interp2

Convenient wrapper to <code>signal::interp1()</code> for linear
interpolation. Assumes that you want interpolated values of
<code>xy_old</code> at <code>n_xy_new</code> equidistant data points.

Helping psychologists and other behavioural scientists
to analyze mouse movement (and other 2-D trajectory) data. Bundles
together several functions that compute spatial measures (e.g., maximum
absolute deviation, area under the curve, sample entropy) or provide a
shorthand for procedures that are frequently used (e.g., time
normalization, linear interpolation, extracting initiation and movement
times). For more information on these dependent measures, see Wirth et al.
(2020) <doi:10.3758/s13428-020-01409-0>.

Roland Pfister

mousetRajectory

Mouse Trajectory Analyses for Behavioural Scientists

Solveig Tonn

Moritz Schaaf

Robert Wirth

interp2 function

<dl><dt>time_old</dt>
<dd>Timestamps of the <code>xy_old</code> coordinates.</dd>
<dt>xy_old</dt>
<dd>To-be normalized x or y coordinates.</dd>
<dt>n_xy_new</dt>
<dd>Number of equidistant timepoints that should be generated.
Defaults to 101.</dd></dl>

Arguments

Interpolation aka Time-Normalization — interp2

<dl>

<dt>time_old</dt>
<dd>Timestamps of the <code>xy_old</code> coordinates.</dd>


<dt>xy_old</dt>
<dd>To-be normalized x or y coordinates.</dd>


<dt>n_xy_new</dt>
<dd>Number of equidistant timepoints that should be generated.
Defaults to 101.</dd>

</dl>

interp2: Interpolation aka Time-Normalization

Description

Usage

Value

Arguments

References

Examples