mt_align_start_end {mousetrap}

Align start and end position of trajectories.

Description

Adjust trajectories so that all trajectories have an identical start and end point. In some articles, this is also referred to as space-normalization (e.g. Dale et al., 2007).

Usage

mt_align_start_end(
  data,
  use = "trajectories",
  save_as = use,
  dimensions = c("xpos", "ypos"),
  start = c(0, 0),
  end = c(-1, 1),
  verbose = FALSE
)

Arguments

data

a mousetrap data object created using one of the mt_import functions (see mt_example for details). Alternatively, a trajectory array can be provided directly (in this case use will be ignored).

use

a character string specifying which trajectory data should be used.

save_as

a character string specifying where the resulting trajectory data should be stored.

dimensions

a character vector specifying the dimensions in the trajectory array that should be aligned.

start

a numeric vector specifying the start values for each dimension, i.e., the values the first recorded position should have in every trial. If NULL, trajectories are aligned to the mean first position across all trials.

end

a numeric vector specifying the end values for each dimension, i.e., the values the last recorded position should have in every trial. If NULL, trajectories are aligned to the mean last position across all trials. Note that in this case trajectories should be remapped to one side before alignment (e.g., using mt_remap_symmetric) so that the mean last position is meaningful.

verbose

logical indicating whether function should report its progress.

Value

A mousetrap data object (see mt_example) with aligned trajectories. All other trajectory dimensions not specified in dimensions (e.g., timestamps) will be kept as is in the resulting trajectory array. If the trajectory array was provided directly as data, only the trajectory array will be returned.

Author(s)

Pascal J. Kieslich

Felix Henninger

References

Dale, R., Kehoe, C., & Spivey, M. J. (2007). Graded motor responses in the time course of categorizing atypical exemplars. Memory & Cognition, 35(1), 15-28.

See Also

mt_align_start for aligning the start position of trajectories.

mt_align as a general purpose function for aligning and rescaling trajectories.

mt_remap_symmetric for remapping trajectories.

Examples

# Align start and end positions to specific coordinates
mt_example <- mt_align_start_end(mt_example,
  start=c(0,0), end=c(-1,1))
  
  
# Import raw trajectories for demonstration
mt_example <- mt_import_mousetrap(mt_example_raw)

# Remap trajectories
mt_example <- mt_remap_symmetric(mt_example)

# Align trajectories to mean first and last coordinates
mt_example <- mt_align_start_end(mt_example,
  start=NULL, end=NULL)