| plot.eeg_lst | R Documentation |
plot creates a ggplot object in which the EEG signal over the whole
recording is plotted by electrode. Useful as a quick visual check for major
noise issues in the recording.
## S3 method for class 'eeg_lst'
plot(x, .max_sample = 6400, ...)
## S3 method for class 'psd_lst'
plot(x, ...)
x |
An |
.max_sample |
Downsample to approximately 6400 samples by default. |
... |
Not in use. |
Note that for normal-size datasets, the plot may take some time to compile.
If necessary, plot will first downsample the eeg_lst object so that there is a
maximum of 6,400 samples. The eeg_lst object is then converted to a long-format
tibble via as_tibble. In this tibble, the .key variable is the
channel/component name and .value its respective amplitude. The sample
number (.sample in the eeg_lst object) is automatically converted to seconds
to create the variable time. By default, time is then plotted on the
x-axis and amplitude on the y-axis, and uses scales = "free"; see ggplot2::facet_grid().
To add additional components to the plot such as titles and annotations, simply
use the + symbol and add layers exactly as you would for ggplot2::ggplot.
A ggplot object
Other plotting functions:
annotate_electrodes(),
annotate_events(),
annotate_head(),
eeg_downsample(),
ggplot.eeg_lst(),
plot_components(),
plot_in_layout(),
plot_topo(),
theme_eeguana()
# Basic plot
plot(data_faces_ERPs)
# Add ggplot layers
library(ggplot2)
plot(data_faces_ERPs) +
coord_cartesian(ylim = c(-500, 500))
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