Plot one-dimensional timecourse data. — plot

Typically event-related potentials/fields, but could also be timecourses from frequency analyses for single frequencies. Averages over all submitted electrodes. For group data, plot_timecourse will average within-participants first, using weighted averaging where possible, then across participants using unweighted averaging. Output is a ggplot2 object.

Usage

plot_timecourse(data, ...)

# S3 method for class 'data.frame'
plot_timecourse(
  data,
  electrode = NULL,
  time_lim = NULL,
  add_CI = FALSE,
  baseline = NULL,
  colour = NULL,
  color = NULL,
  mapping = NULL,
  facets = NULL,
  ...
)

# S3 method for class 'eeg_evoked'
plot_timecourse(
  data,
  electrode = NULL,
  time_lim = NULL,
  add_CI = FALSE,
  baseline = NULL,
  colour = NULL,
  color = NULL,
  mapping = NULL,
  facets = NULL,
  ...
)

# S3 method for class 'eeg_ICA'
plot_timecourse(
  data,
  component = NULL,
  time_lim = NULL,
  add_CI = FALSE,
  baseline = NULL,
  colour = NULL,
  color = NULL,
  mapping = NULL,
  facets = NULL,
  ...
)

# S3 method for class 'eeg_epochs'
plot_timecourse(
  data,
  electrode = NULL,
  time_lim = NULL,
  add_CI = FALSE,
  baseline = NULL,
  colour = NULL,
  color = NULL,
  mapping = NULL,
  facets = NULL,
  ...
)

# S3 method for class 'eeg_group'
plot_timecourse(
  data,
  electrode = NULL,
  time_lim = NULL,
  add_CI = FALSE,
  baseline = NULL,
  colour = NULL,
  color = NULL,
  mapping = NULL,
  facets = NULL,
  ...
)

# S3 method for class 'eeg_tfr'
plot_timecourse(
  data,
  electrode = NULL,
  time_lim = NULL,
  add_CI = FALSE,
  baseline = NULL,
  colour = NULL,
  color = NULL,
  mapping = NULL,
  freq_range = NULL,
  type = "divide",
  ...
)

Arguments

data: EEG dataset. Should have multiple timepoints.
...: Other arguments passed to methods.
electrode: Electrode(s) to plot.
time_lim: Character vector. Numbers in whatever time unit is used specifying beginning and end of time-range to plot. e.g. c(-.1, .3)
add_CI: Add confidence intervals to the graph. Defaults to 95 percent between-subject CIs.
baseline: Character vector. Times to use as a baseline. Takes the mean over the specified period and subtracts. e.g. c(-.1,0)
colour: Variable to colour lines by. If no variable is passed, only one line is drawn.
color: Alias for colour.
mapping: A ggplot2 aes() mapping.
facets: A right-hand-side only formula specifying which variables should be used to create facets.
component: name or number of ICA component to plot
freq_range: Choose a specific frequency range to plot. If NULL, calculates the mean over all frequencies. Note that this does not imply that there is power at an included frequency. For example, lower frequencies will have shorter timecourses than high frequencies.
type: Type of baseline correction to use for eeg_tfr objects

Value

Returns a ggplot2 plot object

Methods (by class)

plot_timecourse(data.frame): Plot a data.frame timecourse
plot_timecourse(eeg_evoked): plot eeg_evoked timecourses
plot_timecourse(eeg_ICA): Plot individual components from eeg_ICA components
plot_timecourse(eeg_epochs): Plot timecourses from eeg_epochs objects.
plot_timecourse(eeg_group): Plot timecourses from eeg_group objects.
plot_timecourse(eeg_tfr): Plot timecourses from eeg_tfr objects.

Author

Matt Craddock, matt@mattcraddock.com

Examples

library(ggplot2)
plot_timecourse(demo_epochs, "A29")
#> Creating epochs based on combinations of variables: participant_id 

plot_timecourse(demo_epochs, "A29", baseline = c(-.1, 0))
#> Baseline: -0.1 - 0s
#> Creating epochs based on combinations of variables: participant_id 

plot_timecourse(demo_epochs, "A29", baseline = c(-.1, 0), add_CI = TRUE)
#> Baseline: -0.1 - 0s

plot_timecourse(demo_spatial, "Oz", baseline = c(-.1, 0), mapping = aes(colour = epoch_labels))
#> Baseline: -0.1 - 0s
#> Creating epochs based on combinations of variables: participant_id epoch_labels 

plot_timecourse(demo_spatial, "Oz", baseline = c(-.1, 0), facets = ~epoch_labels)
#> Baseline: -0.1 - 0s
#> Creating epochs based on combinations of variables: participant_id epoch_labels