A tool for visualising the timecourse of raw data over a single trial. If data from multiple trials are present, then a single trial will be sampled at random. Alternatively, the trial_number can be specified. Data can be plotted across the whole trial, or can be split into bins to present distinct plots for each time window.
Usage
plot_seq(
data = NULL,
trial_number = NULL,
AOIs = NULL,
bg_image = NULL,
res = c(0, 1920, 0, 1080),
flip_y = FALSE,
plot_header = FALSE,
bin_time = NULL,
bin_range = NULL
)Arguments
- data
A dataframe with raw data. If multiple trials are used, then one trial is sampled at random.
- trial_number
can be used to select a particular trial within the data
- AOIs
A dataframe of areas of interest (AOIs), with one row per AOI (x, y, width_radius, height).
- bg_image
The filepath of an image to be added to the plot, for example to show a screenshot of the task.
- res
resolution of the display to be shown, as a vector (xmin, xmax, ymin, ymax)
- flip_y
reverse the y axis coordinates (useful if origin is top of the screen)
- plot_header
display the header title text which explains graphical features of the plot.
- bin_time
if wanting to split data into bins, the time (in ms) for each bin of data to be displayed
- bin_range
if wanting to split data into bins, the first and last bin to be display, e.g., c(1,5)
Examples
data <- combine_eyes(HCL)
# plot the raw data
plot_seq(data = data[data$pNum == 118,])
#> Multiple trials detected: randomly sampled - trial:5
# with AOIs
plot_seq(data = data[data$pNum == 118,], AOIs = HCL_AOIs)
#> Multiple trials detected: randomly sampled - trial:4
# plot raw data with bins
plot_seq(data = data[data$pNum == 118,], bin_time = 500)
#> Multiple trials detected: randomly sampled - trial:5
