View source: R/pipeline-detransient.R
detransient | R Documentation |
The intended use of this method is for removing pupil samples that emerge
more quickly than would be physiologically expected. This is accomplished by
rejecting samples that exceed a "speed"-based threshold (i.e., median
absolute deviation from sample-to-sample). This threshold is computed based
on the constant n
, which defaults to the value 16
.
detransient(eyeris, n = 16, mad_thresh = NULL)
eyeris |
An object of class |
n |
A constant used to compute the median absolute deviation (MAD) threshold. |
mad_thresh |
Default
then, with the default multiplier
In this situation, any speed
|
Computed properties:
pupil_speed
: Compute speed of pupil by approximating the derivative
of x
(pupil) with respect to y
(time) using finite differences.
Let x = (x_1, x_2, \dots, x_n)
and
y = (y_1, y_2, \dots, y_n)
be two numeric vectors with
n \ge 2
; then, the finite differences are computed as:
\delta_i = \frac{x_{i+1} - x_i}{y_{i+1} - y_i},
\quad i = 1, 2, \dots, n-1.
This produces an output vector p = (p_1, p_2, \dots, p_n)
defined by:
For the first element:
p_1 = |\delta_1|,
For the last element:
p_n = |\delta_{n-1}|,
For the intermediate elements (i = 2, 3, \dots, n-1
):
p_i = \max\{|\delta_{i-1}|,\,|\delta_i|\}.
median_speed
: The median of the computed pupil_speed
:
median\_speed = median(p)
mad_val
: The median absolute deviation (MAD) of pupil_speed
from the median:
mad\_val = median(|p - median\_speed|)
mad_thresh
: A threshold computed from the median speed and the MAD,
using a constant multiplier n
(default value: 16):
mad\_thresh = median\_speed + (n \times mad\_val)
An eyeris
object with a new column in timeseries
:
pupil_raw_{...}_detransient
.
system.file("extdata", "memory.asc", package = "eyeris") |>
eyeris::load_asc() |>
eyeris::deblink(extend = 50) |>
eyeris::detransient() |>
plot(seed = 0)
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