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Select cycles from a work loop object

Source: R/data_transformation_functions.R
select_cycles.Rd

Retain data from a work loop experiment based on position cycle

Usage

select_cycles(
  x,
  cycle_def,
  keep_cycles = 4:6,
  bworth_order = 2,
  bworth_freq = 0.05,
  ...
)

Arguments

x

A workloop object (see Details for how it should be organized)

cycle_def

A string specifying how cycles should be defined; one of: "lo", "p2p", or "t2t". See Details more info

keep_cycles

The indices of the cycles to keep. Include 0 to keep data identified as being outside complete cycles

bworth_order

Filter order for low-pass filtering of Position via signal::butter() prior to finding L0

bworth_freq

Critical frequency (scalar) for low-pass filtering of Position via signal::butter() prior to finding L0

...

Additional arguments passed to/from other functions that make use of select_cycles()

Value

A workloop object with rows subsetted by the chosen position cycles. A Cycle column is appended to denote which cycle each time point is associated with. Finally, all attributes from the input workloop object are retained and one new attribute is added to record which cycles from the original data were retained.

Details

select_cycles() subsets data from a workloop trial by position cycle. The cycle_def argument is used to specify which part of the cycle is understood as the beginning and end. There are currently three options:
'lo' for L0-to-L0;
'p2p' for peak-to-peak; and
't2t' for trough-to-trough

Peaks are identified using pracma::findpeaks(). L0 points on the rising edge are found by finding the midpoints between troughs and the following peak. However the first and last extrema and L0 points may be misidentified by this method. Please plot your Position cycles to ensure the edge cases are identified correctly.

The keep_cycles argument is used to determine which cycles (as defined by cycle_def should be retained in the final dataset. Zero is the index assigned to all data points that are determined to be outside a complete cycle.

The muscle_stim object (x) must be a workloop, preferably read in by one of our data import functions. Please see documentation for as_muscle_stim() if you need to manually construct a muscle_stim object from another source.

See also

analyze_workloop, read_analyze_wl, read_analyze_wl_dir

Other data transformations: fix_GR(), invert_position()

Other workloop functions: analyze_workloop(), fix_GR(), get_wl_metadata(), invert_position(), read_analyze_wl_dir(), read_analyze_wl(), summarize_wl_trials(), time_correct()

Author

Vikram B. Baliga and Shreeram Senthivasan

Examples


library(workloopR)

# import the workloop.ddf file included in workloopR
wl_dat <-read_ddf(system.file("extdata", "workloop.ddf",
                              package = 'workloopR'),
                  phase_from_peak = TRUE)

# select cycles 3 through 5 via the peak-to-peak definition
wl_selected <- select_cycles(wl_dat, cycle_def = "p2p", keep_cycles = 3:5)


# are the cycles of (approximately) the same length?
summary(as.factor(wl_selected$Cycle))
#>   a   b   c 
#> 357 357 357