Interpolate across the gaps in data — interpolate

Once data is smoothed, it is important to deal with missing observations, such as blinks. This allows simple interpolation over missing values, either linear, or cubic. Depending on the analysis planed, this may not be a necessary option, but it is strongly recommended for the functional analyses planned in this package.

Usage

interpolate_data(data, pupil, type = c("linear", "cubic"), maxgap = Inf)

Arguments

data: a PupillometryR dataframe
pupil: Column name for pupil data to be interpolated
type: string indicating linear or cubic interpolation to be performed.
maxgap: numeric value specifying the maximum gap size (number of consecutive NAs) to interpolate. Default is Inf (interpolates gaps of any length).

Value

interpolated pupillometry data

Examples

Sdata <- make_pupillometryr_data(data = pupil_data,
subject = ID,
trial = Trial,
time = Time,
condition = Type)
mean_data <- calculate_mean_pupil_size(data = Sdata,
pupil1 = RPupil, pupil2 = LPupil)
filtered_data <- filter_data(data = mean_data,
pupil = mean_pupil,
filter = 'hanning',
degree = 11)
#> Performing hanning filter 
int_data <- interpolate_data(data = filtered_data,
pupil = mean_pupil,
type = 'linear')
#> Performing linear interpolation