_alignment.TargetsFrameAlignment#

None

sampling_rate: float#

None

offset_sec: float#

None

align_sec: float#

None

property length_align_position: int#
property length_offset_int: int#
elasticai.preprocessor.eventdetection.frame_alignment.DefaultSettingsFrameAlignment#

‘SettingsFrameAlignment(…)’

class elasticai.preprocessor.eventdetection.frame_alignment.FrameAligner(settings: elasticai.preprocessor.eventdetection.frame_alignment.SettingsFrameAlignment)[source]#

Initialization

Class for aligning frame waveforms after event detection

Parameters:

settings – Class SettingsFrameAlignment for defining the properties

get_aligned_position(frame_in: numpy.ndarray) → list[int][source]#

Extracting aligning position of spike frames

Parameters:

frame_in – Numpy array with detected spike frames

Returns:

List with integer of starting positions

abstractmethod create_design() → None[source]#