Pre-prepared plots of PupillometryR data

The plot functions are designed to run with just data and pupil selections, with some additional options for fun with plotting. To see these plots, you must first use one of the run_functional tests.

Usage

# S3 method for class 'Pupil_test_data'
plot(x, show_divergence = TRUE, colour = "black", fill = "grey", ...)

Arguments

x

A Pupil_test_data dataframe

show_divergence

logical indicating whether divergences are to be highlighted

colour

string indicating colour of geom_line, passed to ggplot2

fill

string indicating fill hue of divergence highlights, passed to ggplot2

...

Ignored

Value

A ggplot object

Examples

Sdata <- make_pupillometryr_data(data = pupil_data,
                               subject = ID,
                               trial = Trial,
                               time = Time,
                               condition = Type)
regressed_data <- regress_data(data = Sdata, pupil1 = RPupil, pupil2 = LPupil)
mean_data <- calculate_mean_pupil_size(data = regressed_data,
pupil1 = RPupil, pupil2 = LPupil)
base_data <- baseline_data(data = mean_data, pupil = mean_pupil, start = 0, stop = 100)
#> Baselining for each subject and trial. If this is not the intended behaviour you may wish to do this manually.
differences <- create_difference_data(data = base_data,
pupil = mean_pupil)
#> Hard minus Easy  -- relevel condition if this is not the intended outcome  
spline_data <- create_functional_data(data = differences, pupil = mean_pupil, basis = 10, order = 4)
ft_data <- run_functional_t_test(data = spline_data,
pupil = mean_pupil)
#> critical value for n = 8 is 2.36462425159278 
p <- plot(ft_data, show_divergence = TRUE, colour = 'red', fill = 'orange')
p