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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