tonic.functional.time_skew
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Module Contents#
Functions#
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Skew all event timestamps according to a linear transform, potentially sampled from a |
- tonic.functional.time_skew.time_skew_numpy(events: numpy.ndarray, coefficient: float, offset: int = 0)[source]#
Skew all event timestamps according to a linear transform, potentially sampled from a distribution of acceptable functions.
- Parameters:
events (numpy.ndarray) – ndarray of shape [num_events, num_event_channels].
coefficient (float) – a real-valued multiplier applied to the timestamps of the events. E.g. a coefficient of 2.0 will double the effective delay between any pair of events.
offset (int) – value by which the timestamps will be shifted after multiplication by the coefficient. Negative offsets are permissible but may result in in an exception if timestamps are shifted below 0.
- Returns:
the input events with rewritten timestamps.