Apply a filter across an aniframe's spatial columns

The aniframe-level entry point to the filter_*() family. Applies a named filter to the columns given by the variables_where metadata field, within the frame's existing grouping.

Usage

filter_across(
  data,
  method = c("gaussian", "rollmean", "rollmedian", "triangular", "sgolay", "lowpass",
    "highpass", "lowpass_fft", "highpass_fft", "kalman", "kalman_irregular", "one_euro",
    "ccma"),
  variables = NULL,
  ...,
  on_deltas = FALSE
)

Arguments

data

An aniframe.

method

Filter to apply. One of "gaussian", "rollmean", "rollmedian", "triangular", "sgolay", "lowpass", "highpass", "lowpass_fft", "highpass_fft", "kalman", "kalman_irregular", "one_euro" or "ccma".

variables

Columns to filter, as a tidyselect expression. Defaults to the variables_where metadata field.

...

Arguments passed to the underlying filter.

on_deltas

If TRUE, difference each column, filter the differences, and re-integrate from the original starting value. For trackball data, where the raw measurements are per-frame displacements and the coordinates were integrated from them, smoothing belongs on the displacements rather than on the integrated positions.

A NA among the filtered differences counts as no movement when accumulating, and is restored as NA at its own position, so one missing step does not blank the rest of the series.

Value

An aniframe of the same shape, with the selected columns filtered.

Details

This is the aniframe tier of the interface:

• filter_gaussian() and friends filter one vector — use them inside dplyr::mutate().

• filter_with() does the same but picks the method by name.

• filter_across() applies a method to a whole aniframe.

Beyond looping over columns, it fills in what the frame already knows: sampling_rate comes from metadata for the methods that need it, and "kalman_irregular" takes its times from the column named by variables_when. Either can still be passed explicitly to override.

"ccma" is multivariate — each output coordinate depends on all of them — so it is applied jointly rather than column by column.

See also

filter_with() for the vector-level generic.

Examples

if (FALSE) { # \dontrun{
# sampling_rate is taken from the aniframe's metadata
filter_across(tracking_data, "lowpass", cutoff_freq = 5)

# restrict to some of the spatial columns
filter_across(tracking_data, "gaussian", variables = c(x, y), sigma = 2)
} # }