:py:mod:`tonic.functional.to_timesurface`
=========================================

.. py:module:: tonic.functional.to_timesurface


Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   tonic.functional.to_timesurface.to_timesurface_numpy



.. py:function:: to_timesurface_numpy(events, sensor_size: tuple[int, int, int], dt: float, tau: float, overlap: int = 0, include_incomplete: bool = False)

   Representation that creates timesurfaces for each event in the recording. Modeled after the
   paper Lagorce et al. 2016, Hots: a hierarchy of event-based time-surfaces for pattern
   recognition https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7508476. Unlike the paper,
   surfaces are always generated across the whole sensor, not just around the event.

   :param sensor_size: x/y/p dimensions of the sensor
   :param dt: time interval at which the time-surfaces are accumulated
   :param tau: time constant to decay events around occuring event with.
   :type tau: float

   :returns: array of timesurfaces with dimensions (n_events//dt, p, h , w)