Should data have been exported at an incorrect scale, apply an isometric transformation to the position data and associated mean marker errors (if found)
The input viewr object; a tibble or data.frame with attribute
The original scale at which data were exported. See Details if unknown.
The desired scale
Additional arguments passed to/from other pathviewr functions
desired_scale is divided by the
scale_ratio internally. If the
not explicitly known, set it to 1 and then set
desired_scale to be
whatever scaling ratio you have in mind. E.g. setting
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.
viewr object that has position data (and
mean_marker_error data, if found) adjusted by the ratio of
Vikram B. Baliga
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## 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$position_length) range(motive_gathered$position_length)
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