tonic.functional.to_frame
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Module Contents#
Functions#
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Accumulate events to frames by slicing along constant time (time_window), constant number of |
- tonic.functional.to_frame.to_frame_numpy(events, sensor_size, time_window=None, event_count=None, n_time_bins=None, n_event_bins=None, overlap=0.0, include_incomplete=False)[source]#
Accumulate events to frames by slicing along constant time (time_window), constant number of events (event_count) or constant number of frames (n_time_bins / n_event_bins).
- Parameters:
events – ndarray of shape [num_events, num_event_channels]
sensor_size – size of the sensor that was used [W,H,P]
time_window (None) – window length in us.
event_count (None) – number of events per frame.
n_time_bins (None) – fixed number of frames, sliced along time axis.
n_event_bins (None) – fixed number of frames, sliced along number of events in the recording.
overlap – overlap between frames defined either in time in us, number of events or number of bins.
include_incomplete (False) – if True, includes overhang slice when time_window or event_count is specified. Not valid for bin_count methods.
- Returns:
numpy array with dimensions (TxPxHxW)