motion_detectors: Motion detector for Ethocope data
In rethomics/sleepr: Analyse Activity and Sleep Behaviour

Description Usage Arguments Details Value See Also

Defines whether a single animal is moving according to:

max_velocity_detector(data, time_window_length,
  velocity_correction_coef = 0.003, masking_duration = 6)

max_velocity_detector_legacy(data, velocity_threshold = 0.006)

virtual_beam_cross_detector(data, time_window_length)

`data`	data.table::data.table containing behavioural variables of a single animal (no id). It must have the columns `xy_dist_log10x1000`(for computing subpixel velocity), `x`(beam cross), `t` and `has_interacted` (whether a stimulus was delivered).
`time_window_length`	number of seconds to be used by the motion classifier. This corresponds to the sampling period of the output data.
`velocity_correction_coef`	an empirical coefficient to correct velocity with respect to variable framerate.
`masking_duration`	number of seconds during which any movement is ignored (velocity is set to 0) after a stimulus is delivered (a.k.a. interaction).
`velocity_threshold`	uncorrected velocity above which an animal is classified as ‘moving’ (for the legacy version).

Validated and corrected subpixel velocity (max_velocity_detector), the most rigorous
Uncorrected subpixel velocity (max_velocity_detector_legacy)
Crossing a virtual beam in the middle of the region of interest (virtual_beam_cross_detector)

max_velocity_detector is the default movement classification for real-time ethoscope experiments. It is benchmarked against human-generated ground truth.

These functions are rarely called directly, but typically used is in the context of sleep_annotation.

an object of the same type as data (i.e. data.table::data.table or behavr::behavr) with additional columns:

moving Logical, TRUE iff. motion was detected.
beam_crosses The number of beam crosses (when the animal crosses x = 0.5 – that is the midpoint of the region of interest) within the time window
max_velocity The maximal velocity within the time window. The resulting data is sampled at a period equals to time_window_length.