Should data have been exported at an incorrect scale, apply an isometric transformation to the position data and associated mean marker errors (if found)
Arguments
- obj_name
The input viewr object; a tibble or data.frame with attribute
pathviewr_stepsthat includes"viewr"that has been passed throughrelabel_viewr_axes()andgather_tunnel_data()(or is structured as though it has been passed through those functions).- original_scale
The original scale at which data were exported. See Details if unknown.
- desired_scale
The desired scale
- ...
Additional arguments passed to/from other pathviewr functions
Value
A viewr object that has position data (and
mean_marker_error data, if found) adjusted by the ratio of
desired_scale/original_scale.
Details
The desired_scale is divided by the original_scale to
determine a scale_ratio internally. If the original_scale is
not explicitly known, set it to 1 and then set desired_scale to be
whatever scaling ratio you have in mind. E.g. setting original_scale
to 1 and then desired_scale to 0.7 will multiply all position axis
values by 0.7.
The default arguments of original_scale = 0.5 and
desired_scale = 1 apply a doubling of tunnel size isometrically.
Examples
## Import the example Motive data included in the package
motive_data <-
read_motive_csv(system.file("extdata", "pathviewr_motive_example_data.csv",
package = 'pathviewr'))
## Clean the file. It is generally recommended to clean up to the
## "gather" step before running rescale_tunnel_data().
motive_gathered <-
motive_data %>%
relabel_viewr_axes() %>%
gather_tunnel_data()
## Now rescale the tunnel data
motive_rescaled <-
motive_gathered %>%
rescale_tunnel_data(original_scale = 0.5,
desired_scale = 1)
## See the difference in data range e.g. for length
range(motive_rescaled$position_length)
#> [1] 0.07131 5.35294
range(motive_gathered$position_length)
#> [1] 0.035655 2.676470
