mousetrap (version 1.2.0)

mt_resample: Resample trajectories using a constant time interval.

Description

Resample trajectory positions using a constant time interval. If no timestamp that represents an exact multiple of this time interval is found, linear interpolation is performed using the two adjacent timestamps.

Usage

mt_resample(data, use = "trajectories", save_as = "rs_trajectories", step_size = 10, exact_last_timestamp = TRUE, show_progress = TRUE)

Arguments

data

a mousetrap data object created using one of the mt_import functions (see mt_example for details). Alternatively, a trajectory array can be provided directly (in this case use will be ignored).

use

a character string specifying which trajectory data should be used.

save_as

a character string specifying where the resulting trajectory data should be stored.

step_size

an integer specifying the size of the constant time interval. The unit corresponds to the unit of the timestamps.

exact_last_timestamp

logical indicating if the last timestamp should always be appended (which is the case by default). If FALSE, the last timestamp is only appended if it is a multiple of the step_size.

show_progress

logical indicating whether function should report on its progress.

Value

A mousetrap data object (see mt_example) with an additional array (by default called rs_trajectories) containing the resampled trajectories. If a trajectory array was provided directly as data, only the resampled trajectories will be returned.

Details

mt_resample can be used if the number of logged positions in a trial should be reduced. mt_resample achieves this by artificially decreasing the resolution with which the positions were recorded. For example, if mouse positions were recorded every 10 ms in an experiment, but one was only interested in the exact mouse position every 50 ms, mt_resample with step_size=50 could be used. In this case, only every fifth sample would be kept.

In addition, mt_resample can be used to only retain values for specific timestamps across trials (e.g., if for each trial the position of the mouse exactly 250 ms and 500 ms after onset of the trial are of interest). In case that a trial does not contain samples at the specified timestamps, linear interpolation is performed using the two adjacent timestamps.

Note that mt_resample does not average across time intervals. For this, mt_average can be used.

See Also

approx for information about the function used for linear interpolation.

mt_average for averaging trajectories across constant time intervals.

mt_time_normalize for time-normalizing trajectories.

Examples

mt_example <- mt_resample(mt_example,
  save_as="rs_trajectories",
  step_size=50)