Parameters: |
- epochs : instance of Epochs
The epochs object
- picks : array-like of int | None
Channels to be included. If None only good data channels are used.
Defaults to None
- scalings : dict | ‘auto’ | None
Scaling factors for the traces. If any fields in scalings are ‘auto’,
the scaling factor is set to match the 99.5th percentile of a subset of
the corresponding data. If scalings == ‘auto’, all scalings fields are
set to ‘auto’. If any fields are ‘auto’ and data is not preloaded,
a subset of epochs up to 100mb will be loaded. If None, defaults to:
dict(mag=1e-12, grad=4e-11, eeg=20e-6, eog=150e-6, ecg=5e-4,
emg=1e-3, ref_meg=1e-12, misc=1e-3, stim=1, resp=1, chpi=1e-4,
whitened=10.)
- n_epochs : int
The number of epochs per view. Defaults to 20.
- n_channels : int
The number of channels per view. Defaults to 20.
- title : str | None
The title of the window. If None, epochs name will be displayed.
Defaults to None.
- events : None, array, shape (n_events, 3)
Events to show with vertical bars. If events are provided, the epoch
numbers are not shown to prevent overlap. You can toggle epoch
numbering through options (press ‘o’ key). You can use
mne.viz.plot_events() as a legend for the colors. By default, the
coloring scheme is the same.
Warning
If the epochs have been resampled, the events no longer
align with the data.
- event_colors : None, dict
Dictionary of event_id value and its associated color. If None,
colors are automatically drawn from a default list (cycled through if
number of events longer than list of default colors). Uses the same
coloring scheme as mne.viz.plot_events() .
- show : bool
Show figure if True. Defaults to True
- block : bool
Whether to halt program execution until the figure is closed.
Useful for rejecting bad trials on the fly by clicking on an epoch.
Defaults to False.
- decim : int | ‘auto’
Amount to decimate the data during display for speed purposes.
You should only decimate if the data are sufficiently low-passed,
otherwise aliasing can occur. The ‘auto’ mode (default) uses
the decimation that results in a sampling rate at least three times
larger than info['lowpass'] (e.g., a 40 Hz lowpass will result in
at least a 120 Hz displayed sample rate).
- noise_cov : instance of Covariance | str | None
Noise covariance used to whiten the data while plotting.
Whitened data channels are scaled by scalings['whitened'] ,
and their channel names are shown in italic.
Can be a string to load a covariance from disk.
See also mne.Evoked.plot_white() for additional inspection
of noise covariance properties when whitening evoked data.
For data processed with SSS, the effective dependence between
magnetometers and gradiometers may introduce differences in scaling,
consider using mne.Evoked.plot_white() .
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