Import a file and then, akin to clean_viewr
, run through as many
cleaning steps as desired.
Usage
import_and_clean_viewr(
file_name,
file_id = NA,
relabel_viewr_axes = TRUE,
gather_tunnel_data = TRUE,
trim_tunnel_outliers = TRUE,
standardization_option = "rotate_tunnel",
get_velocity = TRUE,
select_x_percent = TRUE,
rename_viewr_characters = FALSE,
separate_trajectories = TRUE,
get_full_trajectories = TRUE,
fill_traj_gaps = FALSE,
...
)
Arguments
- file_name
Target file
- file_id
Optional
- relabel_viewr_axes
default TRUE, should axes be relabeled?
- gather_tunnel_data
default TRUE, should tunnel data be gathered?
- trim_tunnel_outliers
default TRUE, outliers be trimmed?
- standardization_option
default "rotate_tunnel"; which standardization option should be used? See Details for more.
- get_velocity
default TRUE, should velocity be computed?
- select_x_percent
default TRUE, should a region of interest be selected?
- rename_viewr_characters
default FALSE, should subjects be renamed?
- separate_trajectories
default TRUE, should trajectories be defined?
- get_full_trajectories
default TRUE, should only full trajectories be retained?
- fill_traj_gaps
default FALSE, should gaps in trajectories be filled?
- ...
Additional arguments passed to the corresponding functions.
Value
A viewr object (tibble or data.frame with attribute
pathviewr_steps
that includes "viewr"
) that has passed
through several pathviewr
functions as desired by the user,
resulting in data that have been cleaned and ready for analyses.
Details
Each argument corresponds to a standalone function in
pathviewr
. E.g. the parameter relabel_viewr_axes
allows a
user to choose whether pathviewr::relabel_viewr_axes()
is run
internally. Should the user desire to use any non-default parameter values
for any functions included here, they should be supplied to this function
as additional arguments formatted exactly as they would appear in their
corresponding function(s). E.g. if the "autodetect" feature in
pathviewr::separate_trajectories()
is desired, add an argument
max_frame_gap = "autodetect"
to the arguments supplied to this
function.
See also
Other all in one functions:
clean_viewr()
Examples
library(pathviewr)
## Import the example Motive data included in the package
motive_data <-
read_motive_csv(system.file("extdata", "pathviewr_motive_example_data.csv",
package = 'pathviewr'))
motive_full <-
motive_data %>%
clean_viewr(desired_percent = 50,
max_frame_gap = "autodetect",
span = 0.95)
#> autodetect is an experimental feature -- please report issues.
## Alternatively, used the import_and_clean_viewr()
## function to combine these steps
motive_import_and_clean <-
import_and_clean_viewr(
file_name = system.file("extdata", "pathviewr_motive_example_data.csv",
package = 'pathviewr'),
desired_percent = 50,
max_frame_gap = "autodetect",
span = 0.95
)
#> autodetect is an experimental feature -- please report issues.